BILATERAL MEASUREMENT OF PELVIC FLOOR MUSCLE DYSFUNCTION IN

FEMALES WITH LOWER URINARY TRACT SYMPTOMS USING NEAR INFRARED

SPECTROSCOPY

by

Emily Grace Deegan

B.A., The University of Western Ontario, 2009

B.Sc.N., The University of Toronto, 2011

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF

THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE

in

THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES

(Experimental Medicine)

THE UNIVERSITY OF BRITISH COLUMBIA

(Vancouver)

March 2019

© Emily Grace Deegan, 2019

ii

The following individuals certify that they have read, and recommend to the Faculty of Graduate

and Postdoctoral Studies for acceptance, a thesis/dissertation entitled:

Bilateral measurement of pelvic floor muscle dysfunction in females with lower urinary tract

symptoms using near infrared spectroscopy

submitted by Emily Deegan in partial fulfilment of the requirements for

the degree Master of Science

in Experimental Medicine

Examining Committee:

Lynn Stothers, Urological Sciences Supervisor

Andrew Macnab, Urological Sciences Supervisory Committee Member

Supervisory Committee Member

Gary Gray, Division of Urology Additional Examiner

Additional Supervisory Committee Members:

Tania Lam, School of Kinesiology Supervisory Committee Member

iii

Abstract

Introduction and Objective: Near infrared spectroscopy (NIRS) is a noninvasive method of

measuring oxygen recovery kinetics in skeletal muscle. NIRS detects changes in oxygenated

(O2Hb) and deoxygenated (HHb) hemoglobin in response to exercise, to provide interpretation of

muscular capacity to restore incurred oxygen debt. Assessment of pelvic floor muscle (PFM)

function is central to managing urinary incontinence (UI) and lower urinary tract symptoms

(LUTS) but currently lacks oxygen kinetic parameters. This project aims to develop a NIRS

probe that measures oxygen kinetics of bilateral PFM in females with UI/LUTS (cases) related to

altered pelvic innervation compared to continent controls.

Methods: A transvaginal NIRS prototype to detect bilateral PFM was developed. The vaginal

NIRS probe monitored female volunteers during sustained PFM contraction (SMVC). O2Hb,

HHb and HbDiff (O2Hb-HHb) allowed measurement of oxygen kinetics unique to bilateral PFM.

Oxygen recovery kinetics determined by HbDiff half recovery time (½RT). PFM manometry

assessed SMVC peak and average cmH2O. Home-based 8-week PFM therapy (PFMT)

intervention was performed by both participant groups and an exercise diary measured

adherence, determined as total percentage of volume and frequency.

Results: Observational NIRS findings demonstrated typical hemodynamic and ½RT responses

in controls. Case group demonstrated atypical findings consistent with impaired muscle function.

NIRS found quicker ½RT for controls (7.87 vs 38.03 seconds, p 0.01). Manometer detected

greater PFM strength and endurance in controls (SMVC peak 35 vs 13 cmH2O, p <0.01, SMVC

iv

average 23 vs 10 cmH2O, p 0.02). Intra-group improvements of PFM NIRS and manometer

variables after PFMT were not determined. Post-PFMT ½RT in cases was highly correlated to

SMVC peak and average cmH2O (r -0.83 and r -0.82, respectively). High adherence of PFMT

frequency demonstrated in cases, 78%, which correlated to SMVC peak and average cmH2O (rs

0.78 and rs 0.88, respectively), ½RT (rs -0.85) and reduced urgency (rs -0.85).

Conclusions: This study shows the feasibility of NIRS to provide novel physiologic data

regarding PFM function. PFM oxygen kinetics could provide more insight into PFM pathology

and PFMT rehabilitation. Further refinement of the NIRS probe is required for use in larger

studies with PFMT interventions incorporating adjunctive therapies.

v

Lay Summary

Many women experience involuntary urinary leakage related to pelvic floor nerve injury.

Assessment of pelvic floor muscle is important aspect for managing this issue. This study

developed a new method of assessment using near infrared light to measure pelvic floor muscle

oxygen levels. The oxygen levels determine how well pelvic floor muscles perform during

exercise. Two participant groups were in this study, females with urinary leakage related to nerve

injury and females without urinary leakage or nerve injury. Participants had their pelvic floor

muscles measured before and after 8-weeks of therapeutic exercise. This study found a

difference in pelvic floor muscle function between the two groups and that urinary leakage

symptoms were reduced after 8-weeks of therapeutic exercise. Further development of the near

infrared light method to assess pelvic floor muscle oxygenation is needed to help manage urinary

leakage.

vi

Preface

This is an original thesis of independent efforts by the author, E.G. Deegan. All work was

completed at the International Collaboration on Repair Discoveries (ICORD) located in the

Blusson Spinal Cord Centre, affiliated with the University of British Columbia, Vancouver

campus. E.G. Deegan was responsible for project coordination, participant recruitment, data

collection procedures, statistical analysis and written thesis.

Dr. Lynn Stothers, as acting supervisor, oversaw the grant proposal, study design, ethics

proposal, participant recruitment and screening. Dr. Stothers provided her clinical and academic

expertise and guidance through the span of this study, as well as assistance editing this thesis. Dr.

Andrew Macnab and Dr. Tania Lam, as supervisory committee members helped to develop this

project, contributed to the methods and provided feedback and edits for this thesis.

Components from Chapter 1 section 1.1.3 Evaluation of PFM function, describing current

methodologies of PFM assessment is part of a manuscript titled: “Quantification of pelvic floor

muscle strength in female urinary incontinence: A systematic review and comparison of

contemporary methodologies.” that has been published the in the journal, Neurology and

Urodynamics. E.G. Deegan was responsible for the literature review, and primary manuscript

composition. Dr. Alex Kavanagh and Dr. Andrew Macnab provided editorial assistance. Dr.

Stothers oversaw the complete proceedings, provided guidance of literature selection and

analysis, and edited the manuscript.

All data obtained from this research project was approved by the UBC Clinical Research

Ethics Board and Vancouver Coastal Health Research Institute under the respective Certificate

numbers, H15-02040 and V15-02040.

vii

Table of Contents

Abstract .................................................................................................................................... iii

Lay Summary ........................................................................................................................... v

Preface ...................................................................................................................................... vi

Table of Contents .................................................................................................................... vii

List of Tables.......................................................................................................................... xiv

List of Figures ........................................................................................................................ xvi

Abbreviations ....................................................................................................................... xviii

Acknowledgements ................................................................................................................. xx

Dedication .............................................................................................................................. xxi

Chapter 1: Introduction ........................................................................................................... 1

1.1 Background and rationale ............................................................................................ 1

1.1.1 Urinary incontinence and pelvic floor muscle dysfunction ................................... 1

1.1.2 Pelvic floor muscle therapy.................................................................................. 3

1.1.3 Evaluation of PFM function ................................................................................. 5

1.1.4 Measurement of skeletal muscle oxygen kinetics ................................................. 7

1.2 Principles of Near Infrared Spectroscopy ..................................................................... 8

1.2.1 Development ....................................................................................................... 8

1.2.2 NIRS instrumentation .......................................................................................... 9

1.2.3 Principles of NIRS ............................................................................................. 10

1.2.3.1 Scatter ........................................................................................................... 11

1.2.3.2 Absorption ..................................................................................................... 11

viii

1.2.3.3 Pathlength ...................................................................................................... 12

1.2.4 Contribution of myoglobin and cytochrome-c-oxidase to light absorption .......... 13

1.2.5 Optical Density defined by the Beer Lambert Law ............................................. 14

1.2.6 NIRS adaptation to PFM.................................................................................... 15

1.3 Objectives and Hypotheses ........................................................................................ 17

1.3.1 Primary Aim ...................................................................................................... 17

1.3.2 Objectives ......................................................................................................... 17

1.3.3 Hypotheses ........................................................................................................ 18

Chapter 2: Methods ................................................................................................................ 19

2.1 Participants ............................................................................................................... 19

2.2 Protocol ..................................................................................................................... 20

2.3 Objective measures ................................................................................................... 23

2.3.1 Urinalysis and post void residual volume ........................................................... 23

2.3.2 Standing force plate ........................................................................................... 24

2.3.3 PFM manometry ................................................................................................ 25

2.3.4 NIRS ................................................................................................................. 27

2.4 Subjective measures .................................................................................................. 30

2.4.1 Bladder symptom questionnaires ....................................................................... 30

2.4.2 Waterloo footedness questionnaire..................................................................... 31

2.4.3 Bladder diaries................................................................................................... 31

2.5 Data analysis ............................................................................................................. 32

2.5.1 Standing force plate and WFQ ........................................................................... 32

2.5.2 SMVC focused analysis ..................................................................................... 32

ix

2.5.3 PFM manometry ................................................................................................ 33

2.5.4 NIRS ................................................................................................................. 35

2.5.4.1 Oxygen saturation patterns in response to exercise ......................................... 36

2.5.4.2 Unilateral PFM dominance based on contraction magnitude change .............. 38

2.5.4.3 Oxygen recovery kinetics in response to exercise (Half Recovery Time)........ 39

2.5.4.4 Original adaption of ½RT calculation analysis ............................................... 41

2.5.4.5 Unilateral PFM dominance based on ½RT ..................................................... 42

2.5.5 Bladder symptom questionnaires, bladder diaries and post void residual ............ 43

2.6 Statistical analysis ..................................................................................................... 44

Chapter 3: Results .................................................................................................................. 45

3.1 Participant demographics .......................................................................................... 45

3.2 Questionnaires, post void residual and bladder diary outcome measures .................... 47

3.2.1 Intra-group comparison...................................................................................... 47

3.2.2 Inter-group comparison of questionnaires and post void residual ....................... 49

3.3 Force plate, WFQ and NIRS dominance outcome measures ...................................... 50

3.3.1 Intra-group comparison...................................................................................... 50

3.3.2 Inter-group comparison...................................................................................... 52

3.4 NIRS observational outcome findings ....................................................................... 54

3.4.1 Observational NIRS findings ............................................................................. 54

3.4.1.1 Control group trends ...................................................................................... 54

3.4.1.2 Case group trends .......................................................................................... 58

3.4.1.2.1 High mobility clinical sub-group .............................................................. 59

3.4.1.2.2 Multiple Sclerosis clinical sub-group ....................................................... 63

x

3.4.1.2.3 SCI Clinical Sub-group ............................................................................ 67

3.5 NIRS objective outcome measures ............................................................................ 70

3.5.1 ½RT NIRS measurements ................................................................................. 70

3.5.1.1 Intra-group ½RT comparison ......................................................................... 70

3.5.1.2 Inter-group ½RT comparison ......................................................................... 70

3.5.2 DMag NIRS measurements ................................................................................ 74

3.5.2.1 Intra-group DMag comparison ....................................................................... 74

3.5.2.2 Inter-group DMag comparison ....................................................................... 75

3.5.3 Unilateral PFM ½RT and DMag NIRS Correlation ............................................ 79

3.5.3.1 Intra-group comparison .................................................................................. 79

3.6 Manometer objective outcome measures ................................................................... 81

3.6.1 Within assessment measurements ...................................................................... 81

3.6.1.1 Intra-group manometer comparison ............................................................... 81

3.6.2 Across assessment manometer measurements .................................................... 85

3.6.2.1 Intra-group manometer comparison ............................................................... 85

3.6.2.2 Inter-group PFM manometer comparison ....................................................... 87

3.6.3 Post-PFMT PFM manometer and NIRS dominance measures ............................ 90

3.6.4 Baseline unilateral PFM ½RT and PFM manometer measures ........................... 91

3.6.5 Post-PFMT ½RT and PFM manometer measures............................................... 92

3.7 Exercise adherence outcome measures ...................................................................... 94

3.7.1 Exercise adherence and post-PFMT PFM manometer measures ......................... 96

3.7.2 Exercise adherence correlation to questionnaire and PVR measures ................... 97

3.7.3 Exercise adherence and post-PFMT ½RT measures ........................................... 98

xi

3.7.4 Exercise adherence and post-PFMT DMag measures ....................................... 100

Chapter 4: Discussion ........................................................................................................... 102

4.1 Successful development of NIRS probe ................................................................... 102

4.2 Participant demographics ........................................................................................ 103

4.3 Observational NIRS findings ................................................................................... 105

4.3.1 Hemodynamic and oxygen kinetic response observed in heathy PFM .............. 105

4.3.2 Hemodynamic and oxygen kinetic response observed in PFM dysfunction ...... 109

4.3.2.1 High mobility clinical sub-group.................................................................. 109

4.3.2.2 MS and SCI clinical sub-groups ................................................................... 111

4.3.3 Explanations for atypical hemodynamic and oxygen kinetic response .............. 111

4.3.3.1 Innervation .................................................................................................. 111

4.3.3.1.1 Pudendal nerve innervation .................................................................... 111

4.3.3.1.2 Denervation related to pregnancy and labour .......................................... 112

4.3.3.1.3 Recruitment ........................................................................................... 112

4.3.3.1.4 Activation .............................................................................................. 113

4.3.3.2 Microvasculature ......................................................................................... 114

4.3.3.3 Contractile Intensity..................................................................................... 114

4.3.3.4 Cross Contamination ................................................................................... 115

4.3.3.5 Applicability of theoretical considerations to an individual case ................... 116

4.3.4 Objective outcome measures............................................................................ 118

4.3.4.1 Inter-group objective PFM function outcomes ............................................. 118

4.3.4.1.1 Half Recovery Time (½RT) outcomes .................................................... 119

4.3.4.1.2 Delta magnitude change (DMag) outcomes ............................................ 120

xii

4.3.4.1.3 PFM manometry outcomes .................................................................... 121

4.3.4.2 Intra-group objective PFM function outcomes ............................................. 121

4.3.4.2.1 ½RT outcomes ....................................................................................... 122

4.3.4.2.2 DMag outcomes ..................................................................................... 124

4.3.4.2.3 ½RT and DMag associated outcomes ..................................................... 125

4.3.4.2.4 PFM manometer outcomes ..................................................................... 125

4.3.4.2.5 ½RT and PFM manometer associated outcomes ..................................... 126

4.3.4.3 Lower limb and PFM dominance outcomes ................................................. 127

4.3.4.3.1 Fz and WFQ dominance outcomes ......................................................... 127

4.3.4.3.2 NIRS dominance outcomes .................................................................... 129

4.3.4.3.3 Degree of NIRS dominance and PFM manometer outcomes .................. 131

4.3.4.3.4 Degree of NIRS dominance and PFMT adherence outcomes .................. 131

4.3.4.4 QOL and clinical symptom outcomes .......................................................... 132

4.3.4.4.1 Inter-group QOL and clinical symptom outcomes .................................. 132

4.3.4.4.2 Intra-group QOL and clinical symptom outcomes .................................. 132

4.3.4.5 PFMT Adherence outcomes ......................................................................... 133

4.3.4.5.1 Adherence and reduced urgency symptoms ............................................ 135

4.3.4.5.2 Adherence and PFM function outcomes ................................................. 135

Chapter 5: Conclusion .......................................................................................................... 136

5.1 Main Findings ......................................................................................................... 136

5.2 Limitations .............................................................................................................. 138

5.3 Strengths and Future Directions ............................................................................... 142

5.4 Conclusion .............................................................................................................. 145

xiii

Bibliography ......................................................................................................................... 147

Appendix A ........................................................................................................................... 169

Appendix A Methods .......................................................................................................... 169

A.1 PFMT Instruction Sheet ....................................................................................... 169

A.2 PFMT Recording Sheet ....................................................................................... 170

A.3 Bladder Diary ...................................................................................................... 171

A.4 Questionnaire for Urinary Incontinence Diagnosis (QUID).................................. 172

A.5 Urogenital Distress Inventory Short Form (UDI-6) .............................................. 173

A.6 Incontinence Impact Questionnaire Short Form (IIQ-7) ....................................... 174

A.7 Subjective Assessment of Improvement............................................................... 175

A.8 Waterloo Footedness Questionnaire-Revised ....................................................... 176

xiv

List of Tables

Table 2.1 SPAM stratification of oxygen patterns. .................................................................... 37

Table 3.1 Demographics of study sample by participant group. ................................................. 46

Table 3.2 Demographic details of case participants listed by participant ID. ............................. 46

Table 3.3 Demographic details of control participants listed by participant ID. ......................... 47

Table 3.4 Intra-group comparison of questionnaires and PVR. .................................................. 48

Table 3.5 Case group 3-day bladder diary variables. ................................................................. 49

Table 3.6 Inter-group SSI comparison. ...................................................................................... 50

Table 3.7 Intra-group Fz lower limb dominance comparison. .................................................... 51

Table 3.8 Intra-group Fz and WFQ lower limb dominance correlation. ..................................... 51

Table 3.9 Intra-group Fz, WFQ and NIRS dominance correlations. ........................................... 52

Table 3.10 Inter-group Fz, WFQ and NIRS dominance comparison. ......................................... 53

Table 3.11 Intra-group 1/2RT variables at baseline and post-PFMT. ......................................... 72

Table 3.12 Inter-group 1/2RT variables at baseline and post-PFMT. ......................................... 73

Table 3.13 Intra-group DMag variables at baseline and post-PFMT. ......................................... 76

Table 3.14 Inter-group DMag variables at baseline and post-PFMT. ......................................... 77

Table 3.15 Intra-group 1/2RT and DMag correlations at baseline and post-PFMT. .................... 80

Table 3.16 Within assessment control group PFM manometer variables. .................................. 83

Table 3.17 Within assessment case group PFM manometer variables. ....................................... 84

Table 3.18 Across assessment intra-group PFM manometer variables. ...................................... 86

Table 3.19 Inter-group PFM manometer variables at baseline and post-PFMT. ......................... 88

xv

Table 3.20 Intra-group correlation of post-PFMT PFM manometer and NIRS dominance

variables. .................................................................................................................................. 90

Table 3.21 Intra-group correlation of unilateral PFM 1/2RT and PFM manometer variables at

baseline. ................................................................................................................................... 91

Table 3.22 Correlation of unilateral 1/2RT and PFM manometer variables at post-PFMT. ........ 93

Table 3.23 Inter-group exercise adherence. ............................................................................... 95

Table 3.24 Intra-group correlation of PFM manometer and exercise adherence variables. ......... 96

Table 3.25 Intra-group correlation of 1/2RT and exercise adherence variables. ......................... 99

Table 3.26 Intra-group correlation of DMag and exercise adherence variables......................... 101

xvi

List of Figures

Figure 2.1 Flow diagram for study procedures from baseline to post-PFMT assessment............ 22

Figure 2.2 Force plate configuration for lower limb dominance measures. ................................ 25

Figure 2.3 PFM manometer. .................................................................................................... 26

Figure 2.4 NIRS probe prototype design. ................................................................................. 28

Figure 2.5 NIRS probe prototype design details and equipment configuration. ......................... 30

Figure 2.6 SPAMD algorithm. .................................................................................................. 38

Figure 2.7 Example of 1/2RT calculation in control participant. ................................................ 41

Figure 2.8 Example of inverse 1/2RT calculation in a case participant. ..................................... 42

Figure 3.1 Case group QUID-UUI score reduction. ................................................................... 48

Figure 3.2 Intra-group DisFz and QFz association. ................................................................... 51

Figure 3.3 Inter-group DisFz and QFz comparison. ................................................................... 53

Figure 3.4 Control participant CS1 performing MVCs, SMVC and REP. .................................. 55

Figure 3.5 Control participant CS1 performing SMVC at baseline and post-PFMT. .................. 56

Figure 3.6 Control participant CS1 SMVC oxygenation patterns at baseline and post-PFMT. ... 56

Figure 3.7 Control participant CS7 performing SMVC at baseline and post-PFMT. .................. 57

Figure 3.8 Control participant CS7 SMVC oxygenation patterns at baseline and post-PFMT. ... 57

Figure 3.9 Case participant SS11 performing MVCs, SMVC and REP. .................................... 61

Figure 3.10 Case participant SS11 SMVC oxygenation patterns at baseline. ............................. 62

Figure 3.11 Case participant SS14 performing SMVC at baseline and post-PFMT. ................... 62

Figure 3.12 Case participant SS14 SMVC oxygenation patterns at baseline and post-PFMT. .... 63

Figure 3.13 Case participant SS12 performing MVCs, SMVC and REP.................................... 65

xvii

Figure 3.14 Case participant SS12 performing SMVC at baseline and post-PFMT. ................... 66

Figure 3.15 Case participant SS12 SMVC oxygenation patterns at baseline and post-PFMT. .... 66

Figure 3.16 Case participant SS3 performing SMVC at baseline including full recovery time

interval. .................................................................................................................................... 68

Figure 3.17 Case participant SS3 performing SMVC at baseline and post-PFMT. ..................... 68

Figure 3.18 Case participant SS3 SMVC oxygenation patterns at baseline and post-PFMT. ...... 69

Figure 3.19 Case participant SS4 SMVC at baseline. ................................................................ 69

Figure 3.20 Inter-group 1/2RT variables at baseline and post-PFMT. ........................................ 74

Figure 3.21 Inter-group DMag at baseline and post-PFMT. ....................................................... 78

Figure 3.22 Inter-group 1/2RT and DMag dominance at baseline and post-PFMT. .................... 79

Figure 3.23 Intra-group correlations for 1/2RT and DMag. ........................................................ 81

Figure 3.24 Across assessment correlation of PFM manometer measures. ................................. 87

Figure 3.25 Inter-group PFM manometer variables at baseline and post-PFMT......................... 89

Figure 3.26 Correlation of Right PFM 1/2RT and PFM manometer variables. .......................... 93

Figure 3.27 Correlation of Left PFM 1/2RT and PFM manometer variables. ............................. 94

Figure 3.28 Inter-group PFMT adherence mean values for Exercise Volume and Frequency..... 95

Figure 3.29 Intra-group exercise adherence percentage. ............................................................ 95

Figure 3.30 Case group correlation of PFM manometer and exercise adherence variables. ........ 97

Figure 3.31 Case group correlation of QUID-UUI score and exercise adherence. ...................... 98

Figure 3.32 Control group correlation of 1/2RT and exercise adherence. .................................. 99

Figure 3.33 Case group correlation of 1/2RT and exercise adherence. ..................................... 100

Figure 3.34 Case group correlation of DMag and exercise adherence. ..................................... 101

xviii

Abbreviations

Abbreviated terms are in keeping with the International Urogynecological Association and the

International Continence Society recommended terminology and definitions.1

DMag Magnitude change of hemoglobin concentration

½RT Half-Recovery Time

31P-MRS Phosphorus magnetic resonance spectroscopy

CWS Continuous wave spectroscopy

DisFz Distracted stance dominance measured by percentage difference of ground reaction force of bilateral lower limbs

HbDiff Difference between oxygenated and deoxygenated hemoglobin

HHb Deoxygenated hemoglobin

IAP intra-abdominal pressure

IIQ-7 Incontinence impact questionnaire short form, see Appendix A.6

LUTS Lower urinary tract symptoms

MS Multiple sclerosis

MUI Mixed urinary incontinence

MVC maximal voluntary contraction

NIRS Near infrared spectroscopy

O2Hb Oxygenated hemoglobin

PFM pelvic floor muscle

PFMT pelvic floor muscle therapy

PVR Post void residual

xix

QFz Quiet stance dominance measured by percentage difference of ground reaction force of bilateral lower limbs

QUID-SUI Questionnaire for urinary incontinence diagnosis – stress urinary incontinence score, see Appendix A.4

QUID-UUI Questionnaire for urinary incontinence diagnosis – urgency urinary incontinence score, see Appendix A.4

REP Fast repeated contractions

SB Spina bifida

SCI Spinal cord injury

SMVC Sustained maximal voluntary contraction

SSI Subjective survey of improvement, see Appendix A.7

SUI Stress urinary incontinence

tHb Total sum of oxygenated and deoxygenated hemoglobin

UDI-6 Urogenital distress inventory short form, see Appendix A.5

UI urinary incontinence

UUI Urgency urinary incontinence

WFQ Waterloo footedness questionnaire, see Appendix A.8

xx

Acknowledgements

Foremost I would like to acknowledge my supervisory committee. I would like to thank Dr.

Lynn Stothers, for believing in my capability, for encouraging my academic pursuit and for

providing me with the support needed to complete this project. I would like to thank Dr. Andrew

Macnab, for sharing his NIRS expertise, keen advise and patience. I would like to thank Dr.

Tania Lam whose assistance on methodological components and support with statistical analysis

is greatly appreciated. Also, a special thanks to the Lam Lab who graciously shared equipment

and patiently guided me through Matlab.

I would like to acknowledge the Rick Hansen Foundation and the Blusson Integrated Cures

Partnership, whom without their appreciation for continued research and financial support this

project would not have been made possible.

I would also like to acknowledge the entire community at ICORD who not only facilitated the

day to day activities of this project but also connected me to the SCI community at large.

Special thanks are owed to the nurses and administrative staff of the Urology Clinic at the

Brenda and David Mclean Integrated Spine Center, whose assistance, cooperation and patience

made the data collection possible.

A very sincere thanks is owed to the volunteers who participated in this study. Their gracious

commitment is deeply appreciated and their contributions to this research is extremely valued.

xxi

Dedication

I dedicate the completion of this thesis my supportive husband and parents.

1

Chapter 1: Introduction

This chapter will introduce the research topic, providing background literature on urinary

incontinence, pelvic floor muscle (PFM) dysfunction and lower urinary tract symptoms

experienced in females. Specific attention will be given to how neurologic conditions and

injuries contribute to these issues. To better appreciate the physiologic consequences of

neurologic conditions and injuries on continence and PFM function, near infrared spectroscopy

is introduced as a technology to address gaps in the current PFM literature surrounding oxygen

kinetics and hemodynamics within the PFM, thus providing the rationale for this project.

Subsequently objectives and hypotheses that guided the research are stated.

1.1 Background and rationale

1.1.1 Urinary incontinence and pelvic floor muscle dysfunction

Urinary incontinence (UI) is a detrimental health condition that negatively impacts

quality of life and generates a huge economic burden, totaling $2.3 billion in Canada alone.2-7 As

many as 36.5 % of adult Canadian women are living with UI and this number increases to 55%

among women older than 65 years of age.2 As determined by the International Urogynecological

Association/International Continence Society (IUGA/ICS), there are three different types of

urinary incontinence: stress incontinence, urgency incontinence and mixed incontinence.8 Stress

incontinence is defined as involuntary urinary leakage due to physical exertion and urgency

incontinence is defined involuntary urinary leakage due to strong urge to void that cannot be

suppressed.8 Mixed urinary incontinence is defined as stress and urgency incontinence

presenting in conjunction.8 UI, particularly urge incontinence, is even more pervasive among

2

individuals living with neurological conditions that cause interruption of innervation to the pelvic

viscera, resulting in neurogenic bladder.9 Research from the U.S. reports frequency of

neurogenic bladder to be 40-90% in those with multiple sclerosis (MS), 40-61% in those with

spina bifida and 70-84% in those living with spinal cord injury (SCI).10 Neurogenic bladder

leads to urinary incontinence due to overactivity or underactivity of the detrusor (contractile

muscle of the bladder). Spinal injuries above the vertebral level of T12 results in overactive

detrusor, resulting in urgency symptoms and incontinence and impaired bladder emptying as the

external urethral sphincter muscles in the pelvic floor become uncoordinated with the detrusor

contraction, resulting in detrusor sphincter dyssynergia which impedes urine flow when the

bladder is attempting to empty.9,11 Underactive bladder, or loss of detrusor contractility, occurs

in spinal injuries below the vertebral level of T12, resulting in over filling of the bladder, causing

incontinence as the bladder volume exceeds the bladder’s capacity to retain increasing amounts

of urine.10,11 On top of impaired detrusor activity, innervation to the pelvic floor muscle (PFM)

is also interrupted. This further exacerbates the incontinence experienced in spinal cord injury as

the somatic control of these skeletal muscles is inhibited. As the PFM is the only skeletal muscle

in the lower urinary tract, it is the only mechanism that can be voluntarily controlled for

maintaining continence. Not only is the motor control of the PFM inhibited in spinal cord injury

but another detriment is the resulting consequence of PFM atrophy. This means that even in

incomplete injuries with pudendal motor neuron sparing, the PFM will have weakened muscle

function limiting the ability to produce contractions meaningful for maintaining continence. A

wide variety of pathologies can result in disruption of innervation to the PFM, including: SCI,

MS, spina bifida, Parkinson’s disease and even trauma induced by vaginal delivery.9,12,13

3

1.1.2 Pelvic floor muscle therapy

Pelvic floor muscle therapy (PFMT) is defined by Bø et al. 2016 in the IUGA/ICS joint

report as “exercise to improve PFM strength, endurance, power, relaxation or a combination of

these parameters.”1 Prominent urological associations recommend PFMT as the first line

therapy for management of UI.14-17 PFMT has been demonstrated to improve PFM function and

strength by means of neuromuscular adaptations and muscle hypertrophy. 18,19 These beneficial

responses to PFMT have been shown to improve or cure both stress and urge incontinence.20,21

Stress incontinence is improved by means of the strengthened PFMs increased capability

to generate more force and at greater velocity.22,23 Such increased capability allows the external

urethra to remain closed, by nature of compression exerted from PFM contraction, during

situations of high intra-abdominal pressure (such as physical exertion, coughing or sneezing).

