FEMORAL MIDSHAFT HISTOMORPHOMETRIC PATTERNING:

IMPROVING MICROSCOPIC AGE AT DEATH ESTIMATES FROM

ADULT HUMAN SKELETAL REMAINS

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy

in the Graduate School of The Ohio State University

By

Megan E. Ingvoldstad, MA

Graduate Program in Anthropology

The Ohio State University

2012

Dissertation Committee:

Dr. Sam Stout, Advisor

Dr. Clark Spencer Larsen

Dr. Paul W. Sciulli

Dr. Julie Field

Copyright by

Megan E. Ingvoldstad

2012

ii

ABSTRACT

Use of microscopic techniques to estimate adult age at death is well established

within physical anthropology’s subfields of bioarchaeology and forensic anthropology. In

order to become a more robust approach, however, the long-standing problems of the

osteon population density (OPD) asymptote and high standard error of the estimate (SEE)

must be overcome.

Review of the microscopic age at death estimation literature revealed that

arbitrarily changing skeletal elements, histological variables, sample demographics, and

sampling locations have not allowed for accurate age estimation of individuals over ~50

years or reduced the standard error of age estimates. This investigation therefore began

with substantiated theory. All healthy, mobile femurs have in common: genetic

programming to establish initial size and shape; the developmental processes of

endochondral ossification, appositional growth, and modeling; biomechanical and

periosteal adaptation; cortical thinning and shape change during aging; mechanosensation

and mechanotransduction; and bone remodeling.

Building from this theoretical knowledge base, it was first hypothesized that

topographical variation in remodeling exists around human femoral midshaft periosteal

cortices that reflects the constraints of normal anatomical development, customary

biomechanical usage, and standard mechanobiological functioning. Second, it was

hypothesized regions of interest (ROIs) associated with the Imin second moment of area

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would exhibit the lowest remodeling as a result of minimal biomechanical loading. Third,

it was hypothesized remodeling at biomechanical ROIs would be histomorphometrically

more consistent than at anatomical ROIs due to femoral functional constraints related to

obligate striding bipedalism.

These hypotheses were tested by counting remodeling events at eight standardized

periosteal ROIs [four anatomical—A (anterior), P (posterior), M (medial), L (lateral)—

and four biomechanical—ImaxAnt, ImaxPost, IminMed, and IminLat] of 200 adult femoral midshaft

cross-sections originally harvested by M.F. Ericksen from George Washington University

dissecting room cadavers.

While no evidence was found for reduced remodeling at Imin ROIs or for more

consistent remodeling at biomechanical ROIs, 14 statistically significant differences were

found between ROI OPD medians indicating topographical variation in remodeling exists

around the femoral midshaft. Specifically, the lowest OPDs occurred at the Anterior ROI,

followed by the Posterior, IminMed, ImaxPost, ImaxAnt, IminLat, Medial, and Lateral ROIs.

Additionally, although the anterior femoral cortex has traditionally been sampled

for microscopic age at death estimation, here, the Anterior ROI was found to reach the

OPD asymptote at approximately 50 years of age and was associated with the highest

SEE. Alternatively, the Posterior ROI, the location possessing the second lowest median

OPD value, was found to be associated with the lowest SEE and showed no sign of

having reached the OPD asymptote. It is therefore suggested bioarchaeologists and

forensic anthropologists utilize the Posterior ROI for production of the most accurate and

precise microscopic age at death estimates from adult human skeletal remains.

iv

For my Family –

My Parents, Dorothy and David,

And My Sisters, Lauren and Kiera.

v

ACKNOWLEDGEMENTS

I am truly grateful to the people and institutions that contributed to the successful

completion of my PhD: Dr. Joyce Sirianni at The State University of New York at

Buffalo who first sparked my interest in physical anthropology, Dr. Susan Antón at New

York University who provided opportunities to apply my osteological knowledge, the

NYC Office of Chief Medical Examiner Forensic Anthropology Unit for collective

mentorship, my OSU Anthropology Department instructors for their encouragement to

become a well-rounded anthropologist, my dissertation committee for improving the

quality of this research beyond measure, and Dr. Sam Stout, a truly skilled advisor and

role model. This research could also not have been completed without access to the

Ericksen collection, for which I would like to thank Dr. Sam Stout and Dr. Christian

Crowder; interobserver error data collection, for which I would like to thank Victoria

Dominguez; and editorial assistance, for which I would like to thank George Tsiatis.

vi

VITA

2005……………… BA, summa cum laude, The State University of New York at Buffalo

2007…………………………………………………………... MA, New York University

2006–2008………………..…………… Editorial Associate, Journal of Human Evolution

2006–2008………Graduate Student Intern, NYC Office of Chief Medical Examiner FAU

2007–2008…Lead Osteologist, Oriental Institute Nubian Expedition, 4th Cataract, Sudan

2008–2011.……..Graduate Teaching Associate, The Ohio State University Anthropology

Department

2011………Forensic Science Academy Fellow, Joint Prisoners of War Missing in Action

Accounting Command, Joint Base Pearl Harbor-Hickam, Hawaii

2012………………………...Adjunct Faculty, Queens College Anthropology Department

2012……Forensic Anthropologist, Joint Prisoners of War Missing in Action Accounting

Command, Joint Base Pearl Harbor-Hickam, Hawaii

FIELDS OF STUDY

Major Field: Anthropology

Area of Emphasis: Physical Anthropology

Minor Field: Anatomy

vii

TABLE OF CONTENTS

Abstract……………………………………………………………………………………ii

Dedication………………………………………………………………………………...iv

Acknowledgements………………………………………………………………………..v

Vita………………………………………………………………………………………..vi

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

List of Tables……………………………………………………………………………viii

List of Figures…………………………………………………………………………….ix

Chapter 1: Introduction……………………………………………………………………1

Chapter 2: Literature Review…………………………………………………………….19

Chapter 3: Hypotheses…………………………………………………………………...55

Chapter 4: Materials and Methods……………………………………………………….62

Chapter 5: Results………………………………………………………………………..74

Chapter 6: Discussion and Conclusion…………………………………………………111

Bibliography……………………………………………………………………………117

Appendix A: Total Ericksen Sample Data……………………………………………...124

Appendix B: Research Sample Biomechanical Data…………………………………...135

Appendix C: Research Sample Cross-Sectional Images……………………………….140

Appendix D: Research Sample Cortical Thickness Data………………………………151

Appendix E: Research Sample Remodeling Data……………………………………...156

Appendix F: Research Sample Remodeling Data Images……………………………...161

viii

LIST OF TABLES

Table 1. Chronological Changes to Histologically Analyzed Skeletal Elements…………9 Table 2. Chronological Changes to Histological Variables Collected…..………………12 Table 3. Samples Used in Femoral Microscopic Age at Death Estimation Methods……13 Table 4. Definitions of Cross-Sectional Geometric Properties…………………………..31 Table 5. Anterior Compartment Muscles of the Thigh...…………………………….......43 Table 6. Medial Compartment Muscles of the Thigh...………………………………….45 Table 7. Posterior Compartment Muscles of the Thigh...………………………………..46 Table 8. Tests of Normality for the Cortical Thickness Measurements…………………75 Table 9. Correlations between Cortical Thickness Locations and Age………………….79 Table 10. Tests of Normality for the Biomechanical Variables…………………………82 Table 11. Correlations between Biomechanical Variables and Age……………………..82 Table 12. Intraobserver and Interobserver Error Raw Data……………………………...89 Table 13. Tests of Normality for the Observer Error Data………………………………90 Table 14. Test of Sphericity for the Observer Error Data………………………………..91 Table 15. Tests of Within-Subjects Effects for the Observer Error Data………………..91 Table 16. Intraobserver and Interobserver Error Test Descriptives……………………...92 Table 17. Tests of Normality for the Original OPD Data by ROI…...………………......94 Table 18. Tests of Normality for the OPD Data (Outliers Excluded) by ROI…………...96 Table 19. Significant Differences between ROI OPD Means (Outliers Excluded)…..….97 Table 20. Significant Differences between ROI OPD Means (Outliers Included)..........100 Table 21. Significant Differences between ROI OPD Medians………………………..102 Table 22. Correlations between ROI OPD Data and Age……………………………...107 Table 23. ROI OPD Linear Regression Data…………………………………………...108

Table 24. ROI OPD Linear Regression Data (Continued)……………………………..109

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LIST OF FIGURES

Figure 1. Microradiographs of the Femoral Cortex Over the Human Lifespan……….….3 Figure 2. Skeletal Elements Histologically Analyzed….…………………………………8 Figure 3. Histological Variables……………...………………………………………….11 Figure 4. Femoral Regions of Interest………….….…………………………………….15 Figure 5. Endochondral Ossification Process……………………………………………22 Figure 6. Bone Modeling………………………………………………………………...25 Figure 7. Forces Acting on Bones to Deform or Fracture Them………………………...28 Figure 8. The Relationship between Bone Stress and Strain…………………………….29 Figure 9. From Preosteoblast to Osteocyte………………………………………………37 Figure 10. The Structure of Bone………………………………………………………..39 Figure 11. Superficial Structures of the Thigh…………………………………………...41 Figure 12. The Anterior, Medial, and Posterior Compartments of the Thigh…………...42 Figure 13. Muscles of the Anterior Compartment of the Thigh…………………………43 Figure 14. Cross-Section of the Midshaft of the Femur…………………………………44 Figure 15. Muscles of the Medial Compartment of the Thigh…………………………..45 Figure 16. Muscles of the Posterior Compartment of the Thigh………………………...47 Figure 17. Neurectomy Effect on Tibia Shape…………………………………………..50 Figure 18. Remodeling Process………………………………………………………….54 Figure 19. The Lifecycle of the Femur…………………………………………………..55 Figure 20. Bar Chart: Research Sample Female-to-Male Ratio.…………………….......63 Figure 21. Bar Chart: Research Sample Black-to-White Ratio.………………………....63 Figure 22. Pie Chart: Research Sample Age Distribution...……………………………..64 Figure 23. Pie Chart: Research Sample Cause of Death Distribution…………………...64

x

Figure 24. Study Methodology………………………………………………………......65 Figure 25. Boxplots: Femoral Cortical Thickness Values at Standardized Locations…..75 Figure 26. Significant Pairwise Comparisons between Cortical Thickness Locations….77 Figure 27. Scatterplots: Linear Associations between Cortical Thicknesses and Age…..78 Figure 28. Scatterplots: Associations between Anterior, Medial, Posterior, and Lateral Cortical Thicknesses and Age……………………………………………...…80 Figure 29. Scatterplot: Linear Association between Cortical Area and Age.....................81 Figure 30. Scatterplot: Linear Association between Medullary Area and Age………….83 Figure 31. Scatterplot: Linear Association between Total Subperiosteal Area and Age...84 Figure 32. Scatterplot: Linear Association between Ix/Iy Ratio and Age………………..85 Figure 33. Scatterplot: Linear Association between Theta and Age ……………………87 Figure 34. Location of Imax over the Lifecycle of the Femur………………………….....87 Figure 35. Scatterplot: Linear Association between Zp and Age.......................................88 Figure 36. Boxplots: Intraobserver and Interobserver Error Data……...………………..90 Figure 37. Boxplots: All OPD Data Organized by Region of Interest………………......93 Figure 38. Boxplots: OPD Data (Outliers Excluded) Organized by Region of Interest…95 Figure 39. Bar Chart: Mean OPDs by Region of Interest (Outliers Excluded).…………98 Figure 40. Bar Chart: Mean OPDs by Region of Interest (Outliers Included)..………..101 Figure 41. Significant Pairwise Comparisons between ROI OPD Medians…………....103 Figure 42. Bar Chart: Median OPDs by Region of Interest (Kruskal-Wallis Test)..…...104 Figure 43. Scatterplots: Linear Associations between OPD and Age by ROI…...……..106 Figure 44. Scatterplots: 95% Confidence/Prediction Intervals for Age by ROI…….….110

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CHAPTER ONE: INTRODUCTION

Physical anthropologists need to produce both accurate and precise age at death

estimates from human skeletal remains. Bioarchaeologists, for example, require correct

skeletal age data to comment on population structure, life expectancy, fertility, and

mortality rates in the past and to ultimately compare population trends. Similarly,

forensic anthropologists must develop an age at death estimate from unidentified skeletal

remains to eventually associate them with a missing individual of known chronological

age. In both cases, imprecise and inaccurate age estimates are detrimental: the

bioarchaeologist misunderstands the adaptive success of a past population, and the

forensic anthropologist fails to make an identification.

Accurate and precise age estimation is especially problematic for adult human

skeletal remains. Traditionally, physical anthropologists have assessed the degeneration

of macroscopic skeletal structures, such as the fourth sternal rib end (Iscan and Loth,

1986), pubic symphysis (Brooks and Suchey, 1990), and the auricular surface (Lovejoy et

al., 1985) to estimate adult age at death. The skeletal elements required to perform

macroscopic age analyses, however, ―are often missing or obliterated in fragmented,

eroded, or incomplete skeletons‖ (Kerley, 1965: 149), frequently preventing use of such

techniques. Additionally, as qualitative indicators of adult age, ―the accuracy of the

estimate [resulting from application of macroscopic techniques] depends greatly on the

experience of the examiner‖ (Kerley, 1965: 149).

2

As early as 1911, Balthazard and Lebrun recognized the need for an adult age at

death estimation technique based on quantitative traits that could be utilized even when

only fragments or degraded bone were available—development of such a technique

would circumvent the issues of poor preservation and observer experience. Thus, when

Jowsey (1960: 215; Fig. 1) demonstrated microscopic biological changes in the femoral

midshaft cortex were broadly correlated with chronological age, within five years,

physical anthropologist Ellis R. Kerley (1965) provided linear regression equations for

quantitatively correlating microscopic osseous data with adult age at death. Kerley (1965:

162) further examined femoral specimens 500–5000 years old from the Philippines,

Aleutian Islands, Virginia, and Florida to test the applicability of his proposed

microscopic method on remains exposed to a variety of taphonomic conditions. He found

all slides sufficiently clear and detailed for microscopic analysis, prompting its use in

bioarchaeological paleodemographic reconstruction (see Ubelaker, 1974: 53–58).

Later, forensic anthropologists also incorporated and further developed

microscopic methods for estimating adult age at death in an effort to assist the medico-

legal community. For example, following Kerley (1965), Stout (1986) provided an

equation for estimating age at death from the ribs, Stout and Paine (1994) a method for

using the rib and clavicle together, Stout and colleagues (1996) a revised clavicle

formula, and Cho and colleagues (2006) ancestry dependent equations to predict age at

death from the ribs. The ribs and clavicle were specifically chosen for forensic

microscopic analysis because they are easily accessed during routine autopsy, and

because they are typically removed from unidentified remains as part of forensic

anthropologists’ standard macroscopic age assessment procedure.

3

Figure 1. Micro-radiographs of the femoral cortex of a (a) 2 ½ -year-old male; (b) 17-

year-old male; and (c) 77-year-old female (x20). Modified from Jowsey (1960: 215) with

permission from Lippincott Williams & Wilkins.

4

Thus, use of microscopic, or histological, techniques to estimate adult skeletal age

at death is well established within physical anthropology’s subfields of bioarchaeology

and forensic anthropology. Just like the macroscopic techniques that preceded them,

however, microscopic approaches for estimating skeletal age at death also contain

challenges that have discouraged numerous researchers. Some of these challenges are

unavoidable aspects of histological research, such as the great expense incurred for

necessary embedding, grinding, sectioning, and microscopic equipment; the intensive

time and labor required to produce cross-sections for microscopic analysis; and the often

destructive sampling techniques (Kemkes-Grottenhalter, 2002). There are three long-

standing problems, however, that must be overcome to ensure the future of the field: high

observer error, the osteon population density (OPD) asymptote, and relatively high

standard error of the estimate (SEE).

To expand, because histological methods of estimating age at death are

quantitative, or largely based on counting of discrete traits, the experience level of the

observer should be unimportant. Lynnerup and colleagues (1998), however, found

intraobserver and interobserver error to be quite high. To test and document error rates in

histological age at death analysis, they photographed 29 anterior region femoral midshaft

sections from the Institute of Forensic Pathology at the University of Copenhagen and

covered each printed photograph with a clear plastic sheet. They then requested three

experienced histomorphologists count secondary osteons, Haversian canals, and osteon

fragments on two occasions approximately two months apart. When intraobserver error

was quantified by plotting difference between the two counts against the mean, there was

considerable lack of agreement with discrepancies of up to 14 for osteons, 13 for

5

Haversian canals, and 49 for osteon fragments. Interobserver discrepancies were of

almost the same magnitude: while osteons were reliably identified by all observers, the

limits of agreement in counts of fragments and Haversian canals were wide, indicating

difficulty in reliably assessing such structures (Lynnerup et al., 1998).

This documented high observer error rate likely stems from a lack of standardized

definitions for commonly encountered osseous histological structures. Robling and Stout

(2008), for example, have noted how histomorphologists differentially define the basic

structure of an osteon: Kerley (1965) counted an osteon when greater than or equal to 80

percent of the original lamellar area was present in association with an intact Haversian

canal, Stout (1986) required greater than or equal to 90 percent of a Haversian canal be

present, while Ericksen (1991) required 100 percent of the Haversian canal in order to be

counted. It is understandable that considerable observer error results when current

researchers differentially adhere to different structural definitions. Heinrich and

colleagues (2012) have therefore standardized the definitions of histological structures

commonly quantified for microscopic age at death estimation (intact and fragmentary

secondary osteons) in order to reduce future observer error.

The OPD asymptote and high SEE, however, are histological aging problems

without obvious solutions, and researchers have had less success resolving them. The

OPD asymptote is the age estimation limitation whereby ―as total osteon creations

accumulate in diaphyseal cross sections, some new osteons begin to remove all evidence

of some preexisting ones, and eventually the visible osteons plus fragments of partly

replaced ones tend to reach an asymptotic value and stay there during further creations‖

(Frost, 1987b: 240). As the microscopist only sees and measures visible osteons and

6

fragments, not missing ones, omitting the latter causes age underestimations. Although

different bones of the human skeleton likely reach the OPD asymptote at varying ages

(Amprino and Marotti, 1964; Frost et al., 1960; Marotti, 1976) depending on new osteon

creation rate, osteon size, and cortical area (Cho et al., 2002: 17), Wu and colleagues

(1970) have estimated it occurs around 60 years of age in the human rib. This suggests

estimating age of individuals over ~60 years with microscopic methods is impossible.

Frost (1987b) provided an algorithm for estimating missing osteons in an attempt

to adjust for the OPD asymptote. Stout and Paine (1994), however, tested this algorithm

on 44 autopsy rib samples and demonstrated estimates produced by it were in reasonable

agreement with age-matched tetracycline-based values, except for those individuals

beyond their fifth decade of life. This finding confirmed that estimating age in older

individuals is problematic, and it remains so today: individuals greater than or equal to 50

are often grouped into the single broad cohort of 50 years and older (Cho and Stout,

2003), a significant setback for bioarchaeologists comparing population structures and

forensic anthropologists attempting to age unidentified mature skeletal remains.

A final challenge is that age estimates produced from histological techniques are

associated with relatively high standard error, or inaccuracy of the prediction, due to

human variation in the aging process. Kerley (1965), for example, generated linear

regression equations that quantitatively correlated the microscopic variables of femoral,

tibial, and fibular osteons, osteon fragments, circumferential lamellar bone percentage,

and non-Haversian canals with adult age at death. These age predicting equations,

however, include standard errors that range from ± 5.27 years for fibular osteon

fragments to ± 13.85 years for femoral non-Haversian canals. Further, the standard error

7

of an age estimate generated for an independent sample could be even greater. An age

range of 35–45 or 26–54 years produced from a 40-year-old point age estimate is again of

limited utility to bioarchaeologists comparing populations containing middle-aged and

mature adults, and forensic anthropologists hoping to narrow a missing persons list.

Retrospective review of histological age at death estimation methods to the

present reveals how arbitrarily changing the (1) selected skeletal element analyzed, (2)

histological data type collected, (3) sample demographics, and (4) regions of interest

(ROIs) microscopically viewed will not provide the solutions to eliminating the pervasive

issues of the OPD asymptote and high SEE.

To expand, because various bones of the dog skeleton reach the OPD asymptote

at different ages (Marotti, 1976), skeletal element subjected to microscopic analysis for

age at death estimation has been considered as a factor influencing the adult human OPD

asymptote and SEE. Kerley (1965: 162; Fig. 2f–h), for example, originally chose to

analyze ―any or all of the major long bones of the leg [femur, tibia, and fibula],‖ since

they could be ―articulated with the axial skeleton through the hip joint to establish

continuity with the spine and skull.‖ When the difficulties of aging older individuals and

high standard error associated with his method were recognized, however, Singh and

Gunberg (1970) departed from Kerley’s original method and microscopically analyzed

mandibular in addition to tibial and femoral thin sections (Fig. 2b). Similarly, Thompson

(1979; Fig. 2d) sampled humeri and ulnae in addition to femurs and tibias, Cool and

colleagues (1995; Fig. 2a) occipital bones, Stout and colleagues (1996; Fig. 2c) the

clavicle, and Cho and colleagues (2002; Fig. 2e) ribs.

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Figure 2. Skeletal elements histologically analyzed include: (a) occipital, (b) mandible,

(c) clavicle, (d) humerus, (e) sixth rib midshaft, (f) femur, (g) tibia, and (h) fibula.

Modified from Robling and Stout (2008) with permission from John Wiley and Sons.

Stout and colleagues (1996: 140) suggested clavicles are subjected to lower

biomechanical loading than long bones, and are thus more appropriate for analysis, and

Cool and colleagues (1995: 789) indicated no accurate method exists for aging the

isolated and edentulous adult cranium. Beyond these considerations, however, no

anatomical, biomechanical, or mechanobiological theory was typically provided for why

specific bones selected for analysis might produce better results than Kerley’s (1965)

method, and for the most part, they did not: analyzing new skeletal elements has not

provided a solution to the OPD asymptote. Cho et al. (2002: 17), for example, still state

―changes in bone remodeling rates in older adults are not well understood, and, therefore,

make histological age estimation less reliable for individuals over 60 years.‖ Analysis of

new skeletal elements has also not lowered the SEE (Table 1): rather, each technique

following Kerley’s (1965) contains greater or equivalent error excepting the Singh and

Gunberg (1970) method, which misleadingly appears quite accurate because its age

9

predicting equations are based on a small sample of males. Similarly, a mean absolute

difference between reported and predicted ages of 5.5 years extended by Stout et al.

(1996) is encouraging, but includes a maximum absolute age difference of 22.2 years.

Table 1. Chronological Changes to Histologically Analyzed Skeletal Elements for

Microscopic Age at Death Estimation.

Method Year New Elements SEE

Kerley 1965 Femur, Tibia, Fibula ± 5.27–13.85

Singh &

Gunberg

1970 Mandible ± 2.55–3.83

Thompson 1979 Humerus, Ulna ± 6.2–10.6

Cool et al. 1995 Cranium (Occipital) Unreported, but ―the amount of random

variation in the parameters

examined preclude [occipital] use for

accurate age estimation‖ (789)

Stout et al. 1996 Clavicle Mean absolute difference between

reported and predicted ages is 5.5 years

Cho et al. 2002 Rib Mean absolute difference between

reported and predicted ages is 11.8 years

A second factor that has been considered to relate to the problems of the OPD

asymptote and high SEE is the type of histological data collected. For example, Kerley

(1965) originally documented the four variables of osteon number (to be counted, an

osteon has 80 percent or more of its area easily distinguishable and canal intact; Fig. 3e),

number of old osteon fragments (Fig. 3g), percentage of circumferential lamellar bone

(Fig. 3c), and non-Haversian canal number (Fig. 3d). Once tabulated, the mean value for

each variable was plotted against known age. All variables in each bone significantly

correlated with age, but often with high standard error and increasing inaccuracy for older

10

adults. Ahlqvist and Damsten (1969), however, suggested it was difficult to distinguish

osteons from osteon fragments given the 80 percent definition and to estimate

circumferential lamellar bone in a circular visual field. Their follow-up method for

estimation of age at death therefore required estimating percent Haversian bone inside a

superimposed square reticule. Because osteon fragments are often cut obliquely,

however, Singh and Gunberg (1970) suggested documenting total number of osteons (for

their purposes, an osteon is defined as having a complete Haversian canal), average

number of lamellae per osteon (Fig. 3h), and average Haversian canal diameter (Fig. 3h).

Frustrated with largely incommensurable correlations of age with different

histological variables, Thompson (1979) collected 19 types of histomorphological data to

find the variable or combination of variables that would estimate age at death in skeletons

with the lowest SEE and highest coefficient of determination. Recognizing the existence

of skeletal incoherence, however, Drusini’s (1987) method required finding number of

osteons (where an osteon must be 80 percent or more complete) and average number of

secondary osteons across multiple fields of a bone surface. Taking a more metric

approach, Samson and Branigan’s (1987) method called for collecting data including

mean cortical thickness (Fig. 3f), mean Haversian canal diameter (tabulated from a set of

30 canals), number of Haversian canals, and morphological character, the product of the

number of Haversian canals and the mean Haversian canal diameter. Ericksen (1991)

documented the traditional variables of secondary osteons (for whom an osteon must

have 100 percent of its Haversian canal intact), osteonal fragments, non-Haversian

canals, and unremodeled circumferential bone, but also new variables such as numbers of

resorption spaces (Fig. 3a) and type II osteons (Fig. 3b), and average percentages of

11

osteonal and fragmental bone. Finally, in the newest method for histological age

estimation, Crowder and Dominguez (2012) collected osteon and fragmentary osteon

counts and densities (an osteon has an intact Haversian canal), OPD, mean osteonal

cross-sectional area, mean anterior cortical width, and surface area.

These researchers have eased some difficulties in collecting histological data and

provided new, creative histological variables: Samson and Branigan’s (1987) metric data

types, for example, are ideal when bone is not sufficiently preserved for structural counts.

Again, however, anatomical, biomechanical, or mechanobiological theory is not typically

incorporated into why newly proposed variables might perform better than simple counts

of remodeling events in accurately estimating age at death across all phases of adulthood,

and for the most part, they have not: this second approach of changing variable types has

also not allowed for age estimation over ~50 years or reduced the error associated with

all age estimates (Table 2). The Singh and Gunberg (1970) results are again misleading

as they are based on a small sample of males, and Drusini’s (1987) results stem from

analysis of only 20 young modern Italians.

Figure 3. Histological variables. (a) Resorptive bay, (b) type II osteon, (c) circumferential

lamellar bone, (d) primary osteon, (e) secondary osteon, (f) cortical thickness, (g) osteon

fragment, and (h) lamellae number per osteon [#s] and Haversian canal diameter [line].

12

Table 2. Chronological Changes in Histological Variables Collected for

Microscopic Age at Death Estimation.

Method Year Variables SEE

Kerley 1965 Osteons, osteon fragments, percent

circumferential bone, non-Haversian canals

± 5.27–

13.85

Ahlqvist &

Damsten

1969 Percent Haversian bone ± 6.71

Singh &

Gunberg

1970 Osteons, lamellae number per osteon, average

Haversian canal diameter

± 2.55–

5.01

Thompson 1979 Cortical thickness, core weight, cortical bone

density, mineral content, mineral index, aggregate

osteon lamellae area, aggregate Haversian canal

area percent, osteon area, secondary osteon

number, Haversian canal number, individual

osteon lamellae area percent, individual

Haversian canal area percent, aggregate osteon

perimeter, aggregate Haversian canal perimeter,

individual osteon perimeter, individual Haversian

canal perimeter, ratio I, ratio II, ratio III

± 6.2–10.6

Drusini 1987 Osteons, average number of secondary osteons

per mm2

± 3.93

Samson &

Branigan

1987 Mean cortical thickness, mean Haversian canal

diameter, Haversian canals per unit area

± 6.0 (m),

± 16.0 (f)

Ericksen 1991 Osteons, type II osteons, osteonal fragments,

resorption spaces, non-Haversian canals, percent

circumferential, osteonal, fragmental bone

± 10.1–

12.2

Crowder &

Dominguez

2012 Intact secondary osteons, intact secondary osteon

density, fragmentary secondary osteons,

fragmentary osteon density, OPD, mean osteonal

cross-sectional area, mean anterior cortical width,

surface area

± 12.87

(m),

± 10.49 (f)

Since sex, ancestry, and genetic and metabolic disorders have been shown to

affect histological age estimates (see Robling and Stout, 2008), a third factor that has

been considered to relate to the problems of the OPD asymptote and the SEE is influence

of sample composition (Table 3).

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Table 3. Sample Demographics and Sizes Used in Femoral Microscopic Age at

Death Estimation Methods.

Method Year Sample Sample Demographics SEE

Drusini

1987

n = 20

19–50 years (Avg. is 28.7 years) ± 3.93

Unstated numbers of males/ females

Modern Italians

No pathological condition data

Ahlqvist &

Damsten

1969 n = 20 ―Of known age‖ (Avg. is 55 years) ± 6.71

Unstated numbers males/ females

Unstated ancestry Unstated ancestry

No pathological condition data

Singh &

Gunberg

1970 n = 33 39–87 years (Avg. is 62.3 years) ± 3.24–

5.01 All males

US cadavers, but no ancestry data

No pathological specimens used No pathological specimens used

Samson &

Branigan

1987 n = 58 16–91 years ± 6.0 (m),

± 16.0 (f) 31 males, 27 females

Caucasians Caucasians

No pathological condition data

Kerley 1965 n = 67 0–95 years (Avg. is 41.6 years) ± 9.4–

13.95

43 males, 17 females, 7 unknown

Unknown dist. of Whites and Blacks

No pathological specimens

No pathological specimens

Thompson 1979 n = 116 64 males (30–97, Avg. is 71.5 years) ± 7.1–8.6

52 females (43–94, Avg. is 71.9 years)

New England Whites

Healthy and pathological included

Crowder &

Dominguez

2012 n = 328 172 males (15–97, Avg. is 48.4 years) ± 12.87

(m),

± 10.49 (f) 156 females (19–96, Avg. is 54.2 years)

Ericksen, Kerley, and FAU collections

No pathological condition data No pathological condition data

Ericksen 1991 n = 328 174 males (16–97, Avg. is 61.2 years)

154 females (14–94, Avg. = 64.6 years)

± 10.1–

12.2 154 females (14–94, Avg. is 64.6 years)

1 US Asian, 251 US Whites, 12 US

Blacks, 5 Chilean Hispanics, and 58

Dominican blacks

Various pathologies included

14

Table 3 demonstrates how utilizing more defined samples that contain less of all

modern human variation, such as only males (e.g., Singh and Gunberg, 1970), individuals

less than 50 years of age (e.g., Drusini, 1987), individuals all belonging to one population

(e.g., Drusini, 1987), or only healthy individuals (e.g., Samson and Branigan, 1987)

generally reduces the SEE. Age predicting equations produced from population-specific

approaches, however, are often only accurate for the populations they were created from,

and again, do nothing to negate the OPD asymptote. Alternatively, techniques developed

from the largest, most diverse samples produce the most substantial error because they

contain greater modern human variation in the aging process, resulting in loss of value.

