University of Ghana

DETERMINING BEST REGRESSIONAL MODEL IN PREDICTING FOETAL

WEIGHT IN PHILIPS ClearVue 350 ULTRASOUND EQUIPMENT

BY

EDEM ANASTASIUS KWAMI BUADY

(10434064)

A DISSERTATION SUBMITTED TO THE, UNIVERSITY OF GHANA, LEGON IN

PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF MSc

ULTRASONOGRAPHY DEGREE

JULY, 2014

University of Ghana http://ugspace.ug.edu.gh

ii

DECLARATION

I EDEM ANASTASIUS KWAMI BUADY do hereby declare that this thesis which is being

submitted in fulfillment of the requirements for the Master degree of MSc in Ultrasonography is

the result of my own research performed under supervision, and that except where otherwise

other sources are acknowledged and duly referenced, this work has not previously been accepted

in substance for any degree and is not being concurrently submitted in candidature for any

degree. I hereby give permission for the Department of Radiography to seek

dissemination/publication of the dissertation in any appropriate format. Authorship in such

circumstances to be jointly held between me as the first author and the project supervisors as

subsequent authors.

Signed ………………………………….…... Date……………………

EDEM ANASTASIUS KWAMI BUADY

(Student ID No.10434063)

Signed ……………………………………… Date……………………

DR. SAMUEL OPOKU

Signed …………………….…………………. Date……………………..

DR. S. ANIM-SAMPONG

Signed ……………………………………… Date………………………

DR. SAMUEL OPOKU

(Head of Department)


iii

DEDICATIONS

But for the protection of the Almighty God, this work would have been an impossible task. I

therefore dedicate this write up to the Almighty God for his wisdom, knowledge, understanding,

and guidance.

Consequently, dedication of this work is extended to my ever-loving mother Mrs. Janet Yawa

Komla-Buady and father Anthony Kwaku Buady who even in your sickbeds demonstrated a lot

of support, encouragement and love to me but as nature has it, you have all pass on to glory. May

the Almighty god protect you under his strong wing: Mum and Dad, I miss you all dearly.


iv

ACKNOWLEDGEMENT

Firstly, I would like to acknowledge the almighty God for his immense grace towards this

dissertation. My immense appreciation goes to the under mentioned personalities who helped in

diverse ways to ensure the success of this work.

Dr. S.Y. Opoku, Mr. K. Bamfo-Quaicoe, Dr. E.K. Ofori, Mr. W.K. Antwi, Mr. Sulley, Mr.

B.O..Botwe, Mr L. Arthur all of Department of Radiographer, School of Biomedical and Allied

Health Sciences for their incalculable intellectual contributions throughout the thesis process. I

would also like to thank Dr. V.K. Hewlett for his time and contribution towards this research

work. Finally, Dr. S. Anim-Sampongis highly acknowledged for his tireless effort in bringing

this dissertation to the successful end.

I also appreciate the cooperation of all the staff of Ussher and Mamprobi Polyclinics‟ ultrasound

and maternity units. To the departments of Radiography and Audiology, School of Allied Health

Sciences, College of Health Sciences of the University of Ghana, I want to render many thanks

for your diverse contribution for this study. In respect of their friendship and encouragement

towards the completion of the thesis, I thank my course mates, Mr. Ampofo, Richard, Seth,

Jonathan (Kamkpee) and Eric Saka-Boateng (Sharpest) for their advice, support and prayers.

And finally to my family and friends, especially my brother Senyo and Nana Akua Adubea your

care and support in physical and financially has been really appreciated. Thanks for your

unceasing love, encouragement and emotional support.


v

TABLE OF CONTENTS

DECLARATION.............................................................................................................................ii

ACKNOWLEDGEMENT ............................................................................................................. iv

TABLE OF CONTENTS................................................................................................................ v

LIST OF TABLES ......................................................................................................................... ix

LIST OF FIGURES ........................................................................................................................ x

LIST OF ABBREVIATIONS........................................................................................................ xi

ABSTRACT.................................................................................................................................. xii

CHAPTER ONE:INTRODUCTION .......................................................................................... 1

1.1 BACKGROUND.............................................................................................................. 1

1.2 PROBLEM STATEMENT .............................................................................................. 4

1.3 RESEARCH QUESTION/HYPOTHESES ..................................................................... 6

1.4 SIGNIFICANCE OF STUDY.......................................................................................... 6

1.5 AIMS ................................................................................................................................ 7

1.6 OBJECTIVES .................................................................................................................. 7

CHAPTER TWO: LITERATURE REVIEW.............................................................................

8

2.1 INTRODUCTION............................................................................................................ 8

2.2 HISTORICAL REVIEW OF ESTIMATING FOETAL WEIGHT ................................. 8

2.3 TACTILE ASSESSMENT OF FOETAL SIZE............................................................... 9

2.4 FOETAL WEIGHT PREDICTIONS USING ALGORITHM DERIVED FROM

MATERNAL AND PREGNANCY-SPECIFIC CHARACTERISTICS.................................. 10

2.5 OBSTETRIC ULTRASONOGRAPHY IN ESTIMATING FOETAL WEGHT .......... 11

2.5.1 Group 1: Abdominal Circumference Only ............................................................ 12

2.5.2 Group 2: Abdominal Circumference and Femur Length ........................................ 12


vi

2.5.3 Group 3: Abdominal Circumference and Biparietal Diameter ............................... 13

2.5.4 Group 4: Abdominal Circumference, Head Circumference(±Biparietal Diameter)14

2.5.4 Group 5: Abdominal Circumference, Femur Length, and Biparietal Diameter ..... 14

2.5.6 Group 6: Abdominal Circumference, Femur Length, and Head Circumference.... 15

2.5.7 Group 7: Abdominal, Head Circumferences, Femur Length, Biparietal Diameter 15

2.6 MAGNETIC RESONANCE IMAGING IN ESTIMATING FOETAL WEIGHT ....... 18

2.7 GENDER-SPECIFIC ESTIMATION OF FOETAL WEIGHT..................................... 19

2.8 ETHNIC AND RACIAL DIFFERENCES IN ESTIMATED FOETAL WEIGHT ...... 21

2.9 GENETIC FACTORS.................................................................................................... 23

CHAPTER THREE: METHODOLOGY .................................................................................28

3.1 INTRODUCTION.......................................................................................................... 28

3.2 STUDY DESIGN ........................................................................................................... 28

3.3 STUDY SITES ............................................................................................................... 30

3.4 STUDY POPULATION ................................................................................................ 30

3.6 INCLUSION AND EXCLUSION CRITERIA ............................................................. 32

3.6.1 Inclusion Criteria .................................................................................................... 32

3.6.2 Exclusion Criteria ................................................................................................... 32

3.7 EQUIPMENT/INSTRUMENT CAPABILTY .............................................................. 32

3.7.1 Ultrasound Equipment Suitability for Obstetric Work ........................................... 33

3.8 QUALITY ASURANCE TESTS ON THE EQUIPMENT/INSTRUMENT ................ 34

3.9 ASSESSMENT OF RELIABILITY OF THE MEASUREMENTS .............................. 35

3.10 REGRESION MODELS ................................................................................................ 35

3.10.1 Campbell and Wilkin Approach for EFW (AC) only ............................................. 35


vii

3.10.2 Hadlock Approaches for EFW Calculations: (AC, FL) only.................................. 35

3.10.3 Hadlock Approaches for EFW Calculations: (AC, BPD) Only.............................. 36

3.10.4 Hadlock Approaches for EFW Calculations: AC, FL and HC Only ...................... 36

3.10.5 Hadlock Approaches for EFW Calculations (AC, BPD, FL) ................................. 36

3.10.6 Hadlock Approaches for EFW Calculations (BPD, HC, AC, FL).......................... 36

3.10.7 Osaka Approach for EFW Calculations (BPD, FTA, FL) ...................................... 37

3.10.8 Tokyo Approach for EFW Calculations (BPD, AD, FL) ....................................... 37

3.10.9 Shephard Approach for EFW Calculations (AC, BPD).......................................... 37

3.10.10 Shinozuka Approach for EFW Calculations (AC, BPD, FL) ..................................38

3.10.11 Shinozuka Approach for EFW Calculations (APTD, TTD, BPD, FL) .................. 38

3.11 PROCEDURE FOR DATA COLLECTION ................................................................. 40

3.12 DATA MANAGEMENT ............................................................................................... 44

3.13 ETHICS .......................................................................................................................... 44

3.13.1 Standard Protocol Adopted for the Study ............................................................... 45

CHAPTER FOUR: RESULTS .....................................................................................................46

4.1 INTRODUCTION.......................................................................................................... 46

4.2 DEMOGRAPHICS ........................................................................................................ 46

4.3 FOETAL BIOMETRICS ............................................................................................... 48

4.4 HYPOTHESIS ............................................................................................................... 49

CHAPTER FIVE: DISCUSSION............................................................................................... 53

5.1 INTRODUCTION........................................................................................................... 53

5.2 RESPONSE RATE ......................................................................................................... 53

5.3 DEMOGRAPHICS ..........................................................................................................53

5.3 FOETAL BIOMETRICS ................................................................................................ 54


viii

CHAPTER SIX: CONCLUSIONS, RECOMMENDATIONS AND LIMITATIONS.......... 58

6.1 INTRODUCTION........................................................................................................... 58

6.2 CONCLUSIONS ............................................................................................................. 58

6.3 RECOMMENDATIONS ................................................................................................ 59

6.4 LIMITATIONS OF THE STUDY .................................................................................. 60

REFERENCES............................................................................................................................. 61

APPENDICES ............................................................................................................................... 79

APPENDIX I: PARTICIPANTS INFORMATION SHEET......................................................... 79

APPENDIX II: INFORMED CONSENT FORM ......................................................................... 80

APPENDIX III: DATA COLLECTION SHEET .......................................................................... 81

APPENDIX IV: ETHICAL CLEARANCE ...................................................................................82


ix

LIST OF TABLES

Table 3.1: Technical specifications of Philips ClearVue 350 ultrasound equipment…………...33

Table 3.2: Estimated foetal weight formulae used in the study………………………………....39

Table 4.1: Maternal Demographics……………………………………………………………...47

Table 4.2: Correlation coefficient between maternal demographics and neonates‟ ABWs…......47

Table 4.3: Mean and S.D. of BPD, HC, FL, and AC foetal biometrics………………………....48

Table 4.4: Birth weights at term………….……………………………………………………...48

Table 4.5: Comparison between EFW generated by the regression models to ABWs……….....50


x

LIST OF FIGURES

Figure3.1: BPD measurement………………………………………………………………….41

Figure 3.2: AC measurement…………………………………………………………………..42

Figure 3.3: HC measurement…………………………………………………………………..43

Figure 3.4: FL measurement…………………………………………………………………...43

Figure 4.1: Scatter plot of ABW against regression models…………………………………...49

Figure 4.2: Box and Whisker distribution of ABW and regression EFWs…………………….52


xi

LIST OF ABBREVIATIONS

BPD Biparietal diameter

HC Head circumference

AC Abdominal circumference

FL Femur length

AD Abdominal diameter

FTA Foetal trunk area

APTD Anterior posterior trunk diametre

TTD Trans-thoracic diametre

BW Birth weight

ABW Actual birth weight

MRI Magnetic resonance imaging

USG Ultrasonography

EFW Estimated foetal weight

IUEFW Intrauterine estimated foetal weight

OAUTHC Obafemi Awolowo University Teaching Hospital Complex

IQR Interquartile range

PPW Pre-pregnancy weight


xii

ABSTRACT

Background: Earlier investigations have demonstrated that the accuracy of foetal weight

estimation is significantly higher if several ultrasonic foetal parameters are measured, because

the total body mass depends on the size of foetal head, abdominal circumference and femur

length.