During situations of high intra-abdominal pressure force is exerted on to the bladder, and when

storage mechanisms are not competent, involuntary leakage of urine occurs. Thus, a strengthened

PFM can maintain closure of the external urethral sphincter and prevent stress incontinence.

Furthermore, strengthening the PFM also improves the structural integrity of the pelvic organs,

including the urethra, bladder and uterus.19,22 The PFM supports optimal anatomical positioning

of these pelvic organs, and improving PFM strength to maintain structural support prevents stress

incontinence that can occur from pelvic organ prolapse.

PFMT helps to improve urge incontinence by means of activating the “guarding reflex”.

Contraction of the PFM, causes compression and contraction of the external urethral sphincter,

this stimulates afferent nerves in the autonomic pathway of the sphincter to reduce

parasympathetic excitation promoting detrusor contractions which generate urgency.19,24 PFM

4

contractions stimulate the afferent nerves in the somatic pathway of the lumbosacral spinal cord

which also prevents activation of detrusor contractions.24

Most of the existing literature supports PFMT as a beneficial rehabilitation for females

with stress incontinence. More recent literature supports the beneficial effects in females with

urge and mixed incontinence. A current systematic review by Dumoulin et al. 2018, reports

PFMT is beneficial for management of all UI.20 However, only limited investigations have

examined the benefits of PFMT in females with UI and neurologic conditions. Investigations

have demonstrated that PFMT with and without adjunctive EMG biofeedback and electrical

stimulation was effective in reducing lower urinary tract symptoms (LUTS) in females with

MS.25-27 Voorham et al. 2017 and Fitz et al. 2017, both examined the effectiveness of PFMT

(which included biofeedback or supervised PFMT sessions) on a female population with

overactive bladder symptoms and demonstrated improvements in PFM function with EMG,

reduced symptoms and improved quality of life (QOL).28,29 Described by IUGA/ICS, common

overactive bladder symptoms include urgency, frequency and nocturia with or without urgency

continence,8 which makes this study relevant to a neurologic population, as these are also

common symptoms experienced by individuals with neuronal impairments in the PFM.9

Vasquez et al. 2015, examined the effectiveness of home-based PFMT in a case-based study of 2

males with incomplete SCI and found improvements in voluntary PFM control which helped to

reduce detrusor overactivity and incontinence.30 Based on this literature it seems reasonable to

evaluate PFM function in individuals with neurological impairment to the PFM and to further

assess the physiologic parameters contributing to the effectiveness of PFMT in this population.

5

1.1.3 Evaluation of PFM function

The positive therapeutic effects of PFMT for UI were first discovered by Dr. Arnold

Kegel in 1948, at this time he developed the first vaginal manometer to measure PFM strength

and evaluate outcomes of PFMT.31,32 Although research has progressed the understanding of the

PFM and furthered development of evaluative instruments, there still remains no current gold

standard methodology for quantifying PFM function.33-38 Evaluation of skeletal muscle function

and strength involves consideration of both slow and fast twitch muscle fibers (type I and type

IIA, IIX). Slow type I fibers are dependent upon oxygen and reflect the aerobic capacity of

muscles. This fiber type is of particular importance when evaluating PFM as this muscle group is

comprised of approximately 70% slow twitch fibers.39 Fast type IIA and type IIX fibers are

recruited under high muscle force demands, metabolize anaerobically and reach peak tension two

times faster than type I fiber.40 Although type II fibers are responsible for producing quick and

forceful muscular contractions, slow twitch fibers are important for muscular endurance, as they

help sustain repeated muscular contractions at certain intensity levels over time. Active

engagement from both fiber types in the PFM are integral for maintaining continence. The

fatigue resistance of type I is crucial for supporting continued demands placed on the PFM as it

contributes to pelvic stability during everyday physical activities, such as walking, and

counteracting intra-abdominal pressure (IAP) occurring with postural changes that exert

downward on the pelvic floor, to prevent stress incontinence.22,41-43 The type II fibers are

necessary for providing quick, strong contractions and are responsible for facilitating urethral

closure during intensive brief changes in IAP, like coughing or sneezing, and to suppress

urgency until voluntary micturition.22,44 As such, both fiber types of the PFM are assessed by

6

measuring strength and endurance, and these are important outcome measures when evaluating

PFM function after PFMT interventions.

When assessing PFM strength in females, a maximal voluntary contraction (MVC) is

performed, produced by voluntarily squeezing the pelvic floor while pulling upward and inward

to generate as much force as possible. The measurement of strength can be determined by digital

palpation, manometry or dynamometry.1 Endurance is determined by the duration of the PFM to

sustain a percentage of MVC or by the number of repeated contractions at percentage of MVC.1

Although these parameters are reported by the IUGA/ICS, they do not identify a gold standard

methodology for quantifying PFM strength and endurance. This lack of standardization is not

only problematic for proper assessment of PFM function within the general female population

experiencing UI, but also complicates the difficult assessment of PFM function among females

with neurological conditions. Their impaired motor function often only allows generation of

weak contractions, if any, that can be indiscernible by an examiner or undetected by current

assessment devices, thus preventing appropriate application and progression of PFMT therapy

for these individuals.

The metabolic properties of muscle fiber type dictate their functional roles in muscular

function. Type II fibers rapidly generate force through the breakdown of phosphocreatine and

glycogen stores within the tissue. However, the energy derived from these metabolic processes is

only capable of maintaining high intensity contractions for short periods of time as the

phosphocreatine and glycogen quickly depletes.40,45 Once these energy fuel sources are depleted

muscular function is sustained by aerobic glycolysis, utilizing oxygen from the vascular system

to generate energy.40,45 Measuring these metabolic pathways within the PFM would provide

insight on the different fiber type contributions to PFM function during exercise and help explain

7

the interplay between the demands placed on the metabolic processes of PFM during functional

situations that require both strength and endurance. Further understanding of the metabolic

processes specific to the PFM will provide more insight to how the PFM performs in both

healthy and pathologic conditions. Such information could be utilized to best direct PFMT

methods for management of LUTS.

A common way of assessing skeletal muscle metabolic processes is by measuring oxygen

kinetics. This is routinely performed in sports medicine to better facilitate athletic training

regimes and in medicine to better understand pathophysiology of disease, as oxygen kinetics

provides valuable information about the workload capacity of muscle (oxygen extraction) and

fatigue resistance (oxygen recovery). Methods utilized to measure oxygen kinetics will be

addressed in the following section.

1.1.4 Measurement of skeletal muscle oxygen kinetics

In the fields of sport medicine and physiology skeletal muscle fitness is quantified by

examining the oxygen kinetics of muscle tissue during exercise conditions, and the gold standard

measurement for this is performing muscle biopsies.46,47 Due to this severely invasive and often

impractical method, new approaches for assessing in vivo skeletal muscle oxygen kinetics have

been developed. Phosphorus magnetic resonance spectroscopy (31P-MRS) is currently accepted

as the gold standard for measuring in vivo skeletal muscle oxygen kinetics, which, although it is

not a direct measure like muscle biopsy, has the advantage of allowing for in vivo assessment of

skeletal muscle oxygen kinetics as changes occur in real time with response to exercise.48,49

Although this method is definitely less invasive than sampling of tissue from muscle biopsy, 31P-

MRS is an expensive methodology to employ and requires the use of a magnetic coil that limits

8

the ability of this measurement to be utilized during various exercise modalities.49 Near infrared

spectroscopy (NIRS) is another method of in vivo assessment of skeletal muscle oxygen kinetics,

which, similar to 31P-MRS, allows for real time measurement of skeletal muscle oxygen kinetics

in response to exercise. However, unlike 31P-MRS, NIRS equipment does not require the limb of

muscle under investigation to be confined to a magnetic coil. NIRS devices are applied

superficially over the muscle area of interest, and being relatively small in size can be easily

secured with tape and wraps, allowing the limbs to move freely with movement naturally

occurring with various exercise modalities.50 This particular advantage of NIRS makes it more

suitable to clinical investigations of skeletal muscle oxygen kinetics and as a result it is rapidly

becoming a ubiquitous and valuable research modality to evaluate skeletal muscle oxidative

metabolism in both states of health and disease.50-52 More recently, NIRS has been utilized to

investigate hemodynamic pathophysiology occurring in the presence of neurological conditions

and muscular disorders.53-56 Validation studies performed by Ryan et al. 2014, have

demonstrated that NIRS methodology is considered to provide reliable and sensitive measures

when compared to the gold standard of muscle biopsy and the currently accepted 31P-MRS

measures.46

1.2 Principles of Near Infrared Spectroscopy

1.2.1 Development

NIRS is an emerging scientific tool being used to advance the understanding of

hemodynamic properties in human tissue. Since the 1970’s NIRS technology has progressed and

become adopted by a broad range of research communities to study hemodynamic characteristics

9

of cerebral, skeletal muscle and visceral organ tissue as a means to better understand human

health and disease.50,51,57-59 NIRS was utilized for hemodynamic studies in animal models by

Jöbsis et al. 1977,60 which demonstrated that NIRS could noninvasively detect concentration

changes of oxygen in cerebral tissue. Wray et al. 1988, further progressed this finding by

defining separate near infrared light spectra for specific chromophores that indicated

oxygenation status.61 NIRS was applied to human skeletal muscle by De Blasi et al. 1991,

demonstrating oxygen desaturation in the forearm8 Efforts from Mancini et al. 1994 validated the

use of NIRS in human skeletal muscle, determining its detection of oxygenation changes to be

more sensitive than that of traditional plethysmography measurements.62 NIRS is now a

commonly used technology, particularly in exercise physiology due to its sensitivity and

specificity in detecting skeletal muscle oxygenation patterns.50

1.2.2 NIRS instrumentation

There are three main types of NIRS instrumentation used to detect chromophore

concentration in biological tissue and they are defined by the means with which they measure

optical properties. They consist of time-resolved, frequency-modulated and continuous wave

spectroscopy. Time-resolved spectroscopy uses rapid pulses of light and examines the shape of

the light pulses as they propagate through tissue to derive chromophore concentrations, allowing

the exact flight time of light travel to be quantified.63-66 Frequency-modulated spectroscopy

compares different frequency of light intensity at distinct points within the light cycle, along with

the rate of the light cycle shift to derive chromophore concentrations.50,64,66 Both time-resolved

and frequency-modulated spectroscopy have the benefits of deeper tissue penetration and

10

provide absolute chromophore concentrations by their ability to derive precise pathlength

variables.50,64,66

The third type is continuous wave spectroscopy (CWS), which continuously emits light

and detects chromophore concentration changes based on the amount of light attenuation that

occurs.51,57,64,66,67 Unlike time-resolved and frequency-modulated spectroscopy, CWS provides

only relative chromophore concentration changes, as it utilizes the Beer Lambert Law equation

with estimated coefficient values to calculate light attenuation. Newer CWS instruments have

incorporated spatially-resolved spectroscopy (SRS), which emits continuous light at multiple

distances within a tissue. SRS provides absolute chromophore concentrations to be quantified by

summing the values measured across all the distances of light emission.50,51

1.2.3 Principles of NIRS

In order to apply NIRS to any field of hemodynamic investigation, the principles of NIR

light must be considered. It is established that NIR light, which propagates between 700 to 1000

wavelengths (nm) within the light spectrum, can penetrate through biological tissue to reach

small vessels with the microvasculature.60,61,64 Within these small vessels, NIR light is absorbed

by three biological chromophores: hemoglobin, myoglobin and cytochrome-c-oxidase. 57,67,68

The amount of absorption that occurs provides an indication of the oxygenation status, as the

ability of hemoglobin and myoglobin to absorb NIR light is directly influenced by whether or not

oxygen is bound to these molecules.60,61,64,66 There are several factors that influence the

transmission of NIR light as it travels from its source through biological tissue to reach its

targeted absorption site.

11

1.2.3.1 Scatter

Light scatter refers to how much light is lost along its full trajectory path originating from

its source to targeted end point. As NIR light does not travel is one direct straight line, it is

subject to light loss from scattering in divergent directions through multiple planes and from

coming into contact with tissue that can either reflect or absorb it. Thus, this scattering property

of light can result in a reduction in the strength of the light signal when it has reached its targeted

end point.60,66 The amount of scattering that occurs is also dependent on the wavelength the light

is transmitted at. At higher wavelengths, such as in the NIR spectrum (700-1000nm), there is less

light scatter than in the visible light spectrum, which facilitates NIR light being able to penetrate

through biological tissue.60,69

Based on studies that defined the amount of NIR light scattering at different wavelengths

and through multiple types of biological tissue, scattering coefficients have been established for

use in mathematical equations to derive NIRS values on hemodynamic patterns.66,70 This

scattering coefficient also incorporates the light scattering that is caused from NIR light

travelling through skin, adipose and fibrous tissue before it reaches its final point of absorption.

1.2.3.2 Absorption

The ultimate absorption of light is also dependent upon the wavelength that the light is

transmitted at and of the molecular characteristics of the tissue the light is being transmitted

through.60,61,66 As previously mentioned the chromophores of hemoglobin, myoglobin and

cytochrome-c-oxidase absorb light differently depending on the presence of a molecular bond

with oxygen. It has been determined that hemoglobin has an isobestic point at the wavelength of

800nm, meaning both deoxygenated hemoglobin and oxygenated hemoglobin absorb light

12

equally at this wavelength.61 However, below this wavelength at approximately 750-770 nm

deoxygenated hemoglobin highly absorbs light, whereas above the isobestic point at

approximately 830-850nm oxygenated hemoglobin has higher light absorbency.61,62 The

comparison of the amount of light absorption occurring at these different wavelengths allows

NIRS to convert the amount of detected absorption into deoxygenated or oxygenated

chromophore concentrations values. Therefore, there must always be at least two light

wavelengths emitted from the light source.64,66 The concentration values that NIRS provides are

then used to infer the oxygenation patterns of the tissue under investigation. Similar to scattering

coefficient values required to derive chromophore concentrations, established absorption

extinction coefficient values for the three chromophores (hemoglobin, myoglobin and

cytochrome) at all the light wavelengths employed during a NIRS measurement are also

required.66

1.2.3.3 Pathlength

When establishing the absorption extinction coefficient, the total distance the light has

travelled is of great importance and is defined as the pathlength. As described by Jacques 2013,

an increasing pathlength will result in an exponential decrease in light absorption. Standard

pathlength values have been defined specific to the type of tissue under investigation, which will

influence the absorption coefficient value used.66 Studies from Deply et al. 1988, were among

the first to establish a known pathlength value for cerebral tissue within a rat model.69 Several

investigations were the completed by, Ferarri et al. 1992, Van der Zee et al. 1992, Essenpreis et

al. 1993, and Duncan et al. 1995, which quantified pathlength for human skeletal muscle

tissues.65,71-73 Derived from these studies, standard pathlength values for skeletal muscle have

13

been established. It is important to note that the pathlength value is also specific to inter-optode

distance. The inter-optode distance is to be determined prior to any measurement and is the

distance between the optode transmitting the light source (light entry point) and the optode

receiving the transmitted light (light exit point). In CWS, which utilizes the Beer Lambert Law to

calculate the chromophore concentration values, the pathlength value is assumed to remain

constant throughout the duration of the NIRS measurement.70,74,75 However, it should be noted

that specific pathlengths for each individual muscle have not been determined and that each

muscle has a different composition of fiber types and varying tissues that result in unique

pathlength parameters.50,62,70 Saitoh et al. 2010, also report that scatter coefficient and pathlength

can change in a given muscle as a direct result of exercise and that more accurate, absolute

values in oxygenation of the muscle should be measured with time-resolved spectroscopy to

account for this.76

1.2.4 Contribution of myoglobin and cytochrome-c-oxidase to light absorption

Although NIR light absorption of reduced cytochrome-c-oxidase was measured in the

founding work of Jöbsis et al. 1977, there remains controversy over this value as it is difficult to

isolate the light absorption occurring solely due to cytochrome-c-oxidase reduction from that of

the much stronger hemoglobin signal. The consensus opinion is that the influence of

cytochrome-c-oxidase only contributes to approximately 10-15% of the light absorbency signal,

and is therefore dismissed by some researchers as an insignificant contributing factor in the

measured values of light absorbency.61,68 Similarly, it has been determined that myoglobin

accounts for approximately 10-20% of the measured hemoglobin light absorbency signals, which

14

at this point cannot be separated from the hemoglobin signal and therefore myoglobin

oxygenation status is inferred from the hemoglobin measures.50,57,62,68

1.2.5 Optical Density defined by the Beer Lambert Law

When collecting NIRS measurements it is essential to consider the type of biological

tissue the NIR light will be transmitted through and the type of tissue at the terminal site of light

transmission, as this determines the specific parameters used for the scatter and absorption

extinction coefficients. With standard estimated values for the absorption extinction coefficient,

scatter coefficient and pathlength, along with a defined inter-optode distance specific to the

measurement, the Beer Lambert Law can then be utilized to derive the oxygenation status of

biological tissue by quantifying optical density.57,61,68,77,78 The Beer Lambert Law defines the

optical density of a medium, and the modified equation utilized in continuous wave instruments

is expressed as: A = e[c]LB+G

In this equation, A represents optical density, e represents the absorption extinction

coefficient, [c] represents the chromophore concentration, L represents the distance from the

light source to terminal end point, B represents the pathlength and G represents scatter

coefficients for other parameters that can interfere with light transmission, such as skin and

adipose tissue.51,57,77

This equation only works for one chromophore, so in order to examine multiple

chromophores simultaneously there needs to be the same number of light wavelengths emitted

for the corresponding number of chromophores under investigation. NIRS systems then employ

algorithms to solve the equations for each chromophore at the varying wavelengths, ultimately

15

providing the relative concentration values of the chromophores to allow for the interpretation of

oxygenation status of the tissue.51,57,77

It is also important to note that only standard values or estimates for these coefficients are

used and that variation in light scatter and absorption occurs across subjects, tissue site and

measurement times.66 This is why relative trends in oxygenation patterns are derived from NIRS

studies using continuous wave spectroscopy, as opposed to absolute oxygenation values

measured with time-resolved or frequency-modulated spectroscopy.51,66,77

1.2.6 NIRS adaptation to PFM

Similar to the use of NIRS in sports medicine and physiology, the adaptation of NIRS for

investigations in urology is appealing due to its sensitive and non-invasive measurements.

Traditional urological measurements of bladder function require insertion of multiple catheters,

causing discomfort and risk for infection. NIRS allows transcutaneous measurement of the

bladder, as it resides rather superficially in the lower abdomen just proximal to the symphysis

pubis. Due to its accessibility, the detrusor (visceral muscle of the bladder) has been investigated

with NIRS techniques similar to that of skeletal muscle investigations. Adapting NIRS to

monitor the bladder was first established by Macnab et al. 2005, and through this research NIRS

has demonstrated its ability to be used as an effective clinical tool for monitoring and diagnosing

urological pathologies.59,79

More recently, this group of UBC based researchers have been adapting NIRS

technologies to examine the skeletal muscle of the female pelvic floor in attempt to address

clinical issues related to LUTS, PFM dysfunction and pelvic organ prolapse.59 Shadgan et al.

2008 developed the first probe for assessment of the PFM in relation to urinary incontinence.74

16

This design utilized CWS NIRS to provide simultaneous tracings of the detrusor and the mid-

urethral sphincter for the purposes of monitoring bladder function in females with stress

incontinence.74 The data collected from the NIRS probe was reported to be reproducible and

consistent with NIRS oxygenation trends captured by their transcutaneous bladder

measurements. Furthermore, they were also able to demonstrate NIRS measurements of

voluntary PFM contractions were consistent with physiologic responses of typical voluntary

skeletal muscle contractions measured with NIRS.74

This prior prototype, although capable of measuring multiple structures of the lower

urinary tract, required repositioning for each targeted site (bladder, urethra, right and left PFM).

Utilizing the same CWS NIRS technology, a new transvaginal NIRS probe will be designed,

allowing simultaneous measurement of bilateral PFM with maintained positioning, in order to

assess the hemodynamic and oxygen kinetic response of the PFM during exercise. Current

devices used to objectively assess this muscle group assess the muscle as one functioning unit,

and do not always account for asymmetry that might occur from weakness to a specific side of

the muscle. This is of particular importance for the female population with LUTS and underlying

nerve impairment, as asymmetrical muscular function of the PFM might occur due to

neurological impairment causing differential motor and sensory function on contralateral sides of

the body.80-82 With this instrument it was planned to compare the hemodynamic trends and

oxygen recovery kinetics of the PFM in response to exercise. These parameters will be assessed

in females with continence (controls) and in females experiencing LUTS due to neurologic

conditions and injury (cases). Both groups will be exposed to a PFMT regime to evaluate

whether a training response in the PFM can be captured by NIRS measures of hemodynamics

and oxygen recovery kinetics.

17

1.3 Objectives and Hypotheses

1.3.1 Primary Aim

The primary aim of this project is to develop a transvaginal NIRS probe capable of

isolating bilateral PFM oxygenation and to determine the feasibility of utilizing NIRS derived

parameters obtained with this probe. Furthermore, this project aims to objectively measure NIRS

parameters of hemodynamics and oxygen recovery kinetics in females with LUTS due to

impaired pelvic innervation (cases) and in continent controls (controls) to determine if beneficial

PFMT training effects can be captured with NIRS instrumentation.

1.3.2 Objectives

The secondary objectives supporting this primary aim are to:

1. Compare oxygen kinetic responsiveness of bilateral PFM as detected by NIRS.

2. Compare NIRS derived parameters to currently used objective parameters of PFM

function derived by manometry.

3. Determine if lower limb dominance contributes to bilateral PFM function.

4. Evaluate the effectiveness of PFMT on NIRS and manometry parameters of PFM

function.

5. Evaluate the impact of PFMT to reduce clinical symptom of LUTS and PFM

dysfunction and improve QOL.

6. Determine how PFMT adherence influence effectiveness of PFM function

improvement and symptom reduction in the cases group.

18

1.3.3 Hypotheses

1. Oxygen kinetic responses of bilateral PFM detected by NIRS will present differences

contralaterally in the case group and similarities contralaterally in the control group.

2. NIRS derived parameters will demonstrate a relation to manometer parameters of

PFM function.

3. Lower limb dominance will be related to bilateral imbalances of PFM.

4. PFMT will improve the proficiency of oxygen kinetics as measured by NIRS and

PFM strength and endurance as measured by manometry.

5. PFMT will reduce clinical symptoms and improve QOL, as measured by validated

questionnaires.

6. Higher PFMT adherence rates will demonstrate greater effectiveness of PFM function

improvement (as measured by NIRS and manometer variables) and demonstrate

greater reduction in clinical symptoms (as measured by validated questionnaires),

within the case group.

19

Chapter 2: Methods

This chapter will provide a detailed description of the methodology of the entire research

project. The eligibility and protocol for participant involvement is described. The objective and

subjective outcome measures are identified, along with the utilized equipment and the means to

which measurements were conducted. A thorough description of the technical development of

the prototype for the NIRS probe is provided. Careful consideration is given in addressing how

outcome measures were analyzed and the rationale for how analysis was conducted.

2.1 Participants

Inclusion criteria for study participants included females 19 years of age or older who

experience urinary leakage, have a history of neurological condition for > 6 months and able to

communicate in English. Inclusion criteria for control participants included females 19 years of

age or older who do not currently experience urinary leakage or bladder symptoms, no history of

a neurological condition and able to communicate in English. Exclusion criteria for all

participants included the following: pregnancy or planned pregnancy, post-partum < 2months,

pelvic radiotherapy, pelvic pain symptoms, use of indwelling catheter, pelvic organ prolapse

beyond introitus, atrophic vaginitis, hypertonic pelvic floor muscles, skin break down of

perineum, orthopedic or cognitive impairment that does not allow for physical exercise.

A total of 45 individuals were screened for eligibility for the case group following

referral from physician or poster recruitment advertisement. Of these individuals 6 did not meet

the criteria. Of the 39 individuals that did meet the criteria for inclusion in the study group after

initial screening 25 individuals decided not to proceed with participation. The remaining 14

individuals were enrolled in the study and all had a baseline assessment. However, one

20

participant began menstruation during baseline assessment, therefore assessment ceased at this

time and the participant subsequently withdrew from further participation. Two participants

experienced falls (unrelated to study procedures) during the home-based PFMT intervention and

were unable to complete follow-up assessment. Two participants reported vaginal discomfort

with attempted manometer insertion at baseline and were therefore excluded from further

participation in the study. One participant completed the study to post assessment but reported

vaginal discomfort on attempted final manometer insertion, and therefore this final measure was

not collected for this participant. Upon baseline assessment one participant was unable to stand

safely on the force plates, and therefore this measure was not collected for this participant. Of

these 14 enrolled participants, 10 participants completed the entire baseline assessment and 8

participants completed their post-PFMT assessments.

Of 31 control participants screened, 4 individuals did not meet the criteria as they

reported bladder symptoms and 12 individuals decided not to proceed participation. The

remaining 15 individuals were enrolled in the study and had a baseline assessment.

2.2 Protocol

This pilot study utilized a prospective, non-randomized study design with pre and post

comparisons. All of the testing took place at the Blusson Spinal Cord Centre, located in

Vancouver, British Columbia, Canada during the time period of November 2016 to April 2018.

Complete protocol of the study was approved by the University of British Columbia’s Research

Ethics Board and by the Vancouver Coastal Health Research Institute Ethics Board. All

participants provided written informed consent prior to participation. All assessments were

scheduled around participants menstruation cycles to avoid active menstruation during

21

assessment appointments. At baseline assessment demographics and health history reviewed,

including parity and delivery type, neurological history, surgical history, urinary incontinence

symptoms and treatments, and current medications. A physical activity Life Style Index score

was given based on participant’s subjective report of being: “Sedentary” (no physical exercise

during the week, score of 0), “Moderate” (20 minutes of vigorous intensity physical activity 3

days a week, score of 1) or “Active” (30 minutes of moderate intensity physical activity 5 days a

week, score of 2).

PFM function was assessed at baseline and after 8-weeks of home-based PFMT

intervention (post-PFMT). Standardized PFMT instruction was provided to participants at the

completion of the baseline assessment. The PFMT was based on previous work by Bø et al.

1990,18 who conducted a study that compared two types of home-based PFMT to address SUI.