Finally, review of a last group of researchers who have focused specifically on

microscopic age estimation from the femur elucidates a fourth factor that has been

considered to influence the OPD asymptote and SEE: the ROI viewed during microscopic

analysis. To expand, Kerley (1965: 162) specifically chose midshafts of long bone

diaphyses because they were anatomically identifiable, survived most conditions of burial

or injury better than bone epiphyses, and because approximately three inches of their

midshafts were microscopically homogenous. He also found that structural changes in the

outer third of long bone cortices more closely reflected total life span of the individual

than the middle or inner third, setting the standard for analysis of microscopic fields

along the bone’s periosteal edge. Finally, he chose sampling locations from the anterior,

posterior, medial, and lateral anatomical axes of each cross section that were ―fairly

representative of the particular anatomic area of the section being examined,‖ (Kerley,

1965: 154; Fig. 4a) and analyzed each to ―minimize the likelihood of basing the age

estimate on a single atypical field‖ (Kerley, 1965: 162).

15

Figure 4. ROIs sampled by: (a) Kerley (1965), (b) Ahlqvist and Damsten (1969), (c)

Singh and Gunberg (1970), (d) Thompson (1979), (e) Drusini (1987), (f) Samson and

Branigan (1987), (g) Ericksen (1991), and (h) Crowder and Dominguez (2012). Modified

from Robling and Stout (2008) with permission from John Wiley and Sons.

Ahlqvist and Damsten (1969; Fig. 4b) also selected the outer third of the femoral

midshaft cortex for analysis. These authors, however, shifted the ROIs to avoid sampling

at the linea aspera. Singh and Gunberg (1970) similarly utilized the periosteal third of

femoral midshaft sections, but analyzed only two microscopic fields at random from each

anterior quadrant (Fig. 4c), as opposed to the four field techniques of Kerley (1965) and

Ahlqvist and Damsten (1969). Likewise, Thompson (1979; Fig. 4d) analyzed periosteal

surfaces of femoral midshafts, but a specifically constructed bone corer attached to a

high-powered Dremel tool was used to obtain four adjacent 0.4 centimeter cortical bone

samples from each femur’s anterior surface. Drusini (1987) also microscopically

analyzed fields found along the periosteal border of femoral midshafts. Unlike earlier

16

methods, however, 10 to 20 readings were taken at regular intervals along the entire

femoral circumference with the exclusion of the linea aspera (Fig. 4e). Samson and

Branigan (1987) alternatively removed one-centimeter squares of bone that extended

across entire anterolateral and anteromedial femoral midshaft cortices (Fig. 4f) for

microscopic analysis. Ericksen (1991) analyzed five adjacent periosteal fields from the

anterior wedge of midshaft femoral cortices (Fig. 4g), and most recently, Crowder and

Dominguez (2012; Fig. 4h) sampled alternating fields in 10 columns that extend from the

periosteal to endosteal surface of the anterior femoral midshaft cortex.

Overall, a trend towards selecting anterior regions of interest is apparent. This

practice reduces destructive sampling procedures (e.g., Thompson, 1979; Ericksen, 1991)

and prevents sampling the area around the linea aspera because ―in this part of the bone

there seems to be a somewhat greater variation in osteons and osteon fragments not

correlated to age than in other parts, possibly because of the powerful muscle insertions

on the femoral crest‖ (Ahlqvist and Damsten, 1969: 208). Beyond those considerations,

why specific locations chosen for analysis might produce better results than Kerley’s

(1965) is rarely addressed. One exception is Crowder and Dominguez (2012) who

explained, following the work of Iwaniec and colleagues (1998), that 10 columns

extending from periosteal to endosteal surfaces account for 95 percent of remodeling

variability within the femoral anterior cross-section. Another partial exception is Drusini

(1987: 170) who chose his 10 to 20 sampling locations ―in consideration of the notable

variability in the density of the bone microstructures along the circumference of a given

section.‖ No explanation is offered, however, for that noted variability in bone

microstructure density. Regardless, this approach, like the others, has not allowed for age

17

estimation of individuals over ~50 years or reduced the error of age estimates (Table 3).

In order to become a more robust approach, the microscopic age at death

estimation field must resolve the inaccuracy and imprecision associated with generated

age estimates. As demonstrated above, arbitrarily changing skeletal elements, histological

variables, sample compositions, and sampling locations without theoretical

considerations has been unsuccessful. This failure is likely due to collective use of

inductive research plans, which, by design, begin with specific observations (e.g., number

of remodeling events viewed in a femoral ROI) and lead to constructions of general,

probable hypotheses based on observed regularities [e.g., Age = 61.642 + (0.560 × OPD)

± 11.542 years]. Therefore, conclusions drawn with inductive reasoning involve a degree

of uncertainty and cannot explain why specific observations are present (Trochim and

Donnelly, 2007: 17).

Deductive approaches, however, have never been used to avoid the OPD and SEE

histological problems. This investigation therefore begins with substantiated theory. All

healthy, mobile femurs have in common: genetic programming to establish initial size

and shape; the developmental processes of endochondral ossification, appositional

growth, and modeling; biomechanical and periosteal adaptation; cortical thinning and

shape change during aging; mechanosensation and mechanotransduction; and bone

remodeling. Building from this theoretical knowledge base, it is first hypothesized that

topographical variation in remodeling exists around human femoral midshaft periosteal

cortices that reflects the constraints of normal anatomical development, customary

biomechanical usage, and standard mechanobiological functioning. Second, it is

hypothesized ROIs associated with the Imin second moment of area will exhibit the lowest

18

remodeling as a result of minimal biomechanical loading. Third, it is hypothesized

remodeling at biomechanical ROIs will be histomorphometrically more consistent than at

anatomical ROIs due to femoral functional constraints related to obligate striding

bipedalism. These hypotheses will be tested by counting remodeling events from eight

standardized periosteal ROIs [four anatomical —A (anterior), P (posterior), M (medial),

L (lateral)—and four biomechanical—ImaxAnt, ImaxPost, IminMed, and IminLat] of 200 adult

femoral midshaft cross-sections.

Since all reasoning employed for development of these hypotheses is valid, and

all premises are true, the conclusions produced will be sound (Trochim and Donnelly,

2007: 16–17). With conclusions that confirm the hypotheses, this investigation will

uncover ROIs that remodel consistently despite modern human variation in the aging

process so as to reduce the SEE, and ROIs that remodel slowly so that the OPD

asymptote is reached at an age above ~50 years. Discovery of such sampling locations

will allow for more accurate and precise age estimations from adult human skeletal

remains by bioarchaeologists and forensic anthropologists.

19

CHAPTER TWO: LITERATURE REVIEW

The adult femoral cortex ―comprises a collection of lamellae exhibiting an array

of different ages‖ (Robling and Stout, 2008: 150). To identify patterns in this cortex that

can be exploited for improved accuracy in histological aging, theoretical knowledge is

required of all processes and influences common to all healthy, mobile adults that

contribute to attainment, maintenance, and degeneration of femoral size and shape:

genetics, endochondral ossification, modeling, environmental factors, physiological and

periosteal loading, mechanosensation and mechanotransduction, periosteal and endosteal

apposition and resorption, and bone remodeling.

A. GROWTH AND DEVELOPMENT OF THE FEMUR

Growth and development of the femur result from both environmental factors,

such as nutrition, and the intertwined processes of genetic programming, endochondral

ossification, bone apposition, and bone modeling. Specific genes switching on and off

influence initial femoral size and shape. After initial formation, endochondral ossification

provides the mechanism for longitudinal bone growth, appositional growth the system for

diaphyseal diameter increase, and modeling the means for moving growing bone through

tissue space to its adult location. If the growth and development environment is poor,

however, those processes are downregulated until an adequate environment is restored.

20

I. Genetics of Femoral Development

In the developing fetus, a four-step process determines initial femoral

materialization, shape, and size: First, previously dispersed populations of cells migrate

to the site of future femoral skeletogenesis. Next, epithelial-mesenchymal interactions

occur. This then results in formation of condensations, or membranes that precede

cartilaginous and osseous elements. Finally, the condensations differentiate into

cartilaginous or osseous tissues (Hall and Miyake, 2000: 138).

Hall and Miyake (2000: 138) note that the third phase of skeletogenesis—

condensation—is the earliest stage during organ formation when tissue specific genes are

upregulated: specifically, ―extracellular matrix molecules, cell surface receptors, and cell

adhesion molecules, such as fibronectin, tenascin, syndecan, and N-CAM, initiate

condensation formation and set condensation boundaries. Hox genes (Hoxd-11-13) and

other transcription factors (CFKH-1, MFH-1, and osf-2) modulate the proliferation of

cells within condensations. Cell adhesion is ensured indirectly through Hox genes (Hoxa-

2, Hoxd-13) and directly via cell adhesion molecules (N-CAM and N-cadherin).

Subsequent growth of condensations is regulated by BMPs, which activate Pax-2, Hoxa-

2, and Hoxd-11 among other genes. Growth of a condensation ceases when Noggin

inhibits BMP signaling, setting the stage for the next stage of skeletal development,

namely overt cell differentiation‖ of chondroblasts and osteoblasts.

II. Intramembranous and Endochondral Ossification

In a few areas of the skeleton like the flat bones of the skull and portions of the

clavicle and scapula, condensations differentiate directly into bone-forming osteoblasts

21

though a process called intramembranous ossification. This straightforward process is

atypical, however, because most condensations in the rest of the body, including the

femoral condensations, form cartilaginous skeletons prior to calcified bones through a

less direct process known as endochondral ossification (Kronenberg, 2003; Fig. 5).

Endochondral ossification provides the mechanism for femoral growth in length

until its completion in adolescence, and occurs over three rough stages of transformation:

chondrogenesis, angiogenesis, and osteogenesis. In chondrogenesis, or the development

of bone precursors, the condensations at their embryonic locations differentiate into

chondrocytes, the primary cell type of cartilage, which begin synthesizing cartilage

matrix. Through secretion of angiogeneic factors, chondrocytes next induce peripheral

blood vessels to enter the synthesized cartilage (Colnot, 2005). Behind the vascularized

blood vessels are osteoblasts, osteoclasts, and hemopoietic bone marrow cells, forming an

ossification front. Using the cartilage matrix as a scaffold, osteoclasts remove obstructive

transverse struts of cartilage while osteoblasts begin laying down true bone matrix,

starting in the primary central spongiosa of the femur and expanding outwards. Without a

means of nutrient diffusion, the chondrocytes undergo cell death (Nuzzo et al., 2003).

While bone is being formed at the primary center of ossification, the distal ends of

the femur are undergoing continued cycles of chondrocyte proliferation, hypertrophy,

vascular invasion, and osteoblast activity to create the epiphyses, or secondary centers of

ossification (Kronenberg, 2003; Mackie et al., 2008). Not all cartilage, though, is

replaced by bone. Longer-lasting growth cartilage is found at two locations in each end of

a developing femur: the growth plates where longitudinal growth takes place, and the

articular-epiphyseal growth cartilages (AEGCs) where the epiphyses grow and take form.

22

At these two locations, related to distance from the encroaching ossification front,

chondrocytes are arranged in morphologically distinct zones reflecting their function. The

zone furthest from the ossification front consists of small and round resting chondrocytes.

Adjacent is the zone of proliferation where multiplying chondrocytes become flattened as

they are packed into multicellular clusters. Proliferating cells eventually hypertrophy,

increasing their volume dramatically, and excrete extracellular matrix, which when

mineralized, causes elongation of bone. This process of cartilage growth and bone

replacement continues through adolescence when proliferative potential of the

chondrocytes seems to become exhausted. At this point, the mineralization front

overtakes the growth plate and AEGC, obliterates them, and fuses metaphysis to

diaphysis and epiphysis. Only the permanent cartilage at each end of the femur is

maintained for proper knee and ankle joint functioning (Mackie et al., 2008).

Figure 5. Endochondral ossification process. Reprinted from Mackie and colleagues

(2008) with permission from Elsevier.

23

III. Appositional Growth

If the femur grew in length without increasing in width, it would become unstable

and break. An increase in femoral length via endochondral ossification must therefore be

closely matched by femoral appositional growth (Rauch, 2007: S138). During apposition,

osteoprogenitor cells on the periosteal surface differentiate directly into osteoblasts that

secrete collagen fibers and organic molecules to add to the bone‘s exterior. Organized

parallel sheets of primary lamellar bone are eventually deposited on the bone surface so

that the bone continues to increase in diameter. Where there are peripheral blood vessels,

mineralized tissue ridges enlarge to create deep pockets that eventually trap the vessels

inside bone, forming primary osteons (Gartner and Hiatt, 2007; Robling and Stout, 2008).

Radiographic studies of growing individuals show periosteal apposition rate ―is

rapid during early life but then continuously slows until it reaches a nadir during early

school age. This is followed by a pubertal peak, after which periosteal growth (almost)

comes to a standstill‖ (Rauch, 2007: S139). Orwoll (2003: 950), for example, documents

periosteal bone formation throughout adulthood, ―albeit at a slower rate than during

growth.‖ Rates are bone-specific, as wider bones must have greater periosteal apposition:

―during male puberty the estimated peak periosteal apposition rate of the metacarpal is

~0.5 µm/day, but it is close to 2 µm/day at the midshaft humerus‖ (Rauch, 2007: S139).

Appositional rates also reflect mechanical usage: ―in 3-month-old infants the humerus

grows in width one-third faster than the femur. At one year, the two bones expand at

approximately the same rate, whereas at 33 months, periosteal apposition is almost four

times as fast at the femur as it is at the humerus‖ (Rauch, 2007: S139).

24

IV. Modeling

Modeling is the dynamic process that ―regularly and rapidly alters the size, shape,

relative position, and age of bone tissue‖ appositionally deposited during femoral

development (Robling and Stout, 2008: 150). Modeling of accumulating osseous tissue is

necessary so that evolving mechanical loads of the lower limb can be effectively resisted

(Robling and Stout, 2008: 149–150). New bone layers are therefore laid down under

certain regions of the femoral periosteum through osteoblast-induced apposition with

concomitant osteoclast-induced resorption under other regions of the femoral periosteum.

Similarly, bone is deposited at certain regions of the femoral endosteal surface while

endosteal bone is simultaneously removed from other locations (Gartner and Hiatt, 2007:

149). This complementary relationship ensures a moderately constant ratio between bone

addition and bone loss (Scheuer and Black, 2000). As a result ―growing bones largely

retain their general architectural shape from the beginning of bone development in the

fetus to the end of bone growth in the adult‖ (Gartner and Hiatt, 2007: 149).

Robling and Stout (2008: 150; Fig. 6), for example, illustrate how modeling

occurring in the sixth rib removes bone from internally-facing periosteal and endosteal

surfaces and concurrently deposits bone on externally-facing periosteal and endosteal

surfaces so that it retains its general architecture. Because bone formation and resorption

are not tethered, however, as formation begins to outpace resorption and cross-sectional

area increases, the rib also moves through tissue space, or is modeled.

25

Figure 6. Bone modeling. Modified from Robling and Stout (2008: 150) with permission

from John Wiley and Sons.

V. Environmental Effects on Bone Growth and Development

Growth in femoral length and width are generally positively correlated with age

through adolescence, but when an individual is malnourished or ill, growth may be

downregulated to conserve nutrients for vital functions (Kayemba-Kay‘s and Hindmarsh,

2006). If downregulation occurs, the femur may not achieve full cortical thickness (Mays

et al., 2009), and the chondrocytes at growth plates essential for longitudinal expansion

are suppressed. When the growth-inhibiting condition is resolved (for example, when an

undernourished child has regained 85 percent of his or her weight for height), leptin, a

26

hormone that regulates size of adipose tissue masses, communicates general energy levels

to the GH-thyroid-IGF-1 axis to alter systemic hormone secretion levels. Leptin receptors

at local growth plates then resume chondrocyte proliferation and differentiation,

ultimately causing catch-up growth. Catch-up growth is limited, however, by genetically

predetermined growth plate potential. Further, if the growth-inhibiting condition is not

treated until later in skeletal maturation, a net loss in stature and cortical thickness may

occur (Kayemba-Kay's and Hindmarsh, 2006; Mays et al., 2009).

B. BIOMECHANICAL ADAPTATION OF THE FEMUR

During and following completion of femoral growth and development, external

physiological forces also act on the bone to influence its cortical area and distribution.

Ruff et al. (2006: 485) have extended the term ―bone functional adaptation‖ (BFA) to

clarify how bone is adapted to its mechanical environment during life. Specifically, bone

morphology reflects its mechanical usage because increased bone strain through an

increase in body size or muscle activity leads to deposition of more bone, while

decreased bone strain caused by inactivity leads to resorption of bone. Maintenance of

optimum customary strain levels is the goal, as bones must provide adequate strength

with the least material. Femurs are ―particularly subject to this constraint, since they have

to be strong enough to support body weight, but they have to be light enough that they are

not energetically too costly to move‖ (Drapeau and Streeter, 2006: 403).

Thus, to elucidate mechanical usage through analysis of morphology, femoral

diaphyses are treated like engineering beams, and their rigidity and strength are

estimated. Rigidity is bone‘s ability to resist deformation, and strength is bone‘s ability to

27

resist structural failure, or fracture. ―Both characteristics are important for bone—

remaining stiff for support of the body while not breaking under load‖ (Ruff, 2008: 185).

Bone rigidity and strength research has revealed several important bone characteristics.

First, as opposed to brittle material that breaks quickly, bone is ductile, meaning it

deforms considerably before failure or fracture occurs (Rogers, 2001). Second, bone is

viscoelastic, meaning it exhibits differences in deformity based on the rate at which

deforming force is applied: in general, bone can absorb more energy at higher rates of

application (Rogers, 2001). Last, bone reacts differently to various forces.

There are five main forces that act on bones to deform or fracture them (Fig. 7). In

tension, forces along the bone‘s long axis act to stretch it apart, and in compression, to

reduce it. In shearing, one portion of the bone slides over another, and in torsion,

diagonal stresses around the bone‘s long axis produce twisting. Last, bending places the

convex side of the bone in tension and the concave side in compression (Rogers, 2001:

17–18; Ruff et al., 2006: 184–185). Bone is typically strongest in compression; it is

generally stronger in tension than in shearing (Keaveny et al., 2001; but see Love and

Symes, 2004).

28

Figure 7. Forces acting on bones to deform or fracture them. Modified from Rogers

(2001) with permission from Elsevier.

When one of those five forces is applied to bone, it is termed a stress, which is

measured as load per unit area. In response to stress, bone first distorts because it is

ductile. The change or distortion is termed the strain, a dimensionless quantity that

expresses the ratio of change in bone length, width, or angulation relative to its original

dimensions. The relationship between stress and strain is best explained graphically

(Rogers, 2001: 17; Fig. 8):

29

Figure 8. The relationship between bone stress and strain. Modified from Rogers (2001)

with permission from Elsevier.

Initially the resultant strain is directly proportional to the stress applied; thus, the

initial portion of the stress/strain curve forms a straight line. ―This zone of proportionality

is the zone of elastic deformation. In this region, when the load is removed, both the

stress and the strain disappear and the object immediately returns to its original

dimension. The object is said to be elastic, and the strain is termed an elastic strain‖

(Rogers, 2001: 17). ―Beyond the straight portion the curve begins to bend. The point at

which the bending occurs is the yield stress and yield strain of the object. Beyond this

point the stress is no longer proportional to the resultant strain; a relatively small degree

of stress results in a larger degree of strain or deformity than was present previously.

30

Furthermore, in this portion of the curve, when the stress is removed the object is unable

to return to its initial shape, and there is a residual deformity or strain. This type is a

plastic strain, and this portion of the curve is termed the zone of plastic deformation‖

(Rogers, 2001: 17). ―With continued application of stress a point is reached beyond

which the object can withstand the effect of the resultant strain, and the object is

disrupted or fractured. This is termed the failure point. The point at which failure occurs

defines the ultimate stress to which the object can be subjected and the ultimate strain

that it can withstand‖ (Rogers, 2001: 17–18).

Utilizing a beam model, the cross-sectional geometric properties of cortical area

(CA), the second moments of area (SMAs) I and J, and the section modulus Z can be

used to estimate femoral midshaft rigidity and strength to applied biomechanical forces

(Ruff, 1999: 290; Table 4). To estimate the first variable, cortical area, we need to find

the total subperiosteal area (TA). TA = π (TAP/2) (TML/2) = .785(TAP * TML) where TAP =

anteroposterior subperiosteal breadth, and TML = mediolateral subperiosteal breadth.

Cortical area can then be determined by the equation CA = [π (TAP/2) (TML/2)] – [π

(MAP/2) (MML/2)] = .785 [(TAP * TML) – (MAP * MML )] where TAP = anteroposterior

subperiosteal breadth, TML = mediolateral subperiosteal breadth, MAP = anteroposterior

endosteal breadth, and MML = mediolateral endosteal breadth (Ruff and Jones, 1981: 72–

73). Finally, the medullary area (MA) can be found utilizing the equation [π (MAP/2)

(MML/2)], or by subtracting the cortical area from the total subperiosteal area.

Alternatively, an image processing program, such as ImageJ, can determine CA, TA, and

MA through the calculation of square pixels comprising a calibrated bone‘s cross-section.

31

Table 4. Definitions of Cross-Sectional Geometric Properties (Modified from Ruff,

2008: 185).

Property Abbrev. Unit Definition

Cortical Area

CA mm

2 Compressive/tensile rigidity/strength

Total Subperiosteal Area TA mm

2 Area within subperiosteal surface

Medullary Area MA mm2 Area within medullary cavity

Tendency to rotate about

a point/ total area in both

the x and y directions

Xbar mm2 Section centroid x coordinate

Tendency to rotate about

a point/ total area in both

the x and y directions

Ybar mm2 Section centroid y coordinate

SMA about M-L (x) axis Ix mm4 A-P bending rigidity

SMA about A-P (y) axis Iy mm4 M-L bending rigidity

Maximum SMA Imax mm4 Maximum bending rigidity

Minimum SMA Imin mm4 Minimum bending rigidity

Polar SMA J mm4

Torsional and (twice) average bending

rigidity

Cross-sectional shape Ix/Iy -----

Bending strength in the A-P plane

relative to the M-L plane

Cross-sectional shape Imax/Imin ----- Relative maximum bending strength

Theta

θ ° Orientation of maximum bending

rigidity relative to M-L anatomical axis

Section modulus about

M-L (x) axis

Zx

mm

3 A-P bending strength

Section modulus about

A-P (y) axis Zy mm

3 M-L bending strength

Maximum section

modulus ZMax mm

3 Maximum bending strength

Minimum section

modulus

ZMin

mm3

Minimum bending strength

Polar section modulus Zp mm3

Torsional and (twice) average bending

strength

Calculating TA and MA in addition to CA are useful for demonstrating whether

an increase in CA is due to endosteal contraction, periosteal expansion, or both (Ruff,

32

1999: 297). Further, once calculated, the CA value is proportional to the bone‘s rigidity

and strength in pure compression and tension, or in loadings applied perpendicularly to

the cross-section surface with the resultant force passing through the center of area of the

section. Therefore, the larger the CA value, the greater the bone‘s robusticity and

resistance to deformation and fracture in pure compression and tension.

Bones, however, are rarely subjected to pure tension or compression due to their

curvatures and effects of muscular forces applied off-center to bones‘ central axes

(Larsen, 1997: 200). Instead, the highest strains and most critical loadings in long bones

occur in bending and torsion (Ruff and Larsen, 2001: 134). SMAs, not areas, must be

used to measure bending and torsional rigidities and strengths, but first Xbar and Ybar,

the x and y coordinates of the cross-sectional center, are needed to find those SMAs. This

centroid point is found by dividing the total moments, or tendency to rotate about a point,

by total area in both the x and y directions (Ruff, 1999).

Once the centroid is found, the SMA, designated I, is a geometric property used to

determine bending rigidity. Its magnitude depends not only on area, but also areal

distribution of bone in the section (Ruff and Hayes, 1983: 360). Accordingly, Ix

specifically measures resistance to bending forces around the mediolateral axis or the A-P

plane bending rigidity, and Iy measures resistance to bending around the anteroposterior

axis or the M-L plane bending rigidity. These values are determined using the equation I

= ∑ad2 where a is the unit area, and d is the perpendicular distance from centroid to

neutral axis (Larsen, 1997: 201), which tends to move towards the side of the bone under

tension (Ruff et al., 2006: 490).

Imax and Imin are found using the same equation, but Imax measures the maximum

33

resistance of bone to bending and Imin the minimum resistance of bone to bending. Imax

and Imin values are indicated by the principal axes on a cross-section: the major axis is the

location of greatest bending rigidity and the minor axis the location of least bending

rigidity (Ruff and Hayes, 1983). The principal axes may be oriented at any angle but are

always perpendicular to one another. Overall, ―the optimal cross-sectional ‗shape‘ of a

bone subjected only to bending in one plane would be to place as much bone as far as

possible from the neutral axis of bending‖ (Ruff and Hayes, 1983: 371; Ruff et al., 2006:

184–186; Ruff et al., 1984: 126). Thus, bone distributed far from the neutral axis where

stress is zero indicates resistance to bending deformation, reflected in larger I values.

There are two I value ratios that are particularly good indicators of cross-sectional

shape since they reflect relative distribution of bone about perpendicular axes. The Ix/Iy

ratio measures bending strength in the A-P plane relative to the M-L plane, and the Imax

/Imin ratio measures the relative maximum bending strength of the bone at that cross-

section. For example, an Ix/Iy ratio of 1.0 indicates an equivalent distribution of bone

about x and y axes, and thus a cross-section close to circular, while ratios greater or less

than 1.0 indicate a direction of greater elongation in the A-P or M-L planes, respectively

(Ruff, 1987: 393). These ratios then, are especially helpful in elucidating specific types of

biomechanical loadings and lifetime behavioral patterns (Ruff and Larsen, 2001: 135).

For example, more bone distributed in the A-P plane indicates frequent A-P bending

loadings, a pattern that develops with great workload and mobility (Ruff, 1987: 411).

Similar to bending rigidity, the SMA designated J is a geometric property used to

determine torsional rigidity. J, also known as the polar SMA, is computed by finding the

product of bone unit area and the squared distances from the outermost fibers of that area

34

to the centroid (Ruff, 2008: 185–186). More simply, J is found by adding I values from

axes at right angles (e.g., Imax + Imin, = J, or Ix + Iy = J; Bridges et al., 2000: 220).

Therefore, ―J represents not only torsional rigidity but also an average bending rigidity

about all planes through the section. As such, it is a useful measure of overall

bending/torsional rigidity‖ (Ruff, 1999: 296). Regarding interpretation, since the greatest

tensile strains are found at the most distant cross-sectional fibers from the centroid (Ruff

and Hayes, 1983: 360), a more outwardly distributed cross-section indicates greater

resistance to torsional deformation, reflected in larger J values (Ruff et al., 1984: 126).

Finally, bending and torsional strengths—not rigidities—are estimated using

related but slightly different cross-sectional geometric properties known as section

moduli, commonly designated Z. Z values are calculated by dividing the various SMA I

and J values by the distance from bone surface to the appropriate neutral axis or centroid,

or half the appropriate diameter of the section (Ruff et al., 1984; Ruff et al., 2006: 186).

More simply, Z values are estimated by raising the appropriate I or J value to the power

of 0.73 (Maggiano et al., 2008). Thus, Zx and Zy measure bending strength in the

respective x and y axes, Zmax and Zmin measure bending strengths calculated in the same

planes as Imax and Imin, and Zp, the polar section modulus, approximates the section‘s

torsional strength or average bending strength. Again, high Z values indicate greater

robusticity, bending/torsional strengths, and resistance to fracture (Orwoll, 2003: 949).

Unfortunately, body mass and distribution of body mass constitute mechanical

loads and are related to other factors, such as muscle size, that also influence

biomechanical loading. Therefore, to compare bone structural properties between

individuals or populations, body size differences must be controlled for. This is

35

problematic for anthropologists studying skeletal materials without soft tissues because

the best body size-standardizing factor is bone length multiplied by body mass. Ix/Iy and

Imax /Imin ratios, however, avoid the complexities associated with standardizing raw data

for body size differences between sexes or population samples (Ruff, 1987: 393).

Overall, biomechanical forces, in addition to growth processes and environmental

factors, influence amount and distribution of femoral cortical bone, as more bone is

deposited in areas under greater stress. Therefore, if suitable precautions are taken to

control for body size, sample from similar skeletal locations, and eliminate pathological

conditions, behaviors can be reconstructed from femoral midshaft cross-sections (Ruff,

2008: 184). For example, if analysis shows CA is low but TA, I, J, and Z values are high,

these findings indicate that there is a relatively low amount of cortical bone, but the

present skeletal tissue is distributed far from the neutral axis and centroid, indicating

adaptation to lifetime activities that produce great bending and torsional stresses and

strains (Larsen, 1997: 203–204).