Aim: This study aimed to determine the best ultrasound regression models that use the common

foetal biometric measurements in predicting foetal weight for normal singleton pregnancies in

ClearVue 350 ultrasound equipment, and also assess the effects of few maternal anthropometric

variables on estimated foetal weight in the Greater Accra Metropolis.

Methodology: The study was quantitative, cross-sectional and quasi-experimental in nature and

was carried out prospectively in which convenient sampling method was used. Forty (40)

participants were scanned in the study. Foetal biparietal diameter, head circumference,

abdominal circumference and femur length measurements were measured according to the

established guidelines. Microsoft Excel and IBM SPSS soft-wares were used for data analysis.

Results: The study demonstrated that, all eight regression models showed no statistically

significant difference with (p-value <0.05) at 95% confidence interval of their mean foetal

weight estimates compared to the actual birth weight of the neonates. The mean and standard

deviations were similar across the eight models.

Conclusion: Findings from this study showed that, the best regressional model is Hadlock3

model. The study further revealed that, with 87% of estimated foetal weights which were within

5% of actual birth weights, demonstrate strong correlation between EFWs and ABWs, therefore

(radiologists, sonographers/radiographers)on one side and (gynaecologists, midwives) on the

other side can (to a high degree) rely on estimated foetal weights generated from Philips


xiii

CleaVue350 ultrasound equipment using the common foetal biometric measurements in a 2D

mode to generate meaningful reports and make important decisions such as mode of delivery

respectively.


1

CHAPTER ONE

INTRODUCTION

1.1 BACKGROUND Prenatal or antenatal development is the process in which a human embryo or foetus gestates

during pregnancy, from fertilization until birth (Shukla, 2012). The term embryo is used to

describe the developing offspring during the first 8 weeks following conception, and the term

foetus is used from about 2 months of development until birth Shukla (2012).

After fertilization the embryogenesis starts. In humans, when embryogenesis finishes, by the end

of the 10th week of gestational age, the precursors of all the major organs of the body have been

formed and the following period, which is the foetal period, is described both topically on one

hand that is by organ, and strictly chronologically on the other, by a list of major occurrences by

weeks of gestational age Shukla (2012). Rapid growth occurs and the embryo's main external

features begin to take form in a process called differentiation, which produces the varied cell

types (such as blood cells, kidney cells, and nerve cells). At 10th week, embryo measures 30–80

millimeters in length with facial features continuing to develop that is, eyelids are more

developed, head comprises nearly half of the foetus' size, the face is well formed, the limbs are

long and thin, the foetus can make a fist with its fingers and genitals appear well differentiated

(Shukla, 2012). It is these well-developed external features or specific parts of a foetus like the

limbs, head and trunk which are measured and are known as foetal biometry.

Growth rate of foetus is linear up to 37 weeks of gestation, after which it plateaus (Daftary and

Chakravarti 2011). The growth rate of an embryo and infant can be reflected as the weight per

gestational age, and is often given as the weight put in relation to what would be expected by the


2

gestational age. Neonate within the normal range of weight for that gestational age is known as

appropriate for gestational age (AGA). Those that have large or small range of weights are

known as large for gestational age (LGA) and small for gestational age (SGA) respectively.

According to literature (Oken et al., 2003; NahlaSubhi et al., 2010), birth weight (BW) is a

composite of foetal growth and length of gestation, each of which has different contributions and

different sequel. The absence of the contribution of gestational age to BW is the first step in

understanding the determinants of foetal growth. Sonographic estimated foetal weight (EFW) is

a foetal biometry parameter whose calculation is based on four common foetal biometric

measurements, that is, biparietal diameter (BPD), head circumference (HC), femur length (FL),

abdominal circumference (AC).

Inaccuracies with EFW have been reported in several literature. In particular, it has been reported

in the published literature (Colman et al., 2006; Scioscia et al., 2008) of the existence of

considerable differences between the sonographic EFW and the actual birth weight ABW with a

mean error of 7% to 10%, even under ideal sonographic conditions. However, despite its

inaccuracies EFW has been used in clinical decisions for over thirty years (Dudley, 2005; Ben-

Haroush et al., 2004). In the search to improve the ability to accurately predict BW from

sonographic EFW, multiple EFW formulae have been published, but limited data exist on their

comparative accuracies, and considerable variation in the EFWs occurs with different formulae

using the same foetal biometric measurements (Burd et al, 2009).

Again, according to Burd et al., (2009), the large number of published EFW formulae provides

clear evidence that none of them are universally accepted and unfortunately, the error of


3

sonographic EFW appears to be greatest at the two ends of the weight scale with most EFW

formulae, having low and high BWs are overestimated and underestimated respectively (Baker et

al., 1994).

During the last decade, EFW has been incorporated into the standard routine antepartum

evaluation of high-risk pregnancies and deliveries (Shittu et al., 2007). For instance, management

of diabetic pregnancy, vaginal birth after a previous caesarean section, and intrapartum

management of foetuses with breech presentations will be greatly influenced by EFW

(Sherman et al., 1998; Chauhan et al., 1998). Furthermore, in dealing with anticipated preterm

delivery, prenatal counseling on likelihood of survival, the intervention undertaken to postpone

preterm delivery, optimal route of delivery, or the level of the hospital where delivery should

occur may be based wholly or in part on the estimation of expected BW (Shittu et al., 2007).

Categorization of foetal weight into either small or large for gestational age may lead to timed

obstetric interventions that collectively represent significant departure from routine antenatal care

(Chauhan et al., 1998; Nzeh et al., 2000; Hanretty et al., 1990; Hendrix et al., 2000).

Previous studies have shown that the accuracy of EFW is significantly higher if several

ultrasonic foetal parameters are measured. This is because the total body mass depends on the

size of foetal head, abdominal circumference and femur length (Mladenović-Segedi et al., 2005).

In affirmation of this observation, Chien et al., (2000) validated 4 different formulae and

concluded that ultrasonic EFW at term with all the four formulae was high.


http://www.ncbi.nlm.nih.gov/pubmed?term=Mladenovi%C4%87-Segedi%20L%5BAuthor%5D&cauthor=true&cauthor_uid=16673856

4

Ultrasound examination and measurements of foetal biometry have become integral to modern

obstetric care and thus provide avenues for dating pregnancies or for assessment of foetal growth

(Leung et al., 2008). The selection of appropriate cross-sectional reference charts is of great

importance to ensuring accurate diagnosis, although some published reference charts are

methodologically flawed (Leung et al., 2008). Some common associated problems include

repeated measurements on the same foetuses, formation of „super normal‟ datasets by

inappropriate exclusion of complicated pregnancies, failure to identify the statistical method of

analysis, and the use of statistical methods which in the opinion of Altman et al., (1994) do not

consider the variability of measurements with gestational age. Consequent to this, appropriate

methodologies have been published (Altman et al., 1994; Royston et al., 1998), and

mathematical equations and foetal biometric charts for various populations using the correct

approaches are now available in the medical literature (Chitty et al., 1994; Kurmanavicius et al.,

1999; Salomon et al., 2006).

1.2 PROBLEM STATEMENT

The influence of ethnicity or race on foetal biometry has been firmly established and widely

published in literature (Yeo et al., 1994; Jacquemyn et al., 2000). Leung et al., (2008) established

that, Hong Kong Chinese have similar reference chart as Singaporeans for all biometric

measurements but differs greatly in biometric measurement with those of UK and France with

respect to femur length (FL).

Several variables including ethnicity are incorporated in developing regression models for global

use in ultrasound foetal biometry. However, these plethora of regression models are mostly


5

based on Western and European populations which might not be representative of Ghanaian‟s,

and thus create opportunities for deviations and errors in ultrasound foetal biometry using Philips

ClearVue 350 ultrasound equipment.

Presently, there is no specific well documented evidence of regressional models of combined

biometric measurements for EFW in Ghana. Thus the use of these regressional models based on

Western and European populations on Ghana‟s obviously presents a challenge in EFW biometry.

In particular, the absence of knowledge of precise foetal weights presents additional problems of

unnecessary caesarean sections and its associated complications, limit women from their preferred

choice of number of children, and perturb critical interventions in cases of macrosomia and breech

presentation.

Furthermore, anecdotal report has shown that enormous complaints from midwives about

inconsistencies of gestational age with respect to EFW, huge gaps between approximate ABW

and EFW, and the prolonged duration of EFW given at a particular date and onset of labor of an

expectant mother have been reported in Mamprobi Polyclinic. These problems may have arisen

from ultrasound foetal biometry using regression models unrepresentative in Ghana or due to

operator inexperience.

Aside these challenges, the Ghana government through the health agencies (Ministry of Health

and Ghana Health Service) has begun nationwide programme of equipping all polyclinics and

district hospitals with Philips ClearVue 350 ultrasound equipment. It is known that the

regressional model used in this equipment does not provide for variations of race influences in

foetal biometrics. It is therefore imperative to determine regression model based on common

biometric measurements most suitable for the Ghanaian population and minimize the stated

problems above.


6

1.3 RESEARCH QUESTION/HYPOTHESES

1.3.1 Research Question: What is the best regression model(s) from Philips ClearVue 350

ultrasound equipment, using common biometric measurements in establishing EFW in utero in

Greater Accra Metropolis?

1.3.2 Hypothesis:

Null Hypothesis H 0: There will be no significant difference between EFWs and ABWs.

Alternative Hypothesis H1: There will be significant difference between EFWs and ABWs

1.4 SIGNIFICANCE OF STUDY

Generally, simple and accurate methods of estimating intrauterine foetal weight that can be

easily applied to all pregnancies are important means of reducing prenatal mortality and

morbidity. These are done through early detection of faltering growth and also in managing

breech presentation, macrosomia and intrauterine growth retardation at term by gyaenacologists

and midwives.

To buttress the point above, several investigations have shown that low EFW is associated with

high prenatal mortality and morbidity according to (Mavalankar et al., 1991). Therefore,

importantly, knowing the weight of a foetus and with other examinations like umbilical

Doppler and laboratory tests can help clinicians significantly reduce the occurrences of prenatal

morbidity, mortality and maternal deaths in some cases.


7

1.5 AIMS

The aim of this research study is to determine the best ultrasound regression model that uses the

common foetal biometric measurements in predicting foetal weight for normal singleton

pregnancies with ClearVue 350 ultrasound equipment, and also assess the effects of some few

maternal anthropometric variables on EFW in the Greater Accra Metropolis.

1.6 OBJECTIVES

To determine EFWs of foetuses.

To determine ABWs of neonates.

To compare EFWs to ABWs.

To obtain records of maternal anthropometrics (height and weight) from the time of

visiting antenatal for the first time and weight at the last antenatal visit.


8

CHAPTER TWO

LITERATURE REVIEW

2.1 INTRODUCTION Before and after the introduction of ultrasound into obstetric work, some forms of assessing

EFW were carried out globally. Earlier assessments were purely via physical examination of

maternal and foetus. After the advent of ultrasound equipment, others were performed

physically, in combination with ultrasonic measurements when EFW formulae were not

incorporated in ultrasound equipment.