Their first PFMT intervention consisted of 8-12 strong contractions repeated 3 times throughout

the day.18 Their second PFMT intervention included this first regime along with weekly

45minute instructor-based sessions that consisted of supervised contractions in lying, sitting and

standing positions.18 Based on their results women with SUI in both the assigned intervention

groups showed significant improvement in PFM strength as measurement by manometer after 1-

month of PFMT.18 These improvements were maintained at 6-months follow-up in the first

regime group and continued to improve at 6-months with the second regime group.18 The PFMT

regime for this current study incorporated the lying, sitting and standing contractions from Bø et

al.’s 1990 supervised sessions which participants were required to perform daily at maximum

effort.18 As each contraction was to be repeated 6-8 times, participants would be performing at

minimum, the same amount of contractions as Bø et al.’s 1990 home-based PFMT.18 In

combining these two exercise regimes into one it was intended to elicit and improvement in PFM

22

strength and fitness within our constructed time span of 2-months. Participants were given

instruction on how to perform all PFMT exercises and given the opportunity to seek clarification,

demonstration and practice. A written instruction sheet of each exercise was given to participants

along with an exercise recording sheet (example in Appendix). Participants were required to

perform the standardized PFMT daily for the duration of 8-weeks. Case group participants were

also instructed on how to perform 3-day bladder diaries and materials required to complete

bladder diary were supplied to participant (example in Appendix). Participants completed

bladder diaries 3-days prior to initiating PFMT and 3-days after completion of 8-week PFMT.

Figure 2.1 Flow diagram for study procedures from baseline to post-PFMT assessment.

23

2.3 Objective measures

2.3.1 Urinalysis and post void residual volume

Upon each visit the participant was requested to arrive with a comfortably full bladder in

order to collect a urine sample and measure post void residual volume. The participant was

instructed on how to properly collect a clean catch midstream urine sample in a sterile urine

container. The participant was also instructed to ensure they voided to perceived complete

emptying, to ensure urine collection did not interfere with complete voiding. The void was

performed in a bathroom just outside the examination room and once the participant returned to

examination room urinalysis was performed on their sample to rule out presence of urinary tract

infection. Siemens Multistixâ 5 reagent strips were used for urinalysis, which tested for

leukocytes, nitrites, protein, red blood cells and glucose. Based on negative findings the

assessment proceeded, positive findings would prompt follow-up with physician and result in

rescheduling until urinary tract infection resolved.

Following urinalysis, the post void residual volume (PVR) was assessed. For this

measure participants were positioned supine on an examination table, scanner settings were

selected as appropriate (depending whether the female had a hysterectomy or not), a water-

soluble lubricant was applied to the pubis, the symphysis pubis was used as a landmark and the

handheld ultrasound was placed 1 inch above the landmark in a downward direction towards the

bladder. Only scans that indicated accurate placement were used to report the PVR volume

measured using a bladder scanner (BladderScanâ BVI 9400, Verathon).

24

2.3.2 Standing force plate

Following PVR assessment participants performed a standing force plate measurement

under two different conditions to quantify percentage of total body weight distributed across the

bilateral lower limbs as determined by ground reaction force (Fz). Force plate equipment used

was that of Bertec; Columbus, Ohio, United States. The participants were positioned in an

upright standing position on the center of two individual side-by-side force plates so that the left

foot was in the center of force plate 1 and the right foot was in the center of force plate 2. Under

the first standing condition participants were not instructed on how to stand, only to not move

their feet, and they were distracted with a video on a screen centred directly in front of them. The

participants were instructed to watch the video which reviewed concepts of pelvic floor muscle

function and contraction. Participants were instructed not to attempt any of the contractions

mentioned in the video while in the standing position. During the duration of this video 3

separate force plate measures were collected for 60-seconds each. After completion of the video

the participant was informed that force plate data had been collected at this time to determine if

altered body weight distribution occurred during distracted standing. This condition was

determined as distracted stance (DisFz). Following this the participant was instructed to stand as

straight, still and centered as possible, while maintaining their feet in the aforementioned

positions, for the duration of 60-seconds. This was considered as quiet stance (QFz). All force

plate data was collected at a sample rate of 100Hz and a low pass filter of 5. Data was

subsequently analyzed in Matlab.

25

Figure 2.2 Force plate configuration for lower limb dominance measures. Force plates within the floor, “X” marked indicators for left and right foot placement during both distracted and quiet stance. During distracted stance video played in front of participant on supported video screen.

2.3.3 PFM manometry

Prior to starting PFM assessment, the participant was given verbal overview of basic

PFM anatomy, function and contraction. Participants were then allowed to practice contractions

and examiner monitored to make sure no accessory muscles were being used. Once participant

felt comfortable performing a contraction examiner confirmed ability of subject to contract PFM

with visual inspection of perineal elevation.1,8 Participants were positioned in the supine

position, knees bent and hips flexed with external rotation so that soles of feet were touching, in

order to minimize accessory muscle contraction.83 The PFM manometer used in this study was

the Peritronâ by Laborie. Individual single use vaginal sensors were used for each participant

and infection control procedures were followed as per manufacturer guidelines and institution

standards. A water-soluble lubricant was applied to manometer prior to insertion and following a

resting time of 60-seconds to allow PFM to relax after response to insertion, a series of

standardized PFM contractions were conducted. Participants completed a set of 3 maximal

voluntary contractions (MVC) where they were instructed to contract the PFM as strong as

26

possible and to relax once they felt they reached their strongest effort. Each MVC was separated

by a 10-second recovery. After the final MVC there was a 5-minute recovery period prior to the

next contraction which was 1 sustained MVC (SMVC), where they were instructed to contract

their PFM as strong as possible and to hold the strong contraction for as long as possible before

allowing their PFM to relax. Another 5-minute recovery period followed the SMVC prior to

conducting a set of fast repeated contractions (REP) to point of perceived exertion. For the REP

participants were instructed to perform quick PFM contractions as strong as possible and quickly

relax, and to continue repeating this until they feel they can no longer perform a strong

contraction (feeling of perceived exertion). Following the REP set there was a 10-minute

recovery period prior to conducting the same set of PFM contractions with the NIRS probe.

Upon completion of PFM contractions with the NIRS probe there was another 10-minute

recovery before the manometry measures were repeated. The purpose of repeating the

manometer measures after the NIRS was to allow for assessment of learner effect and effort

consistency/muscular fatigue since the manometer and NIRS measurements were not occurring

simultaneously.

Figure 2.3 PFM manometer. (Peritronâ by Laborie) used for objective pressure measurements in cmH2O of PFM strength and endurance. Individual single-use vaginal sensors used for each participant.

27

2.3.4 NIRS

The NIRS probe that was used for assessment of PFM for this study was of original

design. This design was structured from a previous NIRS probe prototype created by Shadgan et

al. 2008, which utilized continuous wave NIRS and provided simultaneous tracings of the

detrusor and the mid-urethral sphincter for the purposes of monitoring bladder function and

related incontinence.74 They reported reproducible data with consistent NIRS oxygenation trends

when compared to the NIRS data during transcutaneous measurements of the bladder.74 With

this first prototype they were also able to demonstrate that NIRS measurements of voluntary

PFM contractions were consistent with the physiologic response of typical voluntary skeletal

muscle contractions measured with NIRS.74 When testing the feasibility of this prototype they

also determined that movement artifact did not appear to compromise the NIRS tracings as

positioning was well maintained with the probe handle.74

Based on this prototype and using the same continuous wave NIRS equipment,

(OXYMON MK III, Artinis Medical Systems BV, The Netherlands), a dual channel (2x1) set up

consisting of one emitter and one receiver fiber optic cable were secured on parallel sides of a

transparent disposable speculum. Due to size constrictions of the speculum, miniature fiber optic

cables were attached to standard fiber optic cables which were secured together via an

attachment block. Both the standard and miniature fiber optic cables were screwed into to the

attachment block and the block itself is completely opaque and black in colour to prevent any

external light contamination at the attachment point. During tracings this attachment block was

also covered with an opaque black cloth to further prevent against environmental light

contamination. The ends of the miniature fiber optic cables where actual NIR light transmission

and detection occurs are referred to as the optodes. These optodes were secured to a base foam

28

inlay to ensure consistent position of optodes within the speculums across all measurements.

Placement of the foam inlay was positioned such that optodes were a 2 cm distance from the end

of the probe. This was done with the intention that with transvaginal insertion the optodes would

be emitting/receiving light into the PFM tissue at the same location where the manometer

pressure sensor would be detecting pressure changes from the PFM. The interoptode of each

emitter and receiver was set at 20 mm to yield a tissue penetration depth of 10 mm directly into

the PFM microvasculature. Figure 2.4 provides image of NIRS probe design and Figure 2.5

provides detailed images for NIRS probe configuration and equipment configuration.

Figure 2.4 NIRS probe prototype design. Dual channel (2x1) set up consisting of one emitter and one detector fiber optic cable secured within foam inlay on parallel sides of transparent disposable speculum. Individual single-use speculum for each participant, image without condom cover.

NIR was light transmitted at 766nm, 861nm, 906nm and 971nm. Data captured at 10Hz

included raw optical data from O2Hb, HHb, and calculated values were derived from this raw

data. The first being the sum total hemoglobin (tHb) where tHb= O2Hb + HHb, and the second

being the difference in hemoglobin (Hdiff) where Hdiff= O2Hb – HHb. All raw and calculated

variables produced simultaneous, real time tracings of right and left musculature during NIRS

measurements. A fixed DPF of 4 was used based on previous studies employing the same NIRS

equipment investigating skeletal muscle tissue.70,84,85 Two important factors for maintaining the

trace quality are the laser output setting and the receiver gain. For this study the “Brain” laser

29

output setting was used instead of the “Muscle” setting as the “Brain” setting yields a higher

intensity of light and results in a better signal to noise ratio. The receiver gain level determines

the degree of amplification of the received signal and must be set at a level to optimize the

saturation of received light. Saturation percentages allow you to monitor the quality of trace by

indicating levels that are too low or too high. Levels that are too low indicate that all transmitted

light is being absorbed by the tissue and not enough light is being detected by the receiver to

produce a reasonable signal.57 Levels that are too high indicate over saturation of the received

light signal which indicates contamination from environmental light, resulting in reduction of

received signal and lower detected concentration values.57 Gain settings were adjusted at the

beginning of each measurement to prevent over saturation and maintain acceptable signal

strength within the range of 1-20%.57

In order to collect NIRS probe measurements with participants a new speculum was fitted

with the NIRS configuration as previously described for individual measurement and the NIRS

probe was covered with a latex free condom. The participant was positioned supine with legs in

the “butterfly” position, similar to that of the manometer measurement condition. The probe was

then inserted transvaginally to indicated insertion point. The NIRS laser output was then turned

on and once acceptable signal percentages were confirmed, the trace was biased to arbitrary zero.

Resting baseline values were then recorded prior to initiating the same protocol for PFM

contractions as described above in the manometer section (3 MVCs, 1 SMVC, REP).

30

Figure 2.5 NIRS probe prototype design details and equipment configuration. Both vaginal sensor for manometer and NIRS probe were individual single-use, NIRS probe shown without condom cover.

2.4 Subjective measures

2.4.1 Bladder symptom questionnaires

Participants in the case group were asked complete the Incontinence Impact

Questionnaire (IIQ-7),7,86,87 and the Urogenital Distress Inventory (UDI-6),86,87 at baseline and

post-PFMT assessments. All participants completed the Questionnaire for Urinary Incontinence

Diagnosis (QUID),88 at baseline and post-PFMT assessment. All participants were also asked to

complete a subjective assessment of bladder symptom improvement after completion of the

home-based PFMT. This subjective survey of improvement (which will be referred to as SSI in

this document), was developed by Bø et al. 1990, and it utilizes a Likert scale of 5 to assess for

31

self-identified changes categorized as worsened: (1), unchanged (2), improved (3), almost

continent (4) or continent (5).18

2.4.2 Waterloo footedness questionnaire

Following the force plate measurements at baseline all participants were asked to

complete the Waterloo Footedness Questionnaire-Revised version (WFQ).89 This is a validated

questionnaire to determine footedness preference. It asks a series of 10 imagined scenario

questions were participants must answer: Left always, Left usually, Equal, Right usually, Right

always. These answers are assigned with corresponding values from -2 to 2 to provide a

footedness preference score. Therefore, the minimum score of -20 would indicate the greatest

left footedness preference and the maximum of 20 would indicate the greatest right footedness

preference.

2.4.3 Bladder diaries

Participants in the case group were required to complete bladder diaries. At baseline

participants were instructed on how to complete a 24-hour 3-day bladder diary and were given a

urinary hat in order to measure all urinary output. The 3-day bladder diary has been validated in

previous literature.90 Participants were instructed to complete a baseline 3-day bladder diary

immediately prior to initiating home-based PFMT. Participants were also instructed to complete

an additional 24-hour 3-day bladder diary immediately after completing the 8-week home-based

PFMT, prior to post-PFMT assessment. An example of how to record fluid intake, urinary output

and urinary events in the diary was also provided to the participants.8 (Example of bladder diary

provided in Appendix).

32

2.5 Data analysis

2.5.1 Standing force plate and WFQ

Matlab was used to calculate the percentage of total ground reaction force (Fz) distributed to

both the right and left lower limbs. The 3 trials of distracted stance were averaged. A calculation

was then performed in SPSS to both the averaged distracted stance condition and to the quiet

stance condition to determine Fz Ground Limb Dominance:

Fz Limb Dominance = RFz-LFz

This calculated Fz Limb Dominance value difference between ground reaction force measured

from right limb (RFz) and left limb (LFz). A positive value indicates right limb dominance and a

negative value indicates left limb dominance. The Wilcoxin Signed Rank test was performed to

compare Fz Limb Dominance between Distracted and Quiet stance conditions. A Paired-T Test

was performed to compare Fz Limb Dominance between Distracted and Quiet stance conditions

for the study group.

Spearman’s Rank Correlation was performed to test association between the absolute WFQ

scores and the Fz Limb Dominance in Distracted and Quiet stance conditions separately within

each the control and case groups.

2.5.2 SMVC focused analysis

PFM assessment was carried out in the nature of performing MVCs, SMVCs and REPs

as described and recommended by Laycock and Jerwood 2001 and Devreese et al. 2004.1,91,92

NIRS tracings from this full assessment were used in consideration of the functionality of the

33

tool itself and for the consideration of observational trends which will be further characterized in

the results section.

Although a full PFM assessment was performed, the objective NIRS analysis centred on

the SMVC only. This was done in order to focus the results of the investigation on the ability of

NIRS to detect oxygen recovery kinetics of the PFM. Rationale to do so is supported by the

previous literature of Muthalib et al. 2010, who reported SMVCs are more likely than other

contractions to demonstrate the O2 demand of the muscle tissue under investigation, as it requires

more continued force production than MVCs and does not allow for the amount of resaturation

which occurs during fast repeated contractions.93 The resaturation that occurs during fast

repeated contractions allows for measure of the balance between O2 demand and O2 supply, as

the tissue attempts to maintain equilibrium during a repeated task. As we were mostly interested

in the O2 demand experienced by the PFM, we focused our analysis and objective outcome

measures with values obtained from SMVC only. The SMVC in other PFM literature is also

considered a good measure of both strength and endurance, compared to that of MVC which is

considered to assess strength alone.1,30,94

2.5.3 PFM manometry

The peak pressure of each contraction and the average pressure achieved during each

contraction was evaluated for change from baseline to post-PFMT assessment. These pressure

values were directly recorded from the manometer output. Prior to each contraction the

manometer was set to zero while it remined in situation transvaginally to give absolute pressure

change during the contraction. The peak and average pressures, along with the duration of each

SMVC were used for analysis.

34

Due to participant follow-up attrition the sample size between baseline and post-PFMT

assessments is variable both among the control and case groups. For analysis of manometer

measures among the case group at baseline assessment N = 11 (SS1, SS3, SS4, SS5, SS7, SS9,

SS10, SS11, SS12, SS13, SS14). For analysis at post-PFMT assessment N = 7 (SS1, SS3, SS9,

SS10, SS12, SS13, SS14), SS7 did not complete post-NIRS manometer measurements due to

reporting discomfort. As only the pre-NIRS manometer measurements ended up being used in

analysis as will be described further in this section, analysis for manometer outcomes between

baseline and post-PFMT assessment N=8 (SS1, SS3, SS7, SS9, SS10, SS12, SS13, SS14). For

analysis of within assessment manometer measures among the control group at baseline

assessment N = 14 (CS2 excluded as data missing from post-NIRS manometer measurement).

For analysis within post-PFMT assessment and between baseline and post-PFMT assessment N

= 13 (CS3 and CS5 withdrew after baseline assessment).

Paired sample statistical testing was performed for SMVC Peak cmH2O, SMVC Average

cmH2O and SMVC Timesec for the within session (both at baseline and post-PFMT assessment

individually) pre and post NIRS manometer measurements to assess for evidence of muscular

fatigue and learner effect. Since there was no significant difference found, except in one variable,

post-PFMT assessment Average cmH2O, which still was highly positively correlated, the pre-

NIRS manometer measurements were used for analysis for paired sample statistical testing of

manometer measurements across sessions, comparison to NIRS measurement outcomes and to

interventional exercise adherence.

35

2.5.4 NIRS

Prior to all NIRS analysis a filter was applied to smooth the data. This filter was the Moving

Gaussian Average which is a generic smoothing filter to reduce high frequency noise. This filters

at a width of 1second and calculates the average within that 1second time point.57 This filter is a

function inherent to the Oxysoft software. Similar filters have been utilized in other NIRS

investigations.55,56,95 Also prior to analysis of each contraction (MVCs, SMVC and REPs) the

NIRS tracing was set to arbitrary value of zero and the averaged 30seconds prior to the onset of

each type of contraction was used as the baseline and calculated within the Oxysoft

software.85,93,95-97 Although four NIRS variables were collected during the measurements (O2Hb,

HHb, tHb, HbDiff) only HbDiff was selected for analysis. tHb is representative of blood volume

and shifts in volume are indicative of blood flow changes, therefore it is a value used to assess

hemodynamic changes within the muscle.97 HHb was not assessed independently as a NIRS

variable as it has been determined by previous literature to be an unreliable means of

measurement when employing occlusion free ½RT analysis (which was used in this study and

will be explained further in this section).85 Whereas O2Hb and HbDiff represent relative oxygen

saturation, HbDiff (in occlusion free ½RT analysis) is considered to be more indicative of

metabolic changes within the muscle tissue, and less susceptible to blood flow changes than

O2Hb.67,85,93,98-101 The responsiveness of HbDiff during exercise is a measure of coupled oxygen

demand and supply, and when in recovery from exercise it reflects an index of oxygen

delivery.99

Due to participant follow-up attrition the sample size between baseline and post-PFMT

assessments is variable both among the controls and case participant groups for NIRS

measurements. Also, four earlier NIRS measurements (CS2, CS3, CS4, SS1) had to be excluded

36

from analysis due to inaccurate signal transmission, which was later corrected with adjusted

foam inlay as described previously in this section. For analysis of NIRS measures among the

case group at baseline assessment only N = 10 (SS3, SS4, SS5, SS7, SS9, SS10, SS11, SS12,

SS13, SS14). For analysis at post-PFMT assessment and across baseline and post-PFMT

assessment N = 7 (SS3, SS7, SS9, SS10, SS12, SS13, SS14). For analysis of NIRS measures

among the control group at baseline assessment N = 12 (CS1, CS5, CS6, CS7, CS8, CS9, CS10,

CS11, CS12, CS13, CS14, CS15). For analysis at post-PFMT assessment and across baseline

and post-PFMT assessment N = 11 (CS1, CS6, CS7, CS8, CS9, CS10, CS11, CS12, CS13,

CS14, CS15).

2.5.4.1 Oxygen saturation patterns in response to exercise

Peak magnitude change of the HbDiff NIRS variable was determined by the following

means. The maximum magnitude change of each NIRS variable reached during every

contraction was subtracted from its corresponding baseline value. Magnitude values were based

on oxygen saturation patterns. The oxygen saturation pattern observed during PFM contraction

and corresponding recovery interval is important to take into consideration, as saturation trends

during exercise are an indicator of oxygen stress experienced by the muscle during exercise,

while the oxygen saturation pattern in recovery indicates an oxygen deficit induced by

exercise.102 Chance et al. 1992 describe how the observation of oxygen desaturation occurring

with exercise represents an oxygen demand exceeding the ability of oxygen delivery mechanisms

to maintain consistent oxygenation to the muscular capillaries, implying increased rate of oxygen

consumption.93,102 Inversely, an increased oxygen concentration, or restaturation, pattern

37

indicates that oxygen delivery is greater than that of the muscular oxygen demand, implying

reduced oxygen consumption and return to hemostatic balance within the tissue.93

Therefore, magnitude changes occurring during contractions were assessed based on their

oxygen saturation pattern. In contractions where desaturation was identified the greatest

minimum value reached during contraction was subtracted from the baseline. For contractions

where increased saturation occurred the greatest maximum value reached during contraction had

the baseline subtracted from it. The calculated peak magnitude change during contraction is

referred to in this study as DMag.

Pattern Contraction Recovery 1 Desaturation Resaturation 2 Desaturation Desaturation 3 Increased saturation Resaturation 4 Increased saturation Desaturation (to baseline) 5 No response No response 6 No response Increased saturation 7 No response Desaturation 8 Increased saturation Desaturation 9 Desaturation Resaturation (to baseline)

Table 2.1 SPAM stratification of oxygen patterns. Stratification of oxygen saturation patterns observed during PFM contraction and corresponding 90-sedond recovery interval.

The peak magnitude changes of the Right and Left PFM at baseline assessment were

compared with paired sample statistical testing. Likewise, the peak magnitude changes of Right

and Left PFM at post-PFMT assessment were compared with paired sample statistical testing.

Also, the peak magnitude changes of Right PFM at baseline and post-PFMT assessment and Left

PFM at baseline and post-PFMT assessment were compared with paired sample statistical

testing.

38

2.5.4.2 Unilateral PFM dominance based on contraction magnitude change

Once the Peak DMag were calculated based, all values were converted to absolute values, in

order to determine unilateral PFM dominance. Dominance was determined based an algorithm

accounting for saturation patterns, (Saturation Pattern Algorithm for PFM Dominance-SPAMD),

which is shown below in Figure 2.5. Ultimately this algorithm calculated dominance by

subtracting the absolute Peak DMag of the Left PFM from the absolute Peak DMag of the Right

PFM. This yielded positive values indicative of Right DMag dominance and negative values

indicative of Left DMag dominance. These values were then correlated to Fz scores in Distracted

and Quiet stance conditions, as well as to WFQ scores.

Figure 2.6 SPAMD algorithm. SPAMD algorithm for using saturation patterns to calculate unilateral PFM dominance.

39

2.5.4.3 Oxygen recovery kinetics in response to exercise (Half Recovery Time)

The ability of skeletal muscle to recover from the oxygen deficit induced by exercise

represents the oxidative metabolism of the muscle and implies muscular fitness, or aerobic

capacity in that a muscle tissue has greater aerobic capacity when it is quickly able to restore

depleted oxygen saturation levels after exercise.102,103 Early investigations with NIRS determined

that the time of oxygen recovery following exercise can be used as a means to assess oxygen

delivery deficits in relation to oxygen consumption.98,101,102 The specific NIRS variable of

HbDiff (HbDiff = O2Hb-HHb), a calculation is an inherent function of the Oxysoft software and

occurs in real time with the recorded measurements, is thought to represent deoxygenation102

and provide a stronger signal for analysis.104 Modern NIRS CWS-SRS equipment is able to

provide a more accurate and absolute value of deoxygenation, the tissue saturation index (TSI).

When measured in conjunction with transient occlusions to control for blood volume, TSI

provides a validated and reliable means of noninvasively assessing respiratory capacity in

skeletal muscle.46,97,105 These current TSI and occlusion method measurements evolved from the

early investigations of Chance et al. 1992 and McCully et al. 1994, who both developed means

of assessing the kinetics of muscle tissue recovery from exercise by calculating the half recovery

time (½RT) from the cessation point of exercise to the point of maximum resaturation in

recovery.98,102 As the NIRS equipment employed in this investigation is that of the CWS era,

methods of measurement and analysis were used based on the initial literature derived from

Chance et al. 1992 and McCully et al. 1994.102,98 McCully et al. 1994 further validated this

method by fitting the HbDiff recovery to a mono-exponential curve, which gave similar results

to the gold standard measurement of muscle oxidative metabolism with PCr under conditions of

submaximal exercise.98 McCully et al. 1997 then applied this HbDiff curve fitting in a study

40

investigating peripheral vascular disease in an elderly population. However, they found that

mono-exponential curve did not fit the majority of the HbDiff resaturation response following

cessation of exercise in this clinical population. In order to analyze their data, they employed the

½RT of HbDiff, defined as half the time duration from the HbDiff difference at the end of

exercise to near baseline and either did not change or showed overshoot for at least 30seconds.99

With this method they were able to determine that the ½RT of individuals with peripheral

vascular disease were significantly slower than controls.

Utilizing the ½RT methods, Ichimura et al. 2006 used the O2Hb variable to measure half

recovery time and determined that it was inversely correlated with Peak VO2, meaning that lower

systemic oxygenation capacity is related to having slower ½RT.101 Buchheit et al. 2010

compared ½RT calculations to ½RT mono-exponential curve fitting of O2Hb, HbDiff and HHb

and found that O2Hb and HbDiff were moderately reliable (in occlusion free methods) but not

HHb, and further suggested the ½RT calculation over mono-exponential curve fitting as it can be

applied to more complex data sets.85,95,103 Based on this literature the ½RT calculation (for both

HbDiff and O2Hb) method was used in this analysis in order to assess the muscle oxidative

metabolism of PFM. All of these previous studies had varying recovery time intervals defining

their ending points, based on Muthalib et al. 2010. As they had the most similar exercise

protocol, we utilized their recovery time interval as 90-seonds following cessation of exercise,

which was also used by DeLorey et al. 2002.97,106

41

Figure 2.7 Example of 1/2RT calculation in control participant. NIRS trace of Right SMVC in control participant and ½RT calculation. Vertical green bars denote the onset and cessation of SMVC contraction.

2.5.4.4 Original adaption of ½RT calculation analysis

As we were investigating a population with impaired motor function due to neurologic

conditions, the typically oxygen saturation response expected to be observed did not always

occur in the study subjects. Rather, with some attempted contractions the inverse of the expected

was observed, in that there would be an increase of oxygenation during the active contraction

phase and desaturation (either returning to baseline or continued desaturation) during the

recovery phase. As it is known that increased saturation means the oxygen supply is greater than

oxygen demand,102 in cases where this atypical saturation pattern was observed it suggests a

hemodynamic response, almost a priming response, to supply the muscle with extra oxygen to

support anticipated oxygen consumption. However, no oxygen consumption occurs (lack of

desaturation during contraction) meaning the PFM are not actively engaging or have a weak

contraction with small oxygen demand, which the oxygen delivery exceeds, then returning to

baseline with the relaxation in recovery phase. The presence of continued desaturation beyond

the baseline levels would suggest an inability to fully relax the PFM after attempted contraction.

42

In cases where saturation patterns did not present with desaturation during contraction but rather

an increase of oxygen saturation with desaturation return to baseline or continued desaturation in

90 second recovery period an Inverse ½RT calculation was used. Inverse ½RT determined as

half the time to reach the difference value between the highest saturation point in HbDiff at end

of contraction and the lowest point of desaturation in the recovery period.

Figure 2.8 Example of inverse 1/2RT calculation in a case participant. NIRS trace of Right SMVC in case participant and Inverse ½RT due to an oxygen saturation pattern, Pattern 8 as per stratification Table 2.1. Vertical green bars denote the onset and cessation of SMVC contraction.

The ½RT of the Right and Left PFM at baseline assessment were compared with paired

sample statistical testing. Likewise, the ½RT of Right and Left PFM at post-PFMT assessment

were compared with paired sample statistical testing. Also, the ½RT of Right PFM at baseline

and post-PFMT assessments and Left PFM at baseline and post-PFMT assessments were

compared with paired sample statistical testing.

2.5.4.5 Unilateral PFM dominance based on ½RT

Unilateral dominance of PFM based on ½RT was calculated to provide a means of

comparison to force plate measurements, WFQ scores and NIRS derived magnitude changes.