C. MECHANOBIOLOGY OF THE FEMUR

Mechanobiology, which includes the processes of mechanosensation and

mechanotransduction, provides the explanation for how femoral cortical thickness and

distribution become morphologically well adapted to mechanical environment during life.

To understand these biological processes, one must begin with the most basic bone cell,

the osteocyte. The origin of osteocytes lies in preosteoblasts, some of which differentiate

into active osteoblasts that synthesize osteoid through the process of osteogenesis (Franz-

Odendaal et al., 2006; Knothe Tate et al., 2004: 2). Osteoblasts can then transform into

36

bone lining cells, cells that deposit chondroid, undergo programmed cell death, or

become osteocytes. Therefore, while not all active osteoblasts become osteocytes, all

osteocytes can be understood to be transformed osteoblasts (Bell et al., 2008; Franz-

Odendaal et al., 2006). Figure 9 illustrates how osteoblast-to-osteocyte transformation is

a dynamic, continual process from (1) preosteoblasts, to (2) resting osteoblasts, to (3)

active osteoblasts that sit at the osteoid deposition front, to (4–6) preosteocytes in varying

stages of osteoid engulfment, to (7) young osteocytes near the mineralization front, to (8)

mature osteocytes deeply embedded in mineralized bone. It is evident some osteoblasts of

each cell generation slow their rate of bone deposition or stop laying down bone entirely

so that they are trapped by osteoid secretions of neighboring cells and become osteocytes

(Franz-Odendaal et al., 2006).

As osteoid continues to mineralize, a cell capsule known as a lacuna is formed

around the now embedded osteocyte. The cell sits within the lacuna with approximately

50 cell processes extending outwards into the matrix to other entombed osteocytes, the

active osteoblast layer, and marrow resident cells. The osteocyte‘s processes are also

surrounded by small bone tubular tunnels known as canaliculae, and are connected to

other cell processes via gap junctions at their most distal ends (Fig. 9, inset). Between the

cells and cell processes and their capsules is a microcirculatory system of periosteocytic

fluid that is distinct from blood plasma and lymph fluid in that it has much higher

concentrations of K+ (Knothe Tate et al., 2004: 5). This arrangement of cells, cell

processes, capsules, and pericellular fluid is the basis of the lacunocanalicular system, or

LCS, a dense 3D network of cell and pore connectivity (Bell et al., 2008: 449; Fig. 10).

37

Figure 9. From preosteoblast to osteocyte. Reprinted from Franz-Odendaal et al. (2006)

with permission from John Wiley and Sons.

Osteocyte appearance is related to its stage of maturation (see Fig. 9), but is also

heavily tied to its functions of intercellular communication, osteocytic osteolysis,

mechanosensation, and mechanotransduction. To expand, conducting experiments with

dyes, Yellowley and colleagues (2000) documented inter-osteocyte communication:

Lucifer yellow dye was injected into labeled osteocytes parachuted into connected

osteocytic cells. The dye transferred between adjacent osteocytes demonstrating that they

do have functionally-coupled gap junctions. Additionally, through the same process,

Calcein dye transferred from an injected osteocyte to osteoblasts showing osteocytes

38

remain connected to the active surface layer, even when trapped in mineral. Second,

osteocytes also prevent mineralization and constriction of their own lacunar spaces.

Through a process called osteocytic osteolysis, osteocytes excrete acid phosphatase and

other lysosomal hydrolic enzymes to digest proteins, and glycosaminoglycans to mobilize

calcium in the pericellular matrix (Knothe Tate et al., 2004: 5). Overall, osteocytic

osteolysis ensures continued proper functioning of the cellular transport pathway.

Finally, according the canalicular fluid flow hypothesis, ―the combination of

cellular network and lacunocanalicular porosity performs the functions of

mechanosensing and mechanotransduction in bone‖ (Burger and Klein-Nulend, 1999:

S102), or detecting and directing incoming biomechanical loading information to initiate

a bone response. Osteocytes within the LCS are particularly well suited to detect

mechanical loading because of their sheer numbers, distribution throughout bone matrix,

high degree of connectivity, and ability to absorb larger strains than external bone surface

cells (Bonewald, 2006; Yellowley et al., 2000). Thus, when mechanical stresses are

placed on bones during daily physiological movement, interstitial fluid is squeezed

through the LCS. The combination of narrow canaliculae and wide osteocyte processes

produces appreciable fluid shear stress that conveys mechanical messages to local

osteocytes through mechanosensation (Burger and Klein-Nulend, 1999: S103–S104;

Knothe Tate et al., 2004: 6).

Next, in mechanotransduction, stimulated local osteocytes relay that mechanical

loading energy, via changes in LCS fluid flow and chemical levels, through bone matrix

to endosteal (Islam et al., 1990) and periosteal cells (Burger and Klein-Nulend, 1999:

S101–S105; Yellowley et al., 2000; Knothe Tate et al., 2004: 6; Fig. 10, inset).

39

Figure 10. The structure of bone that allows for mechanosensation and mechano-

transduction. Reprinted from Taylor and colleagues (2007) with permission from

Macmillan Publishers Ltd, Elsevier, and Wiley.

When bone-lining cells receive mechanical overloading information, this triggers

point-specific osteoblasts at the affected bone surface to build an excess of bone, ―which

is the usual case on periosteal bone surfaces‖ (Frost, 1987a: 3). A series of such

increments over time results in a net bone gain and restoration of optimum strain levels.

Alternatively, when bone lining cells sense disuse, this triggers point-specific osteoclasts

at the affected marrow surface to resorb an excess of bone, which over time causes a net

loss of bone, and restoration of optimum strain levels (Burger and Klein-Nulend, 1999:

S105; Frost, 1987a: 3). In this way, loading produced by a repetitive mechanical action

such as running can eventually form a relatively thick, A-P elongated, femoral cross-

section well adapted to resisting associated stresses.

40

D. PERIOSTEAL ADAPTATION OF THE FEMUR

In addition to the physiological forces that act on the femur to influence its

cortical area and distribution, pressures from overlying structures are also exerted on the

femoral periosteal surface. These structures influence the femur‘s ultimate shape by

building up additional bone in periosteal areas under tension and removing additional

bone from periosteal areas experiencing compression.

I. Skin, Superficial Structures, and Fascias of the Thigh

Adult skin is composed of a thin surface epidermis that is supported and

nourished by the thicker and deeper dermis. The skin gives rise to hair follicles,

sebaceous and sweat glands, and nails, and as such, performs a wide range of sensory,

thermoregulatory, and biosynthetic functions. Altogether, the skin also presents an

elaborate and organized outer surface called the stratum corneum, a ―barrier between an

organism and its outer environment [that] acts to prevent desiccation, toxin entry, and

microbial infection‖ (Byrne et al., 2003: 113).

Immediately deep to the skin of the thigh is superficial fascia consisting of a loose

association of lipid-filled adipocytes, pre-adipocytes, fibroblastic connective tissue cells,

leukocytes, and macrophages held together by a reticular fiber framework. This fascia,

also known as unilocular or white adipose tissue, is an especially important heat

conductor in the body, where the degree of insulation is dependent on its thickness.

Additionally, it provides a buffer when energy intake is not equal to energy output: lipids

ingested beyond those needed for current energy use are hydrolyzed by the enzyme

lipoprotein lipase into fatty acids and glycerol. These diffuse into the white adipose tissue

where they are reesterified for storage, or lipogenesis. When needed, triglycerides stored

41

within adipocytes are hydrolyzed back into fatty acids and glycerol through lipolysis,

enter the connective tissue spaces of the white adipose tissue, and from there are

transported to the blood for energy distribution (Gartner and Hiatt, 2007).

Within this fat-rich layer are superficial veins that remove deoxygenated blood

from the lower extremity and cutaneous nerves that innervate the skin. Just below the

superficial fascia is the fat-free deep fascia, a thin layer of connective tissue fibers, which

hug the external surfaces of the underlying muscles (Fig. 11; NetAnatomy, 2001).

Figure 11. (a) Skin, superficial fascia, and cutaneous nerves of the thigh, and (b) the deep

fascia and most superficial muscles of the thigh. Modified from NetAnatomy (2001) with

permission from Dr. Raymond J. Walsh, GWU School of Medicine and Health Sciences.

42

II. Anterior Muscle Compartment

Connected to the deep fascia are sheets of connective tissue called intermuscular

septa that divide the thigh into functional anterior, medial, and posterior compartments

(Fig. 12). The anterior compartment is composed of sartorius, the four quadriceps heads,

pectineus, and iliopsoas (Fig. 13). They are innervated by the femoral nerve and work to

flex the thigh at the hip and extend the leg at the knee (NetAnatomy, 2001).

Figure 12. The anterior (a), medial (b), and posterior (c) compartments of the thigh

separated by the intermuscular septa. Modified from NetAnatomy (2001) with permission

from Dr. Raymond J. Walsh, GWU School of Medicine and Health Sciences.

Table 5 and Figure 14 show how anterior compartment muscles overlie nearly the

entire femoral midshaft surface. Although the courses of sartorius, pectineus, iliopsoas,

and rectus femoris muscles prohibit immediate contact, vastus lateralis, vastus medialis,

and vastus intermedius are in direct contact with the femoral cortex: vastus lateralis and

medialis attach directly to the linea aspera, and vastus intermedius overlies the entire

femoral midshaft anterior surface and also covers significant sections of the medial and

lateral surfaces (NetAnatomy, 2001; Moore and Agur, 2007).

43

Figure 13. Muscles of the anterior compartment of the thigh include (a) sartorius, (b, c)

quadriceps femoris, (d) pectineus, and (e) iliopsoas. Modified from NetAnatomy (2001)

with permission from Dr. Raymond J. Walsh, GWU School of Medicine and Health Sci.

Table 5. Anterior Compartment Muscles. Taken from Moore and Agur (2007).

Muscle Origin Insertion

Vastus lateralis m. Greater trochanter and lateral lip

of the linea aspera

Base of patella and tibial

tuberosity

Vastus intermedius m. Anterior/ lateral surfaces of

femoral diaphysis

Vastus medialis m. Intertrochanteric line and medial

lip of linea aspera

Rectus femoris m. Anterior inferior iliac spine and

ilium superior to acetabulum

Sartorius m. Anterior superior iliac spine and

superior part of inferior notch

Superior part of medial

surface of tibia

Pectineus m Superior pubic ramus Femoral pectineal line

under lesser trochanter

Iliopsoas m Sides of T12–L5, transverse

processes of all lumbar vertebrae,

iliac crest, iliac fossa, sacral ala

Lesser trochanter and

femur distal to it

44

Figure 14. Cross-section of the midshaft of the femur demonstrating vastus lateralis,

vastus medialis, vastus intermedius, the short head of biceps femoris, adductor longus,

and adductor magnus in direct contact with the femoral midshaft. Modified from

NetAnatomy (2001) with permission from Dr. Raymond J. Walsh, GWU School of

Medicine and Health Sci.

III. Medial Compartment Musculature

The medial compartment musculature consists of adductor longus, adductor

brevis, adductor magnus, gracilis, and obturator externus (Fig. 15). All are innervated by

the obturator nerve, and their spatial relationship to the hip joint results in adduction of

the thigh when these muscles are contracted. When operating from a fixed insertion (or

when the lower limb is planted firmly on the ground) the adductor group also stabilizes

the pelvis on the supporting limb (NetAnatomy, 2001).

45

Figure 15. Musculature of the medial compartment of the thigh includes (a) adductor

longus, (b) adductor brevis, (c) adductor magnus, (d) gracilis, and (e) obturator externus.

Modified from NetAnatomy (2001) with permission from Dr. Raymond J. Walsh, GWU

School of Medicine and Health Sciences.

Table 6 and Figure 14 show how gracilis, obturator externus, and adductor brevis

have no immediate contact with the midshaft femoral cortex. Of the medial compartment

muscles, adductor longus inserts at the middle third of the linea aspera, and adductor

magnus inserts on the gluteal tuberosity, linea aspera, medial supracondylar line, and

adductor tubercle of the femur (NetAnatomy, 2001; Moore and Agur, 2007).

Table 6. Medial Compartment Muscles. Taken from Moore and Agur (2007).

Muscle Origin Insertion

Adductor longus m. Body of pubis inferior to

pubic crest

Middle third of linea aspera

Adductor brevis m. Body and inferior ramus of

the pubis

Pectineal line and proximal

part of linea aspera

Adductor magnus m. Inferior pubic ramus, ischial

ramus, ischial tuberosity

Gluteal tuberosity, linea

aspera, medial supracondylar

line, femoral adductor tubercle

Gracilis m. Body and inferior ramus of

the pubis

Superior part of medial tibial

surface

Obturator externus m. Obturator foramen margins Trochanteric fossa of femur

46

IV. Posterior Compartment Musculature

The posterior compartment of the thigh (Fig. 16) contains the hamstring group of

muscles (biceps femoris long and short heads, semimembranosus, and semitendinosus).

With the exception of the short head of biceps femoris, which is innervated by the fibular

part of the sciatic nerve, these muscles are innervated by the tibial part of the sciatic

nerve. Passing posterior to both the hip and knee joints, all three serve to extend the thigh

at the hip and flex the leg at the knee (NetAnatomy, 2001).

Specifically, both semitendinosus and semimembranosus arise from the ischial

tuberosity and insert on the medial surface of the superior tibia. Similarly, the long head

of biceps femoris originates at the ischial tuberosity and inserts onto the lateral side of the

fibular head. In doing so, none of these muscles come into direct contact with the surface

of the femur. The short head of biceps femoris, however, originates at the midshaft of the

linea aspera and femoral lateral supracondylar line to insert on the lateral side of the

fibular head, and thus, comes into direct connect with the femoral midshaft (Fig. 14;

Table 7; NetAnatomy, 2001; Moore and Agur, 2007).

Table 7. Posterior Compartment Muscles. Taken from Moore and Agur (2007).

Muscle Origin Insertion

Biceps femoris m. Ischial tuberosity (long head), lower

half of linea aspera and lateral

supracondylar line of femur (short

head)

Lateral side of fibula

head

Semitendinosus m. Ischial tuberosity Medial surface of

superior tibia

Semimembranosus m. Ischial tuberosity Posterior part of tibial

medial condyle

47

Figure 16. Musculature of the posterior thigh compartment includes semimembranosus,

semitendinosus, and the long and short heads of biceps femoris. Modified from

NetAnatomy (2001) with permission from Dr. Raymond J. Walsh, GWU School of

Medicine and Health Sciences.

V. The Periosteum

Beneath the anterior, medial, and posterior thigh musculature compartments,

periosteum completely covers the femoral diaphysis, with the exception of articular

48

surfaces and tendon insertion sites. Specifically, the periosteum is divided into two

distinct layers: the internal cambium layer and the external periosteal fibrous layer. The

femoral surface is covered by the internal cambium layer, which consists of microvessels,

sympathetic nerves, fibroblasts, adult mesenchymal progenitor cells, differentiated

osteogenic progenitor cells, and osteoblasts capable of periosteal bone formation (Allen

et al., 2004; Orwoll, 2003). Also present are multinucleated polykaryons that may

differentiate into mature osteoclasts. These cells use lytic enzymes to erode bone, and are

therefore capable of surface-based bone resorption (Boyle et al., 2003; Orwoll, 2003).

The periosteal fibrous layer is composed of elastin fibers, collagen, fibroblasts, a nerve

and microvascular network (Allen et al., 2004: 1005), and Sharpey‘s fibers, which affix

the periosteum to the femur (Gartner and Hiatt, 2007).

VI. Effects of Periosteal Loads on Femoral Shape

Carpenter and Carter (2008) demonstrated the effects of adjacent muscles on long

bone shape by comparing normally functioning growing rat tibias to growing tibias from

rats that received full, 75 percent, and 50 percent sciatic neurectomies at four weeks of

age. For all rats, from experiment start to one week of age, active bone formation took

place at all points along the endosteal and periosteal surfaces. By two weeks, bone

resorption began to occur on the medial endosteal surface, while bone apposition

continued at all other locations. This pattern continued through four weeks of age. Once

loading patterns changed for control and neurectomized rats, however, their modeling

patterns and geometries begin to diverge. In control tibias, medial resorption and lateral

apposition on the endosteal surface continued throughout the remaining experiment.

49

After five months of growth, however, bone resorption began to occur in the regions

experiencing periosteal surface pressures, and this pattern continued until 17 months,

when control tibias developed distinctly triangular cross-sections with slightly concave

anterolateral and flattened posterolateral faces (Carpenter and Carter, 2008).

Conversely, in the full, 75, and 50 percent neurectomized tibias, by six weeks,

bone resorption was occurring around the entire endosteal surface, while bone apposition

continued on the periosteal surface. This pattern remained unaltered so that by two

months, the tibia obtained a nearly elliptical cross-section. Periosteal apposition and

endosteal resorption continued to produce a smooth, elliptical final shape by 17 months.

Further, the only difference found between full, 75, and 50 percent neurectomized tibias

was the size of the resulting cross-section (Carpenter and Carter, 2008; Fig. 17).

Based on this experiment, Carpenter and Carter (2008: 237) first state, ―the results

of the [neurectomy] simulations suggest that bone cross-sectional size is largely

determined by the magnitudes of far-field [physiological] loads and that bone cross-

sectional shape is strongly affected by local periosteal surface loads.‖ Second, the authors

find that compressive pressures applied directly to periosteal surfaces impede bone

formation or induce bone resorption by encouraging osteoclastic resorption, and tensile

strains applied perpendicularly to periosteal surfaces impede bone resorption or induce

bone formation by encouraging osteoblastic deposition (Carpenter and Carter, 2008:

229). Finally, the authors conclude bones ―do not always obtain an optimal cross-

sectional geometry for resisting applied far-field loads. Instead, the interaction between

the responses to intracortical stresses and periosteal surface loads leads to a ‗compromise‘

50

between the drive towards optimal mechanical support and need to accommodate

adjacent structures‖ (Carpenter and Carter, 2008: 238).

Therefore, compressive and tensile periosteal surface strains, in addition to

physiological forces, growth processes, and environmental factors, influence ultimate

femoral cortical shape through mechanobiological processes. Specifically in the human

thigh, vastus lateralis, vastus medialis, adductor longus, adductor magnus, and the short

head of biceps femoris attach directly to the posterior femoral diaphysis, and resulting

tensile forces cause development of the linea aspera. Alternatively, vastus intermedius

and other nearby muscle bellies apply differential compressive forces around the anterior,

medial, and lateral surfaces of the femoral diaphysis resulting in its characteristic shape.

Figure 17. Neurectomy effect on tibia shape. Modified from Carpenter and Carter (2008)

with permission from Springer.

51

E. CORTICAL AGING OF THE FEMUR

After the femur is fully developed, biomechanically adapted, and periosteally

adjusted, a net loss of cortical bone begins as the amount of bone deposited on the

periosteal surface lessens in comparison to the amount of bone removed from the

endosteal surface. Decreasing bone gain on one surface and increasing loss from another

slowly and steadily changes the size, shape, geometry, and strength of the femur

throughout adulthood (Szulc et al., 2006: 1859).

To document this bone loss and redistribution, Szulc and colleagues (2006)

collected bone mineral content, bone mineral density, cortical thickness and area, and

biomechanical data from the distal third of the radius of 821 healthy White women aged

30 to 89 years for 7.1 ± 2.5 years. The authors found that endocortical bone loss began in

younger premenopausal women, however, ―periosteal apposition compensated, but only

partly, so the cortices thinned‖ (0.29 ± 0.85 percent/year). Overall, ―there was no net

bone loss because the same amount of bone was distributed as thinner cortex around a

larger perimeter‖ (Szulc et al., 2006: 1859). During the perimenopausal period, however,

―endocortical resorption accelerated, whereas periosteal apposition decelerated. The

cortices thinned (0.66 ± 0.56 percent/year), but now periosteal apposition was insufficient

to maintain bone mass, which declined, but it still maintained estimates of bending

strength. Bone fragility emerged after menopause when further acceleration of

endocortical bone resorption and deceleration of periosteal apposition produced further

cortical thinning (1.10 ± 1.06 percent/year) and little displacement of the cortex. Now the

calculated cortical area and bending strength declined‖ (Szulc et al., 2006: 1859).

While there is no equivalent midlife event in males, Seeman (2002) found their

52

bones to expand similarly in size with resulting cortical bone loss, but not to the same

degree as females‘ bones: ―cortical bone loss is less in men than in women because

periosteal bone formation is greater, not because endosteal resorption is greater in women

than men. On the contrary, the absolute amount of bone lost from the endosteal surface is

greater in men than in women‖ because they have larger skeletons (Seeman, 2002: 1846).

Additionally, with increasing cortical thinning, femoral cross-sectional shape also

changes: young adults often display A-P elongated cortices indicating great workload and

mobility, but by mature adulthood, femoral cross-sections are most elongated in the M-L

plane indicating reduced mobility (Ruff, 1987).

F. INTRACORTICAL REMODELING OF THE FEMUR

The bone deposited during femoral development, biomechanical and periosteal

adaptation, and cortical redistribution provide the material upon which a final dynamic

process, intracortical remodeling, proceeds (Robling and Stout, 2008: 150). Intracortical

bone remodeling is achieved by the coordinated, equivalent actions of a complex

arrangement of osteoblasts and osteoclasts, collectively called a basic multicellular unit

(BMU). As such, intracortical remodeling does not generally affect bone area and

distribution, but rather maintains them (Harada and Rodan, 2003).

Remodeling is, ―at least to some degree, targeted towards the removal of damaged

[bone] areas‖ (Taylor et al., 2007: 263): repetitive mechanical loading of bones

eventually causes fatigue, or microcracks, that may develop parallel to the bone‘s

longitudinal axis or horizontally through its interstitial lamellae. Increased physiological

loading causes microcracks to propagate into more diffuse areas of microdamage. At the

53

microscopic level, this damage interrupts the connectivity of the LCS, and thus, nutrient

transport to osteocytes adjacent to the damage, causing cell death. Osteoclasts ―are

attracted to the apoptopic cells and so preferentially eat away the bone in this region‖

(Taylor et al., 2007: 266). Arrival of osteoclasts activates an intracortical remodeling

cycle (Scheuer and Black, 2000: 30; Henriksen et al., 2009: 1026; Fig. 18).

The activated osteoclasts begin to resorb bone at a rate of approximately 40–50

µm per day by secreting acids that demineralize adjacent bone and enzymes to dissolve

collagen. In this way, 9 to 10 osteoclasts, often referred to as the ―cutting cone,‖ remove a

microcrack, leaving a 2–6 millimeters long resorptive bay in its wake (Parfitt, 1994: 275;

Scheuer and Black, 2000: 31). The tunnel that is cut by the osteoclasts is more or less

longitudinal to the axis of the bone, and the diameter of the tunnel, which typically

reaches roughly 250–300 µm, defines the cross-sectional size of the secondary osteon

that will eventually fill it (Robling et al., 2006: 458; Henriksen et al., 2009: 1027–1029).

Between the leading osteoclastic cutting cone and the following osteoblastic

restoration of lost bone is a transitional, reversal phase. At this time, mononuclear bone

lining cells are recruited to clean the resorption pit and smooth off the scalloped

periphery of the resorptive bay with a thin, mineral-deficient, sulfur-rich layer of matrix

that separates an osteon from surrounding lamellae. This is the ―cement line‖ (Robling et

al., 2006: 458–459; Henriksen, 2009: 1029). Then, as a result of osteoclast signaling, the

bone lining cells either differentiate into or are replaced by several hundred osteoblasts

commonly called the ―closing cone‖ that adhere to the reversal zone and deposit layers of

osteoid that mineralize into concentric lamellae. The tunnel is not completely infilled,

however, as it is necessary to house a nutrient artery in the central Haversian canal of the

54

newly formed bone structural unit (BSU), or secondary osteon. This formation phase

takes approximately three months (Scheuer and Black, 2000: 31; Henriksen et al., 2009:

1027–1030). When bone formation is complete, osteocytes embedded during bone

formation secrete sclerostin leading to termination of the remodeling cycle (Henriksen,

2009: 1027). This bone remodeling process continues as needed until death, creating the

observed association between number of intracortical osteons and chronological age that

forms the primary basis for all histological age predicting methods (Stout, 1989: 44).

Figure 18. Remodeling process. Reprinted from Henriksen and colleagues (2009) with

permission from Elsevier.

55

CHAPTER THREE: HYPOTHESES

Building from this theoretical knowledge base, it is first hypothesized that since

all healthy, mobile femurs have in common: genetic programming to establish initial size

and shape; the developmental processes of endochondral ossification, appositional

growth, and modeling; biomechanical adaptation; periosteal adaptation; cortical thinning

and shape change during aging; and mechanosensation and mechanotransduction (Fig.

19), intracortical remodeling patterns exist around all human femoral periosteal cortices,

despite individual variation in these processes:

NULL HYPOTHESIS #1: There is no evidence for topographic variation in

remodeling around human femoral midshaft periosteal cortices. There are no

statistically significant differences between ROI OPD means.

ALTERNATIVE HYPOTHESIS #1: Topographical variation in remodeling exists

around human femoral midshaft periosteal cortices resulting from normal

anatomical development, customary biomechanical usage, and standard

mechanobiological functioning. There are statistically significant differences

between ROI OPD means.

Figure 19. The life cycle of the femur: (a) 2 years, (b) 5 years, (c) 9 years, (d) 14 years,

(e) 18 years, (f) middle age, and (g) mature adulthood. Modified from Goldman and

colleagues (2009) with permission from John Wiley and Sons.

56

Support for the first alternative hypothesis comes from Marotti (1976) and

Drusini (1987) who provide compelling evidence for topographic variation in

remodeling: studying complete long bone midshaft cross-sections of growing dogs

treated with tetracycline, Marotti (1976) illustrated how amount of newly formed bone

tissue differs considerably by location. This finding emphasized ―the topographic rather

than statistic distribution of the processes of bone reconstruction,‖ where ―reconstruction

may attain for several successive times a given area of bone, while a nearby or distant

area may persist unmodified for a very long time‖ (Marotti, 1976: 202).

Similarly, Drusini (1987) counted secondary osteons present in abutting adjacent

fields along the entire circumferences of three human femoral cross-sections and found

considerable variability in their spatial distribution: a 19-year-old individual had 13.36

osteons on average per field, but a minimum of 2 osteons and a maximum of 21 osteons

were found at different periosteal locations. Similarly, a 35-year-old individual had 16.09

osteons on average per field, but a minimum of 8 osteons and a maximum of 23 osteons

were found at different periosteal locations. A last 50-year-old individual had 22.31

osteons on average per field, but a minimum of 18 osteons and a maximum of 28 osteons

were found at different periosteal locations. Overall, this is excellent evidence for the

existence of topographic variation around the femoral midshaft periosteal surface

throughout much of the human lifespan. Neither Marotti (1976) nor Drusini (1976),

however, provide explanations for the documented histomorphometric variation, nor do

they explain how it can be utilized to improve microscopic age at death estimation.

Contrary to Marotti (1976) and Drusini (1976), Villa and Lynnerup (2010)

assessed microstructural variability in 28 femoral sections at the Institute of Forensic

57

Pathology, University of Copenhagen. The sampled femurs all belonged to Caucasian

males between 28 and 89 years of age at death and none showed evidence of disease

suggestive of altered bone turnover. Further all sections were procured from the midshaft

of the right femur, and all analyses took place as near as possible to the periosteum. To

ensure at least 100 histological structures were observed from each cross-section for

accurate inference of total number of histological elements, between four and seven

regions of interest were selected for microscopic analysis. ―ROI no. 1 was located at the

anterior periosteum, and ROI nos. 2 and 3 were located in the lateral and medial

positions, respectively. ROI nos. 4 and 6 were located in intermediate positions between

ROI no. 1 and ROI no. 2, and ROI nos. 5 and 7 were correspondingly located between

ROI no. 1 and ROI no. 3‖ (Villa and Lynnerup, 2010: 492).

Taking this approach, Villa and Lynnerup (2010: 495) found no significant

differences in remodeling among the ROIs considered, and consequently suggest ―there

are no particular ROIs to be preferred, at least as long as they are close to the periosteum‖

for use in microscopic age at death estimation. Instead, the authors suggested any slight

histomorphometric differences found around the anterior, lateral, and medial femoral

periosteum are attributable to individual variation, not underlying biomechanical,

anatomical, or mechanobiological differences.

Villa and Lynnerup’s (2010) approach, however, samples a small number of

remodeling events per individual, neglects investigation of the posterior femoral cortex,

and essentially standardizes arbitrary ROIs that do not take into account locations of the

principle axes of maximum and minimum bending rigidity, which vary by individual

(Goldman et al., 2009: 59): ―ROIs were selected by overlaying a grid with cells

58

measuring 1.9 mm × 1.4 mm on each cross-section. The grid was printed on a

transparency and fixed on each cross-section, positioning the upper grid line adjacent to

the anterior periosteal margin‖ (Villa and Lynnerup, 2010: 492). This method is therefore

unsatisfactory for detecting meaningful patterns in topographic histomorphometric

variation that may exist as a result of anatomical development, customary biomechanical

usage, and standard mechanobiological functioning.

Following the concept of bone functional adaptation, the locations of greatest

typical femoral midshaft cortical bone strains can be found by identifying the areas where

bone has been preferentially added as far as possible from the neutral axis of bending

(Ruff et al., 2006). These locations are indicated in ImageJ where the Imax axis crosses the

bone’s periosteal edges (Ruff and Hayes, 1983). Repetitive mechanical loading of bones

in these highest strain areas eventually causes fatigue microcracks, and intracortical

remodeling often targets that damaged bone with interrupted LCS connectivity (Taylor et

al., 2007: 263). It is therefore secondly hypothesized that there is increased evidence of

remodeling in locations consistently exposed to the greatest and most repetitive

mechanical loading strains that cause the most microdamage, or the ImaxAnt and ImaxPost

ROIs. Similarly, it is also hypothesized that there is decreased evidence of remodeling in

locations typically exposed to the smallest and least frequent mechanical loading strains

that cause the least microdamage, or the IminMed and IminLat ROIs:

NULL HYPOTHESIS #2: There is no evidence Imin ROI OPD means are statistically

significantly reduced compared to the other six ROI OPD means.