2.2 HISTORICAL REVIEW OF ESTIMATING FOETAL WEIGHT

About four decades ago, Campbell and Wilkin assessed BW prediction of foetuses, using

abdominal circumference only, by ultrasonic means. This measurement showed that:

1. Accuracy of predictions varied with the size of the foetus.

2. The predicted BW and the ABW were not comparable.

For instance, at a predicted weight of 1 kg, 95% of BWs fell within 160 g, while at 2 kg, 3 kg

and 4 kg, the corresponding values were 290 g, 450 g and 590 g respectively. However,

according to Kearney et al., (1978), inclusion of abdominal circumference in determination of

EFW cannot be overemphasized as it presents a higher percentage value for predicting BW.

To date, a lot of mathematical formulae as noted in the literature have been deduced to narrow

the range of foetal weight estimation. Therefore, there is a strong evidence base of using more


9

than two biometric measurements to obtain accurate EFWs which will lead to the common

methods in estimating foetal weight sonographically.

2.3 TACTILE ASSESSMENT OF FOETAL SIZE

Dare et al., (1990) used the tactile assessment, which is the oldest technique for assessing foetal

weight. This is done via manual assessment of foetal size by obstetricians and midwives

worldwide, i.e. by external palpation of the uterus and foetal parts. This method is extensively

used because it is both convenient and virtually costless. However, it has long been known as a

subjective method that is associated with significant predictive errors (Shittu et al., 2007).

According Bossak et al., (1972), it is both patient- and clinician-dependent for its success (less

accurate for obese gravidas than non-obese and significant inter-observer variation in prediction

of BW even among experienced clinicians).

Maternal self-estimation of foetal weight in multiparous women shows comparable accuracy to

clinical palpation in some studies for predicting abnormally large foetuses (Chauhan et al., 1992;

Chauhan et al., 1998). According to Shittu et al. (2007), various calculations and formulae based

on measuring uterine fundal height above symphysis pubis have been developed. For example,

Ojwang et al., (1984) used the product of symphysio-fundal height and abdominal girth

measurement at various levels in centimeters above the symphysis pubis in obtaining a fairly

acceptable predictive value but with considerable variation from the mean. To further simplify

this method, Dare et al., (1990) in OAUTHC, Ile-Ife, used the product of symphysio-fundal

height and abdominal girth at the level of the umbilicus measured in centimeters and expressed

the result in grams to obtain the EFW at term in-utero. The EFW correlated well with BWs.

The Johnson's formula for EFW weight in vertex presentation defined as:


10

nFHgEFW 155)( (2.1)

Where FH= fundal height, and

spineischialabovevertex

spineischailbelowvertexn

,12

,11 (2.2)

If a patient weigh more than 91 kg, 1 cm is subtracted from the FH (Shittu et al, 2007).

2.4 FOETAL WEIGHT PREDICTIONS USING ALGORITHM DERIVED

FROM MATERNAL AND PREGNANCY-SPECIFIC CHARACTERISTICS

According to Shittu et al., (2007) again, a new theoretically-defensible equation capable of

predicting BWs prospectively from maternal characteristics was developed. To do this, the

efficacy of 59 scientifically-justifiable terms was evaluated simultaneously, obviating any

confounding co-variation and determining which of the predictions could account for variation in

BW that others could not. Aside maternal race, only six maternal and pregnancy-specific

variables were important in prediction of BW for otherwise normal gravidas. Using these

routinely-recorded variables, an equation based on maternal demographic and pregnancy-related

characteristics alone was developed to help predict BW as shown by Nahum (2003).

)1(81.4(000237.0262.036.9)( pWWHfdgBW Rmmmg (2.3)

Where d= gestational age, fg= fetal gender, Hm= maternal height, Wm= maternal weight measured at

26 weeks, WRm= maternal weight gain rate (Wm/d), p = parity. From the definition of variables,

equation 2.3 can be re-written as

)]1(81.4(000237.0262.036.9[)( pd

WmW mH mf g

dgBW (2.4)


11

male

unknown

female

f g

,1

,0

,1

(2.5)

As obesity is link to weight gain, Nahum et al., (1995) earlier demonstrated that the effect of

maternal obesity on foetal weight gain at term is small and not clinically significant. The study

also shows that, foetal weight gain was only 0.6g per day greater for obese pregnant women than

for those of normal weight for height and male foetuses gained weight 0.5g per day faster than

females. Therefore, it presupposes that the incorporation of maternal weight gain rate into

Nahum‟s equation is of no significance.

2.5 OBSTETRIC ULTRASONOGRAPHY IN ESTIMATING FOETAL WEGHT

The modern method for assessing foetal weight involves the use of foetal measurement obtained

via ultrasonography and has the advantage of relying on linear and/or planar measurements of in-

utero foetal dimensions that are definable objectively and should be reproducible (Shittu et al.,

2007). However, early expectations that this method might provide an objective standard for

identifying foetuses of abnormal size for gestational age was recently undermined by prospective

studies that showed sonographic estimates of foetal weight to be no better than clinical palpation

predictions based on algorithms using various combinations of foetal parameters, such as AC,

FL, BPD, and HC (Shittu et al., 2007). These common and popular models are classified into

groups depending on the combinations of foetal parameters and are used either singularly or in

combination as shown in literature by (Nahum, 2003; Hadlock et al., 1985; Nzeh et al., 2000;

Campbells, 1975; Comb et al., 1993; Ott et al., 1986 and Deter et al., 1985). The mathematical

equations referred to as Model Reference Equations (MRE) which underpins these algorithms for

calculating EFW are described by Nahum and Stanislaw, (2003) as shown below


12

2.5.1 Group 1: Abdominal Circumference Only

The unlisted group of equations provide for calculating EFWs using:

1. Campbell and Wilkin (in kg):

200331.0282.0564.4ln ACACEFW (2.5)

2. Hadlock et al.

200275.0)(253.0695.2ln ACACEFW (2.6)

3. Jordaan

32

10 )(000036239.0)(0043.0)(1881.06328.0log ACACACEFW (2.7)

4. Warsof et al.

3

10 )(000019.0)(092.08367.1log ACACEFW (2.8)

5. Higginbottom et al.

3)(0816.0 ACEFW (2.9)

2.5.2 Group 2: Abdominal Circumference and Femur Length

These groups of equations provide for calculation of the EFWs using AC and FL only:

6. Hadlock et al

))((004.0)(01938.0)(05281.0304.1log10 FLACFLACEFW

(2.10)

7. Woo et al.

))((00716.0)(28.0)(08.059.0log10 FLACFLACEFW (2.11)

8. Warsof et al.

))((0027.0)(0036.0)(108.0792.2ln 2 FLACACFLEFW (2.12)


13

2.5.3 Group 3: Abdominal Circumference and Biparietal Diameter

The EFW are estimated via these groups of equations using AC and BPD only:

9. Vintzileos et al.

)(026.0)(084.0879.1log10 ACBPDFEW (2.13)

10. Warsof et al.

2

10 ))((000111.0)(032.0)(144.0599.1log BPDACACBPDEFW (2.14)

11. Shepard et al.

))((002546.0)(046.0)(166.07492.1log10 BPDACACBPDEFW

(2.15)

12. Jordaan.

))((0015.0)(0950.0)(0377.01683.1log10 BPDACBPDACEFW (2.16)

13. Hadlock et al.

)(16994.0))((000595.0

)(007365.0)(000604.0)(05845.01134.1log 22

10

BPDBPDAC

BPDACACEFW (2.17)

14. Woo et al.

22

10 ))((00008599.0)(00111.0)(16.063.1log ACBPDACBPDEFW (2.18)


14

15. Hsieh et al.

)(052594.0)(000019782.0

))((00015515.0))((0056541.01315.2log

3

2

10

BPDAC

ACBPDBPDACEFW (2.19)

2.5.4 Group 4: Abdominal Circumference, Head Circumference (±Biparietal Diameter)

EFWs are derived from these groups of equations using AC, HC, and with or without BPD only:

16. Hadlock et al.

))((0002184.0

)(00063.0)(07057.0)(0273.0182.1log 2

10

HCAC

ACACHCEFW (2.20)

17. Jordaan.

))((001599.0)(0824.0)(0488.09119.0log10 HCACACHCEFW

(2.21)

18. Jordaan.

)(0058.0)(0079.0)(02904.03231.2log10 BPDHCACEFW (2.22)

2.5.4 Group 5: Abdominal Circumference, Femur Length, and Biparietal Diameter

Using AC, FL and BPD biometrics only, the EFW can be calculated via:

19. Hadlock et al.

)(1623.0

)(0457.0)(0316.0))((0034.0335.1log10

FL

ACBPDFLACEFW

(2.23)

20. Woo et al-7


15

))((000992.0

)(05.0))((0000764.0)(00111.0)(15.054.1log 22

10

FLAC

FLACBPDACBPDEFW (2.24)

21. Shinozuka et al.

32 )(6230.1))((23966.0 BPDACFLEFW (2.25)

22. Hsieh et al.

2

2

10

))((001745.0

))((00076742.0)(1432.0))((0094962.07193.2log

BPDFL

BPDACFLBPDACEFW (2.26)

2.5.6 Group 6: Abdominal Circumference, Femur Length, and Head Circumference

Using the AC, FL, and HC biometrics, the EFWs can be calculated via:

23. Hadlock et al.

)(158.0

)(0438.0)(0107.0))((00326.0326.1log10

FL

ACHCFLACEFW (2.27)

24. Combs et al.

32 )(03312.0))((23718.0 HCACFLEFW (2.28)

25. Ott et al.

)/(2594.1

))((0008582.0)(05394.0)(04355.00661.2log10

ACFL

HCACACHCEFW (2.29)

2.5.7 Group 7: Abdominal, Head Circumferences, Femur Length, Biparietal Diameter

The EFWs can also be calculated using AC, HC, FL and BPDs via:

26. Hadlock et al.

))((00386.0))((00061.0

)(174.0)(0424.0)(0064.03596.1log10

FLACBPDAC

FLACHCEFW (2.30)


16

In-utero foetal biometric assessment made by obstetric ultrasonography use best-fit algorithms to

make BW predictions (Benacerraf et al., 1988) and this provides an attractive „objective‟ method

of estimating BW. Willocks et al., (1964) were among the first to report their experience with

ultrasound foetal weight estimation, and commented that clinical estimation of foetal weight is

little more than guess work because of the influence of factors such as abdominal wall thickness,

uterine tension, volume of amniotic fluid, and position of the foetus in utero. It was claimed that

in two thirds of cases, foetal weight could be estimated to within about 2.2kg using ultrasound

(Tlale, 2012).

A large number of foetal weight prediction formulae have since been suggested based on foetal

biometry including head BPD, HC, FL, AC and abdominal diameters (AD) known as common

foetal biometry. In particular, a retrospective study has been done by Shamley and Landon

(1994), to evaluate four published equations by Sherpard et al., (1982), Hadlock et al., (1985),

Rose and McCallum (1987), and Sabbagha et al., (1989), as well as clinical estimation for

accuracy in determining foetal weight in labour. According to the study, Hadlock and Shepard

equations were associated with lower percentages of error 6.1% and 6.2% respectively than the

Sabbagha formula (7.8%; p<0.007). For all four equations, 70-79% of foetal weight predictions

were within 10% of ABW. The Shepard formula, however, has limited application in labour

because head descent obscures the BPD which is essential to the foetal weight calculation. The

study concluded that the use of any of the four standard equations or clinical examinations

provides accurate estimation of foetal weight for patients in labour, even in the presence of

ruptured membranes.