43

The calculation was completed by subtracting Left PFM from Right side to give a (+) value for a

quicker Right Sided ½RT and (-) value for a quicker Left Sided ½RT. This was done so that (+)

values for Right sided dominance would correspond with (+) Right sided values for the Fz

Dominance values and WFQ scores. Careful consideration was paid to contraction and recovery

saturation patterns to determine dominance when the patterns did not match, as non-matching

oxygenation patterns could indicate unilateral dominance within itself. For instance, a Right

sided SMVC with oxygen saturation pattern 1 with a concurrent Left sided SMVC with oxygen

saturation pattern 8, would imply a more responsive PFM on the right, regardless if the recovery

time is longer, as it is actually demonstrating oxygen consumption with contraction when the left

side is not. Therefore, the same algorithm, SPAMD (as shown in Figure 2.5), was used to define

unilateral DMag Dominance was also utilized for ½RT Dominance. ½RT Dominance was then

correlated to DisFz, QFz, WFQ and DMag Dominance.

2.5.5 Bladder symptom questionnaires, bladder diaries and post void residual

Intra-group pairwise comparison was performed for questionnaire scores, bladder diary

variables and PVR measures recorded at baseline and post-PFMT. For the bladder diary

comparison n=7 as SS9 did not complete bladder diaries. Inter-group independent parametric and

non-parametric comparisons were performed for QUID (SUI and UUI) and PVR. Inter-group

SSI responses of bladder symptoms improvement were reported as frequency and percentage of

individual group total.

44

2.6 Statistical analysis

Statistical analysis was performed using SPSS version 20. Data sets were analyzed with

shapiro wilk test of normality to determined when parametric or non-parametric statistical testing

should be employed. When performing independent samples testing the levene’s test was also

performed, secondary to the shapiro wilk test to determine if parametric or non-parametric

statistical testing should be employed. For all statistical testing a p-value of a <0.05 was utilized

to determine significance. As outlined by Mukaka 2012, the following parameters were used to

interpret the size of correlation coefficients: Very high correlation = +0.90 to +1.00, High

correlation = +0.7 to +0.9, Moderate correlation = +0.5 to +0.70, Low correlation +0.30 to

+0.50, Negligible correlation +0.00 to +0.30.107

45

Chapter 3: Results

This chapter will provide a detailed account of the data collected and analyzed in this

research project. Participant demographics and subjective outcome measures will be presented

first. Observational findings regarding oxygen saturation patterns captured by the NIRS probe

will be presented in terms of trends found among controls and among clinical sub-groups within

the case group. Lastly, objective outcome measures derived from the NIRS probe and the PFM

manometer are presented, along with their relation to PFMT adherence.

3.1 Participant demographics

Demographic variables for both participant groups are demonstrated in Table 3.1. The

mean age of controls and the case group was not shown to be statistically significant (p-value

0.05), although the controls on average were younger (mean 42 years compared to mean 51

years). Statistical significance was demonstrated between the parity of the two groups, the case

group having a greater proportion of participants with parity >1 (90.9% compared to 46.7%, p-

value 0.04). No significant differences were found between groups among the rest of the

demographic variables including: BMI, menopause status, life style index of physical activity

and smoking. Full summaries of demographic variables for each group at individual participant

level are provided in Table 3.2 and Table 3.3.

46

DEMOGRAPHICS STUDY SAMPLE n=26 CONTROLS n=15 CASES n=11 P-VALUE

AGE mean +SD

range

46 +14

(24 to 72)

42 +15

(24 to 71)

51 +11

(35 to 72)

.05

BMI

mean +SD range

24.6 +5.2

(19.2 to 41.5)

23.5 +3.7

(19.2 to 33.7)

26.0 +6.8

(41.5 to 19.8)

.37

PARITY 0

>1

9 (34.6%)

17 (65.4%)

8 (53.3%) 7 (46.7%)

1 (9.1%)

10 (90.9%)

.04

MENOPAUSE Pre

Post

17(65.4%) 9 (34.6%)

10 (66.7%) 5 (33.3%)

7(63.6%) 4 (36.3%)

1.00

LIFE STYLE INDEX Sedentary Moderate

Active

3 (11.5%) 9 (34.6%)

14 (53.8%)

1 (0.07%) 5 (33.3%) 9 (60.0%)

2 (18.2%) 4 (36.4%) 5 (45.5%)

.41

SMOKING Non-Smoker

Smoker

24 (92.3%) 2 (0.08%)

14 (93.3%) 1 (0.07%)

10 (90.9%) 1 (0.09%)

1.00

Table 3.1 Demographics of study sample by participant group. Mann-Whitney U-test with (2-tailed) performed for the variables: age, BMI (kg/m2) and life style index. Fischer’s Exact test (2-tailed) was performed for the variables: parity, menopause and smoking. Grouped menopause peri status into pre (only one peri-menopause status in case group). Parity grouped as nulliparous and parity>1, (parity range 0-3 for both groups).

PARTICIPANT AGE BMI PARITY MENOPAUSE ETIOLOGY of PFM

DYSFUNCTION LIFE STYLE

INDEX SMOKER

SS1 72 25.5 3 POST Post-Polio Syndrome MODERATE NO

SS3 42 22 1 PRE Non-Traumatic SCI (benign tumor in spine hemorrhage, persisting arachnoiditis) ASIA-B

ACTIVE NO

SS4 53 25.4 1 PRE Traumatic SCI (T8 incomplete paraplegia ASIA-D)

MODERATE NO

SS5 63 24.5 2 POST Multiple Sclerosis (secondary progressive)

MODERATE NO

SS7 59 20.2 1 POST Traumatic SCI (L4-L5 incomplete) & Subsequent TBI

SEDENTARY NO

SS9 48 22.3 1 PRE Labour Trauma ACTIVE YES SS10 45 25.3 1 PRE Labour Trauma ACTIVE NO

SS11 42 23.7 2 PRE Labour Trauma & Congenital Right Hip Dysplasia

ACTIVE NO

SS12 35 36.3 0 PRE Multiple Sclerosis (relapse-remitting)

MODERATE NO

SS13 57 41.5 3 POST

Spinal Stenosis (L4) & Congenital bilateral hip dysplasia (multiple surgical interventions)

SEDENTARY NO

SS14 45 19.8 2 PERI Traumatic SCI (C2-C4 incomplete) & Concurrent TBI

ACTIVE NO

Table 3.2 Demographic details of case participants listed by participant ID.

47

PARTICIPANT AGE BMI PARITY MENOPAUSE LIFE STYLE INDEX SMOKER

CS1 30 20.7 0 PRE ACTIVE NO

CS2 32 26.8 0 PRE MODERATE NO

CS3 32 33.7 0 PRE SEDENTARY NO

CS4 71 23.1 3 POST ACTIVE NO

CS5 56 19.2 3 POST MODERATE NO

CS6 24 26.9 0 PRE MODERATE NO

CS7 60 24 1 POST MODERATE NO

CS8 34 20.2 2 PRE MODERATE NO

CS9 30 22.6 0 PRE ACTIVE YES

CS10 31 22.4 0 PRE ACTIVE NO

CS11 62 22.1 2 POST ACTIVE NO

CS12 38 23.7 1 PRE ACTIVE NO

CS13 58 19.5 2 POST ACTIVE NO

CS14 32 24.7 0 PRE ACTIVE NO

CS15 33 22.5 0 PRE ACTIVE NO Table 3.3 Demographic details of control participants listed by participant ID.

3.2 Questionnaires, post void residual and bladder diary outcome measures

3.2.1 Intra-group comparison

A reduction in mean values for both control and case groups is demonstrated from

baseline to post-PFMT for all questionnaires and PVR, (Table 3.4). These reductions only

demonstrated to be statistically significant for one questionnaire variable among the case group,

and this was the QUID-UUI score (Figure 3.1). Although the case group demonstrated less

urgency symptoms as per reduction in the QUID-UUI score, there were no statistical differences

found for all variables measured in the 3-day bladder diaries completed at baseline and post-

PFMT. Results shown in Table 3.5.

48

Participant Group Variable Baseline Post-PFMT P-value Controls n=13 QUID-SUI

mean +SD range

1.46 +1.56

(0 to 5)

0.85 +0.80

(0 to 2)

.25 NP

QUID-UUI mean +SD

range 1.92 +2.66

(0 to 8) 1.23 +1.48

(0 to 4)

.55 NP

PVR (ml) mean +SD

range

48.23 +41.38

(0 to 138)

47.69 +55.55

(0 to 200)

.96

Cases n=8 UDI-6

mean +SD range

33.85 +9.82

(16.67 to 45.83)

30.73 +12.19

(12.50 to 50.00)

.31 NP

IIQ-7 mean +SD

range

35.08 +27.14

(0.00 to 66.60)

26.87 +24.98

(0.00 to 61.84)

.20

QUID-SUI mean +SD

range 4.75 +3.37 (0 to 11)

2.75 +2.25 (0 to 6)

.08

QUID-UUI mean +SD

range 7.5 +3.89 (1 to 14)

5.0 +2.33 (1 to 7)

.03

PVR (ml) mean +SD

range

51.00 +55.54 (13 to 175)

16.50 +13.40

(0 to 40)

.44 NP

Table 3.4 Intra-group comparison of questionnaires and PVR. Intra-group comparison of questionnaires and PVR measures at baseline and post-PFMT assessments. Parametric and non-parametric paired sample tests performed. NP denotes when non-parametric performed with Wilcoxin Signed Rank test (2-tailed).

Figure 3.1 Case group QUID-UUI score reduction. Case group demonstrated statistically significant (p-value 0.03) reduction in QUID-UUI score at post-PFMT compared to baseline score. * indicates statistical significance.

0

2

4

6

8

10

12

14

16

Baseline Post-PFMT

QU

ID-U

UI S

core

SS1

SS3

SS7

SS9

SS10

SS12

SS13

SS14

*

49

Variable Baseline Post-PFMT P-value

Frequency (mean count) mean +SD

range

6.74 +1.66

(4.5 to 9.00)

7.29 +1.68

(4.67 to 9.67)

.22

DVVmax (ml) mean +SD

range

416.67 +179.83

(200.00 to 733.33)

408.33 +166.18

(150.00 to 66.67)

.88

Nocturia (mean count) mean +SD

range

0.74 +0.88

(0.00 to 2.00)

0.26 +0.27

(0.00 to 0.67)

.37NP

Incontinence (mean count) mean +SD

range

0.67 +0.67

(0.00 to 2.00)

0.60 +1.29

(0.00 to 3.50)

.82

Table 3.5 Case group 3-day bladder diary variables. Comparison of recorded measures from 3-day bladder diaries completed by case group at baseline and post-PFMT. N=7 (SS9 did not complete bladder diaries). Parametric and non-parametric Paired Sample tests performed. NP denotes when non-parametric performed with Wilcoxin Signed Rank test (2-tailed). DVVmax indicates the maximum volume of one void per day. 3.2.2 Inter-group comparison of questionnaires and post void residual

Inter-group comparisons for QUID (SUI and UUI) and PVR did not demonstrate a

statistically significant difference in measured improvement from baseline to post-PFMT

assessment. Results demonstrated in Table 3.6. Results of the SSI inter-group comparison also

did not demonstrate statistical difference in how both groups subjectively rated their bladder

symptoms post-PFMT. Among the control group 6 out 13 (46.15%) reported feeling “continent”,

1 out of 13 (7.69%) reported feeling “almost continent”, 2 out of 13 (15.38%) reported feeling

“improved” and 4 out of 13 (30.77%) reported feeling “unchanged” on the SSI at post-PFMT

assessment. Among the case group 1 out of 8 (12.5%) reported feeling “continent”, 4 out of 8

(50.00%) reported feeling “improved” and 3 out of 8 (37.50%) reported feeling “unchanged” on

the SSI at post-PFMT assessment.

50

Variable Controls n=13 Cases n=8 P-value QUID-SUI

mean +SD range

-0.61 +1.56

(-4 to 2)

-2.00 +2.73

(-7 to 2)

.15

QUID-UUI mean +SD

range

-0.69 +2.53

(-6 to 3)

-2.50 +2.56

(-7 to 1)

.13

SSI mean +SD

range

3.69 +1.38

(2 to 5) 3.06 +0.90

(2 to 5) .22NP

PVR (ml) mean +SD

range

-0.54 +37.08 (-58 to 78)

-34.5 +64.33 (-175 to 13)

.14

Table 3.6 Inter-group SSI comparison. Inter-group comparison for QUID (SUI and UUI), SSI and PVR. PVR values represented are that of the change in score calculated by subtracting post-PFMT score from baseline score. Independent T-Tests (2-tailed) performed. NP denotes when Mann-Whitney U-test (2-tailed) performed.

3.3 Force plate, WFQ and NIRS dominance outcome measures

3.3.1 Intra-group comparison

During intra-group comparison the controls demonstrated a statistically significant highly

positive correlation between DisFz and QFz lower limb dominance, (rs= 0.83, p-value <0.001),

with no demonstrated difference between the values measured during either standing condition,

data shown in Table 3.7-3.8 and Figure 3.2. No positive correlation was demonstrated between

lower limb dominance and NIRS PFM dominance measures for controls, but a moderate inverse

association was demonstrated between QFz and baseline DMag Dom, refer to Table 3.9.

Although the case group suggested a moderately positive correlation between DisFz and

QFz lower limb dominance it was not statistically significant (rs= 0.61, p-value 0.06), suggesting

more variability in standing posture between the two conditions even though the pairwise

comparison did not demonstrate show any difference. Findings shown in Table 3.7-3.8 and

Figure 3.2. Similar to controls the case group did not demonstrate any correlation between lower

51

limb dominance and NIRS PFM dominance measures, refer to Table 3.9, suggesting lower limb

dominance measures did not translate to unilateral PFM dominance. Also, no correlation was

demonstrated between lower limb dominance and NIRS dominance variables at post-PFMT.

Participant Group n Variables Mean +SD P-value

Controls 14 DisFz

QFz 0.11 +0.20 0.09 +0.17

0.17

Cases 10 DisFz

QFz -0.07 +0.09 -0.05 +0.08

0.85NP

Table 3.7 Intra-group Fz lower limb dominance comparison. Intra-group comparison of DisFz and QFz measures of lower limb dominance. Parametric and non-parametric Paired Sample tests performed. NP denotes when non-parametric performed with Wilcoxin Signed Rank test (2-tailed).

Participant Group n Variables Correlation Coefficient P-value Controls 14 DisFz vs QFz rs = 0.83 <0.001 14 DisFz vs WFQ rs = -0.38 0.18 14 QFz vs WFQ rs = -0.45 0.10 Cases 10 DisFz vs QFz rs = 0.61 0.06 10 DisFz vs WFQ rs = 0.08 0.82 10 QFz vs WFQ rs = 0.21 0.57

Table 3.8 Intra-group Fz and WFQ lower limb dominance correlation. Intra-group correlation between Fz and WFQ measures of lower limb dominance. Non-parametric Spearman Rank correlation performed for all variables.

Figure 3.2 Intra-group DisFz and QFz association. Intra-group association between Distracted stance ground reaction force lower limb dominance (DisFz) and Quiet stance ground reaction force lower limb dominance (QFz). Positive value indicates right lower limb dominance and negative value indicates left lower limb dominance. Blue represents controls (rs= 0.83, p-value = <0.001). Orange represents case group (rs= 0.61, p-value = 0.06). * indicates statistical significance.

52

Participant Group n Variables Correlation Coefficient P-value Controls 12 DisFz vs Baseline ½RT Dom rs = 0.00 1.00 12 DisFz vs Baseline DMag Dom rs = -0.36 0.25 12 QFz vs Baseline ½RT Dom rs = -0.15 0.63 12 QFz vs Baseline DMag Dom rs = -0.64 0.03 12 WFQ vs Baseline ½RT Dom rs = 0.29 0.37 12 WFQ vs Baseline DMag Dom rs = 0.18 0.57 Cases 9 DisFz vs Baseline ½RT Dom rs = 0.40 0.29 9 DisFz vs Baseline DMag Dom rs = -1.00 0.80 9 QFz vs Baseline ½RT Dom rs = 0.48 0.19 9 QFz vs Baseline DMag Dom rs = -0.07 0.87 9 WFQ vs Baseline ½RT Dom rs = 0.12 0.76 9 WFQ vs Baseline DMag Dom rs = -0.48 0.19

Table 3.9 Intra-group Fz, WFQ and NIRS dominance correlations. Intra-group correlation between Fz, WFQ lower limb dominance measures and NIRS PFM dominance measures. Non-parametric Spearman Rank correlation performed for all variables.

3.3.2 Inter-group comparison

When performing inter-group comparisons there was a statistically significant difference

in the lower limb dominance in both DisFz and QFz conditions. On average the controls

demonstrated predominant Right lower limb dominance and the case group demonstrated

predominant Left lower limb dominance, which remained consistent for both DisFz and QFz

conditions (0.11 compared to -0.07, and 0.09 compared to -0.05, respectively). Findings shown

in Table 3.10 and Figure 3.3. However, it should be noted that there were 2 significant outliers in

the control group (CS6 and CS7), who demonstrated a large degree of dominance, which

remained consistent across both standing conditions.

53

Variable Controls n=14 Cases n=10 P-value DisFz

mean +SD range

0.11 +0.20

(-0.05 to 0.58)

-0.07 +0.09

(-0.25 to 0.06)

<.01

QFz mean +SD

range

0.09 +0.17

(-0.07 to 0.48)

-0.05 +0.08

(-0.22 to 0.06)

<.01

WFQ mean +SD

range

9.5 +6.36

(-3.00 to 20.00)

7.30 +9.88

(-16.00 to 17.00)

.69

Controls n=12 Cases n=10 Baseline ½RT Dominance

mean +SD range

4.96 +12.21

-0.80 to 43.40

-3.39 +25.10

-57.00 to 33.90

0.47

Baseline DMag Dominance mean +SD

range

1.12 +6.03

-6.04 to 11.03

-2.10 +4.39

-12.51 to 2.80

0.46

Controls n=11 Cases n=7 Post-PFMT ½RT Dominance

mean +SD range

1.67 +23.66

-42.80 to 61.40

-7.56 +26.92

-60.80 to 28.00

0.47

Post-PFMT DMag Dominance mean +SD

range

1.85 +7.02

-9.27 to 15.81

-6.69 +13.00

-34.23 to 3.58

0.18

Table 3.10 Inter-group Fz, WFQ and NIRS dominance comparison. Inter-group comparison of lower limb dominance and PFM dominance measures. Non-parametric Mann-Whiney U T-tests (2-tailed) performed.

Figure 3.3 Inter-group DisFz and QFz comparison. Inter-group comparison between Fz measures of lower limb dominance. Error bars represent + 1 SD. * indincates statistical significance. Distracted stance ground reaction force lower limb dominance (DisFz) and Quiet stance ground reaction force lower limb dominance (QFz). Positive value indicates right lower limb dominance and negative value indicates left lower limb dominance. Statistically significant difference between groups for both DisFz and QFz variables (p-value < 0.01).

54

3.4 NIRS observational outcome findings

3.4.1 Observational NIRS findings

Based on the inter-group observational trends the case group demonstrated more complex

NIRS tracings during measurements, reflected by atypical muscle tissue contraction and recovery

hemodynamic patterns, resulting in slower ½RT and decreased DMag changes on average.

(Please refer to Table 3.12 and 3.14, and Figures 3.20-3.21). Similarly, the exploratory findings

of Ryan et al. 2014, also suggested that individuals with a neurologic condition (amyotrophic

lateral sclerosis), tended to have slower ½RT than controls.53 It should be noted that this

research group used ½RT calculations based on occlusion NIRS methods and TSI%.

To demonstrate the observational trends found between the control and case groups

during PFM assessment an example of control participant NIRS tracings are provided,

evidencing typical hemodynamic response of muscle contraction and recovery patterns.

Following these typical hemodynamic tracings found among the control group a series of case

participant NIRS tracings are presented. Due to large heterogeneity the case group tracings were

further categorized into relevant clinical sub-groups based on NIRS tracing trends characterized

by etiology of PFM dysfunction and mobility status.

3.4.1.1 Control group trends

With each attempted contraction desaturation is demonstrated with resaturation occurring

in recovery, consistent with skeletal muscle oxygenation patterns in response to exercise as

described in previous literature.93,95,99 The following Figures: 3.4 to 3.8, demonstrate the typical

PFM response during the NIRS assessment.

55

Figure 3.4.A. Control participant CS1 performing MVCs. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction.

Figure 3.4.B. Control participant CS1 performing SMVC. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.4.C. Control participant CS1 performing REP. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.4 Control participant CS1 performing MVCs, SMVC and REP.

56

Figure 3.5 Control participant CS1 performing SMVC at baseline and post-PFMT. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.6.A Control participant CS1 SMVC oxygenation patterns at baseline. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.6.B Control participant CS1 SMVC oxygenation patterns at post-PFMT. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.6 Control participant CS1 SMVC oxygenation patterns at baseline and post-PFMT.

-9

-8-7-6

-5-4-3

-2-10

4536 4736 4936

HbD

iff C

once

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Time in Deciseconds

SMVC Baseline

Right PFM Left PFM

-14

-12

-10

-8

-6

-4

-2

0

4872 4922 4972 5022 5072

HbD

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Time in Deciseconds

SMVC Post-PFMT

Right PFM Left PFM

57

Figure 3.7 Control participant CS7 performing SMVC at baseline and post-PFMT. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.8.A Control participant CS7 SMVC oxygenation patterns at baseline. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.8.B Control participant CS7 SMVC oxygenation patterns at post-PFMT. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.8 Control participant CS7 SMVC oxygenation patterns at baseline and post-PFMT.

-15-13-11

-9-7-5-3-11

5607 5807 6007 6207 6407HbD

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Time in Deciseconds

SMVC Baseline

Right PFM Left PFM

-25

-20

-15

-10

-5

0

9104 9604 10104 10604 11104HbD

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Time in Deciseconds

SMVC Post-PFMT

Right PFM Left PFM

58

3.4.1.2 Case group trends

There was large heterogeneity among sampled population in their underlying etiology for

PFM dysfunction (as described in Table 3.2). This heterogeneity resulted in observation of

diverse PFM oxygenation patterns in response to exercise during NIRS assessments.

Observational trends of the oxygenation patterns were categorized according to clinical sub-

groups. Clinical sub-groups were categorized based on consideration of underlying etiology of

PFM dysfunction and mobility status. Mobility status was categorized in the following manner:

high mobility (not dependent on mobility aid), assisted mobility (dependent on mobility aid with

limited ability of independent ambulation), wheelchair user (wheelchair used for primary mode

of mobility). The high mobility group included four case participants (SS9, SS10, SS11, SS13,

SS14) and had the following underlying etiology for PFM dysfunction: labour trauma, congenital

hip dysplasia, traumatic SCI. The specific etiology of PFM dysfunction of each participant

within the high mobility group can be referred to in Table 3.2.

Despite participant SS12 having high mobility status, the oxygenation trends presented

more similarly to other participant, SS5, both presenting with the immune mediated neurologic

condition of multiple sclerosis (MS). Although both had MS, this neurologic condition results in

varying clinical presentations and diagnoses. SS12 had relapse-remitting MS with high mobility

and SS5 had secondary progressive MS and was as a wheelchair user. Both presented with

similar atypical characteristics, but also presented with similarity trends overlapping with the

SCI clinical sub-group. However, due to their underlying etiology of an immune mediated

neurological condition, they were categorized independently for initial observational

characterization of oxygenation pattern trends.

59

The final clinical sub-group were participants with SCI who had either assisted mobility

or were wheelchair users, which included SS3, SS4, SS7, (refer to Table 3.2 for specific

etiology). Specific to mobility status, SS3 was a wheelchair user, whereas SS4 and SS7 were

considered to have assisted mobility status.

3.4.1.2.1 High mobility clinical sub-group

Those participants in the high mobility group tended to demonstrate PFM oxygenation

patterns similar to that of the control group, generating desaturation with contraction and

resaturation during recovery phase, and exhibited on bilateral PFM. Figures 3.9-3.10

demonstrate the oxygenation patterns observed in a participant with labour trauma, congenital

dysplasia of the right hip and LUTS, with unimpaired mobility (SS11). The NIRS assessment

with this participant demonstrated typical saturation patterns, as compared to controls. Similar

tracings were also demonstrated by SS13, who had underlying spinal stenosis, congenital hip

dysplasia and multiple bilateral hip replacement surgeries, with minimal cane assisted mobility.

Similar tracings were also demonstrated by SS14. This participant has a history

incomplete traumatic C2-C4 SCI (no current ASIA score), but independent unassisted mobility,

decreased sensation to pelvis with self-reported hypersensitivity and hyper-reflexes of bilateral

lower limbs. As shown in Figure 3.11-3.12, SS14, demonstrates typical desaturation during

contraction with resaturation in recovery, similar to control group. At post-PFMT assessment

greater desaturation evidenced during contraction and resaturation in recovery is observed.

Furthermore, despite a discrepancy in magnitude change, the contraction patterns evidence

similar curve characteristics bilaterally, see Figure 3.12.

60

SS9 and SS10 were also considered to have high mobility, and both had an underlying

etiology of labour trauma. Interestingly, their NIRS tracings had boarder line trends between the

high mobility and assisted mobility clinical sub-groups. Although both displayed typical

patterning at post-PFMT, the characteristics of the patterning was less similar across bilateral

PFM, a characteristic trend found among the SCI assisted mobility group, as demonstrated in

Figure 3.19.

61

Figure 3.9.A. Case participant SS11 performing MVCs NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction.

Figure 3.9.B. Case participant SS11 performing SMVC NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.9.C. Case participant SS11 performing REP NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.9 Case participant SS11 performing MVCs, SMVC and REP.

62

Figure 3.10 Case participant SS11 SMVC oxygenation patterns at baseline. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.11 Case participant SS14 performing SMVC at baseline and post-PFMT. Case participant SS14 with traumatic SCI, SS14, performing SMVC at baseline and post-PFMT assessment. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

-5

-4

-3

-2

-1

0

1

4699 4719 4739 4759 4779HbD

iff C

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Time in Deciseconds

SMVC Baseline

Right PFM Left PFM

63

Figure 3.12.A. Case participant SS14 SMVC oxygenation patterns at baseline. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.12.B. Case participant SS14 SMVC oxygenation patterns at post-PFMT. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.12 Case participant SS14 SMVC oxygenation patterns at baseline and post-PFMT.

3.4.1.2.2 Multiple Sclerosis clinical sub-group

MS is a very complex auto-immune mediated disease attacking the central nervous

system. This progressive disease causes cell death as chronic inflammation of immune cell

infiltrates form plaques in the central nervous system, resulting in demyelination and axonal

transection.108,109 Due to this pathology the neurological deficits incurred present in a

heterogeneous manner across MS subtypes and across individuals, but often include: autonomic

and sensorimotor defects, ataxia, lower urinary tract symptoms, fatigue, visual disturbances and

cognitive difficulties.109-113 Exercise training is a common therapy used in the MS population to

help manage symptoms and promote quality of life.114,115 Ataxia and sensorimotor defects

typically cause unilateral asymmetries in muscular function,110,116 which result in dominant

muscles taking on more of the workload during functional tasks and exercise.111 Therefore,

-5

-4

-3

-2

-1

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1

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SMVC Baseline

Right PFM Left PFM

-50

-40

-30

-20

-10

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5475 5495 5515 5535

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SMVC Post-PFMT

Right PFM Left PFM

64

exercise therapy in the MS population not only aims to improve muscular strength and endurance

but also targets discoordination and muscular imbalances found with unilateral

asymmetries.111,112,116,117 As such it was expected that NIRS would capture muscular

discoordination and asymmetry in the bilateral PFM during exercise.

Figures 3.13-3.15 demonstrate oxygenation patterns observed in a participant with

relapse-remitting MS (SS12). At the time of NIRS assessments participant was not experiencing

relapse symptoms, although they did occur during the intervention phase and subsequently

remitted. Such symptoms reported by participant were impaired sensation to perineum, abdomen,

and bilateral lower limbs. Participant did not present with mobility issues and did not use any

mobility aids.

SS5 had secondary progressive MS and a wheelchair user, with inability to support

sustained weight bearing on lower limbs. For both MS participants atypical pattern presentation

during SMVC was noted with increase in oxygenation during contraction, although SS12

demonstrated a return to baseline or increased oxygenation in recovery and SS5 demonstrated

increase during contraction with return to baseline or continued desaturation in recovery.

However, both demonstrated typical patterning with REP contractions.