ALTERNATIVE HYPOTHESIS #2: Imin ROI OPD means are statistically

significantly reduced compared to the other six ROI OPD means as a result of

minimal biomechanical loading.

59

Support for the second alternative hypothesis that less mechanical strain results in

less intracortical bone remodeling is provided by Stout (1982) who collected secondary

osteon, secondary osteon fragment, and OPD information from two immobilized

individuals: one individual suffered from multiple sclerosis and was confined to a

wheelchair for 15 years before her death. During this time, she maintained some

mechanical bone loading through muscular contractions, although control of her limbs

was impaired and spastic. A second individual had been a quadriplegic for 26 years as a

result of poliomyelitis. She suffered from true mechanical disuse of her limbs excepting

her right arm, of which she had retained partial use. The remodeling data from the

individual with MS was not significantly different from age-matched values. The same

data from the quadriplegic, however, revealed significant differences from age-matched

samples where densities for each bone fell below the 95% confidence limits of the control

mean values. The only exception was again the right arm where values were found to be

normal. Overall, this study demonstrates mechanical stress stimulates normal intracortical

bone remodeling, and long-term disuse reduces activation frequency of BMUs.

Finally, it was hypothesized above that there should be increased evidence of

remodeling in locations consistently exposed to the greatest and most repetitive

mechanical loading strains that cause the most microdamage, or the two Imax locations.

Similarly, it was also hypothesized that there should be decreased evidence of remodeling

in locations typically exposed to the smallest and least frequent mechanical loading

strains that cause the least microdamage, or the two Imin locations. While Imax and Imin

ROI remodeling are therefore largely determined by their biomechanical functions

relating to obligate striding bipedalism, anatomical axis ROI remodeling is not subject to

60

the same constraints. It is therefore thirdly hypothesized A, P, M, and L ROIs will

demonstrate greater remodeling variation:

NULL HYPOTHESIS #3: There are no statistically significant differences between

biomechanical and anatomical ROI OPD SEEs.

ALTERNATIVE HYPOTHESIS #3: Biomechanical ROI (ImaxAnt, ImaxPost, IminMed,

and IminLat) OPD SEEs will be histomorphometrically more consistent than OPD

SEEs of anatomical ROIs (A, P, M, and L) due to femoral functional constraints.

Evidence in support of the third alternative hypothesis comes from several studies:

I. ANTERIOR ROIs: When Drusini (1987: 170) counted secondary osteons present in

abutting adjacent fields along three complete femoral circumferences, he found marked

spatial variability, but also that ―especially along the anterior surface of the femur, the

[secondary osteon] microstructures were very seldom or never visible‖ and therefore

opted in his own research to ―exclude this zone from the computation‖ for production of

a regression equation to predict age at death from histological structures.

Pfeiffer and colleagues (1995) also provided evidence in support of anterior ROIs

remodeling most variably. In questioning whether sampling location affects cortical

remodeling and thus age at death estimates, the authors collected percent remodeled bone

data at anatomically and mechanically derived points at four depth levels of periosteal

though endosteal bone. Using nine femoral cross-sections from four males and five

females, they histologically examined seven fields at each of the eight sampling locations

for a total of 56 fields per specimen and a total of 493 total fields observed. When percent

remodeled bone from the seven fields at each sampling location were averaged—and thus

include radial differences in endosteal remodeling—the authors found the anterior

61

anatomical locations exhibited the lowest mean levels of remodeling activity and the

highest levels of variability. They therefore suggested, ―future attempts to establish age

estimation methods from the femur might do well to focus on a different, less

heterogeneous sampling location‖ (Pfeiffer et al, 1995: 91).

II. POSTERIOR ROIs: Similarly, Ahlqvist and Damsten (1969: 208) provided anecdotal

evidence that in the part of the bone around the linea aspera ―there seems to be a

somewhat greater variation in osteons and osteon fragments not correlated to age than in

other parts, possibly because of the powerful muscle insertions on the femoral crest.‖

Since that observation was made, the researchers who have focused specifically on

microscopic age estimation from the femur have not viewed posterior ROIs for collection

of histomorphometric data (see Fig. 4).

III. ANATOMICAL vs. BIOMECHANICAL ROIs: After analyzing the variance in percent

remodeled bone within and between the eight fields, Pfeiffer and colleagues (1995: 90)

conducted a Fisher’s protected least significant difference test to further explore and

compare the mean of one group against the means of each of the other groups. These

results revealed the anatomical locations to be significantly different from one another

with regards to average percent remodeled bone. The mechanically defined locations,

however, did not differ among themselves with regards to mean percent remodeled bone,

but rather, were only significantly different from the anatomical locations. Overall, ―the

mean percent remodeled values exhibit greater consistency among the four mechanical

axes [coefficient of variation (CV) = 0.02] than among the anatomical axes (CV = 0.1)‖

(Pfeiffer et al., 1995: 90–91).

62

CHAPTER FOUR: MATERIALS AND METHODS

A. MATERIALS

M.F. Ericksen extracted 318 femoral midshaft blocks from George Washington

University Medical School dissecting room cadavers between 1972 and 1989 (Appendix

A). From these samples, 200 were chosen for this research (Appendix A, shaded boxes)

that met the following criteria: (1) the entire periosteal border was present for analysis,

(2) the medial cortex was distinguished from the lateral by presence of an inked black

line and specimen number as per Ericksen’s notes, and (3) the sample contained

individuals with ages at death extending from young to mature adults.

The research sample ultimately consisted of 98 males and 102 females (Fig. 20),

and 191 White and 9 Black individuals (Fig. 21). The age range extends from a minimum

of 30 years of age at death to a maximum of 97 (Fig. 22), with an average age at death of

71 years. More specifically, the sample contains one individual who died in his thirties,

eight who died in their forties, 26 in their fifties, 54 in their sixties, 56 in their seventies,

46 in their eighties, and nine individuals who died in their nineties. Regarding causes of

death, one individual committed suicide, 38 individuals died of cancer, 103 died of heart

related disease, three of liver related disease, two of kidney related disease, seven of

respiratory failure, three of gastric or gastrointestinal ulcer, one of pancreatic disease, six

of pulmonary disease, two of pneumonia, two of complications from diabetes, two from

sepsis, and 12 from cerebrovascular accident or intracranial clot. Additionally, six

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individuals died from unique conditions and were thus placed in the ―Other‖ cause of

death category. Finally, 12 individuals had unknown causes of death (Fig. 23).

Figure 20. Bar chart illustrating the research sample female-to-male ratio.

Figure 21. Bar chart illustrating the research sample Black-to-White ratio.

64

Figure 22. Pie chart illustrating the age distribution of the research sample.

Figure 23. Pie chart illustrating the research sample cause of death distribution.

Decade of Death

65

B. METHODS

I. Removal of Bone Blocks from GWU Dissecting Room Cadavers

Ericksen extracted the femoral blocks at approximately midshaft (Fig. 24a). Slight

sampling location imprecision and inaccuracy are of little concern, however, because

between 35 and 65 percent of femoral length, negligible differences exist in medullary

and cortical areas (Stephenson and Seedhom, 1999). Only above 65 percent and below 35

percent does a rise in medullary area and reduction in cortical area occur. This finding

corroborates Kerley’s (1965: 162) statement that ―slides need not be made from the exact

middle of the shaft, since there is a block in the mid-shaft area that is about three inches

in length and is homogenous with regard to microscopic changes. Thus, badly fragmented

bones can be used as long as a cross-section can be obtained anywhere in the area of the

middle of the diaphysis‖ (see also Tersigni, 2005: 69).

Figure 24. (a) Removal of femoral midshaft blocks, (b) anatomical orientation and

scanning of prepared slides, (c) conversion of color scans to grayscale, (d) determination

of biomechanical and (e) anatomical axes, and (f) histological data collection from ROIs.

66

II. Slide Preparation Methodology at the NYC Office of Chief Medical Examiner

Histology Lab

Complete femoral midshaft bone wafers were cut from each of the 200 selected

bone blocks (Appendix A, shaded boxes) using a Buehler Isomet 1000 Precision

metallurgical saw. Once detached, the wafers were pressed, dried, and mounted to glass

slides with Permount Toluene Solution. The wafers were next reduced to approximately

75 μm using a Buehler Ecomet 4000 Grinder/Polisher affixed with Buehler Ultra-Prep

Diamond Grinding Discs. The slides were then sonic-cleansed to remove debris, cover-

slipped with Permount Toluene Solution, and dried in a Paramount-Labconco Ductless

Enclosure fume hood in preparation for analysis.

III. Determination of Anterior, Posterior, Medial, and Lateral Femoral Cortices

When viewing a femoral midshaft cross-section, anterior and posterior surfaces

are easily identified through the presence of the linea aspera. Medial and lateral surfaces,

however, are not easily distinguishable. Each prepared slide was therefore

morphologically aligned with the bone blocks from which it was cut. Using the black line

and specimen number printed on each block’s medial cortex, the 200 slides were oriented

into correct anatomical position. Once oriented, anterior, posterior, medial, and lateral

anatomical locations were marked on the glass slides in permanent ink (Fig. 24b).

IV. Determination of Biomechanical Axes and Collection of Biomechanical Data

A 1200 dpi resolution image of each of the 200 anatomically oriented slides was

obtained using an HP 4850 Scanner. Produced images were saved as jpegs to 200

individual digital folders. Each jpeg was then opened in Adobe Photoshop and the rotate

67

tool was utilized to orient each image as close to visual anatomical position as possible,

using the linea aspera as a guide. Next, ImageJ (v. 1.44), available as freeware at

http://rsb.info.nih.gov/ij/download.html, was opened and MomentMacroJ (v. 1.2) was

loaded. Each of the 200 femoral cross-sectional images oriented in visual anatomical

position was opened in ImageJ. Area outside the periosteal surface and trabecular bone

were removed using the drawing tools. The scanned color images of cortical bone only

were next converted to 8-bit grayscale images (Fig. 24c). The density threshold of each

image was then adjusted to provide an accurate estimation of cortical tissue. The wand

tool was used to select the external edge of the femoral cross-section. Finally, utilizing

the lower and upper threshold values previously determined, MomentMacroJ was run at

47.2 pixels per millimeter to draw the principle axes of maximum and minimum bending

rigidity on the image (Fig. 24d). This image was saved for each sample, as was the

associated output log, later imported into an Excel worksheet (Appendix B). This log

provides biomechanical data for each femoral cross-section including total subperiosteal

area (TA), cortical area (CA), medullary cavity area (MA), centroid coordinates Xbar and

Ybar, Ix, Iy, and J values, Imax and Imin values, Ix/Iy and Imax/Imin ratios, theta, Zx, Zy, and Zp

values, and MaxXrad and MaxYrad values.

V. Determination of Anatomical Axes

To determine exact, reproducible locations of anatomical axes in complete

femurs, Stephenson and Seedhom (1999: 160) defined the antero-posterior plane ―by

considering the femur lying dorsal side down on a flat surface, resting naturally on the

femoral condyles and the greater trochanter. Considering the shaft of the femur from

68

directly above, (i.e., the frontal plane), the anterior surface is in view. The antero-

posterior plane of the femur is perpendicular to the frontal plane and passes through the

mid-points of the shaft at a point approximately 15 cm proximal to the femoral condyles

and at a point slightly distal to the lesser trochanter. The medio-lateral plane is then

defined as being perpendicular to the antero-posterior plane passing through the mid-

points of the shaft. The longitudinal axis of the femur is then formed by the intersection

of these two planes.‖ Similarly, Ruff and Hayes (1983: 362–363) established the femoral

frontal plane ―by placing the bone, dorsal side down, on a flat surface and raising the

proximal end until the A-P midpoints of two locations on the shaft—just distal to the

lesser trochanter and just proximal to the distal condyles—are equidistant above the

supporting surface. In this position, the centers of articulation of the femoral condyles are

taken as the most distally projecting points on the condyle surfaces. The frontal plane is

then defined as a plane parallel to the supporting surface equidistant between the A-P

positions of the condylar centers. The sagittal plane of the femur is perpendicular to the

frontal plane, and contains the deepest point in the intercondylar notch and the M-L

midpoint of the shaft at the same proximal location used to establish the frontal plane.‖

A complete femur, though, is required to utilize the techniques presented by Ruff

and Hayes (1983) and Stephenson and Seedhom (1999). When working with fragmentary

remains and thin-sections removed from dissecting room cadavers, however, accurate and

precise determination of anatomical axes locations becomes problematic. No method for

anatomical axis standardization currently exists for disassociated sections; the various

femoral ROIs viewed for microscopic age at death estimation are therefore generally

imprecise (see Fig. 4). Given variation in femoral size and shape throughout the aging

69

process, standardized ROIs should be viewed to help improve repeatability and reduce

observer subjectivity. Therefore, to standardize anatomical axis locations from sample to

sample, both within and between observers so that useful remodeling patterns may be

uncovered, the A-P anatomical axis was geometrically determined by drawing a vertical

line, and the M-L axis by drawing a horizontal line, through the mathematically

determined section centroid (Fig. 24e).

VI. Collection of Cortical Thickness Data

Each femoral cross-sectional image with located biomechanical and anatomical

axes was once again opened in Adobe Photoshop and placed over a background that

standardizes measurement of every 22.5° of a circle (Appendix C). Using this technique,

ImageJ was used to measure cortical thickness at 16 places around each femoral cross-

section. Appendix D presents cortical thicknesses (in mm) obtained from the 200 femurs.

VII. Determination of Regions of Interest

Utilizing the A-P and M-L anatomical axes and the Imax and Imin biomechanical

axes drawn via Adobe Photoshop and ImageJ, respectively, eight exact and reproducible

histological sampling locations were determined wherever an axis crossed the bone’s

periosteal border: four anatomical—A (anterior), P (posterior), M (medial), L (lateral)—

and four biomechanical—ImaxAnt, ImaxPost, IminMed, and IminLat. To transfer the standardized

sampling locations from digital image to glass slide for histological analysis, each image

was printed at 100% of its actual size on white paper. This paper was placed beneath the

corresponding specimen’s clear slide so that the eight sampling locations could be

marked on the glass with ink. For each of the 200 glass slides with marked anatomical

70

and biomechanical axes, the eight locations where an axis crossed the bone’s periosteal

border were examined using an Olympus BX41 microscope with an Olympus DP72

mounted camera at 40x total (10x eyepiece × 4x) magnification. Overall, then, a total of

(200)(8) = 1600 3 mm2 regions of interest (ROIs) were observed (Fig. 24f).

Once this process was complete, each femoral sample had a digital file that

contained: (1) an original high-resolution color scan of the slide, (2) the image rotated

into visual anatomical position, (3) an image with drawn biomechanical axes, (4) the log

output of biomechanical data produced by ImageJ, and (5) a Photoshop image with A-P,

M-L, Imax, and Imin axes drawn over a background that standardizes cortical thickness

measurement. Additionally, three cumulative Excel files were created: one contained the

ImageJ outputs of all biomechanical data for each sample in the study (Appendix B),

another all cortical thickness measurements (Appendix D), and another all data collected

from histomorphometric analysis of each specimen’s standardized ROIs (Appendix E).

VIII. Collection of Histomorphometric Data at Standardized ROIs

To test the hypotheses that (1) topographical histomorphometric variation exists

around human femoral midshaft periosteal cortices, (2) ROIs associated with the Imin

second moment of area biomechanical axis exhibit the lowest remodeling rates, and (3)

bone remodeling at biomechanical ROIs (ImaxAnt, ImaxPost, IminMed, and IminLat) is

histomorphometrically more consistent than at anatomical ROIs (A, P, M, and L),

secondary osteons, fragmentary secondary osteons, and OPD were quantified at each

exact and reproducible femoral sampling location. Tests of intraobserver and

interobserver error were conducted (see Results).

71

A. Number of Secondary Osteons. Given how researchers differentially define basic

histomorphological structures, Heinrich and colleagues (2012) standardized the

definitions of intact and fragmentary secondary osteons for use in microscopic age at

death estimation in order to reduce observer error. These standardized definitions have

been utilized in this study for consistency.

An intact secondary osteon, in line with its biological function, is thus identified

as such when it has an intact Haversian canal and is bounded by a scalloped line

(Heinrich et al., 2012). Regarding when to count these structures, (1) where multiple

osteons are connected by a clearly defined Volkmann’s canal, each is counted separately,

(2) where two or more structures share a Haversian canal or scalloped reversal line, they

are counted as one osteon, (3) where it is impossible to determine whether a branching

event has occurred or whether they are connected by a Volkmann’s canal, one osteon is

counted, (4) hemiosteons specific to trabecular bone remodeling are not counted as

osteons, (5) secondary osteons found in trabecularized cortical bone are counted as

osteons, and (6) primary osteons are not counted as intact secondary osteons.

Within the category of secondary osteons, Type II, double zonal, and drifting

osteons pose challenges for the histomorphologist. Type II or embedded osteons form

when a portion of a preexisting Haversian canal remodels (intraosteonal remodeling),

possibly in response to the demands of mineral homeostasis. ―The completed type II

osteon appears as a small Haversian system—complete with a reversal line and

concentric lamellae—embedded completely within a larger, parent osteon‖ (Robling and

Stout, 2008: 154). When observed, Heinrich et al. (2012) suggest treating the peripheral

osteon as one fragment and the intact embedded structure as one secondary osteon.

72

Alternatively, double zonal osteons exhibit a ―hypercalcified ring within their

concentric lamellae, demarcating a point during the formation phase where matrix

elaboration temporarily ceased‖ possibly due to severe stress, similar to a Harris growth

arrest line or linear enamel hypoplasia (Stout, 1989: 48). These structures can be

distinguished from type II osteons by absence of scalloped reversal lines and presence of

concentric lamellae on either side of the arrest line. When observed, Heinrich and

colleagues (2012) suggest they be counted as only one intact secondary osteon.

Finally, ―drifting osteons form from BMUs that simultaneously travel

longitudinally and transversely through the cortex, a process that results in a transversely

elongated osteon exhibiting a hemicyclic lamellar tail‖ (Robling and Stout, 2008: 154).

Typically, Heinrich and colleagues (2012) suggest a drifting osteon be counted as one

intact secondary osteon, unless close observation reveals clear evidence of reversal lines

between an intact osteon and closely associated fragments that only give it the

appearance of a drifting osteon.

B. Number of Secondary Osteon Fragments. Similarly, a secondary osteon fragment is

identified when a secondary osteon with a partially visible Haversian canal has been

breached by a neighboring osteon or resorptive bay, or when a secondary osteon’s

Haversian canal is absent. Secondary osteon fragments are counted when (1) concentric

lamellae disassociated from a Haversian canal are surrounded by a scalloped edge, and

(2) when osteocytic lacunae are not parallel to those in surrounding structures.

C. Osteon Population Density. Finally, Stout has combined the density (number per

millimeter squared) of intact and fragmentary osteons to form the variable osteon

73

population density. Osteon population density ―represents all visible remains of past

cortical remodeling activity in a given cross-section of bone‖ (Stout, 1989: 48), and

minimizes ―errors due to different interpretations of what constitutes a complete or

fragmentary osteon‖ (Stout, 1989: 47). All secondary osteon, secondary osteon fragment,

and OPD data collected from the eight ROIs of each of the 200 femurs are summarized in

Appendix E and visualized in Appendix F.

74

CHAPTER FIVE: RESULTS

Although the data is cross-sectional and not longitudinal in nature, and thus,

cannot provide definitive information regarding cause and effect relationships, the

collected cortical thickness (Appendix D), biomechanical (Appendix B), and

histomorphometric data (Appendix E) were analyzed with SPSS Statistics 20.0 to identify

femoral periosteal ROIs best suited to reduce the standard error of microscopic age at

death estimates and prevent the OPD asymptote from being reached by ~50 years.

A. CORTICAL THICKNESS

Cortical thickness data was collected from 16 standardized locations [0°

(anterior), 22.5°, 45°, 67.5°, 90° (medial), 112.5°, 135°, 157.5°, 180° (posterior), 202.5°,

225°, 247.5°, 270° (lateral), 292.5°, 315°, and 337.5°] around each of the 200 analyzed

femoral cross-sections. Of the 3200 total cortical thickness measurements, five were

outliers, as evidenced by Figure 25. Nine of the 16 cortical thickness distributions were

abnormal as assessed by Shapiro-Wilk tests (p ≤ 0.05; Table 8), and the assumption of

homogeneity of variances was violated, as assessed by Levene’s test [(15, 3184) = 9.948,

p < 0.0005)]. Given the outliers, distribution abnormalities, and variance inequalities, an

independent samples Kruskal-Wallis test, the non-parametric alternative to the one-way

analysis of variance (ANOVA), was conducted to determine whether the 16 locations

differ with respect to average cortical thickness.

75

Figure 25. Boxplots of femoral cortical thicknesses (mm) at 16 standardized locations.

Table 8. Tests of Normality for the Cortical Thickness Measurements.

Group

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

0° .050 200 .200* .983 200 .017

22.5° .057 200 .200* .981 200 .008

45° .070 200 .018 .988 200 .081

67.5° .037 200 .200* .996 200 .928

90° .041 200 .200* .992 200 .297

112.5° .033 200 .200* .995 200 .740

135° .052 200 .200* .987 200 .070

157.5° .072 200 .014 .980 200 .006

180° .083 200 .002 .980 200 .005

202.5° .053 200 .200* .986 200 .044

225° .052 200 .200* .985 200 .027

247.5° .055 200 .200* .991 200 .229

270°

292.5

.059 200 .086 .990 200 .166

292.5° .078 200 .005 .986 200 .050

315° .080 200 .003 .979 200 .004

337.5° .052 200 .200* .983 200 .014 a Lilliefors Significance Correction

* This is a lower bound of the true significance

76

Results of the Kruskal-Wallis test indicate median cortical thickness differs

significantly around the femoral midshaft [X2(15) = 609.567, p < 0.0005]. Specifically,

post-hoc pairwise comparisons discovered 71 statistically significant differences between

median cortical thicknesses (p ≤ 0.05; Fig. 26). From these results, a general pattern

emerges where cortical thickness increases from the 0° location (Median = 4.146 mm) to

the 22.5° location (Median = 4.362 mm) to the 225° location (Median = 4.724 mm) to the

337.5° location (Median = 4.940 mm) to the 202.5° location (Median = 5.096 mm) to the

45° location (Median = 5.200 mm) to the 247.5° location (Median = 5.245 mm) to the

135° location (Median = 5.308 mm) to the 112.5° location (Median = 5.791 mm) to the

157.5° location (Median = 5.857 mm) to the 67.5° location (Median = 5.887 mm) to the

90° location (Median = 6.203 mm) to the 315° location (Median = 6.212 mm) to the 270°

location (Median = 6.431 mm) to the 180° location (Median = 6.820 mm) to the 292.5°

location (Median = 7.001 mm).

This pattern makes clear that the smallest median cortical thicknesses generally

occur in the anteromedial and posterolateral quadrants of the femoral midshaft.

Alternatively, the anterolateral quadrant possesses all of the largest cortical thicknesses,

with the one exception of the posterior 180° location (linea aspera). The posteromedial

quadrant is characterized by median cortical thicknesses between the low

anteromedial/posterolateral and high anterolateral values. These findings substantiate

those of Goldman and colleagues (2009: 59) who identified the AL-PM plane as the

average location of the Imax axis in adult modern humans.

77

Figure 26. Insignificant (black) and significant (gray) pairwise comparisons between

cortical thickness locations. Top number: cortical thickness location by degree. Bottom

number: each node shows the sample average rank of the group.

Having established that the 16 locations differ with respect to average cortical

thickness, the assumption of a linear association between the 16 cortical thickness

locations and age was next tested. Figure 27 provides evidence to suggest the

relationships are all linear.

78

Figure 27. Scatterplots showing the linear associations between the 16 cortical thickness

(mm) locations and age.

79

The 45°, 67.5°, 90°, 112.5°, 135°, 247.5°, and 270° data are normally distributed

as assessed by Shapiro-Wilk tests (p > 0.050; Table 8). Therefore, Pearson correlations

were used to measure the strengths of association between age and these cortical

thickness locations: moderately negative statistically significant correlations were

generally found (Table 9).

Table 9. Correlations Between Cortical Thickness Locations and Age.

Correlation Test Correlation with Age n p-value

0° Spearman’s rho -0.410** (Moderate) 200 < 0.0005

22.5° Spearman’s rho -0.411** (Moderate) 200 < 0.0005

45° Pearson -0.411** (Moderate) 200 < 0.0005

67.5° Pearson -0.377** (Moderate) 200 < 0.0005

90° Pearson -0.281** (Slight) 200 < 0.0005

112.5° Pearson -0.314** (Moderate) 200 < 0.0005

135° Pearson -0.352** (Moderate) 200 < 0.0005

157.5° Spearman’s rho -0.419** (Moderate) 200 < 0.0005

180° Spearman’s rho -0.405** (Moderate) 200 < 0.0005

202.5° Spearman’s rho -0.438** (Moderate) 200 < 0.0005

225° Spearman’s rho -0.463** (Moderate) 200 < 0.0005

247.5° Pearson -0.407** (Moderate) 200 < 0.0005

270° Pearson -0.347** (Moderate) 200 < 0.0005

292.5° Spearman’s rho -0.306** (Moderate) 200 < 0.0005

315° Spearman’s rho -0.298** (Slight) 200 < 0.0005

337.5° Spearman’s rho -0.375** (Moderate) 200 < 0.0005

** = Correlation is significant at the 0.01 level (2-tailed)

The 0°, 22.5°, 157.5°, 180°, 202.5°, 225°, 292.5°, 315°, and 337.5° data, however,

are not normally distributed as assessed by Shapiro-Wilk tests (p ≤ 0.050; Table 8). Since

the data are monotonic, however, Spearman’s rank order correlations were chosen to

measure the strengths of association between age and these cortical thickness locations:

moderately negative statistically significant correlations were generally found (Table 9).

80

Overall, cortical thickness was found to decrease with age. This finding is in line

with the work of Szulc and colleagues (2006) who documented increasing cortical

thinning in premenopausal (0.29 ± 0.85 percent/year), perimenopausal (0.66 ± 0.56

percent/year), and postmenopausal women (1.10 ± 1.06 percent/year), and Seeman

(2002) who documented a similar pattern in aging males. The negative correlations found

are significant for all cortices, but are highest for the 0°, 22.5°, 45° locations (anterior and

anteromedial femoral cortices) and the 157.5°, 180°, 202.5°, 225°, 247.5° locations

(posterior and posterolateral femoral cortices), and lowest for the 90°, 112.5°, 292.5°,

315° locations (medial and lateral femoral cortices). Therefore, cortical thickness is not

lost uniformly with age: Figure 28 illustrates how the anterior and posterior femoral

midshaft cortices lose more thickness beginning earlier than the medial/ lateral cortices.

Figure 28. Scatterplots of (a) anterior, (b) medial, (c) posterior, and (d) lateral femoral

midshaft cortical thicknesses (mm) with age. Lines are locally weighted scatterplot

smoothing (LOESS) curves.

a b

c d

81

B. BIOMECHANICS

Biomechanical data collected from each of the 200 analyzed femoral cross-

sections demonstrate how the femur slowly and steadily changes in size and shape, and

therefore rigidity and strength throughout adulthood. The first biomechanical variable

assessed is cortical area (CA), which has a linear association with age (Fig. 29).

Figure 29. Scatterplot showing the linear association between CA (mm2) and age.

The CA data, however, is not normally distributed as assessed by a Shapiro-Wilk test (p

= 0.005; Table 10). Since it is monotonic, however, Spearman’s rank order correlation

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was chosen to measure the strength of the association between age and CA. This test

indicates there is a moderately negative statistically significant correlation: rs (198) = -

0.371, p < 0.0005 (Table 11). Together, the statistics and graph suggest femoral midshaft

cross-sectional cortical area declines with age beginning in middle adulthood, indicating

decreased ability to resist deformation and fracture under pure tension and compression.

Table 10. Tests of Normality for the Biomechanical Variables.

Kolmogorov-Smirnov

a Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

CA .093 200 .000 .979 200 .005

MA .066 200 .032 .949 200 .000

TA .034 200 .200* .989 200 .134

Ix/Iy .039 200 .200* .997 200 .971

Theta .121 200 .000 .910 200 .000

Zp .071 200 .016 .979 200 .004 a Lilliefors Significance Correction

* This is a lower bound of the true significance

CA = cortical area, MA = medullary area, TA = total subperiosteal area, Ix/Iy = femoral

cross-sectional shape, Theta = orientation of Imax, Zp = polar section modulus

Table 11. Correlations Between Biomechanical Variables and Age.

Correlation Test Correlation with Age n p-value

CA Spearman’s rho -0.371** (Moderate) 200 < 0.0005

MA Spearman’s rho +0.387** (Moderate) 200 < 0.0005

TA Pearson -0.125 (Insignificant) 200 0.078

Ix/Iy Pearson -0.236** (Slight) 200 0.001

Theta Spearman’s rho -0.264** (Slight) 200 < 0.0005

Zp

Spearman’s rho -0.265** (Slight) 200 < 0.0005

** = Correlation is significant at the 0.01 level (2-tailed)

CA = cortical area, MA = medullary area, TA = total subperiosteal area, Ix/Iy = femoral

cross-sectional shape, Theta = orientation of Imax, Zp = polar section modulus

83

The second biomechanical variable assessed is medullary area (MA), which, like

cortical area, has a linear association with age (Fig. 30).

Figure 30. Scatterplot showing the linear association between MA (mm2) and age.