17

In these comparisons, the percentage of predictions within 10% of the BW for ultrasound

estimation ranged from 39% to 69% (Hendrix et al., 2000; Chauhan et al., 1992; Chauhan et al.,

1992; Barnhard et al., 1996; Sherman et al., 1998). While ultrasound foetal weight estimation may

not appear significantly better than clinical methods, a recent comparison by Peregrine et al.,

(2007) has shown that ultrasound estimations of foetal weight immediately before labour was

more accurate than clinical estimation for low and high BW babies, where clinical estimates are

known to be relatively inaccurate.

A study by Yoni et al., (1996) investigated the effect of oligohydramnios on intrapartum

estimation of foetal weight, and concluded that in term patients, intrapartum sonographic

prediction of BW in the presence of reduced amniotic fluid volume offered no advantage over

EFW obtained by abdominal palpation. However, the presence of oligohydramnios significantly

reduced the accuracy of intrapartum clinical and sonographic foetal weight estimations,

therefore, it was suggested that intrapartum foetal weight estimation be obtained prior to artificial

rupture of membranes (Almonem, 2015)

Although the validity and reproducibility of these formulae have been documented in clinical

practice with a reported systematic error of 10% or less relative to the ABW, it is well

recognized that various foetal factors may influence the accuracy of foetal weight estimations.

However, there are few reports that document the effect of certain maternal characteristics,

specifically maternal size and obesity, on the ability to obtain ultrasonographic foetal biometric

measurements and consequently calculate reliable foetal weights (Field et al., 1995)


18

Newer technologies may be able to provide better foetal weight estimation, for example, three-

dimensional (3-D) sonography potentially allows superior foetal weight estimation including soft

tissue volume of the foetal thigh, upper arm and abdomen (Schild et al., 2000; Bennini et al.,

2010). Its advantage over conventional two-dimensional (2-D) ultrasonography is that

reproducible circumference and volumetric measurements become feasible by simultaneous

visualization of three orthogonal foetal limb sections. However, the disadvantage is that 3-D

sonography is a more time consuming process, requires technically advanced and expensive

equipment, and special operator training and skills which may also be more difficult to apply

during labour (Tlale, 2012). According to Lindell and Marsal (2009), it seems unreasonable to

abandon the 2-D ultrasound imaging for foetal weight estimation.

2.6 MAGNETIC RESONANCE IMAGING IN ESTIMATING FOETAL WEIGHT

Magnetic resonance imaging (MRI) has recently been used for estimating foetal volume and

weight in diabetic and normal pregnancy using high-resolution MRI machine combined with

semi-automatic segmentation software (Shittu et al., 2007). Its use may be recommended for

clinical situation where accurate estimation is essential. Its strong disadvantage is that it is

expensive even where it is available (Uotila et al., 2000). However, the promising new

development in foetal weight estimation by echo-planer MRI cannot be overemphasized and its

advantages compared with other imaging techniques include the ability to obtain multi-planar

acquisitions and therefore theoretically improved resolution (Shamar et al., 2012)

Although it is feasible to calculate MRI foetal weight in sagittal, coronal, or axial planes, (the

recommended plane of imaging,) slice of thickness, and associated number of acquisitions that

most accurately determine term foetal weight had not yet been established or published at the


19

time when Hassibi et al. (2004) presented their findings. According to (Tlale, 2012) sought to

determine whether there are differences in foetal weight calculation based on plane of imaging or

thickness by comparing sagittal 5mm, 3mm, and axial 8 mm MRI acquisitions with term BW

and sonography foetal weight calculations. Their goal was to establish an optimal, practical

protocol for foetal MRI in the prediction of foetal weight in the term infant. Calculated weights

from a 90-sec single-shot fast spin- echo sequence MRI acquisition with 8mm thick slices in the

axial plane at term were found to be better than sonographic estimates (Tlale, 2012). The

problem with these methods, according to Loffler (1967) is that, addition to its expensiveness, its

impracticability for obtaining measurements during labor. However as indicated earlier that only

measurements of foetus such as BPD, HC, AC, FL, FTA, AD, APTD, and TTD had stood the

test of time in deducing EFW which is inexpensive. Despite the discrepancies between EFW and

ABW, these equation models based on foetal biometric measurements are extensively being used

global currently.

2.7 GENDER-SPECIFIC ESTIMATION OF FOETAL WEIGHT

It has been previously suggested and also published in the literature that differences exist in the

accuracy of sonographic weight estimation between male and female foetuses, and that these

differences may be the result of gender-specific intrauterine growth patterns (Pang et al., 2003;

Parker et al., 1984; Pineau et al., 2003; Fields et al., 2009; Schild et al., 2004; and Schwarzler et

al., 2004). These also include gender-related differences in body composition and percent of

body fat and in ratios among various biometric indices (Fields et al., 2009; Schwarzler et al.,

2004).


20

Indeed, Melamed et al., (2011) have recently reported that sonographic weight estimation was

consistently more accurate for male than female foetuses, irrespective of the model used. It may

be reasonable to hypothesize that the use of two distinct gender-specific models, optimized for

male and female foetuses, may overcome this limitation. However, the impact of such gender-

specific models on the accuracy of foetal weight estimation is as yet unclear. Surprisingly, none

of the widely accepted sonographic models for foetal weight estimation (Shepard et al.,1982;

Hadlock et al., 1984; Hadlock et al., 1985; Warsof et al., 1986; Ott et al., 1986; and Combs et al.,

1993) includes foetal gender in the equation, and the results of only one study indicated that the

use of such gender-specific model may result in more accurate estimation than several widely

used models (Schild et al., 2004; Siemer et al.,2008a; Siemer et al., 2008b).

Moreover, it is unknown whether such gender-related model optimization merely reflects a

different set of gender-specific model coefficients or whether these gender-specific models also

differ in the combination of biometric indices incorporated into the model (Melamed et al.,

2012). However, the quest for simple and understandable approach of EFW deduction, other

formulae have emerged recently. For instance, it has been established that gender-specificity has

an effect on EFW, that male foetuses have more weight than their female counterparts for the

same gestational age. Hence, as proposed by Schild et al., (2004), different models should be

applied to different groups of foetuses depending on gender.

To augment Schild‟s work, Siemer et al., (2008) demonstrated that Schild‟s gender-specific

formula had the highest degree of accuracy than those equations widely use in the weight range

between 2,500 and 3,999 g where majority of BWs falls but fare poorly at the extremes with BW

< 2500g and >3999g. In improving on Schild‟s gender-specific model, Melamed et al., (2012)

adjusted Schild‟s formula and hard more accurate result. However, these gender-specific models


21

were associated with highest accuracy (lowest systematic error) only in the larger interquartile

BW subgroup, while this advantage was not clearly observed in the extremes of BW (below the

first quartile and above the third quartile) as was observed in many studies (Melamed et al.,

2012).

2.8 ETHNIC AND RACIAL DIFFERENCES IN ESTIMATED FOETAL WEIGHT

The effects or impact of racial variations and ethnicity on EFW have been questioned by Richard

et al., (1997) in a study on differing BWs among infants of US-born Blacks, African-born

Blacks, and US-born Whites. In this research, during the past 40 years, epidemiologic research

has elucidated many important associations between the socio-demographic characteristics of

mothers and the BW of infants. For example, the extremes of childbearing age (Kleinman &

Kessel, 1987), cigarette smoking (Fox et al., 1994), inadequate prenatal care (Murray &

Bernfield., 1988), urban poverty (Collins & David, 1990) and black race (David and Collins.,

1991) are well-documented risk factors for low BW. Other obstetrical risk factors account for

part of the racial disparity in BW, but differences persist (Lieberman et al., 1987; Rawlings et

al., 1995; Klebanoff et al., 1989; Sheehan & Gregorio, 1995). Although the incidence of low

BW decreases in both blacks and whites as the number of risk factors declines, the improvement

is faster among whites, resulting in a wider BW gap between blacks and whites among infants of

low-risk women (Kleinman & Kessel, 1987; Collins & David, 1990). This led some investigators

to believe that genetic factors associated with race influence BW. (Naylor & Myrianthopoulos

1967; Little & Sing 1987; Magnus 1984; Hulsey et al., 1991; Goldenberg et al., 1991;

Wildschutt et al., 1991).


22

In the National Collaborative Prenatal Project, only 1% of the total variance in BW among

18,000 infants was accounted for by socioeconomic variables, leading the authors to conclude

that “race behaves as a real biological variable in its effect on BW and this effect of race is

presumably genetic” (Naylor & Myrianthopoulos, 1967). The assumption that black women

differ genetically from white women in their ability to bear normal or large infants persists in

more recent studies of foetal growth (Hulsey et al., 1991; Amini et al., 1994) one of which, for

example, refers to “genetic factors affecting growth, such as neonatal gender and race” (Amini et

al., 1994). Few data have been published on the BWs of infants born to African-born women in

the United States. Most African Americans trace their origins to Western Africa, where the slave

trade flourished in the 17th and 18th centuries (Oliver & Fage, 1988; Reed 1969). It is estimated

that U.S. blacks derive about three quarters of their genetic heritage from West African ancestors

and the remainder from Europeans (Reed, 1969; Chakraborty, 1991; Adams & Ward, 1973;

Glass, 1953). To the extent that population differences in allele frequency underlie the observed

differences in BW between blacks and whites in the United States, one would expect women of

“pure” West African origin to bear smaller infants than comparable African Americans,

considering the European genetic admixture in the latter (Richard et al., 1997). However, this

assumption appear not to be true according to (Richard et al., 1997).

In summary, African-born black women have infants with a greater mean BW and a different

birth-weight distribution than U.S. - born black women born (Richard et al., 1997). Therefore,

from the literature, there is clear evidence of the effect of race and ethnicity of a particular

population on EFW which clearly suggests that, research must be conducted to find out and

ensure that, the most accurate regression model is used for a particular population in question.


23

2.9 GENETIC FACTORS Interest in determining the relative contributions of factors that produce BW variation, namely

the maternal and foetal genetic factors and the environment of the foetus have been expressed.

Approximately 40% of total BW variation is due to the genetic contributions from mother and

foetus (approximately half from each), and the other 60% is due to contributions from the foetal

environment (Polani, 1974).

Although both parents' genes affect childhood growth and final adult size, the maternal genes

have the main influence on BW as the classic horse-pony cross-breeding experiments by Walton

and Hammond (1938) demonstrated the important role of the mother that foals of the maternal

horse and paternal pony are significantly larger than foals of the maternal pony and paternal

horse, and foals of each cross are comparable in size to foals of the pure maternal breed which

clearly demonstrated the widely held study of a maternally related constraint on foetal growth.

Similar conclusions of maternal constraint to growth are reached from family studies in humans.

Low and high BWs recur in families with seemingly otherwise normal pregnancies. Sisters of

women with intrauterine growth restriction (IUGR) babies tend to have IUGR babies, a trend

that is not seen in their brothers' babies (Johnstone & Inglis, 1974). Mothers of IUGR infants

were frequently growth restricted at birth (Ounsted & Ounsted, 1966; Simpson et al., 1975).

There is also a greater similarity in BW between maternal half siblings and full siblings than

between paternal half siblings and full siblings Robert and Robert (2012). Although the maternal

phenotypic expression particularly maternal height may affect foetal growth, the evidence for

such an influence is not convincing Robert and Robert (2012). Social deprivation has also been


24

associated with IUGR, a finding not explained by known physiologic or pathological factors

(Wilcox et al., 199).