Although both MS participants shared these similarities in patterning, individually they

shared characteristics similar to the SCI clinical sub-group. SS5 demonstrated trends similar to

SS4 and SS7, SCI assisted mobility sub-group, in that atypical patterning was consistent across

different contractions with unilateral discrepancy, as shown in Figure 3.19. In contrast, SS12,

demonstrated patterning characteristics similar to SS3, SCI assisted mobility sub-group, in that

they both demonstrate an apparent lack of response unilateral PFM during attempted contraction,

as shown in Figure 3.14 and 3.17.

65

Figure 3.13.A. Case participant SS12 performing MVCs at baseline. SS12 in MS clinical sub-group. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction.

Figure 3.13.B. Case participant SS12 performing SMVC at baseline. SS12 in MS clinical sub-group. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.13.C. Case participant SS12 performing REP at baseline. SS12 in MS clinical sub-group. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.13 Case participant SS12 performing MVCs, SMVC and REP.

66

Figure 3.14 Case participant SS12 performing SMVC at baseline and post-PFMT. SS12 in MS clinical sub-group. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.15.A. Case participant SS12 SMVC oxygenation patterns at baseline. SS12 in MS clinical sub-group. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.15.B. Case participant SS12 SMVC oxygenation patterns at post-PFMT. SS12 in MS clinical sub-group. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.15 Case participant SS12 SMVC oxygenation patterns at baseline and post-PFMT.

-1

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3.4.1.2.3 SCI Clinical Sub-group

The NIRS observations in this clinical sub-group varied based on mobility status, in that

those with assisted mobility tended to generate more responsive NIRS tracings than the

wheelchair user, SS3, who presented with history of incomplete non-traumatic SCI at T10-12

ASIA-B, and self-reported increased sensation to left side. At both baseline and post-PFMT

assessments SS3 patterning is characterized by an apparent lack of response in unilateral Right

PFM with atypical patterning in the Left PFM, as shown in Figures 3.16-3.18.

SS4 presented with incomplete traumatic SCI at T8-T12 ASIA-D, self-reported increased

sensation in left lower limb compared to right and assisted mobility status. SS4 demonstrates

some apparent typical saturation pattern in contraction, although it is complex. As it is slower to

present on one side compared to the other and at low magnitude. Refer to Figure 3.19. There is

almost a biphasic contraction response (initial increase wit transition to decrease during

contraction), which is also suggested in SS3 left PFM at baseline. However, the larger degree of

magnitude change, in SS4 compared to SS3, with desaturation occurring in contraction, suggests

pattern characteristics more similar to the high mobility than the SCI wheelchair user.

However, the atypical and bilateral variability in oxygen patterns presenting during

recovery period, along with less stable resting periods prior to contractions is observed to be

similar of those trends seen in MS participants. SS7 demonstrated similar trends as observed in

SS4.

68

Figure 3.16 Case participant SS3 performing SMVC at baseline including full recovery time interval. Case participant in SCI clinical sub-group. Black boxes indicate beginning and end of SMVC contraction.

Figure 3.17 Case participant SS3 performing SMVC at baseline and post-PFMT. Case participant in SCI clinical sub-group. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

69

Figure 3.18.A. Case participant SS3 SMVC oxygenation patterns at baseline. Case participant in SCI clinical sub-group. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.18.B. Case participant SS3 SMVC oxygenation patterns at post-PFMT. Case participant in SCI clinical sub-group. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.18 Case participant SS3 SMVC oxygenation patterns at baseline and post-PFMT.

Figure 3.19.A. Case participant SS4 SMVC at baseline. Case participant in SCI clinical sub-group. NIRS traces include 10 seconds prior to contraction and 10 seconds after contraction. Black dotted lines denote contraction onset and cessation.

Figure 3.19.B. SS4 SMVC oxygenation patterns at baseline. Case participant in SCI clinical sub-group. Bilateral PFM HbDiff oxygenation patterns during SMVC at baseline. Starting at contraction onset and inclusive of last 10 deciseconds following end of contraction.

Figure 3.19 Case participant SS4 SMVC at baseline.

-2.5-2

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Time in Deciseconds

SMVC Baseline

Right PFM Left PFM

-0.5

0

0.5

1

1.5

2

5929 5949 5969 5989HbD

iff C

once

ntra

tion

umol

Time in Deciseconds

SMVC Post-PFMT

Right PFM Left PFM

-6-4-202468

1012

4664 4764 4864 4964

HbD

iff C

once

ntra

tion

umol

Time in Deciseconds

SMVC Baseline

Right PFM Left PFM

70

3.5 NIRS objective outcome measures

3.5.1 ½RT NIRS measurements

3.5.1.1 Intra-group ½RT comparison

When comparing intra-group ½RT at baseline only the control group demonstrated a

statistically significant difference bilaterally (p-value 0.02). On average the control group had

faster ½RT in the Right PFM compared to the Left PFM, (6.30seconds and 11.39seconds,

respectively). Despite having quicker ½RT in the Right PFM, Right and Left PFM ½RT had

high positive correlation (rs=0.76) at baseline. The control group did not demonstrate any

significant difference or association in bilateral PFM ½RT at post-PFMT. Nor was any

significant difference or association found in unilateral PFM ½RT or in ½RT Dominance across

baseline and post-PFMT assessments. Refer to Table 3.11.

Intra-group comparison for the case group demonstrated a moderate positive correlation

of bilateral PFM ½RT at baseline (rs= 0.68). The case group also demonstrated high positive

correlation between baseline and post-PFMT ½RT Dominance (r= 0.91). No other significant

findings were demonstrated among the case group when analyzing bilateral PFM ½RT at

baseline and post-PFMT, unilateral PFM ½RT across baseline and post-PFMT, or in ½RT

Dominance across baseline and post-PFMT. Refer to Table 3.11.

3.5.1.2 Inter-group ½RT comparison

Statistically significant differences were found among the ½RT of the Right PFM at

baseline, where the control group demonstrated on average faster recovery times than the case

group (mean ½RT 6.30seconds and 18.90seconds, p-value <0.01), as shown in Table 3.12 and

71

Figure 3.20. Although the control group also on average demonstrated faster ½RT in the Left

PFM as well, the difference between the two groups was not statistically significant.

Furthermore, the control group demonstrated significantly less unilateral ½RT Dominance at

baseline than the case group, (5.16 compared to 17.41, p-value < 0.01)

At post-PFMT statistical significance was demonstrated between control and case groups

for Right PFM ½RT, providing evidence that the case group had slower ½RT unilateral in Right

PFM compared to the control group, (7.87seconds compared to 38.03seconds, p-value 0.01).

Results shown in Table 3.12. Similar to the baseline inter-group comparison, there was no

statistical difference found between groups for the ½RT among the unilateral Left PFM.

Although a statistically significant difference was not determined, the case group on average did

demonstrate slower ½RT in the Left PFM (18.54seconds compared to 9.55seconds).

Interestingly, the significant difference in degree of ½RT Dominance demonstrated at baseline

between the two groups was not maintained at post-PFMT.

72

Participant Group n Variable

Mean +SD Variable

Mean +SD Pairwise P-value

Correlation Coefficient

Correlation P-value

Controls 12 Baseline Right ½RT Baseline Left ½RT

6.30 +9.75 (Lg10)0.59 +0.36 11.39 +21.83 (Lg10)0.76 +0.12 (Lg10) .02 rs= .76 <.01

11 Post-PFMT Right ½RT Post-PFMT Left ½RT

7.87 +13.34 9.55 +18.11 .72NP rs= .44 .17

11 Baseline Right ½RT Post-PFMT Right ½RT

3.66 +1.51 7.87 +13.34 .79NP rs= .18 .59

11 Baseline Left ½RT Post-PFMT Left ½RT

5.33 +2.51 (Lg10)0.66 +0.23 9.55 +18.11 (Lg10)0.69 +0.44 (Lg10) .82 rs= .06 .87

11 Baseline ½RT Dominance Post-PFMT ½RT Dominance

1.46 +1.65 1.67 +23.66 .13NP rs= .11 .76

Cases 10 Baseline Right ½RT

Baseline Left ½RT

18.90 +11.35 19.36 +19.82 .92 rs= .68 .03

7 Post-PFMT Right ½RT Post-PFMT Left ½RT

38.03 +26.93 18.54 +23.09 .12 (Sqrt)r= .45 .31

7 Baseline Right ½RT Post-PFMT Right ½RT

18.59 +10.38 38.03 +26.93 .15 r= -.23 .62

7 Baseline Left ½RT Post-PFMT Left ½RT

18.71 +20.05 18.54 +23.09 .98 (Sqrt)r= .19 .69

7 Baseline ½RT Dominance Post-PFMT ½RT Dominance

-8.20 +25.77 -7.56 +26.92 .89 r= .91 <.01

Table 3.11 Intra-group 1/2RT variables at baseline and post-PFMT. Intra-group comparison of ½RT measurements at baseline and post-PFMT assessments. Parametric and non-parametric Paired Sample tests performed. NP denotes when non-parametric performed with Wilcoxin Signed Rank test (2-tailed). (Lg10) denotes that log base-10 transformation was performed. (Sqrt) denotes that square root transformation was performed.

73

NIRS Variable Controls n=12 Cases n=10 P-value Baseline Right ½RT

mean +SD range

6.30 + 9.75

1.10 – 36.90

18.90 +11.35 2.40 – 33.90

<.01NP

Baseline Left ½RT mean +SD

range

11.39 + 21.83 1.70 – 80.30

19.36 + 19.82 1.60 – 57.00

.34NP

Baseline ½RT Dominance mean +SD

range

5.16 + 12.12 0.00 – 43.40

17.41 + 17.50 2.50 – 57.00

<.01NP

NIRS Variable Controls n=11 Cases n=7 P-value Post-PFMT Right ½RT

mean +SD range

7.87 + 13.34 2.20 – 47.80

38.03 + 26.93 3.00 – 68.60

.01NP

Post-PFMT Left ½RT mean +SD

range

9.55 + 18.11 1.80 – 63.80

18.54 + 23.09 0.90 – 60.80

.47NP

Post-PFMT ½RT Dominance mean +SD

range

10.38 + 21.08 0.00 – 61.40

15.64 + 22.49 0.20 – 60.80

.39NP

Table 3.12 Inter-group 1/2RT variables at baseline and post-PFMT. Inter-group comparison of unilateral PFM NIRS ½RT at baseline and post-PFMT assessments. Parametric and non-parametric Independent Samples T-tests performed. NP demotes when non-parametric Mann-Whitney U-test with (2-tailed) was performed. Absolute values used for dominance variables as comparing the degree of dominance rather than the side of presenting dominance.

74

Figure 3.20 Inter-group 1/2RT variables at baseline and post-PFMT. Inter-group comparison of unilateral PFM NIRS variable ½RT at baseline (top row) and post-PFMT (bottom row). Error bars represent + 1 SD. * indicates statistical significance. For both baseline and post-PFMT Right ½RT significantly reduced in controls (p <0.01 and 0.01, respectively).

3.5.2 DMag NIRS measurements

3.5.2.1 Intra-group DMag comparison

Intra-group association between bilateral PFM of DMag at baseline demonstrated

moderate positive correlation (r= 0.63) among the control group, suggesting that the desaturation

tended to occur similarly in bilateral PFM. However, this association was not statistically

maintained at post-PFMT assessment.

75

Conversely, the case group demonstrated a high positive correlation in association of

unilateral Left PFM DMag across baseline and post-PFMT, as well as for DMag Dominance

across baseline and post-PFMT, (rs= 0.79 and rs= 0.75, respectively).

Neither the control or casegroups demonstrated a statistically significant pairwise

difference for all DMag NIRS variables, for within and across assessment measurements. Refer

to Table 3.13.

3.5.2.2 Inter-group DMag comparison

At baseline assessment the control group demonstrated on average greater for Right and

Left DMag during SMVC contractions, (-7.31 µmol and -1.53 µmol, -5.04 µmol and -2.21µmol,

respectively), however, the difference was not found to be statistically significant.

At post-PFMT statistical significance was demonstrated between control and case groups

for unilateral Right DMag (-10.34 µmol compared to -2.19 µmol, p-value < 0.01). Suggesting the

case group had reduced oxygenation desaturation in unilateral PFM compared to the control

group, results shown in Table 3.14. and Figure 3.21-3.22. Whereas the average DMag of the Left

PFM appeared comparable between both groups.

76

Participant Group n Variables Mean +SD Paired Samples

P-value Correlation Coefficient

Correlation P-value

Controls 12 Baseline Right DMag Baseline Left DMag

-7.30 +7.00 -5.04 +6.98 .22 r= .63 .03

11 Post-PFMT Right DMag Post-PFMT Left DMag

-10.34 +6.17 -8.49 +6.17 .40 rs= .36 .29

11 Baseline Right DMag Post-PFMT Right DMag

-8.38 +6.23 -10.34 +6.17 .30 r= .54 .09

11 Baseline Left DMag Post-PFMT Left DMag

-6.22 +5.92 -8.49 +6.17 .29 rs= .30 .37

11 Baseline DMag Dominance Post-PFMT DMag Dominance

1.54 +6.13 1.85 +7.02 .91 r= .08 .82

Cases 10 Baseline Right DMag

Baseline Left DMag

-1.53 +2.19 -2.21 +6.02 .71 r= .36 .31

7 Post-PFMT Right DMag Post-PFMT Left DMag

-2.19 +5.48 -8.06 +18.23 .33 rs= .00 1.00

7 Baseline Right DMag Post-PFMT Right DMag

-0.79 +2.21 -2.19 +5.48 .57 r= -.13 .78

7 Baseline Left DMag Post-PFMT Left DMag

-2.98 +6.45 -8.06 +18.23 .87NP rs= .79 .04

7 Baseline DMag Dominance Post-PFMT DMag Dominance

-3.23 +4.57 -6.69 +13.00 .87 NP rs= .75 .05

Table 3.13 Intra-group DMag variables at baseline and post-PFMT. Summary of intra-group comparison DMag at baseline and post-PFMT. Parametric and non-parametric Paired Sample tests performed. NP denotes when non-parametric performed with Wilcoxin Signed Rank test (2-tailed). Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient.

77

NIRS Variable Controls n=12 Cases n=10 P-value Baseline Right DMag

mean +SD range

-7.31 +7.00

-15.89 – 4.47

-1.53 +2.19 -4.57 – 1.70

.13NP

Baseline Left DMag mean +SD

range

-5.04 +6.98

-13.97 – 8.01

-2.21 +6.02

-14.78 – 6.02

.33

Baseline DMag Dominance

mean +SD range

4.98 +3.54

0.00 – 11.03

3.25 + 3.52

0.88 – 12.51

.25 NP

NIRS Variable Controls n=11 Cases n=7 P-value

Post-PFMT Right DMag mean +SD

range

-10.34 +6.17

-19.63 – -1.05

-2.19 +5.48

-13.10 – 2.55 .01

Post-PFMT Left DMag mean +SD

range

-8.49 +6.17

-23.25 – -2.70

-8.06 +18.23 -47.33 – 7.51

.24NP

Post-PFMT DMag Dominance (Lg10)

mean +SD range

5.38 + 4.61 (Lg10)0.54 + 0.49 0.49 – 15.81 (Lg10) -0.31 – 1.20

8.15 +11.99 (Lg10) 0.53 + 0.66 0.35 – 34.23 (Lg10) -0.46 – 1.53

.97

Table 3.14 Inter-group DMag variables at baseline and post-PFMT. Inter-group comparison of unilateral PFM NIRS DMag at baseline and post-PFMT assessments. Parametric and non-parametric Independent Samples T-tests performed. NP demotes when non-parametric Mann-Whitney U-test with (2-tailed) was performed. Absolute values used for dominance variables as comparing the degree of dominance rather than the side of presenting dominance. Lg10 denotes that log base-10 transformation was performed on baseline and post-PFMT data.

78

Figure 3.21 Inter-group DMag at baseline and post-PFMT. Inter-group comparison of unilateral PFM NIRS variable DMag at baseline (top row) and post-PFMT (bottom row). Error bars represent + 1 SD. * indicates statistical significance. For post-PFMT Right DMag significantly greater in controls (p 0.01).

79

Figure 3.22 Inter-group 1/2RT and DMag dominance at baseline and post-PFMT. Inter-group comparison of unilateral PFM NIRS variables of ½RT and DMag dominance (absolute difference) at baseline (top row) and post-PFMT (bottom row). Error bars represent + 1 SD. 3.5.3 Unilateral PFM ½RT and DMag NIRS Correlation

3.5.3.1 Intra-group comparison

The control group demonstrated a moderately positive correlation (rs= 0.65) at baseline in

the unilateral Left PFM between ½RT and DMag measures, suggesting that quicker ½RT

accompanied greater desaturation changes during SMVC contractions. No other correlation was

determined among ½RT and DMag NIRS variables for unilateral PFM at baseline or post-PFMT

assessments for the control group. Refer to Table 3.15 and Figure 3.23.

80

The case group demonstrated a highly positive correlation (rs= 0.93) at baseline in the

unilateral Right PFM between ½RT and DMag measures, suggesting that quicker ½RT

accompanied greater desaturation changes during SMVC contractions. No other correlation was

determined among ½ RT and DMag NIRS variables for unilateral PFM at baseline or post-PFMT

assessments for the case group. Refer to Table 3.15. and Figures 3.23.

Participant Group

n Variables Mean +SD Correlation Coefficient

Correlation P-value

Controls

12 Baseline Right ½RT Baseline Right DMag

6.30 +9.75 -7.30 +7.00 rs= .46 .14

12 Baseline Left ½RT Baseline Left DMag

11. 39 +21.83 -5.04 +6.98 rs= .65 .02

11 Post-PFMT Right ½RT Post-PFMT Right DMag

7.87 +13.34 -10.34 +6.17 rs= .20 .55

11 Post-PFMT Left ½RT Post-PFMT Left DMag

9.55 +18.11 -8.49 +6.17 rs= .31 .36

Cases

10 Baseline Right ½RT Baseline Right DMag

18.90 +11.35 -1.53 +2.19 rs= .37 .30

10 Baseline Left ½RT Baseline Left DMag

19.36 +19.82 -2.21 +6.02 r= .37 .29

7 Post-PFMT Right ½RT Post-PFMT Right DMag

38.03 +26.93 -2.19 +5.48 rs= .93 <.01

7 Post-PFMT Left ½RT Post-PFMT Left DMag

18.54 +23.09 -8.06 +18.23 rs= .00 1.00

Table 3.15 Intra-group 1/2RT and DMag correlations at baseline and post-PFMT. Intra-group association between ½RT and DMag NIRS variables for unilateral PFM at baseline and post-PFMT assessments. Parametric and non-parametric correlation coefficients (2-tailed) performed. rs denotes non-parametric Spearman Rank correlation coefficient.

81

Figure 3.23.A. Control group Left 1/2RT and DMag correlation at baseline. Spearman rank correlation coefficient rs= 0.65 p-value 0.02, for ½RT and DMag of unilateral left PFM at baseline for control group, n=12.

Figure 3.23.B. Case group Right 1/2RT and DMag correlation at post-PFMT. Spearman rank correlation coefficient rs= 0.93 p-value <0.01, for ½RT and DMag of unilateral right PFM at post-PFMT for case group, n=7.

Figure 3.23 Intra-group correlations for 1/2RT and DMag. 3.6 Manometer objective outcome measures

3.6.1 Within assessment measurements

3.6.1.1 Intra-group manometer comparison

The control group demonstrated positive correlation for all manometer variables for

within assessment measurements. No pairwise difference was found among all manometer

variables for within assessment measurements. Refer to Table 3.16. These findings suggest

reliability of the manometer, which has also been shown in previous literature.83,118-120

The case group demonstrated positive correlation at baseline assessment for manometer

Timesec and at post-PFMT assessment for both Peak cmH2O and Average cmH2O. Refer to Table

3.17. This suggests variability in manometer measurements among the case group. However,

similar to the control and case groups, no pairwise difference was demonstrated for within

-20

-15

-10

-5

0

5

10

15

0 20 40 60 80 100

Left DM

ag µ

mol

Left ½RT in seconds

*

-14

-12

-10

-8

-6

-4

-2

0

2

4

0 20 40 60 80

Righ

t DM

ag µ

mol

Right ½RT in Seconds

*

82

assessment testing of all manometer variables during SMV contractions. Due to these results

only the Pre-NIRS manometer values were used for subsequent statistical analysis.

83

Participant Group n Variables Mean +SD Pairwise

P-value Correlation Coefficient

Correlation P-value

Controls

14 Baseline Peak cmH2O Pre-NIRS Baseline Peak cmH2O Post-NIRS

31.83 +17.29 32.61 +16.79 .66 r= .93 <.001

14 Baseline Average cmH2O Pre-NIRS Baseline Average cmH2O Post-NIRS

22.59 +14.69 20.91 +12.72 .23 r= .94 <.001

14 Baseline Timesec Pre-NIRS Baseline Timesec Post-NIRS

23.09 +15.38 26.39 +25.41 .98NP rs= .58 .03

13 Post-PFMT Peak cmH2O Pre-NIRS Post-PFMT Peak cmH2O Post-NIRS

35.68 +18.40 37.52 +18.16 .49 r= .87 <.001

13 Post-PFMT Average cmH2O Pre-NIRS Post-PFMT Average cmH2O Post-NIRS

23.68 +14.11 22.95 +13.68 .62 r= .93 <.001

13 Post-PFMT Timesec Pre-NIRS Post-PFMT Timesec Post-NIRS

33.52 +50.22 38.28 +58.75 .17 (Lg10) r= .93 <.001

Table 3.16 Within assessment control group PFM manometer variables. Within assessment, control group manometer comparison and association. Parametric and non-parametric Paired Sample tests (2-tailed) performed. NP denotes when non-parametric performed with Wilcoxin Signed Rank test (2-tailed). Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient (2-tailed). (Lg10) denotes that log base-10 transformation was performed. (Sqrt) denotes that square root transformation was performed.

84

Participant Group n Variables Mean +SD Pairwise

P-value Correlation Coefficient

Correlation P-value

Cases

11 Baseline Peak cmH2O Pre-NIRS Baseline Peak cmH2O Post-NIRS

13.12 +9.80 (Sqrt) 3.21 +1.76 10.35 +5.34 (Sqrt) 3.02 +1.17 (Sqrt) .66 rs= .29 .39

11 Baseline Average cmH2O Pre-NIRS Baseline Average cmH2O Post-NIRS

8.13 +4.04 (Sqrt) 2.68 +1.01 9.49 +6.94 (Sqrt) 2.73 +1.49 (Sqrt) .83 rs= .19 .58

11 Baseline Timesec Pre-NIRS Baseline Timesec Post-NIRS

13.12 +5.71 19.45 +21.99 .42NP rs= .87 <.001

7 Post-PFMT Peak cmH2O Pre-NIRS Post-PFMT Peak cmH2O Post-NIRS

12.94 +10.61 13.57 +8.08 .67 r= .96 <.01

7 Post-PFMT Average cmH2O Pre-NIRS Post-PFMT Average cmH2O Post-NIRS

9.39 +7.19 8.65 +5.86 .50 r= .93 <.01

7 Post-PFMT Timesec Pre-NIRS Post-PFMT Timesec Post-NIRS

11.89 +7.30 9.53 +5.24 .39 r= .51 0.24

Table 3.17 Within assessment case group PFM manometer variables. Within assessment, case group PFM manometer comparison and association. Parametric and non-parametric Paired Sample tests (2-tailed) performed. NP denotes when non-parametric performed with Wilcoxin Signed Rank test (2-tailed). Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient (2-tailed). (Lg10) denotes that log base-10 transformation was performed. (Sqrt) denotes that square root transformation was performed.

85

3.6.2 Across assessment manometer measurements

3.6.2.1 Intra-group manometer comparison

When assessing for PFM strength (as measured by manometer pressure) after the 8-week

PFMT no statistical difference was found in both control and case groups for all manometer

variables. Although there was no significant difference, both groups demonstrated positive

correlation for all manometer variables across session testing, suggesting that all participants

were likely to have comparable performances at baseline and post-PFMT assessments. The case

group only demonstrated a moderate positive correlation for average manometer pressure across

baseline and post-PFMT assessment, which was also not found to be significant. Refer to Table

3.18 and Figure 3.24.

86

Participant Group n Variables Mean +SD Paired Difference

P-value Correlation Coefficient

Correlation P-value

Controls

13 Baseline Peak cmH20 Post-PFMT Peak cmH20

32.31 +18.03 35.73 +19.22 .31 r= .83 <.01

13 Baseline Average cmH20 Post-PFMT Average cmH20

21.08 +11.93 23.27 +14.66 .42 r= .79 <.01

13 Baseline Timesec Post-PFMT Timesec

23.66 +16.64 (Lg10 1.29+0.28) 35.13 +52.10 (Lg10 1.30 +0.44) (Lg10) .92 (Lg10) r= .79 <.01

Cases

8 Baseline Peak cmH20 Post-PFMT Peak cmH20

14.66 +10.48 (Sqrt) 3.49 +1.68 13.91 +10.20 (Sqrt) 3.37 +1.72 .73 (Sqrt) r= .89 <.01

8 Baseline Average cmH20 Post-PFMT Average cmH20

10.71 +7.37 10.30 +7.14 .79 rs= .55 .16

8 Baseline Timesec Post-PFMT Timesec

18.38 +25.58 (Lg10) 1.06 +0.38 13.15 +7.64 (Lg10) 1.06 +0.26 (Lg10) .94 rs= .76 .03

Table 3.18 Across assessment intra-group PFM manometer variables. Across assessment, intra-group PFM manometer comparison and association. Parametric Paired Sample tests (2-tailed) performed. Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient (2-tailed). (Lg10) denotes that log base-10 transformation was performed. (Sqrt) denotes that square root transformation was performed.

87

Figure 3.24 Across assessment correlation of PFM manometer measures. Association of across assessment PFM manometer measurements. Blue= controls. Orange= cases.* indicates statistically significant correlation coefficient.

3.6.2.2 Inter-group PFM manometer comparison

At baseline assessment the control group had statistically significant greater peak

(32.09cmH2O compared to 13.12cmH2O, p-value < 0.01), and average (20.54cmH2O compared

to 8.13cmH2O, p-value < 0.01) manometer pressures than the case group when performing

SMVCs. At baseline assessment the control group also demonstrated on average greater duration

of SMVC than the case group (24.43 seconds compared to 13.12 seconds, p-value 0.04). Refer to

Table 3.19 and Figure 3.25.

At post-PFMT assessment the control group maintained greater peak (35.68cmH2O

compared to 13.91cmH2O, p-value < 0.01), and average (23.68cmH2O compared to

10.30cmH2O, p-value 0.02) PFM manometer pressures than the case group. However, at post-

88

PFMT assessment there was no statistically significant difference in the duration of SMVC

between the two groups. Refer to Table 3.19. and Figure 3.25.

PFM Manometer Variable Controls n=15 Cases n=11 P-value Baseline Peak cmH20

mean +SD range

32.09 +16.69 11.00 – 59.00

13.12 +9.80 0.00 – 37.40

<.01NP

Baseline Average cmH2O mean +SD

range

20.54 +11.12 7.10 – 42.00

8.13 +4.04

0.00 – 15.80

<.01NP

Baseline Timesec (Lg10) mean +SD

range

24.43 +17.33 (Lg10) 1.30 +0.29 7.25 – 65.04 (Lg10) 0.86 – 1.81

13.12 +5.71 (Lg10) 1.08 +0.21

4.29 – 25.42 (Lg10) 0.63 – 1.41

.04

PFM Manometer Variable Controls n=13 Cases n=8 P-value Post-PFMT Peak cmH20

mean +SD range

35.68 +18.40 12.60 – 72.30

13.91 +10.20 0.00 – 32.70

<.01

Post-PFMT Average cmH2O mean +SD

range

23.68 +14.11 7.10 – 51.40

10.30 +7.14 0.00 – 22.70

.02

Post-PFMT Timesec (Lg10) mean +SD

range

33.52 +50.22 (Lg10) 1.29 +0.42 5.30 – 193.11 (Lg10) 0.72 – 2.29

13.15 +7.64 (Lg10) 1.05 +0.26

4.25 – 26.51 (Lg10) 0.63 – 1.42

.18

Table 3.19 Inter-group PFM manometer variables at baseline and post-PFMT. Inter-group comparison of PFM manometer measurements at baseline and post-PFMT assessments. Parametric and non-parametric Independent Samples T-tests performed. NP demotes when non-parametric Mann-Whitney U-test with (2-tailed) was performed. Lg10 denotes that log base-10 transformation was performed on baseline and post-PFMT data.