The MA data, however, is not normally distributed as assessed by a Shapiro-Wilk test (p

< 0.0005; Table 10). Since it is monotonic, however, Spearman’s rank order correlation

was chosen to measure the strength of the association between age and MA. This test

indicates there is a moderately positive statistically significant correlation: rs (198) =

0.387, p < 0.0005 (Table 11). Together, the statistics and graph suggest the expansion of

84

the medullary cavity is concomitant with cortical area reduction, both beginning in

middle age and continuing through mature adulthood.

The third biomechanical variable assessed is total subperiosteal area (TA), which

has a linear association with age (Fig. 31).

Figure 31. Scatterplot showing a linear association between age and total subperiosteal

area (mm2).

In addition to being linear, the TA data is also normally distributed as assessed by a

Shapiro-Wilk test (p = 0.134; Table 10). Therefore, Pearson correlation was used to

85

measure the strength of association between age and TA. This test indicates there is no

statistically significant relationship: r (198) = -0.125, p = 0.078 (Table 11). Instead, TA

appears to slightly decrease insignificantly throughout adulthood.

Altogether, cortical area reduction, medullary cavity expansion, and slightly

decreasing total subperiosteal area—all beginning in middle age and continuing through

mature adulthood— mirror the findings of Szulc and colleagues (2006) and Seeman

(2002) who showed periosteal apposition partially maintains cross-sectional area in the

face of increasing endosteal surface resorption in early and middle adulthood so that

resistance to loading is preserved. In later adulthood, however, periosteal apposition was

found to decline compared to endosteal resorption, and net bone loss was sustained.

The fourth biomechanical variable assessed is the Ix/Iy ratio, a femoral cross-

sectional shape indicator, which has a linear association with age (Fig. 32).

Figure 32. Scatterplot showing the linear association between the Ix/Iy ratio and age.

86

In addition to being linear, the Ix/Iy ratio data is also normally distributed as assessed by a

Shapiro-Wilk test (p = 0.971; Table 10). Therefore, Pearson correlation was used to

measure the strength of association between age and the Ix/Iy ratio. This test indicates

there is a slight negative statistically significant correlation: r (198) = -0.236, p = 0.001

(Table 11). Together, the statistics and graph suggest that femoral cross-sectional cortical

shape transforms throughout adulthood: the youngest adults in the study sample have the

most A-P elongated cortices, indicating frequent A-P bending loadings, a pattern that

develops with great workload and mobility (Ruff, 1987: 411). This shape is slowly lost so

that by mature adulthood, femoral cross-sections are nearly circular. Eventually, the

femoral cross-section Ix/Iy ratios dip below 1.0, indicating greatest elongation in the M-L

plane and overall reduced mobility (Ruff, 1987).

A fifth biomechanical variable assessed is theta. Theta is the angle (0–90º) formed

between the Imax biomechanical axis and the M-L anatomical axis. Since theta can be

positive or negative depending on Imax orientation, the absolute value of all theta values

was determined and plotted against age (Fig. 33). The relationship was found to be linear

but not normally distributed (p < 0.0005; Table 10). Thus, Spearman’s rank order

correlation was used to measure the strength of the association between theta and age.

This test indicates there is a slight negative statistically significant correlation: rs (198) = -

0.264, p < 0.0005 (Table 11): corroborating the Ix/Iy femoral shape data, the location of

theta approaches 0º, or the M-L anatomical axis, with increasing age (Fig. 34).

A final biomechanical variable assessed is the femoral polar section modulus, Zp,

which has a linear association with age (Fig. 35).

87

Figure 33. Scatterplot showing the linear association between the theta (º) and age.

Figure 34. The locations of the Imax biomechanical axis over the lifecycle of the femur

from toddler through mature adulthood. Modified from Goldman and colleagues (2009)

with permission from John Wiley and Sons.

88

Figure 35. Scatterplot of linear association between age and Zp (mm3).

The Zp data is not normally distributed, however, as assessed by a Shapiro-Wilk test (p =

0.004; Table 10). Therefore, Spearman’s rank order correlation was chosen to measure

the strength of the association between age and Zp. This test suggests there is a slight

negative statistically significant correlation: rs (198) = -0.265, p < 0.0005 (Table 11). In

association with marked cortical bone loss and M-L redistribution of cortical area with

age, this negative correlation between Zp and age indicates additional loss of femoral

robusticity and torsional and average bending strengths, or overall reduced resistance to

fracture in mature adulthood (Orwoll, 2003).

89

C. HISTOMORPHOMETRICS

I. Observer Error

The author collected secondary osteon, secondary osteon fragment, and OPD data

from 1600 ROIs (Intraobserver I group). Sixteen of those 1600 ROIs were then randomly

selected to test intraobserver error (Intraobserver II group). Recounts were conducted

between one week and three months after the initial Intraobserver I group counts. Those

same 16 ROIs that were randomly selected for tests of intraobserver error were also given

to a second experienced histomorphologist who was instructed to quantify secondary

osteons, secondary osteon fragments, and OPD (Interobserver I group). The raw data

from the observer error tests is provided in Table 12.

INDIV # ROI Osteons Frags OPD Osteons Frags OPD Osteons Frags OPD

19 ImaxPost 39 0 13.000 39 1 13.333 38 7 15.000

107 ImaxAnt 52 0 17.333 54 0 18.000 50 8 19.333

121 Anterior 44 0 14.667 44 0 14.667 38 4 14.000

130 IminMed 51 0 17.000 51 1 17.333 45 8 17.667

219 IminMed 40 0 13.333 40 0 13.333 37 4 13.667

252 IminLat 52 3 18.333 53 3 18.667 50 9 19.667

822 IminLat 51 0 17.000 50 0 16.667 42 4 15.333

823 ImaxPost 39 0 13.000 39 0 13.000 38 3 13.667

1017 ImaxAnt 44 1 15.000 44 1 15.000 40 13 17.667

1017 IminMed 48 0 16.000 48 0 16.000 43 6 16.333

1021 Medial 67 0 22.333 68 0 22.667 62 8 23.333

1026 Lateral 67 2 23.000 65 3 22.667 60 8 22.667

1122 IminMed 73 0 24.333 72 0 24.000 53 5 19.333

1214 Medial 55 0 18.333 54 0 18.000 48 2 16.667

1313 IminLat 50 0 16.667 50 0 16.667 43 4 15.667

1313 Lateral 55 4 19.667 55 4 19.667 50 12 20.667

Interobserver ErrorIntraobserver Error

Table 12. Intraobserver and Interobserver Error Raw Data.

90

Focusing only on total remodeling events (OPD), zero of the 48 OPD data points were

outliers, as assessed by inspection of Figure 36.

Figure 36. Boxplots of intraobserver and interobserver error data.

All data was further found to be normally distributed as assessed by Shapiro-Wilk tests (p

> 0.05; Table 13).

Table 13. Tests of Normality for the Observer Error Data.

Kolmogorov-Smirnov

a Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Intraobserver Error Test I .149 16 .200* .931 16 .252

Intraobserver Error Test II .127 16 .200* .932 16 .266

Interobserver Error Test I .113 16 .200* .940 16 .351 a Lilliefors Significance Correction

* This is a lower bound of the true significance

91

Mauchly’s tests of sphericity, however, indicated the groups do not have equal variances

[X2(2) = 43.330, p < 0.0005; Table 14].

Table 14. Test of Sphericity for the Observer Error Dataa.

Measure: OPD

Within

Subjects

Effect

Mauchly’s

W

Approx.

Chi-

Square

df Sig. Epsilonb

Greenhouse-

Geiser

Huynh-

Feldt

Lower-

bound

Observer .045 43.330 2 .000 .512 .514 .500

Tests the null hypothesis that the error covariance matrix of the orthonormalized

transformed dependent variables is proportional to an identity matrix

a. Design: Intercept

Within Subjects Design: Observer

b. May be used to adjust the degrees of freedom for the averaged tests of

significance. Corrected tests are displayed in the Tests of Within-Subjects

Effects table.

Without homogeneity of variances (ε = 0.512) the Greenhouse-Geiser correction was

applied to correct the degrees of freedom for the F-distribution (Table 15).

Table 15. Tests of Within-Subjects Effects for the Observer Error Data.

Measure: OPD

Source Type III

Sum of

Squares

df Mean

Square

F Sig. Partial

Eta2

Observer Sphericity Assumed .088 2 .044 .042 .959 .003

Greenhouse-Geiser .088 1.023 .086 .042 .846 .003

Huynh-Feldt .088 1.028 .086 .042 .847 .003

Lower-bound .088 1.000 .088 .042 .841 .003

Error

(Observer)

Sphericity Assumed 31.616 30 1.054

Greenhouse-Geiser 31.616 15.347 2.060

Huynh-Feldt 31.616 15.423 2.050

Lower-bound 31.616 15.000 2.108

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Once corrected, a repeated measures ANOVA was used to determine whether or not the

group means were equal. The results indicate the three groups’ OPD means are

statistically insignificantly different [F (1.023, 15.347) = 0.042, p = 0.846], although

mean OPD did increase slightly from Intraobserver I (17.438 ± 0.871) to Intraobserver II

(17.479 ± 0.854) to Interobserver I (17.542 ± 0.764; Table 16).

Table 16. Intraobserver and Interobserver Error Test Descriptives.

Measure: OPD

Observer Mean Std. Error 95% Confidence Interval

Lower Bound Upper Bound

Intraobserver I 17.438 .871 15.582 19.293

Intraobserver II 17.479 .854 15.659 19.300

Interobserver I 17.542 .764 15.913 19.171

II. Hypothesis Testing

NULL HYPOTHESIS #1: There are no statistically significant differences between

ROI OPD means.

ALTERNATIVE HYPOTHESIS #1: Topographical variation in remodeling exists

around human femoral midshaft periosteal cortices. There are statistically

significant differences between ROI OPD means.

To test this first hypothesis, all collected OPD data sets were analyzed. Twenty-

three of the 1600 data points are outliers, as assessed by inspection of Figure 37. Twenty-

one of those outliers lay more than 1.5 box-lengths from their associated box edges and

are illustrated as circular dots. Additionally, there are two extreme outliers more than 3

box-lengths away from their associated box edges illustrated by asterisks. More

93

specifically, the Anterior and IminLat ROIs each contain one outlier, the IminMed ROI

displays seven outliers, and the remaining ROIs all show between two and four outliers.

Figure 37. Boxplots of all OPD (mm2) data organized by region of interest.

In addition to possessing outliers, the OPD data was also not normally distributed

overall as assessed by Shapiro-Wilk tests (p ≤ 0.050; Table 17). Three of the eight ROIs

(Medial, ImaxPost, and IminMed) have significances greater than 0.050 indicating their OPD

values are normally distributed. The Anterior, Posterior, Lateral, ImaxAnt, and IminLat ROIs,

however, have p-values less than 0.050 indicating normality has been violated.

94

Table 17. Tests of Normality for the Original OPD Data by ROI.

Kolmogorov-Smirnov

a Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Anterior .061 200 .070 .983 200 .014

Posterior .071 200 .016 .974 200 .001

Medial .050 200 .200* .989 200 .116

Lateral .049 200 .200* .972 200 .001

ImaxAnt .062 200 .060 .981 200 .009

ImaxPost .059 200 .089 .991 200 .254

IminMed .053 200 .200* .988 200 .097

IminLat .069 200 .021 .983 200 .014 a Lilliefors Significance Correction

* This is a lower bound of the true significance

Transforming the data by taking the square root of the OPD values was attempted

and removed some non-normality issues, created some new non-normalities, and 18

outliers remained afterwards. Transforming the data by taking the log10 of the OPD

values was attempted and also removed some non-normality issues, created some new

non-normalities, and 22 outliers were still present afterwards. Finally, transforming the

data by taking the inverse of the OPD values only exacerbated the non-normality

problems and produced more outliers than the original data contained.

Overall, transformation was not successful at normalizing the OPD data set.

Therefore, in a different approach, the 23 outliers were excluded from the data and the

boxplots reassessed. Four new outliers were present. Once the four were removed, only a

single outlier persisted. Finally, after removing the single outlier [28 data sets total

(1.75% of the data); 1572 data sets retained], no outliers remained, as evidenced by

inspection of Figure 38.

95

Figure 38. Boxplots of OPD data (mm2; 28 outliers excluded) organized by region of

interest.

With outliers excluded, OPD data at each ROI was found to be normally distributed, as

assessed by Shapiro-Wilk tests (p > 0.05; Table 18).

96

Table 18. Tests of Normality for the OPD Data (Outliers Excluded) by ROI.

OPD Group Kolmogorov-Smirnov

a Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Anterior .054 198 .200* .993 198 .504

Posterior .051 194 .200* .990 194 .189

Medial .033 197 .200* .997 197 .954

Lateral .052 198 .200* .993 198 .489

ImaxAnt .056 195 .200* .994 195 .552

ImaxPost .052 198 .200* .989 198 .146

IminMed .043 193 .200* .993 193 .509

IminLat .067 199 .032 .990 199 .187 a Lilliefors Significance Correction

* This is a lower bound of the true significance

Levene’s tests [(7, 1564) = 1.403, p = 0.200] indicate that without outliers, the normally

distributed groups also have equal variances. With homogeneity of variances, the results

of the one-way ANOVA are valid: mean OPD is statistically significantly different

between ROIs [Welch’s F (7, 1564) = 18.069, p < 0.0005]. Specifically, Tukey’s post-

hoc pairwise comparisons revealed 15 statistically significant differences between ROI

OPD means (Table 19). From these results, a general pattern emerges (Fig. 39) where

mean OPD increases from the Anterior ROI group (17.209 ± 3.56) to the Posterior ROI

group (17.658 ± 3.780) to the IminMed ROI group (17.924 ± 3.627) to the ImaxAnt ROI group

(18.532 ± 4.084) to the ImaxPost ROI group (18.557 ± 3.778) to the Medial ROI group

(19.228 ± 3.857) to the IminLat ROI group (19.489 ± 4.118) to the Lateral ROI group

(20.865 ± 4.041). It is therefore evident from these results that topographical variation in

remodeling exists around adult human femoral midshaft periosteal cortices resulting from

normal anatomical development, customary biomechanical usage, and standard

mechanobiological functioning. The first null hypothesis is rejected.

97

Table 19. Statistically Significant Differences Between ROI OPD Means

(Outliers Excluded).

1 OPD increases from the Anterior ROI group (17.209 ± 3.56) to the Medial ROI

group (19.228 ± 3.857), an increase of 2.020 (95% CI, 0.840 to 3.199; p = 0.000).

2 OPD increases from the Posterior ROI group (17.658 ± 3.780) to the Medial ROI

group (19.228 ± 3.857), an increase of 1.576 (95% CI, 0.390 to 2.761; p = 0.001).

3 OPD increases from the IminMed ROI group (17.924 ± 3.627) to the Medial ROI

group (19.228 ± 3.857), an increase of 1.304 (95% CI, 0.118 to 2.491; p = 0.20).

4 OPD increases from the Anterior ROI group (17.209 ± 3.56) to the Lateral ROI

group (20.865 ± 4.041), an increase of 3.657 (95% CI, 2.479 to 4.834; p = 0.000).

5 OPD increases from the Posterior ROI group (17.658 ± 3.780) to the Lateral ROI

group (20.865 ± 4.041), an increase of 3.212 (95% CI, 2.029 to 4.396; p = 0.000).

6 OPD increases from the Medial ROI group (19.228 ± 3.857) to the Lateral ROI

group (20.865 ± 4.041), an increase of 1.637 (95% CI, 0.458 to 2.816; p = 0.001).

7 OPD increases from the ImaxAnt ROI group (18.532 ± 4.084) to the Lateral ROI

group (20.865 ± 4.041), an increase of 2.333 (95% CI, 1.151 to 3.516; p = 0.000).

8 OPD increases from the ImaxPost ROI group (18.557 ± 3.778) to the Lateral ROI

group (20.865 ± 4.041), an increase of 2.308 (95% CI, 1.130 to 3.486; p = 0.000).

9 OPD increases from the IminMed ROI group (17.924 ± 3.627) to the Lateral ROI

group (20.865 ± 4.041), an increase of 2.941 (95% CI, 1.760 to 4.127; p = 0.000).

10 OPD increases from the IminLat ROI group (19.489 ± 4.118) to the Lateral ROI

group (20.865 ± 4.041), an increase of 1.376 (95% CI, 0.199 to 2.553; p = 0.009).

11 OPD increases from the Anterior ROI group (17.209 ± 3.56) to the ImaxAnt ROI

group (18.532 ± 4.084), an increase of 1.323 (95% CI, 0.141 to 2.505; p = 0.016).

12 OPD increases from the Anterior ROI group (17.209 ± 3.56) to the ImaxPost ROI

group (18.557 ± 3.778), an increase of 1.348 (95% CI, 0.171 to 2.526; p = 0.012).

13 OPD increases from the Anterior ROI group (17.209 ± 3.56) to the IminLat ROI

group (19.489 ± 4.118), an increase of 2.280 (95% CI, 1.104 to 3.457; p = 0.000).

14 OPD increases from the Posterior ROI group (17.658 ± 3.780) to the IminLat ROI

group (19.489 ± 4.118), an increase of 1.836 (95% CI, 0.654 to 3.019; p = 0.000).

15 OPD increases from the IminMed ROI group (17.924 ± 3.627) to the IminLat ROI

group (19.489 ± 4.118), an increase of 1.565 (95% CI, 0.381 to 2.750; p = 0.002).

98

Figure 39. Bar chart demonstrating mean OPDs (mm2) by ROI (outliers excluded).

To test the effect of removing the outliers on the final results, the same test was

run with all outliers included. The OPD data was therefore not normally distributed

overall, as assessed by Shapiro-Wilk tests (p ≤ 0.050; Table 17). Three of the eight ROIs

(Medial, ImaxPost, and IminMed) have significances greater than 0.050 indicating their OPD

values are normally distributed. The Anterior, Posterior, Lateral, ImaxAnt, and IminLat ROIs,

however, have p-values less than 0.050 indicating the assumption of normality has been

violated. Levene’s Test of homogeneity of variance (7, 1592) = 1.100, p = 0.360),

though, indicates the eight groups have equal variances. Therefore, since the one-way

99

ANOVA is fairly robust to violations of normality—it requires only approximately

normal data with an equal number of cases in each group—no further modifications to

the one-way ANOVA were required and the results are valid: mean OPD is statistically

significantly different between ROIs [Welch’s F (7, 1592) = 15.035, p < 0.0005].

Specifically, Tukey’s post-hoc pairwise comparisons again discovered 15 statistically

significant differences between ROI OPD means (Table 20). While this was the same

result produced from the ANOVA conducted with outliers excluded, a slightly different

general pattern emerges when outliers are included (Fig. 40) where mean OPD increases

from the Anterior ROI group (17.340 ± 3.79) to the IminMed ROI group (17.945 ± 4.168) to

the Posterior ROI group (18.020 ± 4.275) to the ImaxPost ROI group (18.677 ± 3.943) to

the ImaxAnt ROI group (18.865 ± 4.548) to the Medial ROI group (19.305 ± 4.220) to the

IminLat ROI group (19.581 ± 4.311) to the Lateral ROI group (21.033 ± 4.378).

Regardless, running the ANOVA with outliers included again produces the same overall

results: the first null hypothesis is rejected, and topographical variation in remodeling

around adult human femoral midshaft periosteal cortices resulting from normal

anatomical development, customary biomechanical usage, and standard

mechanobiological functioning is accepted.

100

Table 20. Statistically Significant Differences Between ROI OPD Means

(Outliers Included).

1 OPD increases from the Anterior ROI group (17.340 ± 3.79) to the Medial ROI

group (19.305 ± 4.220), an increase of 1.965 (95% CI, 0.687 to 3.243; p = 0.000).

2 OPD increases from the Posterior ROI group (18.020 ± 4.275) to the Medial ROI

group (19.305 ± 4.220), an increase of 1.285 (95% CI, 0.007 to 2.563; p = 0.048).

3 OPD increases from the IminMed ROI group (17.945 ± 4.168) to the Medial ROI

group (19.305 ± 4.220), an increase of 1.360 (95% CI, 0.082 to 2.638; p = 0.028).

4 OPD increases from the Anterior ROI group (17.340 ± 3.79) to the Lateral ROI

group (21.033 ± 4.378), an increase of 3.693 (95% CI, 2.416 to 4.971; p = 0.000).

5 OPD increases from the Posterior ROI group (18.020 ± 4.275) to the Lateral ROI

group (21.033 ± 4.378), an increase of 3.013 (95% CI, 1.736 to 4.291; p = 0.000).

6 OPD increases from the Medial ROI group (19.305 ± 4.220) to the Lateral ROI

group (21.033 ± 4.378), an increase of 1.728 (95% CI, 0.451 to 3.006; p = 0.001).

7 OPD increases from the ImaxAnt ROI group (18.865 ± 4.548) to the Lateral ROI

group (21.033 ± 4.378), an increase of 2.168 (95% CI, 0.891 to 3.446; p = 0.000).

8 OPD increases from the ImaxPost ROI group (18.677 ± 3.943) to the Lateral ROI

group (21.033 ± 4.378), an increase of 2.357 (95% CI, 1.079 to 3.634; p = 0.000).

9 OPD increases from the IminMed ROI group (17.945 ± 4.168) to the Lateral ROI

group (21.033 ± 4.378), an increase of 3.088 (95% CI, 1.811 to 4.366; p = 0.000).

10 OPD increases from the IminLat ROI group (19.581 ± 4.311) to the Lateral ROI

group (21.033 ± 4.378), an increase of 1.452 (95% CI, 0.174 to 2.729; p = 0.013).

11 OPD increases from the Anterior ROI group (17.340 ± 3.79) to the ImaxAnt ROI

group (18.865 ± 4.548), an increase of 1.525 (95% CI, 0.247 to 2.803; p = 0.007).

12 OPD increases from the Anterior ROI group (17.340 ± 3.79) to the ImaxPost ROI

group (18.677 ± 3.943), an increase of 1.337 (95% CI, 0.059 to 2.614; p = 0.033).

13 OPD increases from the Anterior ROI group (17.340 ± 3.79) to the IminLat ROI

group (19.581 ± 4.311), an increase of 2.242 (95% CI, 0.964 to 3.519; p = 0.000).

14 OPD increases from the Posterior ROI group (18.020 ± 4.275) to the IminLat ROI

group (19.581 ± 4.311), an increase of 1.562 (95% CI, 0.284 to 2.839; p = 0.005).

15 OPD increases from the IminMed ROI group (17.945 ± 4.168) to the IminLat ROI

group (19.581 ± 4.311), an increase of 1.637 (95% CI, 0.359 to 2.914; p = 0.003).

101

Figure 40. Bar chart demonstrating mean OPDs (mm2) by ROI (outliers included).

Finally, to test the validity of the ANOVA test results (conducted with outliers

excluded and included), a Kruskal-Wallis test, the non-parametric alternative to the one-

way ANOVA, was conducted. Similar to the two ANOVAs, results from the Kruskal-

Wallis non-parametric test also indicate OPD differs significantly between ROIs [X2(7) =

99.366, p < 0.0005]. Specifically, post-hoc pairwise comparisons conducted using

Dunn’s (1964) procedure with a Bonferroni correction for multiple comparisons revealed

14 statistically significant differences between ROI OPD medians (Table 21). Figure 41

also indicates the statistically significant pairwise comparisons in light gray.

102

Table 21. Statistically Significant Differences Between ROI OPD Medians

(Kruskal-Wallis Test).

1 OPD increases from the Anterior ROI group (Median = 17.000) to the ImaxPost ROI

group (Median = 18.500) (p = 0.025).

2 OPD increases from the Anterior ROI group (Median = 17.000) to the ImaxAnt ROI

group (Median = 18.500) (p = 0.017).

3 OPD increases from the Anterior ROI group (Median = 17.000) to the Medial ROI

group (Median = 19.334) (p = 0.000).

4 OPD increases from the Anterior ROI group (Median = 17.000) to the IminLat ROI

group (Median = 19.000) (p = 0.000).

5 OPD increases from the Anterior ROI group (Median = 17.000) to the Lateral ROI

group (Median = 21.000) (p = 0.000).

6 OPD increases from the Posterior ROI group (Median = 17.667) to the Medial ROI

group (Median = 19.334) (p = 0.015).

7 OPD increases from the Posterior ROI group (Median = 17.667) to the IminLat ROI

group (Median = 19.000) (p = 0.003).

8 OPD increases from the Posterior ROI group (Median = 17.667) to the Lateral ROI

group (Median = 21.000) (p = 0.000).

9 OPD increases from the IminMed ROI group (Median = 18.000) to the IminLat ROI

group (Median = 19.000) (p = 0.012).

10 OPD increases from the IminMed ROI group (Median = 18.000) to the Lateral ROI

group (Median = 21.000) (p = 0.000).

11 OPD increases from the ImaxPost ROI group (Median = 18.500) to the Lateral ROI

group (Median = 21.000) (p = 0.000).

12 OPD increases from the ImaxAnt ROI group (Median = 18.500) to the Lateral ROI

group (Median = 21.000) (p = 0.000).

13 OPD increases from the Medial ROI group (Median = 19.334) to the Lateral ROI

group (Median = 21.000) (p = 0.009).

14 OPD increases from the IminLat ROI group (Median = 19.000) to the Lateral ROI

group (Median = 21.000) (p = 0.045).

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Figure 41. Insignificant (black) and significant (gray) pairwise comparisons between ROI

OPD medians. Top row: Region of interest. Bottom row: each node shows the sample

average rank of the group.

Use of the Kruskal-Wallis test produced one less significant difference between

ROI OPDs than the ANOVA tests. Additionally, a slightly different general pattern

emerges (Fig. 42) where OPD increases from the Anterior ROI group (Median = 17.000)

to the Posterior ROI group (Median = 17.667) to the IminMed ROI group (Median =

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18.000) to the ImaxPost and ImaxAnt ROI groups (Medians = 18.500) to the IminLat ROI group

(Median = 19.000) to the Medial ROI group (Median = 19.334) to the Lateral ROI group

(Median = 21.000). Regardless, the Kruskal-Wallis test again produces the same overall

result: the first null hypothesis is rejected and topographical variation in remodeling

around adult human femoral midshaft periosteal cortices resulting from normal

anatomical development, customary biomechanical usage, and standard

mechanobiological functioning is accepted.

Figure 42. Bar chart demonstrating statistically significantly different median OPDs

(mm2) by ROI (results of Kruskal-Wallis test).

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NULL HYPOTHESIS #2: There is no evidence Imin ROI OPD means are statistically

significantly reduced compared to the other six ROI OPD means.

ALTERNATIVE HYPOTHESIS #2: Imin ROI OPD means are statistically

significantly reduced compared to the other six ROI OPD means as a result of

minimal biomechanical loading.

Results of the Kruskal-Wallis non-parametric test indicate OPD differs

significantly between ROIs, X2(7) = 99.366, p < 0.0005 and OPD increases from the

Anterior ROI (Median = 17.000) to the Posterior ROI (Median = 17.667) to the IminMed

ROI (Median = 18.000) to the ImaxAnt and ImaxPost ROIs (Medians = 18.500) to the IminLat

ROI (Median = 19.000) to the Medial ROI (Median = 19.334) to the Lateral ROI

(Median = 21.000). Based on the ordering of these results, the second null hypothesis of

no evidence for reduced remodeling at Imin ROIs is accepted. There is no evidence for

reduced remodeling at Imin locations as compared with the other ROIs. Similarly, there is

no evidence for enhanced remodeling at Imax ROIs, likely because the location of the Imax

biomechanical axis was found to shift throughout adulthood.

NULL HYPOTHESIS #3: There are no statistically significant differences between

biomechanical and anatomical ROI OPD SEEs.

ALTERNATIVE HYPOTHESIS #3: Biomechanical ROI (ImaxAnt, ImaxPost, IminMed,

and IminLat) OPD SEEs will be histomorphometrically more consistent than OPD

SEEs of anatomical ROIs (A, P, M, and L) due to femoral functional constraints.

To test this hypothesis, the assumption of a linear association between OPD and

age was first investigated. Figure 43 provides evidence to suggest the association is

approximately linear at all ROIs. The Medial, ImaxPost, and IminMed data are also normally

distributed as assessed by Shapiro-Wilk tests (p > 0.05; Table 17).

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Figure 43. Scatterplots of the linear associations between OPD (mm2) and age by ROI.

Gray lines are locally weighted scatterplot smoothing (LOESS) curves.

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Therefore, Pearson correlations were used to measure the strengths of association

between age and these OPDs. Spearman’s rank order correlations were chosen to

measure the strengths of association between age and the non-normally distributed

Anterior, Posterior, Lateral, ImaxAnt, and IminLat ROI OPD data (Table 17). These tests

revealed the Lateral, IminMed, and IminLat ROI OPD values to be insignificantly correlated

with age (Table 22). Further, LOESS curves plotted through all ROI OPD data (Fig. 43)

indicate OPD remains constant at the Anterior, ImaxAnt, Medial, IminMed, Lateral, and IminLat

ROIs after approximately 45 to 50 years of age. These findings resonate with the work of

Frost (1987b), Stout and colleagues (1994), and Robling and Stout (2000), who found

OPD ultimately increases in a quadratic nonlinear way: ―OPD increases with advancing

age until an asymptote is reached—a point at which subsequent osteon creations remove

all evidence of previous ones. When the cortex reaches asymptote, OPD cannot increase

anymore‖ (Robling and Stout, 2008: 153). The Posterior and ImaxPost ROI OPD values,

however, appear to continue to increase slightly throughout mature adulthood.

Table 22. Correlations Between ROI OPD Data and Age.