The one definite paternal influence on foetal growth and size at birth is the contribution of a Y

chromosome rather than an X chromosome (Robert and Robert, 2012). The male foetus grows

more quickly than the female foetus and weighs approximately 150g to 200g more than the

female at birth (Thomson et al., 1968). There is also a suggestion that paternal size at birth can

influence foetal growth, with BWs potentially increased by 100g to 175g (Klebanoff et al.,

1998). Furthermore, the greater the antigenic dissimilarity between the parents, the larger the

foetus. Whether it is genetically determined or not, women who were small for gestational age

(SGA) at birth have double risk of reduced intrauterine growth in their foetuses (Klebanoff et al.,

1997). In similar fashion, foetuses destined to deliver preterm have a higher incidence of reduced

foetal growth (Bukowski et al., 2001). The role of the genetic constitution of mother or foetus in

these observations is not clear.

Specific maternal genotypic disorders can cause IUGR. An example being phenylketonuria

(Saugstad, 1972). Infants born to homozygously affected mothers almost always have IUGR, but

whether the reason is an abnormal amount of metabolite crossing from mother to foetus or an

inherent problem in the foetus is unknown Robert and Robert (2012). There is a significant

association between IUGR and congenital malformations. Such abnormalities can be caused by

established chromosomal disorders or by dysmorphic syndromes, such as various forms of

dwarfism Robert and Robert (2012). Some of these malformations are the expression of a

specific gene abnormality with a known inheritance pattern, whereas others are only presumed to

be the result of a gene mutation or an adverse environmental influence Robert and Robert (2012).


25

Although in some reports only 2% to 5% of IUGR infants have a chromosomal abnormality, the

incidence rises to 20% if IUGR and mental retardation are both present (Snijders et al., 1993).

Birth weights in infants with trisomy 13, 18, and 21 are lower than normal (Chen et al., 1972,

Peuschel et al., 1976). The decrease in BW is less pronounced in trisomy 21. The frequency

distribution of BWs in infants with trisomy 21 is shifted to the left of the normal curve after 34

weeks of gestation, resulting in gestational ages 1 to 1.5 weeks less than normal, and BWs and

lengths are less than in control infants from 34 weeks until term (Creasy et al., 2013). This effect

is more marked after 37 weeks of gestation, but BWs are still only approximately 1 standard

deviation from mean weight. BWs in translocation trisomy 21 are comparable to those in

primary trisomy 21. Birth weights of newborns that are mosaic for normal and 21-trisomic cells

are lower than normal but higher than those of21-trisomic infants (Polani, 1974).

Newborns with other autosomal abnormalities, such as deletions (chromosomes 4, 5, 13, and 18)

and ring chromosome structure alterations, also have had impaired foetal growth. Although

abnormalities of the female (X) and male (Y) sex chromosomes are frequently lethal (80% to

95% result in first trimester spontaneous abortions), they could be a cause of IUGR in a newborn

(Kramer, 1987). Infants with XO sex chromosomes have a lower mean BW than control infants

(approximately 85% of normal for gestational age) and are approximately 1.5 cm shorter at birth.

Mosaics of 45 X and 46, XX cells are affected to a lesser degree (Kramer, 1987). Although a

paucity of reports prevents definite conclusions, it appears that the repressive effect on foetal

growth is increased with the addition of X chromosomes, each of which results in a 200- to 300-

g reduction in BW (Kramer, 1987). In general, IUGR is associated with numerous other

dysmorphic syndromes, particularly those causing abnormal brain development. The overall

contribution that chromosomal and other genetic disorders make to human IUGR is estimated to


26

be 5% to 20% and approximately 25% of foetuses with early-onset foetal growth restriction

could have chromosomal abnormalities, and karyotyping via cordocentesis can be considered

Robert and Robert (2012). A genetic basis should be considered strongly if IUGR is encountered

in association with neurologic impairment or early polyhydramnios.

The two main methods for predicting BW in current sonographic obstetrics are:

(a) clinical techniques based on abdominal palpation of foetal parts, calculations based on

fundal height in combination with some foetal biometric measurements and

(b) sonographic measures of skeletal foetal parts only which are then inserted into regression

equations to derive estimated foetal weight (Hanretty et al., 1990; Hendrix et al., 2000;

Raman et al., 1992).

Although some investigators consider sonographic estimates to be superior to clinical estimates,

others, in comparing both the techniques concurrently, conclude that they confer similar levels of

accuracy (Nzeh et al., 2000; Hanretta et al., 1990; Hendrix et al., 2000; Raman et al., 1992;

Watson et al., 1988; Mehdizadeh et al., 2000; Wilcox et al., 1992;Cecattiet al., 2000; Johar et

al.,1988;Hulsey et al., 1991; Richards et al., 2001;Hadlocket al., 1985, Ebomoyi et al., 1991,

Ojwang et al., 1984).

The available techniques for imaging can be broadly classified under prediction of equations of

BW by ultrasonography (USG) and MRI (Shittu et al., 2007). For imaging purposes, ultrasound

EFW is commonly used worldwide and less expensive. In addition, acquisition of ultrasound

equipment is far affordable compare to other imaging modality such as magnetic resonance

imaging MRI, which is highly expensive. Thus, the aim of the present study was to determine


27

which of the commonly used sonographic model provide better accuracy or precision of foetal

weight estimation, and to provide a better understanding of the reasons why that/those formulae

should be used in deducing foetal weight estimation.


28

CHAPTER THREE

METHODOLOGY

3.1 INTRODUCTION Research methods are approaches or techniques employed in conducting research operations

using scientific and systematic ways in answering a research question. This section therefore

presents the methodology employed in conducting this study and describes key aspects such as

the study design, study population and study sites, and experimental procedure.

3.2 STUDY DESIGN

A quantitative study which is cross-sectional and quasi-experimental in nature was

adopted for this study. Numeric figures were produced and analyzed for the study to become

conclusive.

For a study to be quantitative, Babbie (2010) enumerated that, quantitative methods emphasize

objective measurements and the statistical, mathematical, or numerical analysis of data collected

through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data

using computational techniques. Furthermore, quantitative research focuses on gathering

numerical data and generalizing it across groups of people or to explain a particular phenomenon

(Muijs, 2010). This study adopted a research design that required a quantitative documentation

of foetal biometric measurements and neonatal weights.

Quantitative studies are conducted to determine the relationship between an

independent variable and a dependent or outcome variable within a population associated with

an experiment (subjects measured before and after delivery) (Babbie, 2010). As descriptive study


29

establishes only associations between variables, an experimental study establishes causality

(Babbie, 2010). Therefore, the study ultrasonically measured foetal biometry, compute EFWs

and correlate with the actual BWs.

Quantitative research deals in numbers, logic, and an objective stance and focuses on numeric

and unchanging data and detailed, convergent reasoning rather than divergent reasoning (Brains,

2011) i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-

flowing manner (Brians, 2011). Therefore, this study accordingly, compares EFWs to ABWs in

line with the aim and objectives of this study.

As much as the study was quantitative, with assumption that there was not going be differences

in experimentation and the outcome values, it was cross sectional in nature as well since all the

experimental work was performed on a certain group of people during a particular period and

was carried out prospectively in which convenient sampling method was applied. Convenient

sampling method was used based on the fact that participants in this study must be in their latent

phase during labor which is associated with a lot of pains and discomfort resulting in

participants‟ unwillingness to partake in the study.

Ultrasound scans for EFW were scheduled within thirty minutes on arrival to the delivery ward

after medical histories such as previous antenatal ultrasound and laboratory particulars i.e.

antenatal folders which include their entire previous ultrasound scan and laboratory reports have

been received. The period between the time of arrival and the scheduled time for scanning

became very important due to empirical evidence that, almost 95% of expectant mothers arrived

at the labour-ward in the late latent phase of labour.


30

Foetal biometrics such as BPD, HC, AC and FL measurements were taken according to the

established guidelines (Loughna et al., 2009). All examinations were performed trans-

abdominally using Philips ClearVue 350 equipment, one day prior to vaginal or normal delivery

and within a maximum of one day prior to induction of labour. Birth weights were measured

using properly calibrated Salter scale (model 914) digital weighing scale of maximum range of

20kg.

3.3 STUDY SITES

The research was conducted at the Mamprobi Polyclinic (M-PC) in the Greater Accra

Region of Ghana. This study site was selected based on the following factors:

1. Out-patients records suggested that patients from all the geo-regional groupings in Ghana

residing in Accra attend this polyclinic for antenatal and delivery services.

2. M-PC has a large antenatal and delivery base.

3. M-PC is equipped with the new Philips ClearVue 350 ultrasound equipment.

3.4 STUDY POPULATION

The study included all pregnant women laboring with singleton pregnancies and had been

admitted for birth deliveries at the study site within the stipulated period of four months of data

collection. An anecdotal report from the study site showed one thousand two hundred and sixty-

seven, (1,267) deliveries per year. Therefore, during the four months of data collection period, an

estimated four hundred and twenty-two, (422) expectant mothers went ultrasound examination

for the purpose of this study and biometric measurements, BPD, HC, AC and FL of foetuses

were taken.


31

3.5 SAMPLE SIZE

Knowing the population size and using finite population correction factor, a sample size n was

determined via the equation according to courses.wcupa.edu;

)1(Nn

Nnn

o

o (3.1)

Where no = sample size without considering the finite population correction factor

N Population size

Assuming 442N and 100on then Equation (3.1) yields a sample size of

78)1442(100

)442)(100(

)1(Nn

Nnn

o

o (3.2)

Therefore, the actual sample size from finite population size of four hundred and forty-two (442)

was seventy-eighty, (78) participants.

At the study site, estimated numbers of seventy-eight 78 expectant mothers were expected to

undergo the scanning examination during the data collection period. Participants were selected

according to the inclusion and exclusion criteria, taking into account patient‟s right not to partake

in the research, the pain and discomfort level depending on the labour phase (active or latent)

which made few participants to decline in participation and the time duration of completion of

the study.

Based on the reasons given above, seventy-five, 75 participants took part in the study. However

due to, late referrals of some of the participants to tertiary facilities on account of prolong latent

phase of labor, indication of macrosomia and breech presentations, a sample size of 40

participants was arrived at for the study.


32

3.6 INCLUSION AND EXCLUSION CRITERIA

3.6.1 Inclusion Criteria

Participants were selected taking into account the following:

Expectant mothers with viable singleton pregnancies with cephalic presentations and

admitted for birth delivery at the study sites

Expectant patient‟s presenting with pain and discomfort level on the labour phase (active

or latent).

3.6.2 Exclusion Criteria

Patients presenting the condition below were excluded from the study:

Expectant mothers with polyhydramnios, pre-term labour, ruptured membranes,

abnormal lie and presentation, multiple pregnancies, antepartum haemorrhage,

eclampsia, obvious congenital abnormalities, oligohydramnios, anteriorly-inserted

placenta, and poor visualization of foetal part

Expectant mothers with no contraction and amniotic rapture was excluded from the

study.

3.7 EQUIPMENT/INSTRUMENT CAPABILTY

A Salter scale (model 914) digital weighing scale of maximum range of 20kg and reading up to 6

decimal places was used for the weight measurements of the neonates. Using dry cells as source

of electrical power, makes Salter scale very light in weight and can be moved around with less

effort.

A Philips ClearVue 350 ultrasound imaging equipment was utilized for the study. The technical

specifications of the equipment are listed in Table 3.1.