89

Figure 3.25 Inter-group PFM manometer variables at baseline and post-PFMT. Inter-group PFM manometer measurements at baseline and post-PFMT. Log10 denotes that log base-10 transformation was performed on baseline and post-PFMT data. Error bars represent + 1 SD. * indicates statistical significance.

90

3.6.3 Post-PFMT PFM manometer and NIRS dominance measures

Absolute values of ½RT and DMag Dominance were used as measure of degree of PFM

dominance which were correlated to post-PFMT to assess whether more synergistic PFM

contraction (reduced degree of dominance) were associated with large manometer pressures

(PFM strength).

The control group did not demonstrate any correlation between post-PFMT manometer

variables and NIRS dominance variables. The case group showed a suggestion of association

between ½RT dominance and both Peak and Average cmH2O, however this was only a

moderate negative correlation with which did not prove to be statistically significant. Refer to

Table 3.20.

Participant Group n Variables Correlation

Coefficient Correlation

P-value Controls 11 ½RT Dominance v Peak cmH2O rs= .16 .63

½RT Dominance v Average cmH2O rs= .18 .59

½RT Dominance v Timesec rs= .08 .81

DMag Dominance v Peak cmH2O rs= .09 .79

DMag Dominance v Average cmH2O rs= .14 .69

DMag Dominance v Timesec rs= .18 .59

Cases 7 ½RT Dominance v Peak cmH2O (Sqrt) r= -.69 .09

½RT Dominance v Average cmH2O (Sqrt) r= -.67 .10

½RT Dominance v Timesec rs= -.50 .25

DMag Dominance v Peak cmH2O rs= .04 .94

DMag Dominance v Average cmH2O rs= -.14 .76

DMag Dominance v Timesec rs= .14 .76

Table 3.20 Intra-group correlation of post-PFMT PFM manometer and NIRS dominance variables. Summary of correlation between post-PFMT PFM manometer variables and post-PFMT NIRS dominance (absolute values) variables. Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient (2-tailed). Sqrt denotes square root transformation performed.

91

3.6.4 Baseline unilateral PFM ½RT and PFM manometer measures

The control group demonstrated moderate negative correlation between unilateral Right

PFM ½RT and both Peak cmH2O and Average cmH2O (rs = -0.63 and rs= -0.67, respectively).

The control group did not demonstrate any other associations between unilateral PFM ½RT and

manometer variables at baseline assessment. Refer to Table 3.21. The control group did not

demonstrate any correlation between unilateral PFM DMag and manometer variables.

The case group demonstrated a moderate negative correlation between unilateral Right

PFM ½RT and Average cmH2O (rs= -0.67). The case group did not demonstrate any other

associations between unilateral PFM ½RT and manometer variables at baseline assessment.

Refer to Table 3.21 and Figures 3.26-3.27. The case group did not demonstrate any significant

correlation between unilateral PFM DMag and manometer variables at baseline.

Participant

Group n Variables Correlation Coefficient

Correlation P-value

Controls 12 Right ½RT v Peak cmH2O rs= -.63 .03

12 Right ½RT v Average cmH2O rs= -.67 .02

12 Right ½RT v Timesec rs= .52 .08

12 Left ½RT v Peak cmH2O rs= -.32 .32

12 Left ½RT v Average cmH2O rs= -.35 .26

12 Left ½RT v Timesec rs= .21 .51

Cases 10 Right ½RT v Peak cmH2O rs= -.38 .28

10 Right ½RT v Average cmH2O rs= -.67 .04

10 Right ½RT v Timesec r= -.07 .85

10 Left ½RT v Peak cmH2O rs= -.40 .25

10 Left ½RT v Average cmH2O rs= -.35 .32

10 Left ½RT v Timesec rs= .56 .09

Table 3.21 Intra-group correlation of unilateral PFM 1/2RT and PFM manometer variables at baseline. Summary of association between unilateral PFM NIRS ½RT and PFM manometer variables at baseline. Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient.

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3.6.5 Post-PFMT ½RT and PFM manometer measures

The control group did not demonstrate any associations between unilateral PFM ½RT

and manometer variables at post-PFMT assessment. Refer to Table 3.22. Similar to baseline

findings the control group did not demonstrate any correlation between unilateral PFM DMag

and manometer variables at post-PFMT.

Conversely, the case group demonstrated highly negative correlations between both

unilateral PFM ½RT and all manometer variables, suggesting that reduced ½RT was associated

with greater manometers pressures and duration of pressure at post-PFMT assessment. This was

not demonstrated by the case group at baseline. It should be noted that although the case group

suggested a highly positive correlation (r= -0.73) for unilateral Right PFM ½RT and Timesec, this

correlation was not considered to be statistically significant. Refer to Table 3.22. and Figures

3.26-3.27.

Similar to controls, the case group did not demonstrate any significant correlation

between unilateral PFM DMag and manometer variables at post-PFMT.

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Participant Group n Variables Correlation

Coefficient Correlation

P-value Controls 11 Right ½RT v Peak cmH2O rs= .19 .58

11 Right ½RT v Average cmH2O rs= .21 .54

11 Right ½RT v Timesec rs= .22 .53

11 Left ½RT v Peak cmH2O rs= .00 1.00

11 Left ½RT v Average cmH2O rs= .00 1.00

11 Left ½RT v Timesec rs= .11 .75

Cases 7 Right ½RT v Peak cmH2O r= -.83 .02

7 Right ½RT v Average cmH2O r= -.82 .02

7 Right ½RT v Timesec r= -.73 .06

7 Left ½RT v Peak cmH2O (Sqrt) r= -.84 .02

7 Left ½RT v Average cmH2O (Sqrt) r= -.84 .02

7 Left ½RT v Timesec (Sqrt) r= -.84 .02

Table 3.22 Correlation of unilateral 1/2RT and PFM manometer variables at post-PFMT. Summary of association between unilateral PFM NIRS ½RT and PFM manometer variables at post-PFMT. Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient.

Figure 3.26 Correlation of Right PFM 1/2RT and PFM manometer variables. SMVC unilateral Right PFM ½RT correlation with PFM manometer variables at baseline (top row) and post-PFMT (bottom row) assessments. * indicates statistically significant correlation coefficient.

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Figure 3.27 Correlation of Left PFM 1/2RT and PFM manometer variables. SMVC unilateral Left PFM ½RTcorrelation with PFM manometer variables at baseline (top row) and post-PFMT (bottom row) assessments. * indicates statistically significant correlation coefficient.

3.7 Exercise adherence outcome measures

Exercise adherence to the PFMT intervention was accounted for with self-recording sheet

which allowed for two adherence variables to be measured, exercise volume and frequency.

Exercise Volume is defined as amount of completed exercises per day. Exercise Frequency is

defined as the number of days any exercises were completed during the 8-week PFMT

intervention. Table 3.23 shows no statistical difference among comparison of exercise adherence

between control and case groups, although the case group did demonstrate a higher average for

percentage for Exercise Frequency. On average the control group and case group only performed

51.10% and 52.23% of required amount of exercises, Table 3.23 and Figure 3.29. Both groups

performed better with regards to frequency, completing 62.91% and 78.57% of required exercise

days (control and case group respectively).

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Exercise Adherence Variable Controls n=13 Cases n=8 P-value Exercise Volume

mean +SD

range

51.10 +28.28

0.00-92.86%

52.23 +26.37

0.00-84.82%

.93

Exercise Frequency mean +SD

range

62.91 +29.52

0.00-100.00%

78.57 +33.81

0.00-100.00%

.10NP

Table 3.23 Inter-group exercise adherence. Inter-group comparison of exercise adherence as measured by percentage of completed amount of exercises completed per day (Exercise Volume) and percentage of days any exercises completed (Exercise Frequency). Parametric and non-parametric Independent T-test performed (2-tailed). NP demotes when non-parametric Mann-Whitney U-test with (2-tailed) was performed.

Figure 3.28 Inter-group PFMT adherence mean values for Exercise Volume and Frequency. Error bars represent + 1 SD.

Figure 3.29 Intra-group exercise adherence percentage. Exercise adherence to 8-week PFMT for controls (blue) and case (orange) groups. Dark blue & orange bars = Exercise Volume (total amount of PFMT exercises completed). Light blue & orange bars = Exercise Frequency (number of days PFMT completed).

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3.7.1 Exercise adherence and post-PFMT PFM manometer measures

For the control group no significant correlation between PFM manometer variables and

exercise adherence variables. Refer to Table 3.24. Similarly, among the case group, there was no

correlation found between Exercise Volume and manometry values.

However, the case group did demonstrate a significant positive correlation between

Exercise Frequency and all the PFM manometry variables. This suggests that for the case group,

the number of days that any PFMT is attempted, rather than the amount of PFMT completed

each day, is more likely to help improve PFM function as measured by manometry. Refer to

Table 3.24 and Figure 3.30.

Participant Group n Variables Correlation

Coefficient Correlation

P-value Controls 13 Peak cmH2O v Exercise Volume r= -.45 .12

13 Peak cmH2O v Exercise Frequency r= -.33 .27

13 Average cmH2O v Exercise Volume r= -.50 .08

13 Average cmH2O v Exercise Frequency r= -.38 .20

13 Timesec v Exercise Volume rs= .22 .47

13 Timesec v Exercise Frequency rs= .14 .66

Cases 8 Peak cmH2O v Exercise Volume r= .04 .93

8 Peak cmH2O v Exercise Frequency rs= .78 .02

8 Average cmH2O v Exercise Volume r= .11 .80

8 Average cmH2O v Exercise Frequency rs= .88 <.01

8 Timesec v Exercise Volume r= .13 .76

8 Timesec v Exercise Frequency rs= .76 .03

Table 3.24 Intra-group correlation of PFM manometer and exercise adherence variables. Association between post-PFMT manometer variables and exercise adherence. Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient (2-tailed).

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Figure 3.30 Case group correlation of PFM manometer and exercise adherence variables. Case group association between SMVC post-PFMT manometer variables with percentage of adherence to PFMT measured by Exercise Volume and Frequency. * indicates statistically significant correlation coefficient.

3.7.2 Exercise adherence correlation to questionnaire and PVR measures

As the case group demonstrated a significant reduction in the QUID-UUI, this outcome

measure DQUID-UUI (change in score from baseline to post-PFMT) was correlated with

exercise adherence. There was a highly negative correlation (rs= -.85, p-value <0.01) between

DQUID-UUI and Exercise Frequency. This association suggests that QUID-UUI scores were

more likely to be reduced in participants with higher percentage of completed exercise days.

Data in Figure 3.31 suggests that Exercise Frequency of at least 80% was required in this sample

to demonstrate a reduction in urgency symptoms. There was no correlation demonstrated

between Exercise Frequency and the remaining questionnaire score changes (QUID-SUI, UDI-6,

IIQ-7, SSI) or PVR changes. Nor was any correlation found among Exercise Volume and all

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questionnaire score changes or PVR changes. The control group did not demonstrate any

correlation between exercise adherence and questionnaire or PVR variables.

Figure 3.31 Case group correlation of QUID-UUI score and exercise adherence. Association between subjective change in QUID-UUI score from baseline to post-PFMT and exercise adherence based on Exercise Frequency.* indicates statistically significant correlation. Spearman Rank correlation coefficient (rs= -0.85).

3.7.3 Exercise adherence and post-PFMT ½RT measures

As conducted in post-PFMT PFM manometer and NIRS Dominance analysis, the

absolute ½RT Dominance value was used as measure of degree of PFM dominance was

correlated to exercise adherence variables to assess whether more synergistic PFM contraction

(reduced degree of dominance) were associated with exercise adherence rates.

No correlation found among individual unilateral sides of PFM and both exercise

adherence measures for the control group. However, the controls did demonstrate a moderately

negative correlation between ½RT Dominance and both Exercise Volume and Frequency, (rs= -

0.69 and rs= -0.61, respectively). Results shown in Table 3.25 and Figure 3.32.

The case group demonstrated a highly negative correlation between unilateral Right PFM

½RT and Exercise Frequency, (rs= -0.85). Suggesting that the PFMT intervention only had a

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training effect on the PFM unilaterally, as no other correlations were found. Refer to Table 3.25

and Figure 3.33.

Participant

Group n Variables Correlation Coefficient

Correlation P-value

Controls 11 Right ½RT v Exercise Volume rs= -.12 .73

Right ½RT v Exercise Frequency rs= -.14 .68

Left ½RT v Exercise Volume rs= -.35 .30

Left ½RT v Exercise Frequency rs= -.35 .29

½RT Dominance v Volume rs= -.69 .02

½RT Dominance v Frequency rs= -.61 .05

Cases 7 Right ½RT v Exercise Volume r= -.35 .44

Right ½RT v Exercise Frequency rs= -.85 .02

Left ½RT v Exercise Volume rs= .13 .79

Left ½RT v Exercise Frequency rs= -.52 .23

½RT Dominance v Volume rs = -.38 .40

½RT Dominance v Frequency rs = -.48 .27

Table 3.25 Intra-group correlation of 1/2RT and exercise adherence variables. Association between post-PFMT ½RT (Dominance absolute) variables and exercise adherence. Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient (2-tailed).

Figure 3.32 Control group correlation of 1/2RT and exercise adherence. Association between 1/2RT Dominance (absolute) and exercise adherence among controls. ½RT Dominance and Exercise Volume rs= -0.69. ½RT Dominance and Exercise Frequency rs= -0.61. * indicates statistically significant correlation coefficient.

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Figure 3.33 Case group correlation of 1/2RT and exercise adherence. Association between unilateral Right PFM ½RT and Exercise Frequency among the case group, rs= -0.85.* indicates statistically significant correlation coefficient.

3.7.4 Exercise adherence and post-PFMT DMag measures

As conducted in post-PFMT PFM manometer and NIRS Dominance analysis, the

absolute DMag Dominance value was used as measure of degree of PFM dominance which was

correlated to exercise adherence variables to assess whether more synergistic PFM contraction

(reduced degree of dominance) were associated with exercise adherence rates.

The control group did not demonstrate any significant findings when associating post-

PFMT DMag NIRS variables with exercise adherence, as shown in Table 3.26.

The case group did demonstrate a significant highly negative correlation when

associating post-PFMT unilateral Right PFM DMag and Exercise Frequency variables, (rs= -

0.78). This suggests that case participants were more likely to have greater magnitude of

desaturation in the Right PFM with increase in exercise adherence. Refer to Table 3.26 and

Figure 3.34.

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Participant Group n Variables Correlation

Coefficient Correlation

P-value Controls 11 Right DMag v Exercise Volume r= -.45 .17

Right DMag v Exercise Frequency rs= -.30 .37

Left DMag v Exercise Volume rs= -.02 .96

Left DMag v Exercise Frequency rs= .03 .94

DMag Dominance v Exercise Volume r= .37 .28

DMag Dominance v Exercise Frequency r= .28 .40

Cases 7 Right DMag v Exercise Volume r= -.43 .34

Right DMag v Exercise Frequency rs = -.78 .04

Left DMag v Exercise Volume rs= -.34 .45

Left DMag v Exercise Frequency rs= .11 .81

DMag Dominance v Exercise Volume rs= .18 .70

DMag Dominance v Exercise Frequency rs= -.11 .81

Table 3.26 Intra-group correlation of DMag and exercise adherence variables. Association between post-PFMT DMag (Dominance absolute) variables and exercise adherence. Parametric and non-parametric correlation coefficients performed. rs denotes non-parametric Spearman Rank correlation coefficient (2-tailed).

Figure 3.34 Case group correlation of DMag and exercise adherence. Association between post-PFMT unilateral Right PFM DMag and Exercise Frequency among the case group, (rs = -0.78).* indicates statistically significant correlation coefficient.

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

0 20 40 60 80 100

DMa

g u

mo

l

Exercise Frequency

*

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Chapter 4: Discussion

This chapter will provide interpretation of the research findings within the perspective of

physiological theories and academic literature pertaining to skeletal muscle, NIRS and PFM

dysfunction. The major research findings will be discussed in detail with mention of relevance

for clinical applicability.

4.1 Successful development of NIRS probe

Findings shown in Results section 3.4 demonstrate that the technical design of the NIRS

probe has the capacity to capture hemodynamic and oxygen kinetic response of bilateral PFM

independently and simultaneously. This capability was also demonstrated in both a continent

female control sample and in a sample of females with LUTS.

The probe was tolerated well by participants when used in the manner described in

Methods section 2.3.4. However, it should be noted that two case participants were excluded

from the study due to reported discomfort with manometer insertion and therefore were not

exposed to the NIRS probe. The presence of pelvic pain presents as a limitation for the use of the

NIRS probe, along with other PFM assessment devices that must be used transvaginally. With

this in consideration all other participants (controls n=15 and cases n=11) who did not report any

discomfort with the manometer also did not report any discomfort with the NIRS probe. This

suggests that the NIRS probe has similar tolerability to current transvaginal PFM assessment

devices.

Findings shown in Results section 3.4 demonstrate that the NIRS probe prototype design

has the capacity to capture differential hemodynamic and oxygen kinetic response of bilateral

PFM. PFM assessment was carried out in the nature of performing MVCs, SMVCs and REPs as

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described and recommended by Laycock and Jerwood 2001 and Devreese et al. 2004.1,91,92

NIRS tracings from this full assessment were used in consideration of the functionality of the

tool itself and for the consideration of observational trends to characterize hemodynamic and

oxygen kinetic responses of the PFM.

Based on the inter-group observational trends the case group demonstrated more complex

NIRS tracings during measurements, atypical muscle tissue contraction and recovery

hemodynamic patterns, resulting in longer ½RT and decreased DMag changes on average. Please

refer to Table 3.12, Table 3.14, and Figures 3.9-3.19 in NIRS objective outcome measures

section 3.5. Similarly, the exploratory findings of Ryan et al. 2014, also suggested that

individuals with a neurologic condition (amyotrophic lateral sclerosis), tended to have slower

½RT than controls.53 It should be noted that this research group used ½RT calculations based on

occlusion NIRS methods and TSI%.

The NIRS parameters also demonstrated similar outcomes to that of manometry, which

also found greater PFM strength and endurance in the control group compared to the case group.

Interestingly, both devices did not detect a significant change in PFM function within groups

after the 8-week PFMT intervention.

4.2 Participant demographics

There was a difference in the mean age of each group, the control group on average being

younger than the case group (mean 42 years compared to mean 51 years, respectively). Although

not reaching statistical significance, it should be noted that the difference between the two was

just shy of reaching the significance cut off (p-value <0.05). Refer to Table 3.1.

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Increasing age is associated with muscle atrophy and mass reduction, causing decreased strength

and power.121,122 Reduction in the contractile properties of skeletal muscle tissue, particularly

that of contractile velocity, also decreases fatigue resistance in aging muscle.121,122 More specific

PFM literature also reports aging as a contributor to loss of pelvic floor function.12 These

considerations of age-related factors influencing muscle should be considered, even though

statistical significance was not demonstrated between the two groups. Since the case group was

older on average, age could be a contributing factor in the slower ½RT, reduced DMag and

manometer pressure results. An age matched study design would have helped control for this

confounding variable and should be considered for future studies.

There was also statistically significance found in the parity between groups, with the case

group demonstrating a higher proportion of participants with parity >1 than the controls, (90%

compared to 46.7%, respectively). This is important for consideration as parity status is an

influential factor contributing to structural integrity of the PFM. A recent review article by Van

Geelen et al. 2018, determined that parity is associated with decreased PFM contractility, pelvic

organ prolapse, UI, bladder descent and hypermobility, as well as pudendal denervation.12 Injury

to the pudendal nerve is thought to be influenced by many factors during pregnancy and labour,

although evidence in the literature varies on which factors are most significant, they include:

vaginal delivery, prolonged second stage labour, multiparity, forceps and vacuum assisted

labour, perineal lacerations, infant birth weight and head circumference.12 Van Geelen et al.

2018, conclude that the first vaginal delivery poses the greatest risk for PFM dysfunction

including levator ani trauma and neurogenic injury. Although these complications are likely to

occur, Van Geelen et al. 2018, state they typically resolve within the year post-delivery,

however, 5-20% experience irreversible pelvic floor changes due to PFM trauma and neurogenic

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injury.12 More specifically neurogenic injury has been reported to occur in 25-30% of

primiparous women acutely postpartum with denervation of PFM continuing up to 6-months

postpartum,13,123 which can result in permanent pudendal nerve damage contributing to long

term PFM dysfunction.12

The negative influences that parity, and most specifically vaginal delivery trauma can

have on the PFM, provides rationale for including women who have experienced labour trauma

resulting in bladder symptoms to be included in our study sample population of interest.

Furthermore, the findings of this study further support the negative impact of delivery trauma on

the PFM, as participants with this etiology presented with atypical contraction patterns observed

by NIRS. Such findings will be discussed in further detail in section 4.3.2.

4.3 Observational NIRS findings

4.3.1 Hemodynamic and oxygen kinetic response observed in heathy PFM

The observational NIRS trends observed in the control group, Figures 3.4-3.8, were

consistent with skeletal muscle oxygenation patterns in response to exercise as described in

previous literature.85,93,99 With each PFM contraction, desaturation of the muscle tissue

occurred, as evidenced by drop in both HbDiff and O2Hb. With this desaturation there was also

observable drop in tHb, suggesting that the blood volume of the muscle tissue also decreased

during contraction. At the cessation of contraction all three of these NIRS variables then returned

to baseline levels or increased above baseline levels during the 90-second recovery time interval

before returning to baseline levels. Such physiologic responses of skeletal musculature are well

documented in NIRS research.50,70,97,99 The decline of HbDiff and O2Hb reflect the oxidative

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capacity of the musculature, in that greater desaturation occurs as an actively contracting muscle

uptakes oxygen to meet its oxygen demand and maintain the workload required of it. The decline

in the tHb infers a decrease in blood volume within the musculature, as the muscle contracts the

blood volume immediately available with the muscle tissue is decreased as the contraction

causes mechanical constriction of the vasculature, limiting incoming blood flow.124

Furthermore, after the initial decrease at onset of contraction, HHb levels increase, although not

to the same magnitude as O2Hb desaturation, demonstrated in Figure 3.5. This reflects continued

oxygen consumption with sustained contraction, as HHb levels within the given blood volume of

the musculature rises as a direct result of O2 uptake by the PFM.

This observation was more evident during SMVC contractions. The longer duration

compared to the MVCs created a larger demand on the muscle causing more desaturation of

oxygen levels within the muscle. Also, as the SMVC was sustained, compared to REP

contractions, there was limited capability for the microvasculature to restore oxygen supply to

facilitate continued muscular effort. In REP contractions the brief relaxation between each

contraction allows more opportunity to increase blood flow and oxygenation levels within the

musculature. Were this study to have employed an occlusive NIRS methodology, the amount of

blood volume during contraction would be controlled, constant blood volume then allows for

accurate calculation of muscle oxygen consumption (rate of HbDiff recovery to baseline during

occlusion measured after bout of exercise).47 Furthermore, had the occlusion method been

employed it is suspected that the observation of an inverse response from O2Hb (decreasing) and

HHb (increasing) would be more pronounced. Nonetheless, the fact that in the control group all

four NIRS variables responded in typical pattern reported in NIRS literature demonstrates that

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the NIRS probe is capable of assessing the PFM function in healthy tissue, while providing the

added benefit of isolating bilateral PFM response.

The continued downward slope of HbDiff, with inverse relationship between O2Hb

(downward slope) and HHb (upward slope) during the post-PFMT SMVC’s is demonstrated

particularly well in Figure 3.5. The observations from Figure 3.5 suggest that although the

SMVC contraction was not held as long as during baseline, the O2 consumption of the PFM was

greater during post-PFMT, demonstrating that the oxygen consumption exceeds oxygen delivery

during this contraction as tHb also declines. During arterial occlusion when ischemia is induced,

a similar inverse pattern of O2Hb and HHb occurs, which represents rapid O2 consumption

occurring as a result of impeded blood flow (O2 delivery). In Figure 3.6 (post-PFMT Right

PFM), this contraction appears strong enough to induce such an oxygenation pattern. As

described by Muthalib et al. 2010, isometric contractions sustained at high intensity of MVC

results in intramuscular pressure high enough to impeded O2 supply of the muscle’s

microvasculature.97 This means that oxygenation patterns observed at SMVC’s of high intensity

reflect the O2 consumption related to the force generated by that muscle.97 Furthermore, this

trace of interest appears to demonstrate a quicker ½RT in post-PFMT, (½RT Right, 4.1 vs

3.9seconds and Left 8.5 vs 2.0seconds, at baseline and post-PFMT respectively), despite having

achieved greater O2 consumption during the contraction. Since it has been determined that there

is a direct and proportional relationship between blood flow and O2 consumption, the quicker

½RT corresponding with the greater HbDiff desaturation, suggests that supply is proportionally

and more efficiently meeting the demand in order to restore homeostasis and facilitate

recovery.97,125

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Furthermore, Figure 3.7 (baseline and post-PFMT SMVC), demonstrate similar results.

In baseline SMVC the magnitude of desaturation remains fairly constant throughout the duration

of the contraction, with a less obvious inverse relationship between O2Hb and HHb. Particularly

on the Left PFM, which produces greater desaturation (as per DMag), a hyperemic-like response

is seen in the recovery which is consistent with recovery response when occlusion methods are

used.50,67 The hyperemic response again demonstrates a vasodilatory response proportional to

the oxygen consumption of the active musculature. When comparing bilateral tracings from

baseline to post-PFMT the contraction was approximately twofold at post-assessment. Although

contraction was maintained throughout, some resaturation is occurring as noted by progressive

increase in tHb, O2Hb and HbDiff before the cessation of contraction, although the restoration

still remains well below baseline values. This resaturation, or continued O2 delivery with

incoming blood flow will partially explain the lack of obvious inverse relationship of O2Hb and

HHb, and it could also explain the absence of a hyperemic response in post-PFMT Left

compared to baseline. However, it could also be argued that the ability of the PFM to sustain

such a long contraction with obvious desaturation (without a complete restoration of O2 delivery

or resaturation to baseline), suggests an adapted metabolic training response of the PFM. The

absence of the hyperemia in recovery would further support this, in that the microvasculature can

more efficiently restore oxygen deficits incurred by energy expenditure with exercise.

These two control participants are representative of the tracings obtained from control

participants as a whole and as previously discussed their observational findings are suggestive of

improvement in PFM function in response to the intervention, despite no determined statistical

significance of improved ½RT, DMag or manometer variables. It should also be noted that the

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varying duration of these contractions could skew the interpretation of these baseline and post-

PFMT comparison oxygenation trends.

4.3.2 Hemodynamic and oxygen kinetic response observed in PFM dysfunction

As detailed in the Chapter 3: Results section 3.4.1.2, heterogeneity among the case group

tracings were categorized into to relevant clinical sub-groups. The categorization of

observational trends was conducted according to underlying etiology and mobility status. It

should be noted that mobility status was not determined by a clinical tool but rather by how the

participant presented at time of assessment and based on the degree to which they used a

mobility aid or wheelchair, as described in section 3.4.1.2

4.3.2.1 High mobility clinical sub-group

Participants in the high mobility group tended to demonstrate PFM oxygenation patterns

similar to that of the control group, generating desaturation with contraction and oxygen

restoration during recovery phase. This typical oxygen pattern was also exhibited on bilateral

PFM, with general synchronicity of unilateral oxygen patterns, regardless of the degree of

magnitude of changes occurring during contraction. Figures 3.9-3.10 demonstrate the

oxygenation patterns observed in a participant with delivery trauma, congenital dysplasia of the

right hip and LUTS, with no impaired mobility (SS11). The NIRS assessment with this

participant demonstrated typical saturation patterns, as compared to observations from controls.