Correlation Test Correlation with Age n p-value

Anterior OPD Spearman’s rho 0.166* (Slight) 200 0.019

Posterior OPD Spearman’s rho 0.164* (Slight) 200 0.019

Medial OPD Pearson 0.205** (Slight) 200 0.004

Lateral OPD Spearman’s rho 0.014 (Insignificant) 200 0.849

ImaxAnt OPD Spearman’s rho 0.188 (Slight) 200 0.008

ImaxPost OPD Pearson 0.293** (Slight) 200 <0.0005

IminMed OPD Pearson 0.113 (Insignificant) 200 0.111

IminLat OPD Spearman’s rho -0.024 (Insignificant) 200 0.731

* = Correlation is significant at the 0.05 level (2-tailed)

** = Correlation is significant at the 0.01 level (2-tailed)

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It was next questioned how well age could be predicted based on ROI OPD

values. Linear regression provides valid answers since the linearity of the age and OPD

relationship has been demonstrated (Fig. 43); the Durbin-Watson statistics indicate the

OPD data display little correlation between residuals (there is independence of errors);

there is homoscedasticity of residuals (variances of the errors are constant across

observations) as assessed by scatterplots; and the residuals are normally distributed as

assessed by histograms and Normal P-P plots.

Overall, the linear regression results presented in Tables 23 and 24 and the 95%

confidence and prediction intervals displayed in Figure 44 indicate OPD values can

statistically significantly predict age at the Anterior, Posterior, Medial, ImaxAnt, and ImaxPost

ROIs. For example, Posterior ROI OPD values statistically significantly predict age [F (1,

198) = 5.476, p = 0.020], and OPD accounts for 2.2% of the variability in age at that

location. Further, a regression equation is produced where Age = 63.044 + (0.453 ×

Post_OPD) ± 11.60 years (SEE).

Table 23. ROI OPD Linear Regression Data.

ROI Durbin

Watson

ANOVA Results p-value Adjusted R

Square

Anterior 1.502 F (1, 198) = 4.250 0.041 1.6%

Posterior 1.535 F (1, 198) = 5.476 0.020 2.2%

Medial 1.519 F (1, 198) = 8.699 0.004 3.7%

Lateral 1.565 F (1, 198) = 0.529 0.468 -0.2%

ImaxAnt 1.516 F (1, 198) = 9.072 0.003 3.9%

ImaxPost 1.513 F (1,198) = 18.588 <0.0005 8.1%

IminMed 1.550 F (1, 198) = 2.564 0.111 0.8%

IminLat 1.563 F (1, 198) = 0.115 0.735 -0.4%

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Table 24. ROI OPD Linear Regression Data (Continued).

ROI Regression Equation: AGE = SEE 95% CI 95% PI

Anterior 62.851 + (0.468 × Ant_OPD) ±12.10 16.841–17.907 9.850–24.830

Posterior 63.044 + (0.453 × Post_OPD) ±11.60 17.456–18.647 9.568–26.472

Medial 59.690 + (0.587 × Med_OPD) ±11.84 18.717–19.893 10.962–27.648

Lateral 68.023 + (0.142 × Lat_OPD) ±12.08 20.423–21.644 12.379–29.688

ImaxAnt 60.539 + (0.555 × ImaxAnt_OPD) ±11.83 18.231–19.499 9.873–27.857

ImaxPost 54.269 + (0.897 × ImaxPost_OPD) ±11.60 18.127–19.226 10.882–26.471

IminMed 65.141 + (0.327 × IminMed_OPD) ±12.02 17.364–18.526 9.705–26.185

IminLat 72.336 + (-0.067 × IminLat_OPD) ±12.09 18.981–20.183 11.059–28.104

Of the five ROIs where OPD values can statistically significantly predict age, the

Posterior and ImaxPost ROIs have the smallest SEEs, followed by the ImaxAnt, Medial,

IminMed, Lateral, IminLat, and Anterior ROIs, in that order. This ordering indicates bone

remodeling at biomechanical ROIs (ImaxAnt, ImaxPost, IminMed, and IminLat) is

histomorphometrically neither more nor less consistent than at anatomical ROIs (A, P, M,

and L). The third null hypothesis is accepted. Again, this is likely because the location of

the Imax biomechanical axis was found to shift throughout adulthood.

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Figure 44. Scatterplots with 95% confidence and prediction intervals for age by ROI.

111

CHAPTER SIX: DISCUSSION AND CONCLUSION

In development of the first microscopic age at death estimation technique, Ellis R.

Kerley chose sampling locations from the anterior, posterior, medial, and lateral

anatomical axes of each femoral cross section that were “fairly representative of the

particular anatomic area of the section being examined,” (Kerley, 1965: 154) and

analyzed each to “minimize the likelihood of basing the age estimate on a single atypical

field” (Kerley, 1965: 162). Four years later, however, Ahlqvist and Damsten (1969: 208)

extended a warning for histomorphologists to avoid sampling the posterior area around

the linea aspera because “in this part of the bone there seems to be a somewhat greater

variation in osteons and osteon fragments not correlated to age than in other parts,

possibly because of the powerful muscle insertions on the femoral crest.” This

unsubstantiated warning resulted in the posterior femoral cortex being disregarded and

the anterior femoral cortex becoming the standard sampling location utilized in most

subsequently published microscopic age at death estimation techniques (see Fig. 4).

The results of the femoral histomorphometric patterning research summarized

here, however, ultimately refute Ahlqvist and Damstesn’s (1969) claim and suggest

further research should be conducted on the posterior femoral cortex:

First, median cortical thickness differs significantly around the femoral midshaft.

Post-hoc pairwise comparisons discovered 71 statistically significant differences that

together reveal the thinnest median cortices occur in the anteromedial and posterolateral

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quadrants of the femoral midshaft, and the thickest cortices occur in the anterolateral

quadrant, with the one exception of the posterior 180° linea aspera location.

Second, cortical thickness decreases with age. This negative correlation is

significant for all cortices, but is strongest for the anterior, anteromedial, posterior, and

posterolateral femoral cortices, and weakest for the medial and lateral femoral cortices.

Cortical thickness is therefore not lost uniformly with age. Rather, more thickness is lost

over a longer duration from the anterior and posterior femoral midshaft cortices, and the

medial and lateral cortices lose less thickness and only later in life.

Third, cross-sectional cortical area declines with age, concomitant with expansion

of the medullary cavity, beginning in middle age and continuing through mature

adulthood. Total subperiosteal area also decreases with increasing age, resulting in

reduced ability to resist deformation and fracture under pure tension and compression.

Fourth, Imax shifts and femoral cross-sectional cortical shape transforms

throughout adulthood from presenting A-P elongated cortices in young adults, to nearly

circular cross-sections in middle adults, to M-L elongated cortices in mature adults.

Fifth, Zp decreases with age indicating loss of femoral robusticity and torsional

and average bending strengths, or overall reduced resistance to fracture.

Sixth, 14 statistically significant differences were discovered between ROI OPD

medians indicating topographical variation in remodeling exists around adult human

femoral midshaft periosteal cortices. Specifically, the lowest OPD values occur at the

Anterior ROI, followed by the Posterior, IminMed, ImaxPost, ImaxAnt, IminLat, Medial, and

Lateral ROIs, in that order.

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Seventh, no evidence was found for reduced remodeling at IminMed and IminLat or

enhanced remodeling at ImaxAnt and ImaxPost as compared with other ROIs, likely because

the locations of the biomechanical axes were found to shift throughout adulthood.

Eighth, OPD remains constant after approximately 45 to 50 years at the Anterior,

ImaxAnt, Medial, IminMed, Lateral, and IminLat ROIs. This finding suggests the anterior,

medial, and lateral femoral cortical regions simultaneously reach the OPD asymptote.

Only the posterior ROIs appear to continue to increase through mature adulthood.

Ninth, OPD values can statistically significantly predict age at the Anterior,

Posterior, Medial, ImaxAnt, and ImaxPost ROIs. The Posterior and ImaxPost ROIs are associated

with the smallest SEEs, however, followed by the ImaxAnt, Medial, IminMed, Lateral, IminLat,

and Anterior ROIs, in that order. This ordering indicates bone remodeling at

biomechanical ROIs is neither more nor less histomorphometrically consistent than bone

remodeling at anatomical ROIs, again, likely because the locations of the biomechanical

axes were found to shift throughout adulthood.

Finally, the SEEs associated with each of the eight standardized ROIs are, for all

practical purposes, comparable to the SEEs produced by studies of the anterior femoral

cortex with similarly large sample sizes (e.g., Ericksen, 1991; Crowder and Dominguez,

2012). Together, however, the results presented here specify the ROI best suited for

microscopic age at death estimation is not located on the traditionally sampled anterior

femoral cortex. In fact, the results present a strong argument for why the anterior cortex

is poorly suited for use in microscopic estimation of age at death. First, the anteromedial

quadrant displays some of the thinnest median cortices that occur around the femoral

midshaft. This is an undesirable trait in microscopic age at death estimation as the

114

thinnest cortices will likely reach the OPD asymptote first. Second, while cortical

thickness decreases with age at all cortices, the anterior cortex loses more thickness more

rapidly than the medial and lateral cortices. This is also an undesirable trait in

microscopic age at death estimation because a rapidly declining cortex increases the

likelihood of sampling the encroaching endosteal envelope and producing an elevated age

at death. Third, while the lowest OPD values are found at the Anterior ROI, evidence

suggests this may be due to formation of larger osteons as a result of low strain levels,

since the OPD asymptote is reached there at approximately 50 years of age. Again, this is

undesirable in microscopic age at death estimation as OPD then becomes a poor predictor

of older ages. Finally, the Anterior ROI possesses the highest SEE of any ROI, thus

producing the most imprecise age predictions.

Alternatively, although the posterior section of the femur has been avoided since

Ahlqvist and Damsten’s (1969) article, a strong argument can be made for why this area

of the femoral cortex is best suited for microscopic age at death estimation. First, the

posterior 180° linea aspera location possesses the second largest median cortical

thickness after the anterolateral 292.5º location. A thick cortex is a desirable trait in

microscopic age at death estimation as an increase in cortical area provides more space

for remodeling events before the OPD asymptote is reached, ultimately later in life than a

thin cortex. Second, although the posterior cortex loses more thickness more rapidly than

the medial and lateral cortices, meaning there should be a greater chance of sampling the

encroaching endosteal envelope and producing an elevated age at death estimate, review

of all Appendix C images suggests the linea aspera remains relatively well developed

through mature adulthood, protected by the tensile forces produced by the muscles

115

attaching there. Similarly, the posterior area around the linea aspera appears least affected

by cortical shape transformations with age. Third, the Posterior ROI displays the second

lowest OPD values after the Anterior ROI, except without any indication of having

reached the OPD asymptote. Sampling locations characterized by low remodeling are

desirable as less bone turnover allows age estimates to remain accurate over 50 years.

Finally, the Posterior ROI possesses the lowest SEE of any ROI, and as such, produces

the most precise age predictions.

To conclude, use of microscopic techniques to estimate adult age at death is well

established within physical anthropology’s subfields of bioarchaeology and forensic

anthropology. In order to become a more robust approach, however, the long-standing

problems of the OPD asymptote and high SEE must be overcome. Review of the

microscopic age at death estimation literature revealed that arbitrarily changing skeletal

elements, histological variables, sample demographics, and sampling locations has not

allowed for accurate age estimation of individuals over approximately 50 years or

reduced the standard error of age estimates. This investigation therefore began with

substantiated theory addressing femoral genetic programming, growth and development,

biomechanical and periosteal adaptation, aging, mechanobiology, and bone remodeling.

Building from this theoretical knowledge base, it was first hypothesized that

topographical variation in remodeling exists around femoral midshaft periosteal cortices

that reflects the constraints of normal anatomical development, customary biomechanical

usage, and standard mechanobiological functioning. Second, it was hypothesized ROIs

associated with the Imin second moment of area would exhibit the lowest remodeling due

to minimal biomechanical loading. Third, it was hypothesized remodeling at

116

biomechanical ROIs would be histomorphometrically more consistent than at anatomical

ROIs due to existing femoral functional constraints.

While no evidence was found for reduced remodeling at Imin ROIs or for more

consistent remodeling at biomechanical ROIs, 14 statistically significant differences were

found between ROI OPD medians indicating topographical variation in remodeling

exists. Additionally, although the anterior femoral cortex has traditionally been sampled

for microscopic age at death estimation, the Anterior ROI was found to reach the OPD

asymptote at approximately 50 years of age and was associated with the highest SEE.

Alternatively, the Posterior ROI was associated with the lowest SEE and showed no sign

of having reached the OPD asymptote. It is therefore suggested bioarchaeologists and

forensic anthropologists utilize the Posterior ROI for production of the most accurate and

precise microscopic age at death estimates from adult human skeletal remains.

117

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124

Appendix A: Total Ericksen Sample Data

Shaded boxes indicate the 200 Ericksen samples selected for this research project

ID # AGE SEX ANCESTRY CAUSE OF DEATH

1 47 M White Chronic brain syndrome. Trephination

2 44 F White GSW suicide following cancer diagnosis. Many signs

of premature aging in several organs

3 50 M Black Coronary arteriosclerotic heart disease

5 71 M White Renal failure. Arteriosclerotic heart disease

6 85 F White Coronary thrombosis

7 46 M White Unknown

8 91 F White Acute infarction. Right unhealed femoral neck

fracture with compression screw

9 77 M White Unknown

10 85 F White Bronchopneumonia

11 48 M White Acute myocardial infarction

13 81 F White Coronary arteriosclerosis

14 49 M Black Exposure and alcoholism

15 89 F White Unknown

17 76 M White Unknown

18 47 F White Hepatic coma

19 53 F White Heart

20 80 F White Congestive heart failure

21 71 M White Unknown

22 81 F White Natural causes

23 70 M White Carcinoma of pancreas

24 59 F White Sclerosis of liver

25 77 F White Cancer (?)

26 84 F White Cardiac arrest

27 68 M White Acute coronary insufficiency. Arteriosclerotic heart

disease

28 68 F White Pneumonia. Heart greatly enlarged

29 28 M White Hypoxemia. Had tracheotomy

101 75 M White Cardiorespiratory arrest

102 76 F White Generalized arteriosclerosis

125

103 81 M White Unknown

104 65 M White Respiratory arrest

105 65 M White Coronary artery disease

106 83 F White Unknown

107 58 M Black Hepatic, cirrhosis of liver

108 91 F White Unknown

109 65 M White Myocardial infarction. Diabetes mellitus

110 65 F White Congestive heart failure

111 49 M White Coronary artery disease

112 72 F White Heart attack. Had replaced abdominal aorta and

common iliacs with reaming of carotids

113 66 M White Heart attack

114 43 F White Unknown

115 77 M White Respiratory failure

116 79 M White Septic shock

117 65 M White Pulmonary embolism. Heart failure

118 66 F White Gangrene of right foot

119 71 M White Multiple cancer metastases

120 78 F White Heart attack

121 60 M White Coronary occlusion

122 63 F White Ovarian carcinoma

123 44 M White Cardiorespiratory arrest. Chronic brain syndrome

124 65 F White Cardiac arrest

125 30 M Black Diabetic acidosis and coma

126 74 F White Cancer

127 50 M White Alcoholic liver disease

128 56 M Black Intracerebral hemorrhage. Hypertensive

cardiovascular and chronic renal diseases

129 62 M White Bronchopneumonia

130 80 F White Congestive heart failure

132 47 M Black Hypertensive cardiovascular disease

133 76 F White Cancer of heart

134 61 F White Gastric hemorrhage from penetrating gastric ulcer

135 65 F White Respiratory arrest

136 48 M White Dropped dead without previous signs

201 80 F White Unknown

202 53 F White Renal failure. Chronic alcoholism

203 69 F White Unknown

204 68 M White Pulmonary infarction

205 50 F White Unknown

126

206 76 M White Metastatic cancer of colon to liver

207 20 M White Striated carcinoma

208 74 M White Respiratory and cardiac arrest

209 78 F White Liver and colon cancer (5 years), partial colectomy

210 72 F White Arteriosclerotic heart disease

211 86 F White Myocardial infarction

212 56 F White Cardiorespiratory failure. Encephalomalacia

213 52 M White Cardiac arrest

214 67 M White Cardiac arrest

215 78 F White Unknown

216 69 M White Cancer

217 64 M White Unknown

218 83 F White Unknown

219 77 M White Generalized arteriosclerosis

220 63 M White Acute myocardial infarction

221 67 F White Coma and seizures

222 79 M White Unknown

223 55 F White Respiratory arrest

224 63 F White Carcinoma

225 84 M White Cardiovascular accident

226 58 M White Occlusive coronary artery disease. Arteriosclerosis

227 79 F White Heart disease

228 65 M White Cardiogenic shock

233 88 F White Cerebrovascular accident

250 74 M White Cardiorespiratory arrest, long history of hypertension

251 75 F White Unknown

252 68 F White Occlusive coronary artery disease. Arteriosclerosis

253 87 F White Breast cancer

254 80 F White Bronchopneumonia. Hip prosthesis (b) intact side

255 80 F White Cardiac arrhythmia

256 82 F White Unknown. Left femur had subcapital neck fracture

with head fibrosed into acetabulum (a) intact side

257 69 F White Adenocarcinoma. Colostomy

258 79 F White Arteriosclerotic heart disease

259 69 M White Gram negative sepsis. Hip prosthesis (a) intact side

301 81 F White Left hip fracture with cardiac complications and

congestive heart failure. Specimen from intact side

302 65 M White Cardiovascular heart disease

303 77 M White Prostate cancer. Hypertension

304 69 F White Chronic lymphatic leukemia

127

305 62 F White Cancer of brain, lung

306 77 F White Cancer of breast. Cardiopulmonary failure

307 70 F White Respiratory failure

308 59 M White Lung cancer

309 71 M White Metastatic cerebellar tumor. Cancer of lower left lobe

310 74 F White Occlusive coronary artery disease

311 60 M White Cardiovascular heart disease

312 74 M White Myocardial infarction. Arteriosclerotic heart disease.

Ventricular fibrillation. Coronary insufficiency

313 78 F White Malnutrition presumably from cancer

314 84 M White Acute cerebral hemorrhage. Arteriosclerosis and

hypertension

315 67 M White Acute coronary occlusion

316 71 F White Lung cancer

317 54 M White Ventricular fibrillation. Coronary arteriosclerosis.

Bilateral hip prostheses

318 62 F White Acute myocardial disorder. Uremia. Angina,

congestive heart failure, and longstanding diabetes

319 71 M White Cardiovascular heart disease. Stroke

320 85 F White Acute myocardial infarction

321 65 F White Coronary arteriosclerosis with coronary

insufficiency. Stroke

322 52 F White Ovarian cancer

323 54 M White Pneumonia. Cerebral contusion and skull fracture

from a fall downstairs. Acute and chronic alcoholism

324 57 M Black Lung cancer

325 68 F White Acute myocardial disorder

326 70 F White Respiratory failure. Hip prosthesis (b) intact side

327 35 F White Cerebral herniation. Cancer. Five months pregnant

329 56 M Black Acute massive coronary infarction. Arteriosclerotic

cardiovascular disease

330 75 F White Cardiovascular accident. Pulmonary embolism

401 89 M White Cardiac arrest. Arteriosclerotic cardiovascular and

renal disease

402A 86 F White Generalized sepsis. Hip fracture (a) intact side

403 62 M White Cancer of lungs with brain metastases

404 64 F White Bilateral pneumonia

405 75 M White Myocardial infarction. Arteriosclerotic heart disease

406 53 F White Inanition. Cachexia. Gastric cancer

407 76 F White Chronic obstructive pulmonary disease. Congestive

heart failure

128

408 59 M White Acute myocardial infarction

409 60 F White Respiratory arrest. Intracranial hemorrhage

410 66 F White Cancer of esophagus

411 69 F White Bronchopneumonia. Acute myoleukemia

412 51 M White Meningitis due to pneumonia

413 61 M White Cardiopulmonary arrest

414 79 F White Coronary occlusion. Heart failure. Hip prosthesis (a)

intact

415 54 M White Metastatic cancer

416 66 F White Respiratory arrest. Lung cancer

417 79 F White Cardiovascular arrest. Pulmonary embolism

418 59 M White Cardiac arrest. Myocardial infarction due to coronary

artery disease

419 45 F White Advanced respiratory failure. Pancreatitis. Laennec's

cirrhosis of liver

420 75 F White Cerebrovascular thrombosis. Arteriosclerotic heart

disease

421 75 M White Subarachnoid hemorrhage. Arterial hypertension

422 68 F White Respiratory insufficiency

423 71 M White Cardiovascular heart disease. Stroke

424 84 F White Cerebral hemorrhage

425 92 M White Basilar artery insufficiency. Respiratory arrest

427 58 F White Cancer of esophagus

429 89 F White Cardiopulmonary arrest due to aspiration.

Pneumonitis. Hip prosthesis: no intact side

501 52 M Asian Respiratory failure (2 days). Widespread

bronchogenic cancer (2.5 years)

502 70 M White Arteriosclerotic heart disease

503 63 M White Acute myocardial infarction. Arteriosclerotic heart

disease. Diabetic

504 83 M White

Arteriosclerotic heart disease. Congestive heart

failure. Chronic pulmonary disease. Operated 10 days

before death for urinary retention

505 73 F White Cardiopulmonary arrest. Cancer of colon. Malignant

pulmonary effusions. Ill several weeks

506 66 F White Cardiorespiratory arrest. Cerebrovascular accident

507 28 M White Cardiorespiratory arrest. Recurrent brain astrocytoma

508 74 M White Ventricular fibrillation due to septicemia (1 month)

509 62 M White Acute myocardial infarction. Congestive heart failure

510 81 F White Cerebrovascular accident (7 months). Essential

hypertension (years). GI bleeding. Diverticulosis

129

511 72 M White Acute respiratory failure. Cardiovascular accident.

Diabetes. Arteriosclerotic disease

512 62 F White Respiratory failure. Pneumonia. Metastasis from

frontoparietal tumor

513 50 M White Metastatic cancer from malignant carcinoid

514 56 M White Cardiac arrhythmia. Arteriosclerotic heart disease

515 69 F White Myeloma

516 91 F White Acute myoplastic leukemia. Chronic

myeloproliferative leukemia

517 75 F White Pulmonary emphysema

518 79 F White Hypertensive arteriosclerotic heart disease (10 years)

519 52 F White Hypertensive cardiovascular disease

520 58 F White GI hemorrhage. Gastric ulcer (9 years)

521 77 M White

Acute cardiorespiratory failure. Coronary artery

disease. Old myocardial infarct. Hypertensive

cardiovascular disease. Diabetes mellitus

522 68 M Black Brainstem infarct. Cerebrovascular accident.

Arteriosclerosis. Salivary gland carcinoma

523 74 M White Fibrosarcoma

524 74 F Black Chronic pyelonephritis-uremia (8 years)

525 71 M White Acute myocardial infarct. Arteriosclerotic heart

disease (20 years)

604 52 M White Metastatic liver and intra-abdominal metastases (6

months) due to colon cancer (9 months)

610 56 F White Intracerebral hemorrhage (48 hours). Hip fracture

and pin (intact side)

612 58 M White Acute and chronic myocardial disease

615 57 F White Gastrointestinal hemorrhage. Liver cirrhosis. Chronic

alcoholism

616 57 F White CO asphyxia. Ran car in garage while inside it

618 59 M White Respiratory failure from chronic pulmonary disease.

Not related: inactive pulmonary TB

619 60 F White Cerebrovascular accident 2 days before

620 53 F White Congestive heart failure

621 50 F White Carcinomatosis (3 months). Lung cancer (8 months)

624 60 M White End stage renal failure. Metastatic colon cancer

701 33 M White Elavil overdose

704 48 M White Hepatic failure. Laennec's cirrhosis. Chronic

alcoholism

706 61 F White Cardiopulmonary arrest. Non-Hodgkin’s lymphoma

with bilateral pulmonary infiltration

710 63 F White Mesothelioma of abdomen

130

711 54 F Black Ischemic heart disease (4 years). Hypertensive

cardiovascular disease (5 years)

715 51 F White Carcinomatosis. Death sudden

717 63 F White

Diffuse bilateral bronchopneumonia. Metastatic

adenocarcinoma from pulmonary and cerebral

carcinoma

720 53 F White Respiratory failure. Metastatic breast cancer. Femoral

neck pin (a) intact

801 80 M White Ventricular fibrillation. Cardiomyopathy (7 years)

802 79 M White Cardiovascular arrest

803 95 F White

Chronic renal failure. Acute diverticulitis with

bacteremia and hemorrhage (3+ weeks). Hip

prosthesis (a) intact

804 82 M White Acute coronary insufficiency. Arteriosclerotic heart

disease

805 74 M White Acute cardiac arrest after massive cerebral infarct.

Hypertensive disease

806 80 M White Colon cancer with metastases (20 months)

807 68 M White Cardiac arrest from myocardial infarction

808 93 F White Cardiorespiratory arrest after 24 hour pneumonia.

Arteriosclerotic heart disease

809 83 M White Carcinoma of prostate

810 64 M White Hepatocellular cancer some months.

811 76 F White

Respiratory failure. Chronic obstructive pulmonary

disease. Lifelong respiratory disease including TB at

one time

812 93 F White Terminal myeloma

813 74 F White Bronchial pneumonia

814 88 F White Acute myocardial infarct. Breast cancer (15 years).

Diaphragmatic hiatal hernia

815 81 F White Cardiopulmonary arrest. Congestive heart failure

816 63 M White Coronary artery disease. Hypertensive heart disease

817 77 F White Cardiovascular accident from arteriosclerotic

vascular disease

818 63 F White Septic shock from chemotherapy for multiple

myeloma. Myeloma kidney

819A 80 F Black Chronic renal failure. Also congestive heart failure.

Anemia. Femoral subcapital fracture (a) intact

820 72 F White Acute respiratory failure from emphysema from

chronic bronchitis. Manic depressive psychosis

821 65 M White Cardiopulmonary arrest. Probable arrhythmia. Had

heart valve replacement

131

822 83 M White Generalized arteriosclerosis. Chronic obstructive

lung disease

823 48 M White Cardiorespiratory arrest from lung cancer (8 months)

824 82 F White Cerebral hemorrhage

825 89 M White Probable metastases from prostate cancer

826 56 F White Metastatic ovarian carcinoma

901 86 F White Intestinal obstruction. Colon cancer (months). Severe

rheumatoid arthritis. Femoral neck pin (b) intact

902 92 F White Acute congestive heart failure. Bronchopneumonia

903 80 F White Arteriosclerotic hypertensive heart disease

904 80 F White Cardiorespiratory arrest from coronary heart disease

905 84 F White Cardiac arrest. Chronic arteriosclerotic heart disease

906 85 M White Arteriosclerotic heart disease (5 years)

907 84 F White Left middle cerebral artery occlusion (2 weeks). Hip

prosthesis (a) intact

908B 84 F White

Cardiac arrest from congestive heart failure.

Arteriosclerotic heart disease. Diabetes mellitus. Hip

prosthesis (b) intact

909B 79 M White

Respiratory failure from chronic obstructive

pulmonary disease. Arteriosclerotic. Senility.

Femoral neck fracture, pinned (b) intact side

910 74 F White Cardiorespiratory failure. Subarachnoid hemorrhage

911 89 F White Cardiac arrest. Coronary heart disease (years)

912 84 M White

Pneumonitis from atelectatic collapsed lung lobe

from chronic obstructive lung disease (50 years).

Congestive heart failure

913 85 F White Bronchopneumonia after cerebrovascular thrombosis

914 61 M White Coronary occlusion from coronary heart disease.

Diabetes mellitus. Chronic congestive heart failure

915 90 F White Myocardial infarction from arteriosclerotic heart

disease. Subcapital hip fracture (b) intact side

916 78 F White Congestive heart failure

918 60 M White Arteriosclerotic cardiovascular disease

919 92 F White Cerebral thrombosis. Hypertensive arteriosclerotic

cardiovascular disease

920 68 M White Hepatic cirrhosis

921A 96 F White Cardiopulmonary arrest. Possible metabolic senility.

Femoral neck pin (a) intact

922 94 F White Myocardial failure. Arteriosclerosis. Coronary

disability

923B 80 F White Cerebral hemorrhage with brainstem dysfunction.

Femoral neck fracture not pinned (b) intact

132

924 80 F White Respiratory failure from chronic bronchitis. Seizures.

Femoral neck fracture and pin (a) intact

925 80 M White

Cardiopulmonary arrest. Myocardial infarct.

Arteriosclerosis and coronary heart disease (5 years).

Burst abdominal aortic aneurysm

926 58 M White Congestive heart failure from arteriosclerotic heart

disease. Renal failure

927 80 M White

Cardiac arrest. Myocardial infarction. Arterial heart

disease (27 years). Essential hypertension.

Congestive failure

1005 84 M White Arteriosclerotic heart disease

1006 73 M White Arteriosclerotic heart disease

1010 64 M White Acute coronary insufficiency from arteriosclerotic

heart disease. Contributory: essential hypertension

1014 71 M White Cardiopulmonary arrest due to heart failure.

Contributory: sepsis, kidney failure, seizures

1017 59 M White Arteriosclerotic cardiovascular disease

1019 79 M White Pneumonitis (24 hours). Contributory: paraplegia,

secondary cord compression

1021 63 M White Cardiorespiratory arrest. Contributory: chronic

alcoholism, cirrhosis, recurrent pancreatitis

1022 84 M White Generalized arteriosclerosis

1023 79 M White Arteriosclerotic heart disease

1026 52 M White Acute myocardial infarction

1103 69 M White Pneumonia after left cerebral infarct from

hypertension

1107 64 F White Cardiac arrest

1109 69 M White Respiratory arrest. Pneumonia. Chronic lymphocytic

leukemia

1111 62 M White Cardiac arrest. Cirrhosis (3 years)

1112 81 F White Pneumonia. Congestive heart failure. Contributory:

acute abdomen

1113 39 M White Metastatic melanoma (6.5 years)

1114 64 F White Myeloma (3 years). Contributory: pancytopenia,

internal bleeding

1115 92 F White Myocardial failure (days). Arteriosclerotic heart

disease (years)

1117 72 F Black Cardiac arrest. Arteriosclerotic heart disease. Renal

failure. Chronic pulmonary disease

1119 62 F White

Respiratory arrest after severe cerebral anoxic insult

from aspiration of meat. Prolonged (1+ months)

anoxia and coma

133

1121 55 M White Diabetic ketoacidosis with coma (weeks). Diabetes.