33

Table 3.1: Technical specifications of Philips ClearVue 350 ultrasound equipment

Parameters Screen width Control panel height Monitor width Monitor height Depth

Dimensions 51.8cm 83.4cm 43.2cm 138.4cm 58.6cm

Probe: C5-2: Abdominal, obstetrics/gynaecological, pediatric, vascular, and urological

curvilinear transducer

Gray scales: 255 in 2-D, M-mode, and Doppler

Components Scale lines: Up to 1,024 scan lines, transducer and mode dependent

Input signals: Low-level ECG, Four-port transducer receptacles

Electrical parameters: AC 100-240V ±10%

The advantages of this equipment over others in terms obstetric work is based on the following

factors which have been incorporated into the operational function of this equipment.

3.7.1 Ultrasound Equipment Suitability for Obstetric Work

The suitability of the ultrasound equipment for obstetric work in this study was established by

verification of these factors:

1.Amniotic Fluid Index measurement: This factor provides for calculating the amniotic

fluid in each quadrant (Q1+Q2+Q3+Q4) to give the total amniotic fluid index (AFI) value

which is immediately compared to an already provided reference range between 8.1 to

18.0cm (Rutherford et al., 1987).

2. Biophysical profile: An important factor that defines foetal wellbeing and expressed as

Biophysical profile = movement + tone + breathing + amniotic fluid index volume


34

It ranges from 0 to 2 or „Not Applicable‟ which indicates that the category will not

Contribute to the biophysical profile total (Manning et al., 1990).

3. Selecting of number of foetus in twin, triplets and quadruplets gestations to produce

separate reports on each of the foetuses. In selecting the number of foetuses, typically, the

foetus closest to the cervix is labeled „A‟ and the others are designated sequentially as they

are seen moving up to the fundus as B, C, and D.

4. Colour and power Doppler incorporation. This is done for easy study of arterial and

venous systems of the foetus especial in the foetal brain, umbilical cord and renal vessels.

5. B and M-modes: These mode combinations are used in displaying foetal heart movements

leading to estimation of foetal heart beat and the gradient of the wave produced.

These obstetrics properties of the ultrasound equipment in addition to others like

electrocardiogram, small parts and vascular imaging, and 3-D functions coupled with very clear

quality images produced on a large plasma screen, makes the equipment highly functional.

3.8 QUALITY ASURANCE TESTS ON THE EQUIPMENT/INSTRUMENT

Quality assurance and control was carried out before this study started. The ultrasound

equipment was upgraded by the engineers at the start of the study as biennial routine

maintenance contract to make sure the equipment perform at its maximum operational capacity.

After the upgrading of equipment, an operator manual was used to set its functions to their

optimal level to produce superior image quality for accurate and precise measurements to be

taken.

The Scaler scale was each time set to the zero mark before each neonate was weighed and the

dry cell use to power it was changed at start of work every day.


35

Additionally, a wheel chair was provided to transfer patients from the ward to the scanning room

due to the distance between these two destinations and patients‟ unstable condition at this period.

Wooden stair was provided for smooth climbing to the scanning bed and very long screen was

used to partition the room to provide privacy to the patients.

3.9 ASSESSMENT OF RELIABILITY OF THE MEASUREMENTS

Before the commencement of the study, pilot survey was done to test the reliability of

measurements on the sonographic images. Twenty patients were used in the pilot assessment of

accurate and precise measuring of foetal biometry. The result shows 98% accuracy after

scanning each participant three times and finds their arithmetic means.

The participants did not pay for participating in both the piloting and main research work.

3.10 REGRESION MODELS

As mentioned in Chapter 2, several regression models can be applied to the calculation of EFW

using ultrasonography. The regression models adopted in this study are presented here.

3.10.1 Campbell and Wilkin Approach for EFW (AC) only

The Campbell and Wilkin (1975) regression model for computing AC only is expressed as

200331.0282.0564.4)(ln ACACkgEFW (3.1)

3.10.2 Hadlock Approaches for EFW Calculations: (AC, FL) only

The Hadlock et al., (1985) approach can be applied for computing AC and FL fetal biometrics via

))((004.0)(1938.0)(05281.0304.1log10 FLACFLACEFW (3.2)


36

In particular, the system determines 2 standard deviation ranges based on EFW via the expression

)*154.0( EFWEFW (3.3)

3.10.3 Hadlock Approaches for EFW Calculations: (AC, BPD) Only

In respect of EFW calculations using AC and BPD fetal biometrics only, the Hadlock regressions is

represented as

))(1694.0)(000595.0

)(007365.0)(000604.0)(05845.011.1(log 22

10

BPDACBPD

BPDACACEFW (3.4)

With a corresponding standard deviation ranges based on EFW as

)*182.0( EFWEFW (3.5)

3.10.4 Hadlock Approaches for EFW Calculations: AC, FL and HC Only

Based on AC, FL, and HC variables, the Hadlock regression for EFW calculations is expressed as

))(158.0)(0438.0)(0107.0))((00326.0326.1(log10 FLACHCFLACEFW (3.6)

The system determines two standard deviation ranges based on EFW for this calculation as

follows:

)*148.0( EFWEFW (3.7)

3.10.5 Hadlock Approaches for EFW Calculations (AC, BPD, FL)

FLACBPDFLACgEFW 1623.00457.00316.0034.0335.1log)( 10 (3.8)

The EFW formula via Hadlock et al., (1985) using AC (cm), BPD (cm), and FL (cm) is: The

system determines two standard deviation ranges based on EFW for this calculation as follows:

)146.0( EFWEFW (3.9)

3.10.6 Hadlock Approaches for EFW Calculations (BPD, HC, AC, FL)


37

The formula for the EFW via Hadlock et al., (1985) using AC (cm), BPD (cm), FL (cm), and HC

(cm) is shown below. Normal ranges are broken up by EFW as percent of EFW and a gram offset.

)(174.0)(0424.0

))((00061.0)(0064.0))((00386.03596.1log10

FLAC

ACBPDHCFLACEFW

(3.10)

3.10.7 Osaka Approach for EFW Calculations (BPD, FTA, FL)

The EFW via Osaka University (Nobuaki et al., 1990) using BPD (range: 3.1 t0 10.0cm), fetal

trunk abdominal area (range: 20 to 180.0cm2), and FL (range: 1.0 to 8.0cm) is:

30994.6))((50665.3)(25647.1)( FLFTABPDgEFW (3.11)

3.10.8 Tokyo Approach for EFW Calculations (BPD, AD, FL)

The EFW formula via Tokyo University (Mizuno et al., 1989), using BPD (range: 3.1 to 10.0cm),

AD (AP, range: 5.0 to 15.0cm), AD (transverse: range: 5.0 to 15.0cm), and FL (range: 1.0 to

8.0cm) is:

FLADtrvADapBPDgEFW 42.3)(07.1)( 3 (3.12)

Where ap and trv are antero-posterior and transverse.

3.10.9 ShephardApproach for EFW Calculations (AC, BPD)

The Shephard (1982) formula for EFW using AC, (range: 15.0 to 40.0cm), and BPD (range: 3.1 to

10.0cm) is:

)002646.0046.0166.07492.1(101000)( BPDACACBPDgEFW (3.13)

The system determines one standard deviation range based on EFW for this calculation according

to the following:

ggEFW

ggEFW

ggEFW

566500,3

405500,3500,2

218500,2

(3.14)


38

3.10.10 Shinozuka Approach for EFW Calculations (AC, BPD, FL)

The formula for EFW via (Shinozuka et al., (1996), using AC (cm) (range: none), BPD (cm)

(range: none), and FL (cm) (range: none) is:

)30.0(07.1()( 23 FLACBPDgEFW (3.15)

3.10.11 Shinozuka Approach for EFW Calculations (APTD, TTD, BPD, FL)

The Shinouzuka (1989) formula for EFW using AP trunk diameter (cm) (rang: none), transverse

trunk diameter (cm) (range: none), BPD (cm) (range: none), and FL (cm) (range: none) is:

FLTTDAPTDBPDgEFW 42.3)07.1()( 3 (3.16)

Therefore from the immediate groups of equations above, the equations used in this study are

presented in Table 3.2.


39

Table 3.2: Estimated fetal weight formulae used in the study

Study Year Formulae

Campbell

1975

200331.0282.0564.4)(ln ACACkgEFW

Hadlock1

1984

))((004.0)(1938.0)(05281.0304.1log10 FLACFLACEFW

Hadlock6⃰

1985

)(1694.0)(000595.0

)(007365.0)(000604.0)(05845.011.1log

22

10BPDACBPD

BPDACACEFW

Hadlock3

1985

)(158.0

)(0438.0)(017.0)(00326.0326.1log10

FL

ACHCFLACEFW

Hadlock7

1985

FL

ACBPDFLACgEFW

1623.0

0457.00316.0034.0335.1log)( 10

Hadlock4

1985 )(174.0)(0424.0

))((00061.0)(0064.0))((00386.03596.1log10

FLAC

ACBPDHCFLACEFW

Shephard 1982 )002646.0046.0166.07492.1(101000)( ACBPDACBPDgEFW

Shinozuka2 1989 )30.0()07.1()( 23 FLACBPDgEFW


40

3.11 PROCEDURE FOR DATA COLLECTION

Expectant mother made to lie on the scanning bed in a supine position with the abdomen

exposed, a coupling gel is applied on it and a probe used to search for foetal parts like head,

abdomen and femur length and various measurements were made.

The BPD measurements were done for each foetus by obtaining a longitudinal section of the

foetus using small sliding movements of the transducer on each side of the foetal spine and

tracing the head along the spine. On locating the head, the transducer was moved to the vertex. In

this manner, the probe was slided to the lateral side of the foetal head facing anteriorly which at

this point looks ovoid in shape.

At this position, the probe was adjusted until strong midline echo with the cavum-septum

pellucida is demonstrated. When the section was not the required ovoid shape, minor rotational

adjustments were made until the shape was correct. Slight up and down movements of the

transducer on the maternal abdomen located the correct section, which was then frozen. The

BPD was measured by placing the horizontal component of the on-screen calipers on the outer

aspects of the echoes from the foetal skull. This was done at right angles to the midline and at

widest diameter of the ovoid head shape (Figure 3.1).


41

Figure 3.1: BPD measurement Source: Field data (2014)

Foetal AC was measured by scanning the foetus in a longitudinal plane until the foetal aorta was

visualized in its course, through the foetal chest and abdomen. The probe was rotated through

90° at the level of the lower end of the foetal ribs, with the rips showing posterior acoustic

shadowing. A minor adjustment was then made by moving the transducer up or down the foetal

body through maternal abdomen until the section was obtained. The section appeared almost a

perfect circle, containing only a short section of the umbilical vein in the anterior third of the

foetal abdomen.


42

Figure 3.2: AC measurement Source: Field data (2014)

For HC measurements, ellipsoidal tracing was made by drawing a line at the outer perimeter

around the exact image used in measuring BPD (Figure 3.3). The FL measurement was obtained

by scanning the foetus in longitudinal plane and the spine traced to its tapering end. The probe

was then rotated through small angles to locate a single long bone lying almost horizontal on the

monitor, producing a clean posterior acoustic shadow (Figure 3.4).


43

Figure 3.3: HC measurement Source: Field data (2014)

Figure 3.4: FL measurement Source: Field data (2014)


44

Maternal height and weights were obtained from participants antenatal records which are

retrospective in nature. The participants first visit weight is referred to as initial weight and the

last weight before onset of labour is final weight.