Similar tracings were also demonstrated by SS13, with underlying spinal stenosis, congenital hip

dysplasia and multiple bilateral hip surgeries, with minimal cane assisted mobility. Similar

tracings were also demonstrated by SS14. This participant has a history incomplete traumatic

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C2-C4 SCI no current ASIA score, but independent unassisted mobility, decreased sensation to

pelvis with self- reported hypersensitivity and hyper-reflexes of bilateral lower limbs. As

demonstrated in Figure 3.11-3.12, SS14 demonstrated typical desaturation during contraction

with restoration in recovery, similar to control group. At post-PFMT assessment greater bilateral

desaturation is evidenced during contraction. These observational findings, particularly in Figure

3.12, draw parallels to control findings shown in Figure 3.6. Both illustrate a shorter contraction

at post-PFMT than at baseline, with the greater oxygen consumption, suggestive of greater force

generation.97 Likewise, this trace also demonstrates reduced ½RT in post-PFMT, despite having

achieved greater oxygen consumption during the contraction, (½RT Right, 26.5 vs 5.6seconds

and Left 29.0 vs 5.9seconds, at baseline and post-PFMT respectively). As mentioned previously,

this suggests that oxygen supply is proportionally and more efficiently meeting the demand in

order to maintain workload and facilitate recovery.97,125

Furthermore, despite a discrepancy in magnitude change, the contraction patterns

evidenced similar curve characteristics bilaterally, which is also a trend found among the control

groups, refer to Figures 3.6 and 3.8 and Figures 3.10 and 3.12. That the bilateral musculature is

responding in a synchronized manner suggests coordinated bilateral motor unit activation and

microvascular unit perfusion. Furthermore, the fact that there is a magnitude discrepancy

bilaterally despite their being symmetric in their desaturation pattern might suggest that the

unilateral PFM with the greater magnitude change is activating larger motor pools (when

considering the size principle of motor neuron recruitment), in turn generating a larger

contraction within that muscle.126 In turn with larger contraction a greater metabolic demand

would be generated, producing larger oxygen extraction from the microvasculature, resulting in

the lower oxygenation saturation levels.127

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4.3.2.2 MS and SCI clinical sub-groups

NIRS observations from these two clinical sub-groups demonstrated atypical

hemodynamic and oxygen kinetic patterns during PFM contractions. An increase in oxygenation

during contraction with either restoration to resting levels or continued oxygenation increase in

recovery phase was observed, as shown in Figures 3.13-3.19. There was also less symmetry

observed in the response between the bilateral PFM, as seen in differing curve characteristics in

Figures 3.15, 3.18, 3.19. The atypical NIRS patterns observed in these sub-groups are suggestive

of muscle impairment. A study by Azevedo et al. 2015 investigated oxygen recovery kinetics of

the vastus lateralis with NIRS in COPD patients, not only did they find slower recovery times in

COPD patients, they also observed an increase in oxygenation during both exercise and recovery

intervals, similar to the atypical tracings presented in this study.128 They report that this implies

muscular impairment. The following paragraphs will provide an interpretation attempting to

explain these atypical observations related to muscular impairments.

4.3.3 Explanations for atypical hemodynamic and oxygen kinetic response

4.3.3.1 Innervation

4.3.3.1.1 Pudendal nerve innervation

As Ryan et al. 2014 describes, the oxygenation detected by NIRS is the result of exercise

activating muscle fibers.53 With the atypical patterning characterization similar to clinical sub-

groups with neurological deficits it might possible suggest that certain patterning characteristics

allow inference to motor neuron innervation to the PFM, in that demonstrated atypical patterning

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(either unilaterally or bilaterally), infers impaired motor neuron innervation preventing normal

muscle function and in turn normal oxygenation patterns in response to exercise. With this

possibility of innervation inference, perhaps it could then also be speculated that in the case

group when typical patterning characterization presents in conjunction with urinary symptoms

(as in the high-mobility sub-group), their symptoms might be more related to sensory innervation

rather than motor neuron innervation. This could provide an explanation for why they experience

symptoms but still have similar hemodynamic and oxygen kinetic responses as controls

(suggestive of intact motor innervation).

4.3.3.1.2 Denervation related to pregnancy and labour

SS9 and SS10 were also considered to have high mobility, both had underlying etiology

of vaginal delivery trauma, interestingly, their NIRS tracings had trends boarder lining between

the high mobility and assisted mobility clinical sub-groups. Although both displayed typical

patterning at post-PFMT, the characteristics of the patterning displayed less synchronicity

contralaterally, a characteristic trend found among the assisted mobility group, as demonstrated

in Figure 3.17-3.19. This lack of synchronicity in the musculature response to contraction could

be the result of the delivery trauma (forceps, tears, prolonged 2nd stage labour) causing muscular

defect or pudendal nerve injury, preventing optimal and coordinated muscular

contraction.13,123,129

4.3.3.1.3 Recruitment

Also, when considering motor neuron recruitment, the catch principle may provide some

insight. If impulses to motor units occurring simultaneously generate more force, it may be

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speculated that the control group, with intact innervation was capable of firing impulses

simultaneously or at quicker intervals since they were able to generate higher PFM manometer

pressures. But in the case of interrupted innervation among the case group, impulse conduction

could be less synchronous and have longer time intervals between impulses, resulting in weaker

contractions. This might help to explain the weaker contractions among the case group as

measured by manometer but also the atypical oxygenation patterning observed during

contractions.

4.3.3.1.4 Activation

Weidner et al. 2006 reported that neuropathic injury of the PFM not only caused fewer action

potentials of low amplitude but that they also occurred spontaneously and in fibrillation.13 The

abnormal action potential activity might explain the abnormal increases in oxygen saturation

patterns observed in NIRS. The impulses that are being generated in neuropathic injury occur at

low amplitude and at varying intervals, which could be influencing the weak, delayed,

uncoordinated or absent contractions as observed by NIRS. For example, Figure 3.19,

demonstrates delayed and uncoordinated contraction. At the start contraction, only unilateral

desaturation occurs (and in low magnitude) within the Left PFM, which also begins to resaturate

before cessation of contraction. On the contralateral side, increase in oxygenation occurs at onset

of contraction, with desaturation occurring several seconds after onset of contraction, also

occurring at low magnitude.

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4.3.3.2 Microvasculature

Increased muscle pressure during contraction can cause vascular compression, based on

previous literature demonstrating NIRS response of contracting muscle.50,52,67,100,106,130 As such

the initial sharp downward spike observed at onset of contraction in controls, reflects vascular

compression and the continued desaturation during sustained contraction generates oxygen

demand exceeding that of oxygen supply. Thus, allowing the observation of inverse in O2Hb and

HHb, with HbDiff decrease to reflect oxygen consumption. The slow upward trend of

oxygenation during SMVC before cessation of contraction, can be attributed to the vasodilatory

response of the microvasculature as it attempts to meet oxygen demands. It is probable that

atypical responses in the case group were due to low intensity contraction, not resulting in

vascular compression but through stimulus of attempted contractions a vasodilatory response

might still be occurring. As described by Delorey et al. 2002, exercise causes an increase in

blood volume by means of vasodilation, increased hemoconcentration, and capillary

recruitment.106,127 Vasomotor properties of the vasculature are regulated by the sympathetic

system, which may be responding to cause vasodilation even though there is not enough muscle

activity requiring increased oxygen supply provided from vasodilation.

4.3.3.3 Contractile Intensity

A third explanation for the atypical NIRS responses seen in the case group is the variability

of exercise intensity achieved. Since the high mobility group demonstrated similar tracings to the

control group it can be speculated that they were able to achieve similar contraction intensities.

In the MS group and the SCI sub-groups the atypical pattern presentation could be a result of low

contraction intensity, which is plausible as on inter-group comparison of manometer pressure

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variables were significantly lower for the case group (Baseline: 32.09 vs 13.12 Peak cmH2O,

20.54 vs. 8.13 Average cmH2O and post-PFMT: 35.68 vs 13.91 Peak cmH2O, 23.68 vs 10.30

Average cmH2O; for controls and cases respectively, Refer to Table 3.19 and Figure 3.25).

Boushel et al. 2001, reports that when exercise intensity is not great enough, arterial inflow can

be greater that uptake which causes increased O2 saturation detected by NIRS or no change in

saturation is demonstrated.51 Segal et al. 2005, further describes this physiological occurrence by

the fact that microvasculature supply supports multiple motor units, which allows for increased

blood flow to quiescent muscle fibers as the blood flow is also supporting an active motor

unit.126,131 The increased blood flow to quiescent fibers can be detected by NIRS as unchanged or

increased oxygenation patterns.51 This is also supported by the findings of Ryan et al. 2014, who

reported that even with electrical stimulation they were not always able to achieve desaturation

of the denervated muscle tissue in ALS participants.53 Furthermore, initial response of muscle

microvasculature to contraction is to increase perfusion, which can proceed the activation of

muscle fibers, essentially providing a feed forward mechanism, in that oxygen is made readily

available to support the oncoming muscular contraction.127 This feed forward mechanism could

be what is observed in these NIRS tracings, as increase in oxygenation and blood volume occurs

with attempted contraction, which ultimately occurs at lower intensity not adequate to produce

desaturation or no contraction as result of innervation impairment.

4.3.3.4 Cross Contamination

Another explanation for the atypical changes observed in NIRS oxygenation patterns among

the clinical groups is cross contamination from Valsalva maneuver or accessory muscle use

(obliques, transverse abdominus, hip adductors and flexors, gluteus muscles). Performing a

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correct PFM contraction is difficult even for women without LUTS and intact musculature.132

Although methods, as described in Methods section 2.3.3, attempted to control for this, it could

still be occurring. This cross contamination could be a possibility when the atypical response

occurs with synchronicity across bilateral PFM. Valsalva maneuver and accessory muscle use

result in increased intraabdominal pressure, resulting increased manometer pressures.133 As such

cross contamination may then also increase the oxygenation of the PFM detected by NIRS due to

blood volume distribution from the contraction of adjacent muscle groups, although it may also

be speculated that cross contamination may result in desaturation of PFM due to increased

abdominal pressure causing compression to the microvasculature. This may provide a basis for

lack of cross contamination influence as increased oxygenation was demonstrated. Moreover,

when the atypical response is occurring without synchronicity bilaterally, in that unilateral PFM

produce different responses, such presentation may be more in align with altered innervation,

microvasculature and contractile intensity discussed previously.

4.3.3.5 Applicability of theoretical considerations to an individual case

Altered physiology including innervation, microvasculature, and contractile intensity may

provide insight to the oxygenation responsiveness in isolated unilateral PFM for the case

participants SS12 and SS3, Figures 3.13-3.18. With particular interest in SS3, who demonstrated

oxygenation change detected by NIRS but no measurable pressure with attempted contraction by

manometer. (To reiterate, NIRS and manometer measurements were not performed

simultaneously). Across all three types of contractions: MVC, SMVC and REPS, the manometer

detected no change in pressure. With NIRS the MVCs demonstrated increased O2Hb, tHb, and

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HbDiff to the left PFM. Interestingly, this participant self-reported more sensation below injury

level to their left side.

As has been determined by the concept of central pattern generation, peripheral afferent input

can generate neuronal activation to produce a motor task, without any supraspinal input.126,134-136

Research has concluded that, in the lumbosacral region central pattern generation is crucial for

regulating posture and locomotion.126,134,135 As PFM nerves project from the sacral region, it

may be plausible to consider some degree of central pattern generation regulating PFM,

especially since this muscle group is so closely connected to those of locomotion and

posture.41,42,137-139 It may then be considered that mechanoreceptors in the PFM can send

lengthening sensory information to the lumbosacral spinal cord which in preparation of a motor

response, microvasculature is recruited and increases perfusion to the musculature. Since the

motor innervation is impaired, no contraction occurs and the oxygenation of the PFM remains

elevated due to continued afferent stimuli. The PFM is 70% type I fiber,39 which has a high

concentration of mechanoreceptors sensitive to lengthening.126 Afferent stimuli could be coming

from the mechanoreceptors of the PFM, detecting changes in length due to presence of the probe.

Observations from SMVC of SS3 at baseline, Figure 3.16, are suggestive of NIRS capturing

oxygenation patterns of PFM due to central pattern generation as a result of free nerve ending

excitation. Free nerve ending excitation can be provoked by mechanical and metabolic stimuli,126

and is given particular attention in SCI as a contributor to spasticity.134 It is plausible that in the

case of SS3, excitation of free nerve endings results from PFM mechanoreceptors detecting

change in muscle length induced by the presence of the NIRS probe. Which results in an

oscillatory motor output causing the PFM to contract. As evidenced in Figure 3.16, desaturation

is apparent after an initial increase in HbDiff and O2Hb, within the time frame that the

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participant is actively attempting a contraction. However, once “voluntary” contraction is over

(denoted by the black ox), several more desaturation patterns occur in repetition. This is

suggestive that the unilateral Left PFM at baseline assessment, actually demonstrated a spasm

rather than a voluntary contraction. This would be further supported by that desaturation does not

occur in opposite unilateral PFM, during any other attempted voluntary contraction, no detected

manometer pressures during attempted contractions, along with the clinical history of the

participant, non-traumatic SCI T8 AIS-B.

4.3.4 Objective outcome measures

4.3.4.1 Inter-group objective PFM function outcomes

The control group demonstrated better PFM function than the case group at both baseline

and post-PFMT, with regard to objective measures, including: Peak cmH2O and Average cmH2O

manometer variables (Table 3.19), as well as ½RT (Table 3.12) and DMag (Table 3.14) NIRS

variables. Although, values for these outcome variables were better for the control group

compared to the case group, they did not always achieve statistical significance.

With this in mind, the findings still suggest that the case group has weakened contractile

strength1,22,140 and reduced oxidative performance.49 That the ½RT was slower for the case

group also demonstrates that the oxidative kinetics of the PFM has reduced capacity to restore

homeostasis proceeding muscular contraction, indicating more fatigability than the control

group, as would be expected with assumed PFM atrophy among the case group.126 Furthermore,

the reduction in DMag achieved during contraction suggests reduced oxygen demand generated

during contraction, which supports (1) the manometer evidence of reduced contractile strength,

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in that lower contraction intensity would also create lower oxygen demand, and (2) limited

oxygen uptake capability of the PFM. Which be explained by the physiological consequences

experienced by the case group, such as impaired innervation, muscle atrophy, diminished

microvasculature, transition of muscle isoform composition to type II fibers.

These findings are also supported by previous literature reporting diminished PFM

strength in incontinent females compared to continent controls.92,140-142 Also, NIRS

investigations of oxygen kinetics in individuals with neurologic conditions determined these

sample populations to have slower oxygen recovery kinetics than able-bodied

counterparts.53,130,143 In addition, Jürgensen et al. 2017, reported that in continent females, PFM

strength (measured by manometry) is correlated to whole body aerobic capacity (measured by

oxygen consumption and ventilatory anaerobic threshold), however, the correlation reported only

had moderately positive significance (r= 0.55).137

4.3.4.1.1 Half Recovery Time (½RT) outcomes

At baseline the control group demonstrated faster ½RT than the case group, for both

Right and Left PFM (6.30 vs 18.90 seconds and 11.39 vs 19.36 seconds, respectively, refer to

Table 3.12) with the difference being statistically significant for the unilateral Right PFM (p-

value <0.01). Interestingly, the control group also demonstrated Right PFM dominance based on

Fz, ½RT and DMag measures of dominance (refer to Tables 3.7, 3.10), suggesting that the

controls not only had better bilateral oxygenation recovery kinetics of PFM, but this appeared to

be specific to their dominant side. Furthermore, the case group appeared to demonstrate Left

PFM dominance based on Fz, ½RT and DMag measures of dominance (refer to Tables 3.7, 3.9,

3.10). This suggests that the lack of statistically significant findings on ½RT of unilateral Left

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PFM is due to the fact that the controls generally had worse ½RT in their dominant PFM and the

case group demonstrated greater ½RT in their dominant PFM, making the unilateral left PFM

more comparable to each other. This is in contrast to the contralateral Right PFM, in which the

control was more dominant and the case group less dominant, pronouncing the difference of

PFM oxygen recovery kinetics between the two groups.

At post-PFMT faster ½RT values for the control compared to the case group in both

Right and Left PFM were maintained, (7.87 vs 38.03 seconds, and 9.55 vs 18.54 seconds,

respectively, refer to Table 3.12). Again, statistical difference was only demonstrated among the

unilateral Right PFM (p-value 0.01). Further supporting dominant derived differences among the

two groups.

4.3.4.1.2 Delta magnitude change (DMag) outcomes

At baseline the control group demonstrated greater DMag (oxygen consumption) than the

case group, for both Right and Left PFM, however these differences did not yield statistical

significance (-7.31 vs -1.53 µmol and -5.04 vs -2.21 µmol, respectively, refer to Table 3.12). At

post-PFMT the control maintained greater DMag desaturation values compared to the case group

for both Right and Left PFM, (-10.34 vs -2.19 µmol, and -8.49 vs -8.06 µmol, respectively, refer

to Table 3.14), however, in this instance the difference among unilateral Right PFM yielded

statistical significance (p-value 0.01). Interestingly, this supports the findings of ½RT in relation

to PFM dominance, as the case group demonstrated comparable desaturation values with their

dominant side of the Left PFM and the pronounced difference in desaturation in the Right PFM

between groups due to Right dominance of control group.

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4.3.4.1.3 PFM manometry outcomes

At baseline the controls performed better compared to the case group across all three

variables with statistical significance achieved for: Peak cmH2O, Average cmH2O and Timesec

(32.09 vs 13.12 cmH2O p-value <0.01, 20.54 vs 8.13 cmH2O p-value <0.01, 1.30 vs 1.08

seconds Lg10 p-value 0.04).

At post-PFMT the controls maintained better performance than the case group across all

three variables, with statistical significance achieved for peak and average cmH2O but not for

Timesec (35.68 vs 13.91 cmH20 p-value <0.01, 23.68 vs 10.30 cmH20 p-value 0.02, 1.29 vs 1.05

seconds Lg10 p-value 0.18).

This supports the findings of the NIRS variables demonstrating better oxygen kinetics

among the control group, allowing for more functional strength and endurance of the PFM as

measured by manometry. Although, there was no difference in Timesec between the two groups,

the fact that the Peak and Average cmH2O achieved are lower, implies that the cases do not have

comparable levels of muscular endurance needed to sustain higher levels of contractile intensity.

4.3.4.2 Intra-group objective PFM function outcomes

Neither the control group or the case group demonstrated an improvement of objectively

measured PFM function from baseline to post-PFMT assessment, for the following variables:

Peak cmH2O and Average cmH2O (Table 3.18), as well as ½RT (Table 3.11) and DMag (Table

3.13). This was surprising as previous literature has reported improvement in PFM strength and

symptom scores after PFMT intervention, and PFMT is considered first line therapy for urinary

incontinence (regardless of type).20,21

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A possible contributing factor for this lack of improvement is the fact that the PFMT

utilized was a home-based therapy only; should supervised sessions have occurred throughout

the intervention more pronounced improvements may have been observed, as reported in studies

which have employed such means of supervised PFMT.141,144,145 Also, the duration of PFMT

may not have been long enough to result in improved performance, varying lengths of PFMT

have been used in research and no standardized time frame has been documented. Duration range

for effective therapies reviewed in the literature spanned from 2 to 6 months of training, with

various dosing of exercise intensities and modalities.20,21,146 Impaired innervation within in the

case group may have resulted in insufficient activation of the PFM to produce meaningful

contractions at intensities required to elicit a training effect. For the more severe cases of

neurologic conditions, where only a flicker response was seen at baseline, it is likely that

neuromuscular stimulation may be the best approach to induce beneficial neuronal and muscular

adaptations.25 Overall adherence to PFMT was also low, which has a direct negative impact the

improvement outcome measures. Specific to the control group, it is possible that the PFMT

intensity was not demanding enough promote muscular hypertrophy and oxygen kinetic

improvements, as these adaptations are specific to intensity of exercise regimes, as explained by

the overload principle of strength training.147,148

4.3.4.2.1 ½RT outcomes

Neither group demonstrated an improvement of ½RT from baseline to post-PFMT. In

addition to general explaining factors for this lack of anticipated finding, another consideration

specific to the ½RT should be considered. The PFMT utilized was meant to target both strength

and endurance of PFM, and therefore should be activating both fiber types, although the PFM is

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70% type 1 fibers. With regards to specific endurance training, slow fibers tend to have small

changes in mitochondrial enzymes promoting oxidative phosphorylation, whereas their

neuroelectrical properties tend to demonstrate larger changes.126 This could perhaps be a

contributing factor to lack of improvement in ½RT from baseline to post-PFMT. Furthermore, as

recovery kinetics are most likely to be influenced by increased number of mitochondria within

the muscle tissue, and this adaptation requires consistent progressive training to a point which

exceeds the initial PFM endurance capacity, that which was measured at baseline.149

The control group demonstrated a significant difference between Right and Left PFM

½RT at baseline (6.30 vs 11.39 seconds p-value 0.02 (Lg10), respectively, refer to Table 3.11).

Again, this supports the controls demonstrated greater oxygen recovery kinetics within their

dominant side based on Fz scores. Interestingly, this significant difference disappeared at post-

PFMT (7.87 vs 9.55 seconds p-value 0.72, refer to Table 3.11), although this was initially

thought to suggests improved synergistic recovery response of the bilateral PFM at post-PFMT,

the degree of dominance for controls increased at post-PFMT, contradicting this initial

interpretation (5.16 compared to 10.38 at post-FMT, refer to Table 3.12)

Also, interesting to note is that the ½RT dominance of controls from baseline to post-

PFMT was not significantly different but neither was it correlated (1.46 vs 1.67 p-value 0.13, rs

0.11, refer to Table 3.11) suggesting some degree of variability, even though dominance was

maintained on the Right PFM. Whereas the case group also did not demonstrate any difference in

the ½RT dominance from baseline to post-PFMT, these variables were highly positively

correlated (-8.20 vs -7.56 p-value 0.89, r -0.91 p-value <0.01, refer to Table 3.11). This suggests

that ½RT dominance was not altered among the case group after PFMT, meaning improved

coordination between bilateral PFM did not occur.

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4.3.4.2.2 DMag outcomes

In general, the DMag of desaturation increased for all variables from baseline to post-

PFMT in both groups, although no statistical significance was determined. This may infer some

improvement in oxygen consumption of the PFM, suggesting the muscle tissue may have

responded to certain aspect of the training, but was not enough to elicit a demonstrable difference

or to influence the recovery kinetics. As the PFMT was only for 8-weeks, this duration would not

be long enough to induce muscle hypertrophy, therefore the suggestion of reduced desaturation

after PFMT would likely be due to neuronal adaptations.18,25 Such adaptations could include

increased firing rates and increased motor unit recruitment that can cause increased muscle

contractile properties, which in turn would result in greater desaturation as more muscle fibers

are active and at higher intensity.

Furthermore, both groups maintained the DMag dominant side, similar to the ½RT

dominance variables. The DMag dominance of controls from baseline to post-PFMT was not

significantly different but neither was it correlated (1.54 vs 1.85 p-value 0.91, r 0.08, refer to

Table 3.13) suggesting some degree of variability, even though dominance was maintained on

the Right PFM within the controls. Whereas the case group also did not demonstrate any

difference in the DMag dominance from baseline to post-PFMT, these variables were highly

positively correlated (-3.23 vs -6.69 p-value 0.87, r 0.75 p-value 0.05, refer to Table 3.13). This

further supports the suggestion that PFM dominance, as measured by NIRS variables, was not

altered among the case group after PFMT, meaning improved coordination between bilateral

PFM did not occur.

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4.3.4.2.3 ½RT and DMag associated outcomes

Interestingly the only correlations demonstrated in either group were in the non-dominant

PFM (according to Fz and NIRS variables of dominance). The control group demonstrated a

moderately positive correlation between ½RT and DMag in the Left PFM at baseline (rs 0.65 p-

value 0.02, refer to Table 3.15). This suggests that as the ½RT lengthened, less DMag

desaturation occurred, implying limited oxygen consumption occurred with reduced recovery

kinetics (limited oxygen uptake and limited oxygen supply). However, at post-PFMT correlation

was not demonstrated in the non-dominant PFM of the controls. This does not imply that oxygen

uptake and delivery mechanisms improved but it may support the suggestion of a change in one

of these variables, further supporting the idea of some improved uptake mechanism due to

PFMT, but in this case specific to the non-dominant PFM.

Although the case group demonstrated a correlation between NIRS variables, this did not

occur at baseline as it did in the controls. Rather at post-PFMT data shows a highly positive

correlation between ½RT and DMag (rs 0.93 p-value <0.01, refer to Table 3.13 and Figure 3.23).

That this correlation presented at post-PFMT suggests greater oxygen uptake occurred with

reduced ½RT, suggesting some training effect may have taken effect in the non-dominant PFM.

4.3.4.2.4 PFM manometer outcomes

No statistical significance was determined in both groups in manometry variables from

baseline to post-PFMT. Despite lack of statistically significant findings, the control group

demonstrated slight improvements in all variables whereas the case group actually demonstrated

slight worsening at post-PFMT. The lack of improvement was not anticipated as it has been well

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documented in the literature that PFMT can be effective. It is possible that the standardized

PFMT methods used in this study were not at appropriate dose for individual participants and

therefore the therapeutic effect was not achieved. Furthermore, overall adherence to PFMT was

low which will influence these results. The slight reduction also observed in the case group could

also be due to the fact that one participant had 0% adherence to PFMT, another participant

experienced symptomatic episode of relapse-remitting MS and a third participant reported a

week of hospitalization (cause of which was unrelated to study).

Although there was a lack of difference for both groups between baseline and post-

PFMT, correlation of most variables between assessments were highly positive, suggesting that

participants who performed well at baseline also performed well at post-PFMT.

4.3.4.2.5 ½RT and PFM manometer associated outcomes

When intra-group ½RT and manometer variables were correlated, interestingly only the

case group demonstrated a significant correlation at post-PFMT. Furthermore, the correlation

that was demonstrated for bilateral PFM ½RT and all manometer variables was highly negatively

correlated, as presented in Table 3.22 and Figure 3.26-3.27, (Right ½RT and Timesec had highly

negative correlation although this did not reach significance, r -0.73, p-value 0.06). This suggests

those participants that demonstrated greater PFM strength at post-PFMT, as per higher pressure

measures and increased contraction duration, or endurance, also demonstrated quicker recovery

times, or greater oxidative performance.

This infers that among the case group, greater PFM strength corresponds with oxygen

recovery kinetics of the musculature. As this relation was not observed at baseline, it suggests

that perhaps some training effect occurred for the case group, since in response to exercise,

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corresponding adaptations occur in motor neurons and metabolic properties in order to increase

muscle activation and oxidative capacity.126 Although, if changes in muscle volume and its

consequent adaptations occurred, improvements in manometer and NIRS variables from baseline

to post-PFMT would also be expected, which was not observed in this study, with reasoning for

this lack of finding discussed previously.

4.3.4.3 Lower limb and PFM dominance outcomes

4.3.4.3.1 Fz and WFQ dominance outcomes

Isolating bilateral PFM response to exercise was examined in this study in attempt to see

whether contralateral muscular function might help explain PFM dysfunction and LUTS. It was

also hypothesized that PFM dominance would be more pronounced in the case group due to the

nature of innervation impairment. Furthermore, since the PFM plays an integral role in posture

and lumbosacral support, 41-43 it was thought that measure of lower limb dominance would be

associated with PFM unilateral dominance. For this reason, the relationship between Fz, WFQ

and NIRS dominance variables was assessed.

Inter-group comparisons of both DisFz and QFz demonstrated significance difference

between the two groups, controls demonstrating greater dominance in Right lower limb (as

indicated by positive value) and case group demonstrating greater dominance in the Left

dominant (as indicated by negative value). (DisFz 0.11 and -0.07, p-value <0.01, QFz 0.09 and -

0.05, p-value <0.01, refer to Table 3.10). As demonstrated in Table 3.10, no other differences

were found between groups for the remaining dominance variables.