Contributory: alcoholism

1122 64 F White Increasing intracerebral pressure from subarachnoid

hemorrhage (1 week)

1123 83 M White Cardiac arrest after myocardial infarction

1124 84 M White

Cardiorespiratory arrest. Arteriosclerotic heart

disease. Generalized arteriosclerosis. Femoral neck

fracture with a pin (b) intact

1125 32 M White

Probable myocardial infarction. Arteriosclerotic heart

disease (5+ years). Chronic glomerulonephritis (10

years). Chronic renal failure.

1202 77 M White Respiratory failure from congestive heart failure.

Rheumatoid arthritis

1203 81 M White

Cardiac arrest and respiratory failure. Cardiac

arrhythmia and myocardial infarction. Coronary

artery disease. Cerebral hypoxia and coma

1205 37 M White Undetermined (but assumed natural causes)

1206 67 F White Ruptured abdominal aneurysm due to arteriosclerosis

1208 73 M White Acute renal failure. Chronic congestive heart failure

(7 months). Arteriosclerosis (4 years)

1213 70 M White

Chronic obstructive pulmonary disease (3 years).

Pulmonary emphysema (10 years). Cigarettes (40

years). Contributory: coronary heart disease,

coronary pulmonale

1214 76 M White Cardiac arrest from arteriosclerotic heart disease (5

years). Contributory: myocardial infarction

1215 75 M White Acute respiratory failure. Pneumonitis. Longstanding

cerebrovascular disease

1217 78 M White Cardiac arrest. Arteriosclerotic heart disease (8 years)

1218 97 M White Cardiorespiratory collapse after stroke and

pneumonia (1 week). Senility

1220 49 M White Cardiopulmonary arrest. Asphyxia

1222 75 M White Brainstem hemorrhage from hypertension. Right hip

prosthesis (b) intact side

1224 56 M White Acute myocardial infarction (1 day)

1301 80 M White Acute myocardial infarction due to chronic

myocardial disease

1305 83 F White

Acute myocardial infarction (48 hours) due to

coronary sclerosis. Other: essential hypertension,

diabetes mellitus

1306 68 M White

Cardiorespiratory failure (8 days) due to cardiac

arrhythmia (8 days) due to acute myocardial

infarction. Other: myasthenia gravis

134

1308 96 F White Cardiopulmonary arrest from hypotension.

Dehydration. Probable aspiration pneumonia

1311 73 M White Cardiac failure from cardiomyopathy from ischemic

heart disease and renal insufficiency

1312 60 M White Acute myocardial disease

1313 64 M White Cardiac arrest. Cardiomyopathy

1314 64 M White Pulmonary arrest from chronic obstructive

pulmonary disease. Peripheral neuropathy

1316 83 F Black Congestive heart failure from hypertensive

cardiovascular disease

1319 68 F White Respiratory arrest from emphysema

1323 42 M Black Cardiopulmonary arrest from right intracerebral

hemorrhage

1325 74 F White Asystole due to arteriosclerotic heart disease

1401 86 F White Cardiorespiratory failure from acute myocardial

infarction from coronary heart disease

1402 72 F White Cardiopulmonary arrest. Cardiomyopathy. Ischemic

heart disease. Arteriosclerosis

1403 74 M White

Cardiopulmonary arrest from severe congestive heart

failure from emphysema. Sick sinus syndrome with

pacemaker

1404 88 M White Hypovolemic shock from ruptured aortic aneurysm

1405 85 M White Cardiorespiratory arrest from congestive heart failure

1406 79 F White Gastrointestinal bleeding. Contributory: obstructive

pulmonary disease, hypothyroidism

1410 82 F White Ventricular arrhythmia from acute myocardial

infarction. Ischemic heart disease. Arteriosclerosis

1412 83 M White Bronchitis from chronic obstructive lung disease

1414 68 F White

Acute anterior myocardial infarction from

arteriosclerotic coronary heart disease. High blood

pressure. Diabetes mellitus. Old myocardial infarct

1416 83 F White Cardiac arrest from myocardial infarction. Coronary

artery disease

1418 56 F White Hypertensive cardiovascular disease

1419 73 M White Septicemia from liver failure from portal cirrhosis

1420 71 F White Acute myocardial heart disease

1421 85 F White Acute hemorrhagic pancreatitis

1423 88 F White Acute myocardial disease

1424 87 F White Cardiac arrest from myocardial infarction from

arteriosclerosis

1426 74 M White Arteriosclerotic cardiovascular disease

135

Appendix B: Research Sample Biomechanical Data

136

AG

EID

#S

cale

TAC

AM

AX

bar

Ybar

IxIy

JIx

/IyIm

axIm

inIm

x/Im

nTh

eta

ZxZy

ZpM

axX

rad

Max

Yrad

442

47.2

pxl/m

m40

7.19

431

2.95

694

.238

29.6

0322

.449

1415

7.18

711

446.

368

2560

3.55

51.

237

1423

0.29

011

373.

265

1.25

1205

-80.

796

1011

.848

982.

739

1652

.187

11.6

4740

13.9

9140

715

47.2

pxl/m

m63

4.63

839

6.02

023

8.61

822

.166

25.7

5228

660.

462

2743

0.19

856

090.

659

1.04

530

283.

415

2580

7.24

41.

1734

46-5

2.97

716

85.6

5017

77.8

5929

28.8

0315

.428

8017

.002

6085

647

.2px

l/mm

467.

206

203.

853

263.

354

23.7

6122

.007

1366

6.09

710

464.

960

2413

1.05

81.

306

1419

8.09

499

32.9

641.

4293

9169

.319

863.

215

876.

624

1582

.271

11.9

3780

15.8

3160

918

47.2

pxl/m

m37

9.39

818

4.14

719

5.25

121

.912

21.6

1876

90.9

2093

11.2

4517

002.

165

0.82

693

92.1

8676

09.9

791.

2341

9412

.305

639.

520

782.

334

1225

.372

11.9

0190

12.0

2610

779

47.2

pxl/m

m66

0.41

647

2.66

618

7.74

923

.351

25.0

0135

000.

230

3026

5.35

165

265.

581

1.15

635

137.

202

3012

8.37

91.

1662

4980

.482

1969

.166

2034

.501

3271

.293

14.8

7610

17.7

7410

4811

47.2

pxl/m

m64

9.53

847

5.99

817

3.54

021

.457

23.9

0336

882.

910

2701

4.44

763

897.

356

1.36

536

985.

982

2691

1.37

51.

3743

62-8

4.19

521

68.5

8019

57.8

9432

21.0

8713

.797

7017

.007

9049

1447

.2px

l/mm

679.

787

449.

129

230.

658

30.5

9422

.288

3330

2.74

731

605.

441

6490

8.18

71.

054

3333

0.50

731

577.

681

1.05

5508

82.7

7020

95.8

1621

77.6

3132

58.2

0714

.513

7015

.890

1089

1547

.2px

l/mm

508.

813

318.

860

189.

952

31.9

8023

.853

1774

7.73

618

190.

453

3593

8.18

90.

976

1819

1.00

617

747.

183

1.02

5008

-2.0

2412

84.4

8413

34.1

6921

16.1

9713

.634

3013

.817

0076

1747

.2px

l/mm

597.

334

468.

389

128.

945

28.9

6323

.544

3168

4.83

723

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2016

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251

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1.14

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435

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3.64

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305

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0.85

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335

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268

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112

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2.58

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1993

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1996

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37.5

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2.63

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114

28.1

2812

.064

1013

.353

3094

922

47.2

pxl/m

m52

7.01

225

5.17

627

1.83

631

.409

21.1

1917

745.

673

1521

5.29

832

960.

971

1.16

619

785.

478

1317

5.49

31.

5016

88-5

6.25

410

76.3

1511

86.0

4719

86.7

3512

.828

6016

.487

4080

923B

47.2

pxl/m

m48

5.51

020

8.50

827

7.00

229

.085

20.1

3510

872.

801

1418

3.45

925

056.

260

0.76

714

341.

451

1071

4.80

91.

3384

7012

.047

788.

780

1086

.472

1626

.331

13.0

5460

13.7

8430

8092

547

.2px

l/mm

650.

690

453.

088

197.

602

32.7

8822

.456

3484

4.45

627

425.

121

6226

9.57

61.

271

3521

1.20

027

058.

376

1.30

1305

77.7

5519

98.1

6819

51.1

9531

60.9

7814

.055

6017

.438

2080

927

47.2

pxl/m

m55

1.76

840

9.88

814

1.88

030

.782

21.7

5924

686.

847

2234

0.86

047

027.

707

1.10

526

198.

408

2082

9.30

01.

2577

67-5

7.95

514

82.5

3916

02.2

9925

75.2

4313

.943

0016

.651

7084

1005

47.2

pxl/m

m63

8.02

741

6.11

022

1.91

729

.064

21.7

6332

439.

544

2602

1.89

858

461.

442

1.24

732

688.

607

2577

2.83

51.

2683

36-7

9.06

119

00.2

1718

43.7

0430

18.6

6414

.113

9017

.071

5073

1006

47.2

pxl/m

m61

7.91

545

4.16

516

3.75

030

.378

23.2

9133

392.

566

2542

2.27

758

814.

843

1.31

433

526.

760

2528

8.08

21.

3257

93-8

2.66

819

32.3

2118

28.7

0230

31.9

7413

.901

8017

.281

1064

1010

47.2

pxl/m

m62

5.28

344

8.00

017

7.28

331

.272

21.4

2632

019.

089

2662

4.54

058

643.

629

1.20

332

248.

672

2639

4.95

71.

2217

74-7

8.57

818

59.5

8119

18.4

2230

25.5

2813

.878

4017

.218

4059

1017

47.2

pxl/m

m53

7.90

443

6.69

410

1.21

020

.767

24.9

5622

159.

193

2259

5.97

844

755.

171

0.98

122

898.

638

2185

6.53

31.

0476

79-3

2.61

015

13.4

2316

09.1

1824

83.7

9414

.042

5014

.641

8063

1021

47.2

pxl/m

m62

0.95

548

3.96

413

6.99

130

.072

22.5

4535

963.

974

2459

4.42

460

558.

397

1.46

236

039.

671

2451

8.72

71.

4698

83-8

5.35

120

47.9

3818

20.7

0530

97.3

2913

.508

2017

.561

1079

1023

47.2

pxl/m

m55

8.54

038

3.39

317

5.14

727

.311

28.6

9622

338.

780

2273

1.77

045

070.

549

0.98

325

089.

031

1998

1.51

81.

2556

1242

.794

1511

.609

1650

.502

2496

.559

13.7

7260

14.7

7810

5210

2647

.2px

l/mm

583.

872

401.

010

182.

862

26.8

5322

.512

2506

9.07

725

091.

961

5016

1.03

70.

999

2973

0.54

320

430.

495

1.45

5204

44.9

3015

45.8

6017

02.7

4026

99.4

0214

.736

2016

.216

9069

1103

47.2

pxl/m

m64

2.54

440

9.10

723

3.43

830

.256

25.8

6532

475.

731

2532

3.24

157

798.

972

1.28

232

557.

262

2524

1.71

01.

2898

2083

.940

1875

.762

1841

.873

2993

.655

13.7

4860

17.3

1340

6911

0947

.2px

l/mm

682.

071

405.

513

276.

558

28.0

0423

.594

4021

6.38

224

872.

472

6508

8.85

41.

617

4085

1.44

224

237.

412

1.68

5470

78.7

2621

93.5

7318

08.2

7132

64.8

2413

.754

8018

.333

7062

1119

47.2

pxl/m

m57

9.77

640

4.85

017

4.92

632

.158

23.3

0523

483.

581

2537

7.63

948

861.

220

0.92

526

152.

054

2270

9.16

61.

1516

0828

.312

1601

.717

1771

.519

2648

.158

14.3

2540

14.6

6150

5511

2147

.2px

l/mm

612.

505

417.

879

194.

625

27.9

6624

.756

2696

4.35

226

901.

041

5386

5.39

31.

002

2814

2.45

225

722.

941

1.09

4060

-45.

750

1744

.627

1900

.738

2843

.519

14.1

5290

15.4

5570

6411

2247

.2px

l/mm

486.

587

338.

196

148.

390

27.7

5722

.791

2030

8.45

416

135.

471

3644

3.92

41.

259

2057

6.85

415

867.

070

1.29

6828

-76.

189

1194

.789

1246

.759

2137

.895

12.9

4190

16.9

9750

8311

2347

.2px

l/mm

545.

291

299.

527

245.

763

30.0

5622

.875

2407

5.20

115

664.

543

3973

9.74

41.

537

2410

6.30

815

633.

436

1.54

1971

86.5

2612

92.3

4812

07.4

4122

77.3

7412

.973

3018

.629

0084

1124

47.2

pxl/m

m57

8.34

831

4.40

226

3.94

629

.516

22.1

4424

207.

838

1932

6.91

043

534.

748

1.25

325

207.

896

1832

6.85

21.

3754

6267

.590

1469

.005

1411

.748

2434

.167

13.6

9010

16.4

7910

8112

0347

.2px

l/mm

669.

345

529.

025

140.

320

33.9

9426

.686

3257

7.21

036

281.

615

6885

8.82

50.

898

3884

8.40

730

010.

417

1.29

4497

-32.

610

2051

.815

2347

.494

3401

.814

15.4

5550

15.8

7730

7012

1347

.2px

l/mm

596.

689

472.

406

124.

283

29.1

0427

.407

2875

4.29

126

422.

881

5517

7.17

21.

088

2914

0.47

826

036.

695

1.11

9208

-69.

345

1687

.240

1857

.851

2893

.906

14.2

2230

17.0

4220

7612

1447

.2px

l/mm

701.

699

517.

766

183.

934

20.7

0324

.701

4433

5.80

831

938.

295

7627

4.10

31.

388

4470

9.12

731

564.

976

1.41

6416

-80.

298

2421

.705

2140

.772

3665

.517

14.9

1910

18.3

0770

7512

1547

.2px

l/mm

512.

427

341.

914

170.

513

30.5

5422

.261

2010

9.69

317

502.

559

3761

2.25

11.

149

2079

7.40

116

814.

850

1.23

6847

65.4

4613

51.5

7413

45.1

3021

87.7

1313

.011

8014

.878

7097

1218

47.2

pxl/m

m64

4.27

744

6.56

019

7.71

724

.303

23.8

2236

573.

211

2563

3.31

562

206.

525

1.42

738

751.

277

2345

5.24

81.

6521

37-6

7.83

022

08.5

4317

98.0

2331

58.6

4114

.256

4016

.559

9083

1305

47.2

pxl/m

m51

7.76

730

7.95

820

9.80

929

.635

22.2

2918

680.

071

1772

2.52

436

402.

596

1.05

419

566.

832

1683

5.76

31.

1622

18-5

5.26

212

31.8

1613

17.8

4121

36.1

2513

.448

1015

.164

7068

1306

47.2

pxl/m

m62

0.48

829

1.67

932

8.80

929

.249

23.1

7222

069.

742

2194

0.09

544

009.

837

1.00

622

288.

831

2172

1.00

51.

0261

4251

.599

1285

.557

1553

.626

2453

.530

14.1

2190

17.1

6750

9613

0847

.2px

l/mm

404.

668

143.

832

260.

836

33.7

7823

.083

6603

.538

8652

.115

1525

5.65

40.

763

9234

.021

6021

.633

1.53

3475

25.1

8946

2.11

571

7.31

311

32.1

5112

.061

8014

.289

8073

1311

47.2

pxl/m

m62

3.57

143

2.07

019

1.50

224

.685

22.9

1929

330.

608

2647

6.06

455

806.

672

1.10

829

470.

048

2633

6.62

31.

1189

7677

.822

1914

.258

1854

.529

2917

.970

14.2

7640

15.3

2220

6013

1247

.2px

l/mm

736.

026

508.

483

227.

543

23.0

4525

.761

3897

3.49

138

851.

314

7782

4.80

51.

003

4209

4.86

835

729.

937

1.17

8140

-45.

550

2310

.724

2462

.317

3719

.771

15.7

7840

16.8

6640

6413

1347

.2px

l/mm

790.

077

530.

341

259.

736

33.8

7525

.967

4388

5.98

145

193.

294

8907

9.27

50.

971

4833

4.29

640

744.

979

1.18

6264

40.0

4125

56.1

0327

24.6

8041

05.2

2516

.586

6017

.169

1064

1314

47.2

pxl/m

m52

0.69

037

4.88

714

5.80

323

.891

43.8

6819

058.

334

2057

0.47

139

628.

806

0.92

620

923.

310

1870

5.49

51.

1185

65-2

3.50

714

02.4

1214

61.4

7322

72.7

3114

.075

2013

.589

7068

1319

47.2

pxl/m

m54

0.52

829

3.58

524

6.94

331

.744

24.5

6319

543.

816

1812

8.12

337

671.

939

1.07

819

716.

896

1795

5.04

31.

0981

2671

.734

1169

.710

1319

.010

2190

.247

13.7

4370

16.7

0830

7413

2547

.2px

l/mm

603.

556

332.

185

271.

371

21.9

2721

.360

1519

4.22

332

089.

176

4728

3.39

90.

473

3240

9.70

914

873.

690

2.17

8996

7.77

011

48.9

8319

00.3

2925

85.4

5716

.886

1013

.224

1086

1401

47.2

pxl/m

m58

2.30

631

2.57

226

9.73

429

.150

22.7

2316

987.

139

2733

6.83

044

323.

968

0.62

127

679.

690

1664

4.27

81.

6630

1510

.152

1236

.407

1717

.790

2466

.302

15.9

1400

13.7

3910

7214

0247

.2px

l/mm

565.

562

364.

492

201.

070

22.2

8345

.834

2302

2.24

421

256.

734

4427

8.97

81.

083

2375

8.68

420

520.

294

1.15

7814

61.5

1914

97.4

7415

68.2

8524

64.4

7413

.554

1015

.374

1088

1404

47.2

pxl/m

m63

0.64

850

5.73

012

4.91

821

.553

21.9

1431

037.

465

3128

6.82

462

324.

289

0.99

233

009.

087

2931

5.20

21.

1260

0643

.065

1883

.818

2044

.495

3163

.005

15.3

0300

16.4

7580

8514

0547

.2px

l/mm

663.

699

431.

404

232.

295

21.7

5624

.517

2934

4.01

833

037.

415

6238

1.43

20.

888

3570

4.38

926

677.

044

1.33

8394

32.9

2518

57.1

3121

01.2

5031

65.1

2215

.722

7015

.800

7079

1406

47.2

pxl/m

m55

8.22

141

0.37

014

7.85

023

.990

23.4

6124

783.

750

2187

7.71

546

661.

465

1.13

325

031.

312

2163

0.15

21.

1572

4274

.348

1601

.051

1535

.100

2560

.587

14.2

5170

15.4

7970

8214

1047

.2px

l/mm

524.

757

229.

758

295.

000

24.6

3922

.493

1373

8.92

616

358.

021

3009

6.94

60.

840

1641

8.15

013

678.

796

1.20

0263

-8.5

2010

11.1

6310

92.1

3718

59.1

8014

.978

0013

.587

3083

1412

47.2

pxl/m

m55

9.60

526

1.42

329

8.18

224

.472

25.3

0617

901.

637

1790

2.60

435

804.

242

1.00

018

401.

115

1740

3.12

71.

0573

4544

.972

1221

.796

1306

.230

2110

.436

13.7

0560

14.6

5190

6814

1447

.2px

l/mm

502.

606

359.

632

142.

974

21.8

3520

.705

1845

4.77

918

947.

954

3740

2.73

30.

974

2093

3.44

516

469.

288

1.27

1060

41.8

2912

41.3

1213

98.7

4021

78.8

1013

.546

4014

.867

2083

1416

47.2

pxl/m

m48

2.98

432

9.73

315

3.25

118

.935

22.2

7518

000.

796

1556

0.35

833

561.

154

1.15

718

452.

867

1510

8.28

71.

2213

7468

.429

1242

.859

1281

.155

2013

.079

12.1

4560

14.4

8340

7314

1947

.2px

l/mm

718.

713

496.

992

221.

722

26.1

1824

.965

4222

7.95

832

728.

935

7495

6.89

21.

290

4277

7.37

332

179.

519

1.32

9335

-76.

839

2408

.245

2212

.510

3619

.199

14.7

9270

17.5

3470

7114

2047

.2px

l/mm

474.

607

335.

876

138.

732

23.7

8326

.030

1867

6.73

014

856.

325

3353

3.05

51.

257

1898

9.12

814

543.

927

1.30

5640

74.6

2712

60.4

5112

26.8

7220

11.8

4912

.109

1014

.817

5085

1421

47.2

pxl/m

m48

8.23

123

2.58

325

5.64

825

.045

21.2

8814

047.

837

1349

9.09

627

546.

933

1.04

115

319.

158

1222

7.77

51.

2528

16-5

0.11

288

3.83

410

09.9

4017

42.8

2413

.366

2015

.894

2087

1424

47.2

pxl/m

m43

5.14

231

9.38

211

5.76

031

.609

19.1

7713

512.

488

1470

9.93

528

222.

423

0.91

916

078.

185

1214

4.23

81.

3239

35-3

6.13

910

15.8

0312

07.3

3217

73.9

1912

.183

8013

.302

3074

1426

47.2

pxl/m

m64

3.49

641

3.82

322

9.67

325

.454

23.5

6135

358.

458

2468

7.91

860

046.

376

1.43

235

442.

351

2460

4.02

51.

4405

1084

.953

1925

.098

1715

.055

3078

.190

14.3

9480

18.3

6710

140

Appendix C: Research Sample Cross-Sectional Images

141

142

203

143

144

145

146

147

148

149

150

151

Appendix D: Research Sample Cortical Thickness Data

152

ID # AGE 0° 22.5° 45° 67.5° 90° 112.5° 135° 157.5° 180° 202.5° 225° 247.5° 270° 292.5° 315° 337.5°

2 44 4.303 4.489 5.532 6.339 6.337 5.362 5.477 6.000 8.684 5.362 5.366 5.928 6.024 6.554 6.197 5.188

5 71 3.521 3.472 3.983 5.188 6.572 4.798 5.644 6.349 10.092 5.362 5.201 4.973 5.790 6.494 5.588 4.766

6 85 2.034 2.034 1.384 3.647 4.146 3.710 3.319 3.472 2.973 2.209 2.323 2.065 3.442 5.147 5.366 2.630

8 91 2.034 2.661 3.098 3.996 3.677 3.154 2.379 3.154 5.398 3.196 2.547 2.907 4.381 4.387 1.881 1.366

9 77 5.476 2.928 5.864 6.657 7.041 6.410 5.919 6.451 9.388 6.392 6.196 6.482 7.980 7.613 7.192 6.277

11 48 5.398 6.596 7.192 7.222 6.885 6.800 6.362 8.209 9.310 6.668 6.196 6.061 7.041 7.890 7.192 5.724

14 49 4.472 5.158 6.970 4.468 6.963 6.205 6.030 6.465 7.198 5.681 5.975 6.093 6.493 6.379 6.030 5.681

15 89 3.139 3.214 3.663 5.557 6.333 4.911 4.204 6.314 6.500 7.211 4.292 4.221 4.889 5.441 4.557 4.005

17 76 6.493 7.222 7.303 7.222 7.510 7.090 6.694 6.945 8.371 6.524 6.860 6.831 8.136 8.547 8.741 7.613

18 47 3.442 4.039 5.366 5.958 4.147 3.956 3.486 5.158 6.963 4.838 3.540 3.894 5.399 5.928 5.532 4.664

19 53 5.163 5.651 6.197 7.047 6.650 5.640 5.034 6.102 7.432 6.000 6.141 6.514 7.041 7.078 6.030 5.332

22 81 3.521 3.472 3.596 5.609 6.493 5.290 4.426 5.609 7.510 3.996 3.821 3.924 5.242 7.324 6.971 5.013

25 77 1.302 1.714 4.626 6.426 6.313 4.125 4.397 3.874 3.500 2.430 3.175 5.213 7.927 7.511 5.812 3.832

27 68 5.007 5.724 6.362 6.800 7.198 6.698 6.306 6.117 7.980 6.205 5.421 6.843 8.136 8.341 8.187 6.421

101 75 3.677 4.366 5.333 6.176 6.115 6.185 5.178 5.991 7.979 5.043 4.354 4.979 5.938 7.524 5.561 3.938

102 76 1.799 2.005 2.711 2.979 5.242 3.750 2.987 2.921 5.163 2.979 2.269 2.528 3.208 4.489 3.707 2.661

103 81 5.163 5.201 5.421 5.783 6.180 7.047 8.022 6.175 6.650 4.707 4.980 4.869 6.416 6.975 7.302 5.971

104 65 1.896 2.511 3.256 5.742 6.927 4.986 5.179 3.107 1.938 2.503 3.565 4.068 5.323 4.927 3.734 1.625

105 65 3.286 3.792 5.753 6.975 7.041 6.307 6.030 5.477 6.024 6.421 6.085 5.815 6.885 4.869 5.421 3.966

106 83 3.833 3.647 4.426 6.061 5.946 4.131 3.928 3.792 6.102 3.894 4.039 5.188 5.007 5.434 4.538 3.996

107 58 4.146 6.349 7.746 7.992 8.606 7.499 6.473 7.162 7.510 7.818 8.022 8.865 9.701 9.461 7.856 4.983

108 91 3.010 3.378 4.567 5.990 4.854 3.852 3.669 4.842 3.156 3.538 2.578 3.837 7.281 8.772 6.364 4.503

109 65 4.889 5.617 5.893 7.476 8.917 8.475 7.287 6.904 6.472 6.667 5.696 6.607 7.181 6.970 6.521 5.107

110 65 4.303 4.520 5.698 5.743 5.555 5.712 4.869 5.753 8.762 5.971 4.536 5.147 5.476 6.760 5.809 4.664

113 66 6.180 6.102 6.861 8.095 7.433 7.253 7.136 6.668 7.510 6.073 5.477 6.061 7.354 7.613 8.077 6.639

117 65 5.320 6.898 6.805 5.847 6.728 6.554 5.976 7.396 9.623 7.409 6.694 6.792 7.432 7.715 7.192 6.596

119 71 4.850 5.128 4.868 5.085 5.555 5.815 6.417 6.915 7.745 8.826 4.757 5.188 5.633 6.307 5.644 4.954

120 78 4.068 4.243 5.089 6.268 5.163 4.623 4.094 5.158 1.565 2.702 3.983 5.147 7.432 7.294 6.362 4.562

121 60 5.476 4.315 5.919 6.061 5.555 4.664 5.421 5.826 7.119 5.971 4.924 5.434 5.085 6.688 6.251 5.158

124 65 3.912 3.545 4.204 5.753 6.102 4.489 5.034 6.421 6.572 4.736 6.196 6.585 6.963 6.410 5.034 4.592

125 30 5.868 5.651 6.362 5.783 5.789 5.918 5.809 7.830 8.239 7.409 6.638 5.783 6.806 7.396 7.136 6.843

126 74 3.111 3.216 4.056 6.219 6.597 5.106 4.744 5.986 3.251 3.660 3.486 5.021 7.681 7.104 5.195 3.131

127 50 5.476 4.387 5.809 6.554 5.663 5.290 4.757 5.724 7.823 4.838 4.813 6.164 7.667 8.372 7.634 6.451

128 56 4.616 5.826 6.749 5.886 5.320 6.379 6.030 6.524 8.606 6.030 5.532 5.681 7.432 9.000 8.188 6.175

129 62 5.320 5.506 5.526 7.777 8.293 7.222 6.638 7.860 8.527 5.651 6.251 6.688 7.745 6.945 5.919 4.736

130 80 3.051 2.949 3.872 5.394 5.555 5.815 4.315 5.230 4.929 3.545 3.321 3.956 4.616 6.307 6.306 4.387

132 47 7.417 7.214 7.150 8.312 7.417 6.152 6.659 6.876 7.139 7.051 7.032 7.490 8.417 9.573 8.623 7.830

133 76 3.208 3.051 3.154 4.171 5.476 5.290 3.928 4.707 5.007 4.315 2.655 3.011 4.146 5.219 4.924 3.792

136 48 6.337 7.192 7.745 7.920 7.589 8.064 8.132 8.993 9.936 6.524 5.865 6.334 7.510 9.516 9.516 8.005

203 69 3.599 3.750 7.757 5.085 5.320 5.537 5.256 6.349 7.198 4.766 4.039 4.140 4.850 6.307 5.975 4.707

204 68 5.555 5.561 6.085 6.596 6.180 5.290 5.754 6.741 9.623 6.814 5.698 6.133 7.823 8.198 7.523 6.668

205 50 4.068 3.821 4.868 6.205 6.728 5.918 5.865 8.252 9.388 5.506 5.366 5.856 6.102 6.873 7.274 5.332

208 74 6.180 6.247 6.418 6.093 5.946 5.743 5.421 7.541 10.092 6.554 5.312 5.290 7.276 8.413 8.821 7.685

209 78 2.425 2.836 3.264 4.798 6.103 4.941 5.034 7.032 4.459 3.647 3.651 2.877 3.833 4.766 4.813 3.095

214 67 5.320 6.800 8.187 9.677 9.075 8.485 7.690 8.296 9.232 6.698 5.919 6.554 7.667 8.198 7.468 5.579

216 69 1.878 1.891 3.375 4.060 4.929 3.924 4.039 6.102 7.980 4.809 3.043 2.979 3.209 2.869 3.486 2.281

217 64 5.242 5.158 5.200 6.061 6.416 5.514 5.030 5.712 9.545 6.494 5.422 5.290 6.259 6.863 6.306 5.506

218 83 3.051 2.630 2.877 4.235 5.242 5.465 3.432 3.123 2.816 2.383 3.264 3.678 5.085 5.076 5.256 3.545

219 77 2.895 2.558 5.089 5.783 6.806 7.222 4.757 4.941 10.327 5.230 4.924 4.983 6.493 8.095 8.022 6.247