3.12 DATA MANAGEMENT

All procedures were carried out with strict adherence to standard protocols. Cross checking of

data entries were made to ensure accurate data capture for accurate statistical analysis adhered to.

Participants were given codes for identification. Data collecting sheets were store in safe cabinet

and electronic data is stored in a password protected database. The outcome of the study will be

disseminated to the Department of Radiography, School of Biomedical and Allied Health

Science, College of Health Sciences, University of Ghana. Articles of this study will be

published in Scientific Journals. The study reports shall be presented in various seminars and

conferences.

3.13 STATISTICAL ANALYSIS

The data was entered using Microsoft Excel software package and was exported onto SPATA

software package for all data analysis. Linear regression and Box and Whisker were used to

show the relationship between the various EFWs and the ABWs and correlation coefficient was

used to show the relationship between maternal heights, various weights and ABWs.

3.14 ETHICS

The study conformed to the guidelines for human experimentation in the Helsinki Declaration

“Ethical Principles for Medical Research Involving Human Subjects .Approval was obtained


45

from Ethics and Protocol Review Committee of the School of Biomedical and Allied Health

Sciences. Informed consent was obtained before the study after adequate explanation. Informed

written consents were obtained from the workers prior to scanning (Appendix III). Objectives

and examination procedure of the study were made available for the expectant mothers

(Appendix VI). Confidentiality of participants was maintained in accordance with the conditions

of ethical approval from the above-named ethics committee and privacy was ensured by keeping

the identity of the participants anonymous (Appendix V).

3.14.1 Standard Protocol Adopted for the Study

To prevent the re-occurrence of medical abuse of human subjects, the study was carried out with

strict adherence to the following protocol guidelines:

1. Voluntary participation was read to each participant, explanation given and their consent

obtained.

2. The researcher showed respect for participants and treated each of them as autonomous

agents.

3. Participants were given the right to decline participation in the research at any material

stage.

4. Their privacy was respected and their well-being protected.

5. Participants‟ integrity was safe guarded.

6. Participants were protected from mental, physical, and emotional harm.


46

CHAPTER FOUR

RESULTS

4.1 INTRODUCTION This Chapter presents the results of the study conducted to determine the best formula for

estimating foetal weight. The results are presented in accordance with stated objectives of the

study and included key aspects such as demographics characteristic, biometric measurements

obtained ultrasonically, computation of EFW by the chosen regression equations, weighing of

neonates and comparison of EFW and ABWs.

Seventy-five, 75 expectant mothers reporting for normal delivery at the study site initially

consented to participation following adherence to study protocols and ethics requirements out of

calculated sample size of seventy-eight, 78. However, only forty, 40 participants were used in the

study due to late referral of patients on suspicion of macrosomia, prolonged latent phase of

labour and breech presentations. Therefore, 96% response rate was achieved for the study.

4.2 DEMOGRAPHICS

The age and body mass index (BMI) demographics of the participants are shown in Table 4.1.

The mean age of the population was 26.93±6.06 years. The initial median BMI of the

participants at their first visit in the first trimester was 23.31and an inter-quartile range (IQR) of

5.15, and 27.80(IQR=5.33) at third trimester.


47

Table 4.1: Maternal Demographics (N= 40)

Maternal age (years)

Minimum Maximum Mean ± s.d

17 38 26.93 ± 6.06

BMI (kg/m2)

Median Inter-quartile range

Initial BMI 23.31 5.15

Final BMI 27.80 5.33

Statistical analysis was performed to establish correlation between maternal weight, height, initial

and final BMI, and neonates‟ weights (ABWs). The results are presented in Table 4.2.

Table 4.2: Correlation coefficient between maternal demographics and neonates’ ABWs

Demographic variables Correlation coefficient(R2) p-value

Initial maternal weight (kg) vrs. ABW (kg) 0.0251 0.8777

Final maternal weight (kg) vrs. ABW (kg) 0.1785 0.2705

Initial maternal BMI vrs. ABW (kg) 0.0502 0.7586

Final Maternal BMI vrs. ABW (kg) 0.2043 0.2061

Maternal height (cm) vrs. ABW (kg) -0.0856 0.5996

Source: Field data (2014)

The range of computed correlated coefficients {weight: R2 = 0.0251-0.1787; BMI: R

2= 0.0502-

0.2043; height: R2=-0.0856} and p-values {0.2061-0.8777> 0.05} within 95% confidence


48

intervals established significant differences between maternal anthropometrics and neonates

ABWs.

4.3 FETAL BIOMETRICS

Table 4.3 below shows the results of the sonographically determined fetal biometric data.

Table 4.3: Mean and standard deviation of BPD, HC, FL, and AC (N=40)

Fetal biometric measurements Lower limit Upper limit Mean ± s.d

BPD 8.99 9.28 9.13 ± 0.45

AC 34.91 36.42 35.67 ± 2.37

HC 31.94 33.16 32.56 ± 1.91

FL 7.44 7.71 7.58 ± 0.43


Fetal weights determined via the eight regression models (Campbell & Wilkin 1975, Hadlock 2, 7,

4, 3, 6, 1985, Shephard, 1982, Shinozuka 2 1996) were compared with ABWs of 40 neonates. For

normal delivery at term, 35, (87.5%) newborns had BWs between 2.5kg and 3.9kg (Table 4.4)

Table 4.4: Birth weights at term

Birth weight at term (kg) Number Percent

< 2.5 2 5.0

2.5 – 3.9 35 87.5

> 3.9 3 7.5

Total 40 100.0


The mean ABW ranged from 3.0kg –3.3kg with a mean of 3.2 ± 0.46kg.


49

Act

ual

bir

th w

eigh

t (k

g)

4.4 HYPOTHESIS

As hypothesized that there will be no significant difference between EFWs and ABWs, all the

eight equations or regression models present p-values<0.05 significance level. Therefore, the

study failed to reject the null hypothesis.

5

4.5

4

3.5

3

2.5

2

1.5 2 2.5 3 3.5 4 4.5

Regression model weights eqn_1 eqn_2 eqn_3 eqn_4 eqn_5 eqn_6 eqn_7 eqn_8

Linear (eqn_1) Linear (eqn_5)




Figure 4.1: Scatter plot of ABW against regressional models Source: Field data (2014).

A scatter plot in Figure 4.1 showed a linear trend among all the 8 regression models with outliers

and their statistical measures as shown in table 4.5 below.


50

Table 4.5: Comparison between EFW generated by the regression models to ABWs

ABW &regression models EFWs p-value

Lower limit Upper limit Mean± s.d

ABW (N = 40) 3.03 3.33 3.18 ± 0.46

Eqn_1: Campbell 1975 3.44 3.69 3.57 ± 0.07

Difference -0.52 -0.26 -0.39 ± 0.06 0.0001

Eqn_2: Hadlock 1 1885 3.03 3.33 3.57 ± 0.07

Difference -0.52 -0.26 -0.39 ± 0.07 0.0001

Eqn_3: Hadlock 6 1885 3.03 3.33 3.35 ± 0.05

Difference -0.31 -0.30 -0.17 ± 0.07 0.0200

Eqn_4: Hadlock 3 1885 3.53 3.57 3.55 ± 0.07

Difference -0.50 -0.23 -0.37 ± 0.07 0.0001

Eqn_5: Hadlock 7 1885 3.54 3.58 3.56 ± 0.07

Difference -0.52 -0.25 -0.38 ± 0.07 0.0001

Eqn_6: Hadlock 4 1885 3.53 3.57 3.55 ± 0.11

Difference -0.50 -0.24 -0.37 ± 0.07 0.0001

Eqn_7: Shephard 1982 3.36 3.73 3.55 ± 0.09

Difference -0.52 -0.22 -0.37 ± 0.07 0.0001

Eqn_8: Shinozuka 2 1996 3.55 3.59 3.57 ± 0.08

Difference -0.52 -0.25 -0.39 ± 0.07 0.0001



51

With exception of the Hadlock31985 regression model, the results showed that the absolute

mean difference between the ABWs and the EFW sin all the regressions models were

statistically significant [p-value=0.0001<0.05, with a 95% CI, -0.52 to -0.23-0.26]. The absolute

mean difference between the ABW and Hadlock31985 EFW was also statistically significant [p-

value = 0.02 < 0.05 with a 95% CI of -0.31 to -0.30], showing no difference between the mean

ABW and the mean EFW.

In Table 4.5 Hadlock3 i.e. equation 4 shows a narrow interval of limits around the estimated mean

and the smallest standard deviation.

The Box and Whisker plot illustrating distinctly the relationship between the ABWs and EFWs

generated by the regression models and the associated distribution of the z-scores (median,

minimum, maximum, first quartile, third quartile and inter-quartile ranges) is shown in Figure

4.2 below.


Figure 4.2: Box and Whisker distribution of ABW and EFWs Source: Field data (2014)

52


53

CHAPTER FIVE

DISCUSSION

5.1 INTRODUCTION This Chapter discusses the findings of the study in relationship with reviewed literature. The

findings were presented in relationship to the stated objectives of the study under various themes.

5.2 RESPONSE RATE

A response rate of 75, (96%) out of 78, (100%) was achieved for this study. However, only 40,

53% out of 75 expectant mothers were used in the study. The low final figure of 40 was attributed

to late referral of 35, (47%) patients to tertiary (Specialist) centres on suspicion of macrosomia,

prolong latent phase of labour and breech presentations. Follow up on these participants by

telephone yielded no result in one week of hospitalization. This scenario even present higher

percentage comparable to study by Fernandez et al., (2009) in which the study reported that,

about 15% of participants were lost to follow up after 6weeks post hospitalization.

5.3 DEMOGRAPHICS

The ages of the 40 expectant mothers ranged from 17-38 years with a mean of 26.93± 6.1 years.

An initial and final median BMI of 23.31 and 27.80kg/m2and their corresponding IQR of 5.15

and 5.33 were also obtained respectively. The mean age of the population is representative of the

reproductive age group in Ghana and comparable to a mean age of 27.01±5.40years reported by

Kumarasiri et al. (2013) in an EFW study conducted on singleton pregnancies in Sri Lanka.

However the BMI and IQR in this study are in sharp contrast with the work of Kumarasiri et al.

(2013), which reported a median BMI of 20kg/m² and an IQR of 2.2.Additionally, statistical


54

significance was established between all groups of maternal anthropometric and ABW [p-

values>0.05] i.e. range of computed correlated coefficientR²-values and p-values (> 0.05) within

95% confidence intervals established significant differences between maternal anthropometrics

(Weight, Height, BMI) and neonates ABWs as shown in Table

4.2.

On the contrary, a study by Ojha & Malla (2007) indicated that low maternal anthropometric

(weight, height and BMI) are some risk factors that contribute to low BW, as confirmed by

Jananthan et al., (2009), that a strong correlation existed between maternal anthropometric and

ABW. Additionally, in WHO publication (Backstrand, 1995) of the Mexico Nutrition CRSP

research project in six Leishmann villages in the rural Solis Valley of central Mexico during

1984-1986 also established that weight and BMI showed the highest association with BW while

the effect of maternal height on ABW was insignificant. The contrast of the findings of this study

with the literature might be due to large sample size of those previous studies. However, findings

from this study are consistent with (Nahum et al., 1995).