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Intra-group comparison of DisFz and QFz for both groups did not demonstrate significant

difference, indicating that lower limb dominance during stabilization tasks is maintained during a

distractive cognitive stimulus. This is further evidenced by the high positive correlation between

DisFz and QFz among the control group (rs 0.83, p-value <0.001, refer to Table 3.8 and Figure

3.2).

Despite the objective measure of lower limb dominance during both distracted and quiet

stance, the WFQ measure of self-reported lower limb dominance as described by “footedness”

did not demonstrate a difference between the two groups as both groups reported greater

preference for their Right foot. This WFQ measure indicating Right foot preference among the

controls appears reasonable, since as a group across all measures of dominance (including NIRS)

they demonstrated positive average values, indicating greater responsiveness on their Right side.

However, the WFQ measure indicating Right foot preference among the case groups is curious,

since as a group across all measures of dominance they demonstrated negative average values,

indicating greater responsiveness from their Left side.

It was initially expected that WFQ scores would be associated with Fz scores of

dominance, however, this was not demonstrated. The lack of correlation between these variables

could be due to the fact that the WFQ poses questions that pertain to two type of motor tasks,

stabilization and active movement,89 although both types of questions are equal in number the

responder may be more likely to choose their motor task foot for both types of questions with the

perception that the preferred foot indicates greater strength of that lower limb, making it the best

choice for all tasks. Research by Hart et al. 1997 and Grouios et al. 2009, determined that the

WFQ is not a good indicator of motor task dominance, as they found that participants commonly

switched limbs when actually performing a motor tasks, contradicting what they reported on the

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WFQ.150,151 This could explain why none of the of the lower limb dominance measures

correlated with the PFM NIRS dominance measures, (refer to Table 3.9), as Fz scores measured

lower limb dominance during a stabilization task and the NIRS dominance measures were

assessing PFM dominance during an active movement motor task.

4.3.4.3.2 NIRS dominance outcomes

With implementation of PFMT it was thought that PFM dominance as determined by

NIRS would decrease, as PFMT is thought to promote coordination within the whole muscle

group.28,92,132,152 Also, it has been determined that training can cause neuromotor adaptations in

response to exercise training can result in contralateral limb improvements.148 It was thought

that this might translate to the PFM, in that the weaker or non-dominant side would experience

benefits directly from engagement in the PFMT, and further promoted by this contralateral

phenomenon as the dominant PFM may be producing the majority of the work performed by the

PFM during the training regime.

Among both the control and case groups no difference was demonstrated between

baseline and post-PFMT for ½RT Dominance (refer to Table 3.11) or DMag Dominance (refer to

Table 3.13). Interestingly, the case group demonstrated high positive correlation between

baseline and post-PFMT for ½RT (r 0.91, p-value <0.01) and for DMag Dominance (r 0.75 p-

value 0.05). Although DMag Dominance did not reach statistical significance, these correlations

both suggest that PFM dominance was more consistent within the case group and tended to

remain within the unilateral Left PFM, as values indicated by negative values, refer to Tables

3.11 and 3.13.

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Furthermore, absolute values for both ½RT and DMag NIRS dominance were utilized to

examine the degree of dominance. The absolute ½RT and DMag NIRS dominance (degree of

dominance) provides a parameter representing how pronounced the difference is between

unilateral Right and Left PFM in their oxygen kinetic performance. A smaller absolute value of

degree of dominance indicates the Right and Left PFM were more similar, meaning the dominant

side was less pronounced, suggestive of a more coordinated bilateral PFM oxygen kinetic

performance. A larger absolute value of degree of dominance indicates the Right and Left PFM

were less similar, meaning there was more prominent unilateral dominance in the PFM,

suggestive of less coordination between of the bilateral PFM oxygen kinetic performance. Thus,

allowing for a means of assessing of improved coordination within the bilateral PFM in response

to PFMT. At baseline inter-group comparison demonstrated a significant difference between the

degree of ½RT Dominance, that of controls being much less than the case group (5.16 and 17.41,

respectively, p-value <0.01, refer to Table 3.12). However, at post-PFMT the degree of ½RT

Dominance between the two groups was comparable (10.38 and 15.64, respectively, p-value

0.39, refer to Table 3.12). The fact that the control group demonstrated an increase in the degree

of ½RT Dominance suggests that there might be reduced coordination during PFM after the

PFMT. This could imply that only the dominant PFM responded to the PFMT, thus causing the

increased dominance, however this is not supported by the comparison between Right and Left

½RT post-PFMT which did not demonstrate a significant difference bilaterally. Neither did the

Right of Left ½RT improvement at post-PFMT, refer to Table 3.11.

Interestingly, both groups did not demonstrate any difference between the degree of

DMag Dominance at baseline or post-PFMT (refer to Table 3.14), suggesting that the difference

between desaturation of unilateral PFM within groups at each assessment was comparable.

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4.3.4.3.3 Degree of NIRS dominance and PFM manometer outcomes

Intra-group correlations between degree of ½RT Dominance and Mag Dominance did not

demonstrate any significant findings within the control group. The case group showed some

suggestion of a moderate negative correlation between degree of ½RT Dominance and

manometer Peak and Average cmH2O, however this did not reach statistical significance (r -0.69,

p-value 0.09 and r -0.67, p-value 0.10, respectively, refer to Table 3.20). This implies that less

difference between the ½RT of unilateral PFM, or a more coordinated response from the PFM,

could be related to better PFM strength (higher Peak and Average cmH20 pressures). Since the

correlations were only moderate and not statistically significant this implication is only

suggested and not confirmed.

4.3.4.3.4 Degree of NIRS dominance and PFMT adherence outcomes

The control group demonstrated a moderate negative correlation between degree of ½RT

Dominance and both Exercise Volume and Frequency (r -0.69, p-value 0.02 and r -0.61, p-value

0.05, respectively, refer to Table 3.25 and Figure 3.55), although only the correlation to Exercise

Volume had statistical significance. This provides a possible implication that greater adherence

to PFMT was associated with greater similarity of the bilateral PFM recovery response from

contraction, suggesting more consistent exercise could improve coordinated muscular effort in

health tissue.

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4.3.4.4 QOL and clinical symptom outcomes

4.3.4.4.1 Inter-group QOL and clinical symptom outcomes

According to Dumoulin et al. 2018, general improvements of LUTS are experienced by

females with pelvic floor dysfunction and incontinence who have undergone PFMT.20 These

reported improvements are measured by the same validated questionnaires utilized in this study.

As such it was expected that symptom scores would reduce at post-PFMT for the case group and

demonstrate a larger degree of reduction from the control group. However, inter-group

comparison of both QUID, and PVR score changes did not demonstrate statistically significant

differences of change incurred between groups. Although not statistically significant, these

variables did demonstrate larger reductions among the case group, refer to Table 3.6.

4.3.4.4.2 Intra-group QOL and clinical symptom outcomes

Intra-group reductions in symptom scores were expected at post-PFMT. This hypothesis

was directed towards to the cases group, however, as some controls did report symptoms on the

QUID, diminishment of symptoms would also be expected. Although not significant, controls on

average did show a reduction in all measured questionnaire variables and for PVR. Similar

findings were demonstrated among the cases, however, only a statistically significant reduction

in the QUID-UUI score at post-PFMT was demonstrated (7.5 and 5.0, p-value 0.03, refer to

Table 3.4). As this is an indication of LUTS specific to urgency symptoms, it appears that PMFT

had more of an impact on urge related incontinence rather than stress related incontinence. This

could be due to the fact that urgency and UUI are symptoms related to detrusor overactivity,

which is a common characteristic of neurogenic bladder.8-10,30 PFMT can effectively reduce

133

symptoms of urgency, as PFM contractions can inhibit detrusor activity by means of afferent

stimulation eliciting the guarding reflex to suppress parasympathetic excitation in the sacral

nerves innervating the bladder.24,28 In addition to suppression of the parasympathetic excitation,

PFM contraction also promotes sympathetic excitation of the sacral nerves. This results in

internal sphincter closure and inhibition of detrusor activity.24,28

Even though the case participants reported a reduction in urgency symptoms it is

interesting that the average frequency recorded on the 3-bladder diary increased (6.74 to 7.29

voids/day, refer to Table 3.5), typically a measure associated with urgency.8 However, this

increase from baseline was not significant and nor were any of the other bladder diary variables.

Similar findings in lack of significant improvement of bladder diary measures are reported by

McClurg et al. 2006.25 McClurg et al. 2006, also found that when females with MS received

PFMT without biofeedback or NMES, there was no statistical improvements found on QOL

scores measured by the IIQ and UDI (full length versions).25 This was also demonstrated in this

study, as the results from the IIQ-7 and UDI-6 both reduced, refer to Table 3.4, but not

significantly.

4.3.4.5 PFMT Adherence outcomes

Adherence to is the most important indicator for successful rehabilitative PFMT.25,153,154

An ICS consensus report identified six key barriers to PFMT adherence: knowledge regarding

PFM function and reasoning for PFMT, competence regarding physical skill of correct PFM

contraction, emotional perceptions surrounding PFMT, cognitive engagement, prioritization,

accessibility of service provider.155 In addition to addressing these barriers, Dumoulin et al.

2014 emphasize the importance of instructing proper PFM contraction, education of pelvic floor

134

function and benefits of PFMT.153 This was performed both at baseline and post-PFMT, where

PFM anatomy and function were reviewed, along with instruction and practice of corrected PFM

contraction.

Although adherence is considered an integral part of PFMT there is no standard method

of measuring it and in turn no set parameters to distinguish acceptable levels of adherence.153,156

Adherence in this study was measured by percentage of total amount of required exercises

completed per day (Exercise Volume) and the percentage of days any amount of the exercises

were completed over the course of 8-weeks (Exercise Frequency). McClurg et al. 2006 reported

high adherence rates, considered to be >75%, among their participant population,25 and Borello-

France et al. 2010, reported initial high adherence rates of 81% and 90% for both exercise

frequency and volume measures.157

According to the reported rates from these studies, it can be inferred that both the control

and case groups demonstrated low levels of adherence when considering the Exercise Volume

adherence was 51.10% and 52.23%, respectively (refer to Table 3.23). Similar low adherence

rates were reported by Porta Roda et al. 2016, who had 50% adherence rate among women with

UI performing home-based PFMT.156 Although adherence was better for Exercise Frequency

among both groups, 62.91% and 78.57%, (refer to Table 3.23), with the case group

demonstrating greater frequency. If considering the interpretation by Fitz et al. 2017 and

McClurg et al. 2006, of high adherence as 75-81%, the case group met this criterion for the

Exercise Frequency measure of adherence.25,29

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4.3.4.5.1 Adherence and reduced urgency symptoms

As shown in Table 3.24 and Figure 3.30, a highly positive correlation was determined

between all PFM manometer variables and percentage of Exercise Frequency among the case

group. This provides evidence that participants who performed excises more consistently

throughout the 8-week intervention had better PFM function as measured by PFM manometer

variables of strength and endurance. Furthermore, the significant reduction in QUID-UUI score

from baseline to post-PFMT found among the case group was also highly negatively correlated

to Exercise Frequency (rs -0.85, refer to Figure 3.31). Data presented in Figure 3.31, seems to

suggest that adherence rates of >80% of Exercise Frequency over an 8-week intervention period

is required to reduce urgency symptoms. This finding is supported by Fitz et al. 2017,29 who

found that high adherence of 80% to home exercise routine reduced overactive bladder

symptoms and improved PFM function.

4.3.4.5.2 Adherence and PFM function outcomes

In addition, among the case group, the DMag and ½RT variables of the non-dominant

PFM also demonstrated a high negative correlation to Exercise Frequency (rs -0.78 and rs -0.85,

respectively, refer to Tables 3.25-3.26 and Figures 3.33-3.34), suggesting improved oxygenation

and recovery kinetics with greater frequency of daily exercise. High adherence rates (specific to

Exercise Frequency) among cases was also positively associated with PFM manometer

measures, (Table 3.24 and Figure 3.30). This agrees with literature concerning the importance of

adherence for promoting beneficial PFMT effects.20,28,154-156 Interestingly, the controls on

average did not exceed an adherence rate >75% for both variables (Table 3.21-3.24), which did

not demonstrate correlation to PFM manometer, DMag or unilateral ½RT variables.

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Chapter 5: Conclusion

This chapter will highlight the main findings of the research and address how they align

with the objectives and hypotheses of this project. The strengths and limitations pertaining to this

project will be discussed while also providing suggestions for future directions for continued

research in this area. This chapter will finalize the thesis with concluding statements specific to

the findings within this project while providing relevance for clinical applicability.

5.1 Main Findings

The primary aim of this project was achieved through the successful development of an

original transvaginal NIRS probe capable of isolating bilateral PFM function. This was the first

study to our knowledge that incorporated NIRS technology to investigate the bilateral PFM

physiological response to exercise. Based on the findings of this research we conclude that the

NIRS probe designed in this project is capable of detecting differential oxygen kinetics of the

PFM bilaterally, thus meeting the primary objective. Observational NIRS findings agree with

the hypothesis that contralateral differences would be detected in unilateral PFM responsiveness,

although this finding was specific to underlying etiology and mobility status.

The NIRS variables demonstrated similar results to that of manometry, in that greater

PFM function was established in controls compared to the case group at both assessment points.

In addition, neither device was capable of detecting intra-group differences in PFM function after

implementation of PFMT. Whether this is due to the inherent capabilities of the devices or other

factors such as PFMT dose and adherence remains unanswered and warrants further

investigation. Nevertheless, the comparable findings support the second hypothesis that NIRS

parameters of PFM function will relate to those of manometer parameters. The case group

137

demonstrated high correlation among oxygen recovery kinetics and PFM strength and endurance

at post-PFMT, demonstrating a relationship indicative of greater oxygen recovery capacity

corresponding with greater muscular strength and endurance. However, the second hypothesis

would have been more strongly supported had all NIRS and manometer parameters demonstrated

correlation at both assessment time points for both groups, which was not evidenced in this

study.

In contrast to the original hypothesis, lower limb dominance did not demonstrate a strong

relationship to PFM dominance. It was also thought that lower limb dominance as measured by

percentage of ground reaction force exerted by each limb, might differ during different standing

conditions. In both groups no difference was detected between lower limb dominance in

distracted (DisFz) or quiet stance (QFz). Furthermore, the WFQ did not demonstrate association

with either Fz dominance variables or NIRS dominance variables, suggesting it is not a good

predictor lower limb dominance during stabilizing motor tasks or PFM dominance during active

motor movement tasks. Inconclusive statements can be made regarding PFM dominance based

on the findings in this study, however the suggestion among the case group data of degree of

½RT dominance reducing with higher manometer pressures at post-PFMT and the control group

demonstrating reduced degree of ½RT dominance with increasing exercise adherence, suggest

that this parameter warrants further investigation.

It was hypothesized that PFMT would improve PFM strength, endurance and oxygen

kinetics. This was not demonstrated in either group, likely due to the factors regarding PFMT

dose and adherence. A PFMT with regular supervised sessions, longer duration and adjunctive

therapies such as NMES should be considered in futures studies of this population.

138

Clinical symptoms of urgency were significantly reduced among the case group after

PFMT intervention, but this did not translate into significant improvements of QOL.

Finally, as hypothesized, adherence to PFMT was a strong determinant in promoting

beneficial effects of PFMT, observed in its relation to improved NIRS, manometer variables and

urgency symptoms among females with LUTS due to impaired pelvic innervation. For this

sample population a daily adherence rate of 80% appeared crucial for reducing urgency

symptoms. From the results of this study it appears that daily consistency of PFM exercise is

important to promote therapeutic effects and is positively associated with better PFM strength

and endurance. PFMT adherence did not demonstrate a strong association to oxygen kinetics of

healthy PFM in controls, which was not expected and should be further investigated in future

studies.

5.2 Limitations

With respect to the actual construction of the probe there are some considerations around

light emission and detection. The transparent plastic encasing of the probe adds an extra physical

barrier that the NIR light must travel through, which can alter the path of emitted light directed

towards the musculature. As was experienced with the first probe design a degree NIR light was

being refracted by the plastic encasing, preventing adequate emission of NIR light to the

musculature to get an appropriate signal. With adjustment of the opaque foam inlay, the scatter

of NIR light was reduced to prevent refraction from interfering with the emission and detection

of light attenuation, allowing for sufficient signal strength. (Additional details regarding NIR

light properties and technical probe design, refer to Introduction section 1.2.3 and Methods

139

section 2.3.4, Figure 2.5). However, some degree of light scatter and refraction could still be

occurring due to the inherent nature of light have to pass through this physical barrier.

Although an advantage of NIRS is its specificity in targeting muscular tissue area of

interest, this can also pose a limitation. As the NIRS probe targets only a small cross- sectional

area of the PFM,49 it must be assumed that all the PFM behaves in the same manner as the target

site. Since it is known that microvasculature can supply more than one motor pool, and that not

all motor pools supplied by the same microvasculature may be activated simultaneously, the

NIRS could be detecting hemodynamic changes in quiescent motor pools due to neighbouring

active motor pools. Although this would likely only be in the case when NIRS detected no

change or an unexpected increasing in oxygenation in response with contraction, and since these

atypical NIRS tracings were seen among the case group, it would still be a relevant finding in

that implies that not all motor pools of the PFM are activated when exercise conditions warrant

full activation.

Another technical limitation with the NIRS probe is the consistency of placement during

assessment both at within and across assessments. As described in the Methods section 2.3.4, the

design of the NIRS probe was such have same detection area as the PFM manometer with a

marker to indicate similar insertions depth among the two devices. Although placement during

any PFM assessment method (digital palpation, manometer, dynamometer, EMG,

ultrasonography), is likely to vary to some degree, and all these methods are still employed with

acceptable levels of reliability and validity.1,83,91,159-161

As mentioned in the Methods section this probe design was modelled after that of

Shadgan et al. 2008, which determined that movement artifact during contraction did not

compromise the NIRS tracings as positioning was well maintained with the probe handle.74

140

Furthermore, to maintain consistency of targeted PFM, the optodes were positioned in alignment

with the PFM manometer sensor, as described in more detail with illustrations in Methods

section 2.3.4 and Figure 2.5. However, although we attempted to control for consistency of

placement across the two devices, the NIRS configuration we utilized only had two detection

sites, and should the device move in a clockwise or counter clockwise direction once in situation,

it could alter the target area of investigation.

A constraint in using NIRS to study the PFM is that the specific path length differential

of this muscle has not been identified and therefore the DPF of 4 was used based on previous

NIRS methodology and literature reporting skeletal muscle DPF values. Furthermore, a

definitive DPF cannot be obtained with CW-NIRS modality. Therefore, the fixed value of DPF 4

was used, even though it is known that the pathlength factor will have variability within the

muscle from one subject to the next and due to the cellular environment changes induced by

exercise.66,67,76

An issue posed with any PFM assessment is the influence of activated accessory muscles

during contraction or the inappropriate response of Valsalva and/or straining. Efforts to minimize

accessory muscle contraction are described in Methods section 2.3.3. Although precautions were

taken, it is possible that undetected accessory muscle contributed to some degree with PFM

contractions. This is particularly true in the case group, where participants with very weak

contractions demonstrated only a perineal flicker during contraction.

There were many recruiting challenges for this study that lead to a small sample size and

heterogeneity among the case group of interest. To begin with the population of interest, females

with incomplete spinal cord injury and specific bladder symptoms of urinary incontinence is a

limited population. Interested females also had to be willing to undergo pelvic floor exam which

141

hindered some individual interest. Also, the fact that altered motor and sensory innervation due

to spinal cord injury or neurological condition present with great variation, even when

underlying injury level is the same or neurological condition is similar, further resulting in large

heterogeneity.

Although this is a limitation of the study and presents challenges for statistical

comparison, we are still able to draw some meaningful insight from the observational trends

within the study population. Also, the fact that is a heterogeneous population may make the

findings more clinically relevant as it would be more similar to the clinical population presenting

to health care providers in real life situations. Challenges with recruitment for small clinical

populations of study interest with the use of NIRS has been discussed by Ryan et al. 2014, who

also attest to the value of discussing observational trends of the data in conjunction with the

statistical findings.53 The findings from this pilot study also help to lay the groundwork for

development of a larger scale study with more a targeted population.

Exercise adherence was low among participants as whole and is a warranted factor for the

lack of statistical significance in comparison of outcome variables from baseline to post-PFMT.

Adherence rates for both Exercise Volume and Frequency might have been improved had the

PFMT intervention included supervised sessions or biofeedback during exercise at home, as

these factors have been reported to promote motivation and self-efficacy.28,154 However, 75%

the case participants completed at least 82% of required days (Exercise Frequency), during

PFMT intervention, (refer to Figure 3.29). Given that transportation is an accessibility barrier

limiting exercise participation among individuals with SCI,147 the use of a home-based PFMT

could be well suited for some individuals. Perhaps longer-term follow-up (4, 6, or 12months) of

home-based PFMT that also includes a supervision component, weekly or monthly visits, would

142

better facilitate and capture PFM improvements.20,162,163 Research from Sran et al. 2016

demonstrated that PFMT with weekly supervision in combination with home-based routine for 3-

months was beneficial for women with osteoporosis and UI.144 Bø et al. 1990,18 demonstrated

that with PFMT adherence of 100%, both unsupervised home exercise and supervised home

exercise groups had significant improvements at 1-month but that the supervised group

continued to greatly increase strength at 6-months. 18

Lastly, the average age between groups was determined to be significantly different, with

the case group being older. This introduces a limitation to comparison between groups. Since it

is known that with increasing age skeletal muscle function diminishes.12,121 Utilizing an age

matched cohort design should be considered for future investigations of this nature.

5.3 Strengths and Future Directions

The strengths of this study are the success of the technical development of the NIRS

probe in isolating the physiological response of bilateral PFM and in its capability of detecting

PFM performance under exercise conditions. The fact that the captured NIRS tracings were

different between controls and case groups provides evidence that this NIRS probe can provide

insight to the altered physiological state of impaired PFM function due to neurological

conditions in females. Furthermore, the fact that the NIRS traces of the control group were

typical of that expected of healthy skeletal muscle tissue supports this claim. An additional

strength of this study is that it utilized a clinically relevant objective method of measuring PFM

function with a manometer. The use of this objective tool help to clarify the interpretation of

NIRS findings with meaningful applicability to field of study regarding PFM dysfunction and

LUTS in females.

143

In light of these strengths, further development of the technical construction of the

vaginal NIRS probe to monitor bilateral PFM oxygenation is warranted. In attempt to eliminate

NIR light refraction and scatter, a probe made of medical grade silicone housing the optodes

would be ideal. To increase the cross-sectional area of the PFM targeted by NIRS a complete

circumferential optode configuration, both at the proximal and distal end of the probe would

allow greater inference to the PFM function as a whole muscle group. This would incorporate the

anterior/posterior components as typically isolated with dynamometric force measures,133,164 the

lateral aspects as isolated in this study and the deep and superficial muscular tissue as described

by Devreese et al. 2004, considered to be important for coordination.92 Having a circumferential

optode configuration would also negate the issue of rotational displacement during assessment.

Furthermore, using NIRS technology that employed time-resolved or spatially-resolved

spectroscopy to provide absolute hemoglobin concentration values and a measure of tissue

oxygen percentage, thus allowing more accurate analysis of the hemodynamic and oxygen

kinetic variables.

Conducting NIRS investigations concurrently with other modalities would be greatly

beneficial. The use of simultaneous perineal EMG during NIRS assessment would help to clarify

how impaired innervation from neurologic conditions or injury affects motor unit activation and

corresponding oxygen patterns with the PFM. As well as use of superficial EMG over accessory

muscles in order to rule out their contribution to PFM contraction and/or consider how their

contribution may be beneficial to function PFM contractions and LUTS symptom management.

Some researchers consider the lower abdomen involvement to be beneficial and necessary for

proper PFM contraction.165

144

Future studies should employ supervised progressive PFMT training to maximize the

effects of intervention as described by previous literature, this appears to be more beneficial not

only for improvements in PFM strength but also for reduction in reported symptoms.20,28,144,162,163

Particularly for the complicated neurologic population the use of adjunctive therapy may be

beneficial for more effective PFM improvements, such as the use of neuromuscular stimulation

and biofeedback.25,28,29,166 More involved PFMT for a longer duration with a longer follow-up

period would provide better insight on how to translate this research findings into clinical

management strategies. Using PFMT that employed more supervision and adjunctive therapies

might also help to improve participant adherence to exercise intervention, as it appears studies

that employed supervision had demonstrated effectiveness and high adherence

rates.25,28,29,144,157,162,163,165

Further research is required to determine the applicability of NIRS to investigate the

theoretical concepts regarding the physiological properties of innervation, microvasculature,

contractile intensity that were previously discussed. This is needed to validate methods of

characterizing oxygenation trends and dominance (SPAM stratification and SPAMD algorithm)

used in this study, which may be beneficial for continued investigations of altered PFM

physiology in women with LUTS and for physiological adaptations that might occur in response

to PFMT. This would need to include studies of NIRS technology capable of measuring TSI%,

methods controlling for blood flow, simultaneous measures with EMG, manometry or

dynamometry, and morphological imaging. As this research is exploratory in nature, a more

refined study, with better controlled parameters for objective measurements would need to be

conducted before these speculations can be given weighted consideration. If further advanced,

NIRS would add the benefit of oxygen kinetic and hemodynamic response of the PFM,

145

physiological measures which are not currently utilized in research or clinical settings with the

field of pelvic floor medicine.

Oxygen kinetics and hemodynamics are commonly used as to assess physiologic

alterations that occur in pathologic conditions and as parameters to guide management of these

conditions and as training parameters for athletes.51,52 Therefore, refinement of NIRS

applicability to the PFM could provide new insight to the physiological alterations of the

musculature in PFM dysfunction and could be utilized as in other fields to help manage PFMT to

improve dysfunction and LUTS. Such implications may be that ½RT and desaturation magnitude

levels could be used to guide clinical decisions to determine the appropriateness of home-based

PFMT, supervised PFMT or NMES intervention.

5.4 Conclusion

With the use of NIRS in this study we were able to determine that this technology can be

utilized to detect differential bilateral PFM response to exercise. NIRS is capable of detecting

differences in oxygen kinetics in controls and females with LUTS due to altered pelvic

innervation. This NIRS methodology provided comparable objective outcomes as PFM

manometry, in that both were capable of detecting functional differences between controls and

cases, without determining within group differences in function from baseline to post-PFMT.

While providing comparable PFM assessment as comparable to PFM manometry, NIRS provides

additional information of PFM function through its ability to discriminate between the bilateral

musculature. Females with LUTS and altered pelvic innervation demonstrated a relationship

between oxygen recovery kinetics and strength and endurance of PFM. Adherence to PFMT is

critical for facilitation of beneficial training effects with regards to both muscular adaptations

146

and symptom management. Furthermore, the findings of adherence among the case group

corroborate existing PFM literature in that PFMT provides benefits of strengthening PFM while

also helping to reduce clinical symptoms. Our findings add to the existing literature by showing

that these benefits can also be obtained by females with neurological conditions and injury

impacting the pelvic floor, however, due to the small sample size and heterogeneity of the study

sample, the extent to which benefits of PFMT may be experienced females with specific

neurological conditions (with regard to severity of neurological impairment, chronicity and

underlying etiology) still warrants meaningful analysis. This research also contributes to the field

of pelvic floor medicine by demonstrating NIRS as means to provide physiological assessment

of PFM oxygen kinetics, as is commonly practiced in other fields to investigate pathology and

direct management. As such, NIRS demonstrates promise as an investigational method capable

of providing additional understanding of the pathophysiology occurring in PFM dysfunction,

thus contributing to PFMT rehabilitation.

147

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Appendix A

Appendix A Methods

A.1 PFMT Instruction Sheet

170

A.2 PFMT Recording Sheet

171

A.3 Bladder Diary

172

A.4 Questionnaire for Urinary Incontinence Diagnosis (QUID)

173

A.5 Urogenital Distress Inventory Short Form (UDI-6)

174

A.6 Incontinence Impact Questionnaire Short Form (IIQ-7)

175

A.7 Subjective Assessment of Improvement

176

A.8 Waterloo Footedness Questionnaire-Revised