5.3 FOETAL BIOMETRICS

All the 40 uncomplicated singleton pregnancies seen during the study period were between 35

0

and 406

weeks of gestation. Foetal weights determined via the 8 regression models were

compared with ABWs of 40 neonates. The mean duration from ultrasound scan to delivery was 1

day (range 0-2). For normal delivery at term, most of the newborns (n=35, 87.5%) had BWs in

the range of 2.5 and 3.9kg, while 7.5% (n=3) weighed more than 3.9kg. Only 5% (n=2) weighed

less than 2.5kg. According to WHO, low and high BW limits are defined as BW less than 2.5 kg

and greater than 3.9kgrespectively. Comparatively, the results obtained in this study are

consistent with the WHO limits.


55

According to Nahum et al., (1995) in Gerard et al., (2002), the daily rate of foetal growth is

13.0gfor boys and 12.4g for girls respectively. Hence for term deliveries of 270 days, these

figures translate into 3.51kg for boys and 3.35kg for girls. The EFWs obtained in this study are

in agreement with Nahum et al., (1985) and Gerard et al., (2002) as the mean EFW of all the

models is 3.46±0.65 and ABW ranged from 3.0kg –3.3kg with a mean of 3.2 ± 0.46kg.

From figure 4.2, the findings in this study confirmed many studies which concluded that most

EFW models generally overestimated foetal weight. Heer et al., (2008) established that, among

all known influencing factors, only a time interval of more than 7 days between EFW and

delivery had a negative impact on foetal weight estimation. Therefore, the principle of foetal

weight compensation from scan time to delivery time was therefore ignored in this study as it

presents no clinical significance of affecting neonates ABWs.

Luria et al., (2004) concluded that, there is a very good correlation between ultrasound EFW and

ABW. However, limits of agreement are fairly wide, thus ultrasound estimates of BW turn to

overestimate the neonatal weight by an average of 52g.Differences in anthropometry during

pregnancy appear to be related to BW. It was found that the smallest infants were those whose

mothers had a relatively lower pre-pregnancy weight (PPW) and early pregnancy weight, and

who subsequently failed to gain much weight by the third trimester (Backstrand, 1995) was also

established by this study.

Arguably, no previous study has been done in Ghana to assess the accuracy of using established

regression models in predicting EFW. This present study showed that the regression models

established no significant differences in predicting ABWs. The means and standard deviations


56

within 95% CI of the 4 foetal biometrics (BPD, HC, FL and AC) were very close, indicating the

precision of the theoretical models in determining ABWs in this study. However, inconsistent

with Kearney et al., (1978), who reported that inclusion of AC in estimating BW is the only

biometric measurement that can positively influence accuracy of EFW as it present the highest

standard deviation value of ± 2.37 around its mean compared standard deviation value of ± 0.43

for (FL) shown in Table-3.3.The disagreement might stem from the fact that, foetal abdominal

circumference in other populations differs greatly from that of Ghanaian one or differences in

accurate measurements.

A linear trend was noticed among all the 8 regression models with outliers. This means that,

individual point estimates as well as differences in estimates between any of the regression

models was a precise measure of the ABW. Per the earlier hypothesis, that there will be no

statistically significant difference between the ABWs and any of the 8 regression models. This

study indeed demonstrated that all the regression models showed no statistically significant

difference at (p-value =0.0001) in their mean EFWs compared to the neonates ABWs. This study

demonstrated that 87% of EFWs are within 5% of ABWs agreed with studies by Harlev et al.,

(2006), Shittu et al., (2007) and Atalie et al., (2006) which reported that about 75% of EFWs

were within 10% of ABWs. The 87% of EFW within 5% of ABWs compared to 75% of EFWs

within 10% of ABWs indicated how superior i.e. accuracy and precision of measurements in this

study as compared to others.

The 8 regression models adopted in this work are typically based on western populations and

hence does not account for racial and ethnic differences which present diversities in

anthropometrics. Further to this, regression analysis was used in the comparisons.


57

On the contrary, Altman and Bland (1983) questioned the appropriateness of using regression

analysis in such comparisons, suggesting that many factors influenced the accuracy of EFWs.

Kumarasiri et al., (2013) also concluded that operator experience played an important role in

accurate estimations of foetal weight among others. In this study, the mean BWs at term among

the Ghanaian population (3.53± 0.05kg - 3.57± 0.08kg) was comparable to the reference range of

3.08 ± 0.4kgderived from the global reference range based on WHO surveys of mean BW at

term (Mikolajczyk, 2011) who also used regression analysis.

In conclusion, all the 8 regression models predicted high accuracies of estimating foetal weights

within 5% of ABWs. With the exception of the Hadlock6(1985) regression model which had p-

value of 0.02, the results showed that the absolute mean difference between the ABWs and the

EFW in all the regression models were statistically significant with p-values = 0.0001. This is

suggestive that all the regressions models can be apply to Ghanaian population. However,

measuring BPD in labour period becomes less accurate as the head distends into the pubic bone

which turns to masked the foetal head from complete visualization and accurately measurement

coupled with narrow interval of limits around the estimated mean and the smallest standard

deviation, this study projects Hadlock3 i.e. equation 4 as regressional model which does not

depend on BPD for EFW, to be the best regressional model to be use in Ghanaian population at

term for estimating foetal weight.

.


58

CHAPTER SIX

CONCLUSIONS, RECOMMENDATIONS AND LIMITATIONS

6.1 INTRODUCTION

The study on the accuracy of ultrasound regression models for predicting foetal biometrics for

normal singleton pregnancies has been conducted. It was aimed at determining the best

ultrasound regression models using common foetal biometric measurements in EFW predictions

using the ClearVue 350 ultrasound equipment. The study included assessing records of maternal

anthropometrics (height and weight) from the time of first antenatal visit and weight at the last

antenatal visit, accurate measurements of foetal biometrics (BPD, HC, FL, and AC) as input data

into 8 established regression models, weight measurements of neonates within 1 hour of

delivery, comparisons of EFWs generated by the regression models to ABWs.

A summary of the present findings, conclusions, recommendations and limitations arising from

this research study are presented in this Chapter.

6.2 CONCLUSIONS

Comparisons of EFWs and ABWs have been investigated in various populations like that of (US,

Europe, Latin Americas and Africa) and by different methods. The findings of the study showed

that:

all the 8 regression models with the exception of the Hadlock7 which had (p-value =

0.02), established p-values = 0.0001 < 0.05 level of significance. Therefore, the best


59

ultrasound regressional model in predicting foetal weight in Philips ClearVue 350

ultrasound equipment is/are all the 8 models as there p-values <0.05 significant level.

the regression models predicted 87% of all EFWs in 5%of ABWs within 95%

confidence interval demonstrating high degree of accuracy and consistency.

Per these findings, gynaecologists, radiologists, sonographers/radiographers and midwives can

rely on EFWs produced from the Philips CleaVue ultrasound equipment using common foetal

biometric measurements in a 2D mode.

Prenatal care is essential for preventing foetal and/or maternal mortality and other complications.

However, timely interventions for patients at risk are required to prevent these complications. As

a result, if the method used for identification of patients at risk lacks sensitivity and specificity,

the trial of any intervention will not yield good results. It is therefore a challenge to estimate

actual foetal and BWs using ultrasound scans. Despite the limitations of ultrasound EFWs, the

modality remains the key basis for decisions amongst clinicians in many countries including

Ghana.

6.3 RECOMMENDATIONS

As noted from the study, it was only conducted in a microcosm population. Therefore,

geographical zones and country wide study should be done for better generalization.

Radiographers, sonographers, radiologists, gynaecologists, and midwives (professionally

trained and qualified to scan) should be trained every six months on emerging scan

procedures and produce accurate images and EFWs to enable good clinical decisions to

be taken.


60

The findings from this study have clearly shown that, with 87% of EFWs were within 5%

of ABW. Hence, radiographers, sonographers, gynecologists, radiologists, and midwives

can, to a high degree of accuracy rely on EFWs generated from the Philips ClearVue

ultrasound equipment using the common foetal biometric measurements in a 2D mode.

Caution must however be exercised especially in suspected large for date foetuses as all

models appear to slightly overestimated ABW.

6.3 LIMITATIONS OF THE STUDY

The major limitation as far as this study is concerned was the large number of referrals

from the study site to tertiary facilities after scanning. This has greatly affected the

sample size of this study.

Midwives in the labour-wards, most often, did not call the researcher when patients came

for delivery.

The scanning site was far from the labour-ward making it difficult for patients to walk in.


61

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APPENDICES

APPENDIX I

PARTICIPANTS INFORMATION SHEET

DETERMINING BEST REGERESSIONAL MODEL IN PREDICTING FOETAL

WEIGHT IN PHILIPS ClearVue 350 ULTRASOUND EQUIPMENT

Purpose of the Study

You are being asked to participate in this study in order to test for the best regression model

(Equation) for predicting birth weight (BW).

Study Procedure and General Information.

If you agree to be part of this study, ultrasound scanning will be performed on your abdomen to

measure the head, abdomen, and thigh bone of your foetus.

Risk to the Patient

Patient lying on the examination bed for longer period can cause unnecessary discomfort due to

the pressure exerted on both the aorta and inferior vena cava. Therefore, the examination must be

done quickly with precision.

Additionally, although there is no risk associated with the use of ultrasound waves, however the

principle of ALARA (AS LOW AS REASONABLE ACHIEVABLE) with respect to ultrasound

dose will be strictly adhere to.

Patient’s Right

Any patient has the right to partake or withdraw at any time during study. All participants will be

fairly treated equally with no patient paying for the examination throughout the period of the

study. Any ethical violation by the investigator can be reported to the SAHS Ethical and protocol

review committee, College of Health Sciences, University of Ghana.

All participants shall be identified by codes. The following under listed names who are members

of the Dissertation Advisory Team (DAT) can be contacted for any concerns you have with

respect to this study:


80

APPENDIX II INFORMED

CONSENT FORM

Department of Radiography, School of Biomedical and Allied Health Sciences, College of

Health Sciences, University of Ghana

Title of Project: Determining Best Regeressional Model in Predicting Foetal Weight in Philips

Clearvue 350 Ultrasound Equipment

Purpose of Research: In Partial Fulfilment of MSc Degree

Name of Researcher: EDEM ANASTASIUS KWAMI BUADY

Name of Supervisors: DR. SAMUEL OPOKU, DR. ANIM-SAMPONG CONFIDENTIALITY:

All data will be anonymously and confidentially handle.

I………………………………………………………………………. agree to take part in the

above research and I consent to my participation. I understand that my participation is entirely

voluntary and that there is no personal benefit that I will derive by participating in this study

If you have any concern about this study and wish to contact someone independently, you may

contact the supervisors below. SIGNATURE…………………………………..

DR. SAMUEL OPOKU DR. ANIM-SAMPONG

Dept. of Radiography Dept. of Audiology

SBAHS SBAHS

University of Ghana University of Ghana

P.O. Box KB 143 P.O. Box KB 143

Korle-Bu Korle-Bu

Tel: 0246909286/0207934650 Tel: 0207774000


tel:0246909286/0207934650

81

APPENDIX III

DATA COLLECTION SHEET

SECTION A: MATERNAL DEMOGRAPHIC INFORMATION

A. Code number………………………...

B. Age……………………………..years.

C. Height…………………….............cm

D. Weight………………………….....kg

E. Weight Difference………………...kg

SECTION B: FOETAL BIOMETRIC MEASUREMENTS

BPD…………………………………………..cm

AC………………………...………………….cm

HC……………………………………………cm

FL…………………………………………….cm


82

APPENDIX IV ETHICAL

CLEARANCE


83


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