220 63 4.772 4.911 5.200 5.477 6.415 6.626 7.136 7.962 11.813 7.294 5.975 5.332 6.728 6.379 6.585 6.175

153

ID # AGE 0° 22.5° 45° 67.5° 90° 112.5° 135° 157.5° 180° 202.5° 225° 247.5° 270° 292.5° 315° 337.5°

222 79 5.007 4.664 4.427 5.579 7.120 7.324 7.579 7.119 10.014 6.300 4.260 4.727 6.728 7.530 6.085 5.085

224 63 1.486 3.196 3.653 4.838 4.694 4.274 4.260 6.247 5.555 4.213 3.043 3.575 4.146 3.011 2.490 1.645

225 84 4.303 4.838 6.196 6.903 6.806 6.729 5.919 5.797 4.146 3.853 4.149 5.434 7.120 8.167 7.967 6.349

226 58 4.929 6.073 7.359 8.804 11.109 8.907 6.805 7.643 8.527 7.903 7.136 8.167 9.779 8.865 7.634 5.856

227 79 2.425 2.486 1.992 1.932 5.163 4.345 3.486 4.417 6.337 2.528 1.995 2.383 2.427 5.537 3.931 3.472

228 65 5.868 6.030 6.030 6.392 7.980 7.294 6.528 6.030 6.806 6.698 5.200 6.205 7.823 8.301 7.745 5.651

233 88 1.489 1.366 1.716 2.661 2.661 1.749 2.102 2.312 4.303 1.505 1.992 2.209 2.036 2.137 2.547 1.787

250 74 6.259 6.117 6.473 6.814 7.667 7.715 7.302 8.005 8.762 8.077 7.136 7.047 7.667 7.818 7.302 6.626

251 75 4.616 4.634 4.757 6.093 9.075 5.989 4.536 4.448 5.555 4.387 5.089 7.571 9.466 8.286 7.856 5.797

252 68 2.269 3.516 5.421 6.626 5.399 4.983 4.980 5.579 7.823 6.236 5.698 5.219 5.711 6.657 6.417 3.956

253 87 0.939 1.264 2.102 3.606 4.538 3.575 2.766 2.137 0.939 2.702 2.048 2.281 3.129 4.202 3.375 1.995

255 80 2.425 1.470 1.605 5.609 5.868 4.243 3.210 2.775 2.192 2.107 2.213 3.154 5.085 4.060 3.540 2.979

257 69 3.209 3.792 4.149 5.362 5.711 4.274 5.200 5.826 8.868 3.894 3.928 4.798 6.024 6.657 5.809 3.678

301 81 1.486 1.645 3.985 3.924 3.286 2.702 2.323 2.037 1.721 3.956 3.486 4.027 4.616 4.983 2.213 1.470

302 65 5.242 5.116 6.141 6.379 6.494 5.783 7.579 8.528 10.405 6.175 5.034 5.880 7.823 9.739 8.298 6.421

303 77 6.572 6.626 6.970 8.413 10.249 8.937 7.523 7.336 9.388 6.175 6.417 9.040 10.562 10.725 9.349 7.903

304 69 4.616 6.133 6.306 6.554 8.840 8.444 6.970 7.613 7.119 5.404 4.536 5.776 8.215 9.739 8.243 5.753

305 62 5.163 5.230 5.477 5.640 6.025 6.030 6.196 6.073 6.728 5.477 5.200 5.783 7.119 8.333 6.583 5.898

306 77 2.503 2.949 4.426 4.345 3.756 2.877 2.379 2.804 4.225 4.562 3.596 3.710 4.850 4.448 4.260 3.298

307 70 2.973 2.979 4.039 4.417 3.755 3.750 3.319 2.877 3.051 3.503 3.651 3.115 4.303 4.171 4.149 4.286

308 59 6.102 5.928 6.750 7.787 6.807 6.668 6.030 7.235 10.483 8.775 7.746 7.253 9.075 9.810 8.796 7.701

309 71 3.286 4.243 4.647 6.698 7.667 7.634 5.590 5.856 6.806 5.826 4.204 4.099 5.320 6.482 6.086 4.606

311 60 5.007 4.562 5.421 6.421 5.868 5.640 5.421 7.729 9.623 6.596 5.336 6.093 6.650 7.499 7.690 6.843

313 78 1.799 1.541 3.043 4.520 4.616 4.417 3.486 3.443 2.158 1.831 2.158 4.027 4.850 5.188 3.043 1.787

314 84 5.868 6.175 6.694 8.064 9.310 9.081 7.413 7.613 7.667 6.030 5.753 7.284 8.606 8.968 7.911 6.524

315 67 5.868 6.205 7.026 7.006 7.902 7.920 7.911 8.064 8.919 6.945 5.975 6.554 9.075 9.739 9.128 6.843

316 71 5.163 5.568 6.141 7.890 8.371 7.602 6.805 6.145 7.667 6.030 6.306 6.657 7.746 7.078 5.422 5.506

319 71 4.772 4.243 5.754 6.698 6.259 5.322 4.980 6.988 7.354 5.537 4.757 7.499 9.310 9.358 8.353 6.133

320 85 2.112 1.541 3.540 4.068 4.225 3.719 2.932 2.949 3.755 2.907 3.762 4.655 5.242 3.710 2.545 1.613

321 65 4.068 3.750 5.091 6.236 5.164 5.076 4.813 4.387 6.728 4.881 4.206 4.655 5.868 7.006 5.975 4.274

322 52 4.068 3.370 4.427 5.188 4.929 5.116 5.145 7.511 8.136 6.102 3.872 3.821 5.007 6.688 6.970 5.404

324 57 4.694 5.230 5.366 5.116 5.868 6.133 6.141 5.928 6.337 5.056 4.979 5.568 5.476 5.815 5.533 5.158

329 56 4.616 5.404 5.533 6.307 5.946 6.873 6.694 7.932 6.806 4.780 5.145 6.410 5.476 7.038 6.306 5.404

402A 86 1.330 2.281 4.481 5.085 4.929 4.592 4.039 5.230 3.521 2.528 2.269 3.226 5.085 6.379 5.864 2.281

403 62 6.259 6.421 7.192 7.294 7.041 6.935 7.136 7.511 9.310 5.898 4.536 6.935 7.354 7.038 5.698 5.651

408 59 5.242 5.753 7.136 7.674 8.449 7.222 6.251 5.928 5.868 5.826 6.473 7.006 7.667 7.890 6.749 5.550

409 60 4.381 4.562 5.366 7.951 9.388 7.119 5.312 5.085 7.119 4.315 3.707 4.489 6.337 7.571 5.532 4.243

410 66 3.755 3.617 3.707 4.243 5.633 6.379 4.647 4.140 4.850 3.647 4.094 4.027 5.320 5.434 3.707 3.924

411 69 4.146 4.039 5.256 5.579 6.181 5.958 5.865 5.753 7.041 5.477 4.979 5.537 6.572 7.222 6.307 5.230

413 61 4.147 3.966 5.533 6.800 6.493 6.410 5.809 7.787 6.650 5.332 5.311 5.783 7.041 6.873 6.583 4.634

415 54 4.303 4.809 5.809 6.277 7.667 7.356 6.086 5.943 7.041 5.404 5.034 5.712 7.510 9.000 6.917 5.188

416 66 3.442 3.154 3.430 4.417 4.850 4.838 3.872 3.617 3.912 3.678 3.596 4.973 6.024 5.394 3.707 3.545

419 45 4.694 5.201 5.366 6.268 6.493 5.712 4.979 5.230 7.119 3.956 3.817 5.497 6.259 7.809 6.749 5.506

420 75 3.208 3.924 4.481 4.623 4.695 4.830 4.260 4.881 6.024 3.328 2.932 3.400 4.146 5.394 6.030 2.286

421 75 6.024 6.102 6.749 6.482 7.276 6.554 5.533 7.235 6.102 6.218 6.030 6.831 8.058 7.920 7.302 6.626

422 68 4.303 4.592 5.643 6.379 6.415 5.743 5.809 7.426 6.337 5.303 4.647 5.530 6.337 7.253 6.805 5.158

424 84 3.364 3.924 4.315 5.886 6.416 6.236 5.037 3.996 4.929 2.979 4.204 4.759 6.180 7.530 5.975 3.821

429 89 2.036 2.528 2.658 3.051 3.833 3.853 3.707 2.775 1.645 1.050 2.269 1.194 2.348 3.710 2.048 1.820

502 70 3.677 4.417 5.588 5.609 5.712 5.044 4.204 4.941 4.773 5.753 4.869 5.188 6.963 7.396 6.638 4.941

504 83 6.042 5.813 6.364 7.262 8.097 7.661 6.934 7.119 7.208 6.474 6.374 6.861 7.764 7.961 7.180 6.167

154

ID # AGE 0° 22.5° 45° 67.5° 90° 112.5° 135° 157.5° 180° 202.5° 225° 247.5° 270° 292.5° 315° 337.5°

505 73 3.931 4.462 5.274 4.560 5.528 5.351 5.628 5.726 4.847 5.140 4.537 4.459 6.514 7.922 6.639 4.759

506 66 3.646 4.552 4.324 6.656 6.771 6.014 5.053 5.147 6.771 4.764 5.281 4.990 6.844 7.069 6.268 4.045

508 74 4.000 6.038 5.441 4.679 6.000 5.798 6.865 6.156 7.069 4.889 4.675 5.019 6.292 6.994 6.158 4.576

509 62 7.355 7.749 8.677 8.324 8.105 7.422 6.983 8.294 10.500 8.855 7.661 8.149 9.250 9.367 9.178 8.151

511 72 5.014 5.880 6.384 7.156 7.514 7.826 8.191 7.608 7.681 6.891 5.912 7.089 8.362 8.405 8.014 6.995

512 62 2.366 2.273 2.792 3.935 4.865 3.570 3.661 3.604 2.312 2.481 2.667 2.261 3.292 5.012 5.480 3.530

513 50 4.333 5.195 5.363 6.401 7.431 6.828 6.433 6.644 8.514 6.056 5.343 5.446 7.500 7.054 6.197 4.955

514 56 4.278 4.839 5.500 5.486 6.167 7.207 6.354 6.481 9.194 6.272 4.832 5.696 6.972 7.782 7.926 6.752

515 69 2.063 2.238 3.005 4.008 6.490 5.511 4.699 5.639 2.782 2.524 2.615 3.463 6.240 7.197 3.204 2.609

516 91 3.480 3.310 3.992 5.046 5.583 5.279 4.272 3.660 3.907 3.440 2.666 3.409 4.469 6.418 5.694 3.203

517 75 3.188 3.379 4.780 5.168 4.365 3.616 3.293 4.205 5.281 4.043 3.020 3.563 4.635 5.736 4.972 3.581

518 79 3.490 2.424 4.419 5.573 5.708 4.730 4.537 4.525 5.396 3.878 3.690 4.329 6.792 7.452 6.423 4.620

519 52 3.944 4.070 4.537 6.487 5.361 4.994 4.753 6.789 6.153 5.084 6.413 6.080 7.444 7.756 6.767 5.757

520 58 3.292 4.209 4.292 5.205 5.556 5.345 5.520 5.483 4.583 3.294 3.919 4.534 6.306 5.987 5.077 4.191

521 77 6.563 6.894 7.115 7.567 8.771 7.950 8.324 9.246 8.167 6.813 6.791 7.044 7.834 8.502 8.559 7.656

523 74 5.153 4.931 6.364 7.326 6.847 6.900 6.246 6.051 7.389 6.480 6.462 6.695 7.278 7.421 7.071 5.978

524 74 1.181 1.220 1.188 4.290 6.222 4.802 3.437 1.213 2.431 2.430 2.779 3.529 5.944 7.227 5.912 1.290

525 71 5.896 5.714 6.292 8.885 8.958 9.191 8.353 9.192 12.396 8.852 6.953 6.976 8.000 9.484 8.310 6.585

604 52 5.958 6.058 5.907 7.504 7.834 6.984 6.703 7.873 10.500 6.225 6.055 6.497 8.125 8.324 7.631 6.592

610 56 4.000 4.826 5.136 5.579 5.778 4.878 4.331 5.047 4.792 3.529 5.019 5.754 6.583 5.871 4.498 3.933

615 57 4.021 4.133 5.466 7.047 6.333 5.220 4.950 5.702 7.292 5.513 4.670 4.692 5.333 5.468 5.023 4.848

618 59 4.208 3.938 3.956 5.265 6.938 5.898 4.832 5.537 7.083 4.604 4.773 5.925 6.240 7.277 5.804 4.499

619 60 4.986 5.770 6.600 6.155 5.583 4.946 5.225 7.637 10.528 7.273 5.392 4.842 5.847 6.947 7.219 6.195

620 53 3.750 3.993 4.410 6.073 5.626 4.942 3.930 5.225 5.569 5.372 4.135 5.099 5.958 5.847 5.039 4.220

706 61 3.542 3.885 5.289 6.837 6.646 5.994 5.304 6.263 7.709 5.270 4.980 4.771 5.646 5.496 5.068 4.070

715 51 3.514 3.516 4.607 5.535 6.361 5.974 5.628 7.485 8.278 6.285 4.508 4.106 5.014 5.367 5.549 4.555

717 63 4.486 4.691 6.197 5.841 6.042 5.497 5.510 5.947 7.486 4.671 5.195 6.339 6.944 6.629 6.256 5.715

802 79 5.806 6.053 5.971 6.766 7.375 6.538 5.578 8.478 8.097 5.814 6.267 6.658 7.819 8.338 7.690 6.285

805 74 4.903 5.563 5.902 5.887 6.347 5.857 5.578 5.942 7.958 4.836 4.087 5.283 7.306 7.756 7.160 5.741

806 80 5.015 5.553 6.423 6.722 6.556 6.232 6.403 7.062 9.347 5.940 5.323 6.533 7.361 7.878 6.934 5.868

811 76 2.292 4.348 5.058 6.055 6.069 4.888 4.380 4.854 2.833 3.157 3.830 4.630 5.486 5.101 4.056 2.785

812 93 1.724 1.117 3.349 4.407 3.556 3.467 3.713 4.746 4.472 2.847 2.023 1.899 2.000 2.997 3.575 2.476

813 74 2.945 2.595 3.271 3.945 4.486 4.523 4.047 3.652 1.905 2.056 2.829 3.565 3.820 4.447 3.860 3.425

814 88 1.938 3.052 3.786 4.530 4.063 4.423 4.154 5.652 5.583 2.722 1.856 3.698 4.354 6.143 5.826 4.039

815 81 2.802 3.469 4.250 4.437 3.750 3.530 3.418 3.741 3.438 4.242 4.272 4.827 5.021 4.750 3.256 3.314

816 63 4.656 5.525 6.659 7.677 7.469 5.957 5.915 7.020 6.438 5.929 5.274 5.232 6.979 7.889 7.425 5.793

818 63 2.302 1.983 3.462 4.385 4.948 4.443 3.617 4.199 3.990 2.922 2.873 2.714 3.750 5.362 3.631 3.376

819A 80 1.472 1.371 1.571 4.880 5.215 4.258 4.051 2.904 2.458 1.870 2.249 2.788 3.389 4.270 4.311 2.155

820 72 2.844 3.271 2.740 4.180 5.500 4.845 3.389 2.600 2.448 1.813 2.939 4.008 5.812 5.208 3.226 2.470

822 83 3.986 4.452 5.795 5.705 7.069 6.947 7.110 7.479 7.153 4.666 4.950 4.174 6.639 7.654 6.423 5.403

823 48 6.052 6.749 6.438 7.876 7.385 6.351 6.541 7.267 8.031 6.379 5.856 6.813 8.094 7.824 6.997 6.167

824 82 2.778 3.070 3.840 4.670 5.986 4.276 3.364 4.129 5.611 3.580 3.894 2.646 3.000 3.625 2.878 2.449

826 56 4.514 4.630 5.402 6.514 5.764 6.057 5.510 7.142 11.486 6.445 5.657 5.517 6.125 7.510 7.248 5.140

902 92 2.760 3.219 3.705 5.393 5.948 5.191 4.117 3.349 6.313 3.842 3.020 4.038 4.854 6.201 2.873 2.468

903 80 3.056 3.108 4.164 4.682 5.292 3.642 3.418 4.503 7.917 4.176 2.466 2.688 3.847 5.484 6.089 4.230

904 80 3.511 3.254 3.374 3.413 3.844 4.009 3.366 4.238 5.448 3.637 3.286 3.722 4.406 5.241 4.729 3.486

905 84 2.000 3.059 3.516 4.667 4.250 3.622 2.809 1.997 1.473 2.580 2.023 3.449 4.736 4.416 3.192 2.455

906 85 5.021 5.072 5.613 5.950 6.708 6.423 5.775 5.970 7.708 5.687 5.805 6.295 7.063 6.918 6.364 5.536

908B 84 1.174 1.224 1.601 2.912 4.924 2.416 2.175 1.321 2.292 2.065 2.175 3.144 3.035 4.636 4.390 1.865

909B 79 3.927 4.147 4.869 5.079 7.052 6.305 4.169 2.519 2.854 3.647 2.026 5.395 7.073 7.929 6.069 2.979

155

ID # AGE 0° 22.5° 45° 67.5° 90° 112.5° 135° 157.5° 180° 202.5° 225° 247.5° 270° 292.5° 315° 337.5°

910 74 1.896 1.567 3.292 4.220 4.448 3.716 3.072 3.381 3.542 2.414 1.879 2.485 3.781 5.313 4.795 2.725

913 85 6.181 5.553 5.745 5.418 6.306 5.565 5.529 5.759 8.097 2.858 4.753 5.258 6.889 8.156 8.387 7.781

916 78 3.307 2.442 2.829 4.392 5.014 4.844 3.752 4.328 6.875 3.356 3.516 3.555 5.167 5.457 5.952 4.852

921A 96 1.563 1.646 2.379 3.474 4.073 3.391 3.292 3.544 3.094 2.882 2.615 2.794 3.585 4.741 4.943 3.867

922 94 1.688 1.155 3.992 4.714 5.344 4.626 3.197 4.493 4.406 2.213 2.262 2.552 4.625 6.158 6.180 2.172

923B 80 2.052 1.853 2.461 4.359 4.594 3.663 2.873 2.853 2.136 2.145 2.733 2.910 4.531 4.467 3.042 2.736

925 80 4.979 5.838 6.460 6.530 6.750 6.007 5.878 6.621 8.219 6.381 5.561 6.434 6.833 7.286 6.497 5.385

927 80 5.417 4.864 5.667 7.136 6.917 6.664 6.462 6.139 8.542 5.179 4.832 5.912 7.153 7.979 7.336 5.965

1005 84 4.306 4.449 5.687 5.329 6.208 6.354 6.688 7.851 7.056 6.028 4.479 4.694 5.917 7.321 6.943 5.406

1006 73 4.969 6.428 6.011 6.057 7.219 6.292 5.834 5.468 7.875 8.223 5.230 6.270 7.333 7.690 6.997 5.683

1010 64 5.084 4.601 6.590 7.716 7.306 6.947 6.335 5.965 8.472 6.236 5.294 5.778 6.931 7.822 7.061 5.803

1017 59 6.135 6.329 5.569 6.769 7.771 7.604 6.519 6.438 9.219 7.952 7.682 7.942 8.427 8.658 7.646 6.395

1021 63 6.042 7.118 8.436 6.726 5.639 5.938 6.285 7.740 10.181 7.366 6.217 6.460 7.514 8.535 8.908 7.340

1023 79 4.501 5.359 4.459 5.736 7.111 6.994 6.452 5.847 6.834 6.193 5.313 5.070 6.250 5.876 6.050 4.715

1026 52 4.528 3.626 3.870 4.811 6.514 6.498 6.129 6.195 7.653 5.530 4.606 5.526 7.320 8.776 7.454 6.231

1103 69 4.208 4.501 5.569 5.395 5.528 5.810 5.117 5.927 6.472 5.592 5.264 5.442 6.445 7.986 6.020 5.081

1109 69 3.719 4.664 4.604 4.817 5.646 5.526 4.869 6.335 6.844 5.254 3.882 3.753 5.042 6.690 7.351 4.938

1119 62 4.556 4.232 4.832 6.664 8.431 7.193 6.443 7.616 6.611 5.766 4.881 5.834 6.986 7.264 6.315 4.261

1121 55 5.281 5.261 5.237 6.067 6.875 6.579 6.291 5.633 6.844 5.151 5.370 5.841 6.750 6.605 6.490 6.066

1122 64 4.031 4.217 5.164 6.568 6.198 4.801 4.295 6.588 6.802 4.689 3.861 4.789 6.594 7.803 6.651 4.534

1123 83 2.531 4.358 4.722 5.229 4.594 3.838 3.764 5.246 3.022 2.799 3.904 4.158 4.500 5.325 5.451 4.368

1124 84 3.365 3.138 4.538 4.887 5.115 3.647 3.359 4.305 7.615 3.559 3.618 3.755 4.563 4.973 4.964 4.002

1203 81 5.708 6.399 6.762 7.686 8.646 8.089 8.809 7.815 7.229 6.882 7.329 8.012 9.396 9.283 8.515 7.846

1213 70 6.153 6.123 6.826 7.174 7.611 7.311 7.169 7.902 11.000 7.000 6.492 7.278 8.431 8.669 7.317 6.422

1214 76 6.278 6.138 6.767 7.574 7.278 7.038 6.796 7.632 10.528 7.232 5.686 5.634 6.458 7.517 8.132 7.317

1215 75 4.958 5.349 5.137 4.380 5.097 5.444 5.883 5.251 5.764 5.107 4.508 5.039 5.903 6.542 5.981 5.130

1218 97 4.570 4.903 5.146 4.926 5.097 5.996 7.150 8.555 8.667 6.897 4.773 5.263 6.042 7.968 7.523 6.513

1305 83 3.347 3.362 3.452 5.816 6.722 4.650 4.704 5.750 5.743 3.337 3.295 3.824 4.910 5.432 4.876 4.133

1306 68 1.875 2.311 4.144 4.844 5.833 4.272 4.105 4.013 2.820 3.232 3.585 3.148 4.306 4.691 4.773 3.711

1308 96 1.306 1.429 1.208 2.739 3.743 3.650 2.259 1.654 1.938 1.131 1.493 1.816 3.431 4.168 2.456 1.305

1311 73 5.542 5.774 5.650 5.897 6.021 5.825 5.789 5.413 4.479 6.178 7.042 8.718 9.063 7.418 6.121 5.815

1312 60 4.802 5.873 6.688 8.041 9.323 8.612 7.027 7.528 6.542 5.209 5.568 6.571 7.771 8.447 6.438 4.430

1313 64 6.583 6.306 5.500 6.688 7.181 7.220 7.493 7.317 7.181 4.769 5.383 6.620 7.792 7.572 6.826 6.267

1314 64 5.639 5.328 5.452 6.309 8.167 6.850 5.647 4.887 3.875 4.859 6.590 7.401 7.028 6.766 6.177 6.025

1319 68 2.302 2.491 3.529 5.667 6.271 4.843 3.344 3.981 4.969 3.154 2.932 3.861 5.073 6.675 4.972 3.511

1325 74 2.729 2.366 1.657 5.489 8.875 7.123 4.346 2.207 1.208 1.950 4.235 6.779 8.615 7.959 4.714 3.273

1401 86 2.552 2.905 4.044 6.211 7.219 5.397 3.101 3.774 5.354 5.198 4.044 4.110 5.708 3.844 3.300 2.215

1402 72 4.847 5.442 5.235 5.936 5.889 5.832 6.649 4.635 3.875 3.038 5.146 6.525 7.028 6.491 5.578 4.844

1404 88 4.219 5.820 7.837 8.743 9.115 8.329 7.719 8.474 10.306 7.688 5.490 5.827 8.125 10.319 9.242 7.356

1405 85 4.719 4.230 4.074 5.665 7.146 6.842 5.848 5.857 6.938 4.681 5.090 5.381 7.104 7.077 6.909 5.662

1406 79 4.820 5.965 6.089 6.844 6.181 6.173 6.551 7.448 6.792 5.439 5.657 7.424 9.389 8.362 6.226 4.996

1410 82 2.542 1.909 1.805 2.246 4.406 2.814 3.167 4.308 3.594 3.737 3.550 3.869 3.063 3.511 3.838 3.370

1412 83 2.347 2.569 3.565 3.856 4.708 3.999 3.300 3.967 4.736 4.173 2.495 2.935 4.195 3.576 3.438 2.551

1414 68 3.861 3.954 4.979 6.086 7.514 6.137 4.891 5.104 6.181 4.356 4.508 5.665 6.931 9.181 9.055 5.465

1416 83 3.514 3.026 4.773 6.259 6.958 6.261 5.421 5.202 6.361 4.908 4.439 6.071 6.125 5.696 6.953 4.521

1419 73 4.722 5.012 5.510 6.452 8.208 7.740 7.336 7.549 9.500 6.378 5.755 6.155 6.597 7.412 7.101 5.790

1420 71 4.611 4.186 4.558 5.064 5.278 5.683 5.608 5.803 7.875 5.318 4.587 4.984 6.056 6.872 7.169 5.411

1421 85 2.781 3.337 4.596 5.403 4.385 3.991 3.933 4.389 1.969 1.006 2.541 2.814 3.979 4.031 3.712 2.174

1424 87 4.014 4.661 6.177 7.331 7.319 5.861 4.213 4.544 5.181 4.000 5.902 6.962 7.250 6.996 6.109 4.217

1426 74 4.750 4.488 5.127 6.620 6.028 5.329 4.400 6.045 7.361 4.509 4.694 5.263 6.389 6.992 7.150 6.257

156

Appendix E: Research Sample Remodeling Data

157

INDI

V #

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

239

615

.000

505

18.3

3335

312

.667

553

19.3

3329

310

.667

432

15.0

0038

113

.000

543

19.0

005

434

15.6

6749

317

.333

483

17.0

0064

021

.333

620

20.6

6741

013

.667

490

16.3

3345

015

.000

636

413

.333

541

18.3

3353

017

.667

520

17.3

3338

012

.667

520

17.3

3355

018

.333

551

18.6

678

3313

15.3

3346

115

.667

690

23.0

0050

016

.667

680

22.6

6748

216

.667

610

20.3

3336

012

.000

960

120

.333

683

23.6

6751

117

.333

563

19.6

6759

120

.000

450

15.0

0049

016

.333

630

21.0

0011

460

15.3

3360

220

.667

591

20.0

0061

120

.667

400

13.3

3345

215

.667

542

18.6

6763

021

.000

1440

113

.667

451

15.3

3335

112

.000

470

15.6

6747

116

.000

444

16.0

0029

09.

667

360

12.0

0015

580

19.3

3357

019

.000

620

20.6

6782

328

.333

721

24.3

3389

230

.333

673

23.3

3362

020

.667

1766

022

.000

763

26.3

3381

127

.333

119

742

.000

731

24.6

6776

426

.667

741

25.0

0011

40

38.0

0018

513

18.0

0040

113

.667

570

19.0

0063

021

.000

520

17.3

3345

115

.333

510

17.0

0070

023

.333

1940

013

.333

333

12.0

0057

119

.333

570

19.0

0040

013

.333

390

13.0

0054

018

.000

571

19.3

3322

784

27.3

3392

030

.667

108

036

.000

982

33.3

3386

129

.000

751

25.3

3384

028

.000

731

24.6

6725

402

14.0

0060

120

.333

160

5.33

375

025

.000

730

24.3

3339

013

.000

402

14.0

0052

218

.000

2743

014

.333

521

17.6

6745

115

.333

520

17.3

3341

214

.333

472

16.3

3346

015

.333

560

18.6

6710

141

013

.667

541

18.3

3336

313

.000

441

15.0

0036

212

.667

400

13.3

3333

412

.333

420

14.0

0010

256

219

.333

451

15.3

3365

222

.333

632

21.6

6751

719

.333

675

24.0

0064

021

.333

551

18.6

6710

347

316

.667

520

17.3

3367

022

.333

790

26.3

3372

224

.667

700

23.3

3347

015

.667

510

17.0

0010

446

216

.000

282

10.0

0034

412

.667

431

14.6

6726

510

.333

310

10.3

3352

418

.667

293

10.6

6710

551

318

.000

641

21.6

6764

021

.333

720

24.0

0046

216

.000

730

24.3

3367

022

.333

630

21.0

0010

648

216

.667

360

12.0

0048

016

.000

470

15.6

6751

017

.000

421

14.3

3346

115

.667

442

15.3

3310

745

115

.333

501

17.0

0066

122

.333

730

24.3

3352

017

.333

700

23.3

3345

316

.000

560

18.6

6710

866

022

.000

592

20.3

3340

314

.333

674

23.6

6754

118

.333

454

16.3

3351

017

.000

560

18.6

6710

950

117

.000

361

12.3

3350

016

.667

502

17.3

3353

118

.000

504

18.0

0036

012

.000

500

16.6

6711

058

119

.667

643

22.3

3367

022

.333

730

24.3

3374

125

.000

770

25.6

6766

022

.000

680

22.6

6711

342

014

.000

441

15.0

0057

019

.000

502

17.3

3338

113

.000

600

20.0

0051

117

.333

513

18.0

0011

750

016

.667

491

16.6

6747

015

.667

640

21.3

3343

014

.333

480

16.0

0048

317

.000

620

20.6

6711

957

019

.000

651

22.0

0051

017

.000

520

17.3

3359

220

.333

610

20.3

3346

015

.333

510

17.0

0012

064

121

.667

771

26.0

0065

322

.667

840

28.0

0074

024

.667

640

21.3

3366

222

.667

850

28.3

3312

144

014

.667

540

18.0

0056

018

.667

380

12.6

6765

021

.667

471

16.0

0057

219

.667

463

16.3

3312

452

017

.333

475

17.3

3358

019

.333

594

21.0

0049

116

.667

591

20.0

0050

117

.000

586

21.3

3312

535

513

.333

323

11.6

6727

09.

000

481

16.3

3331

010

.333

350

11.6

673

01.

000

482

16.6

6712

664

121

.667

256

10.3

3352

017

.333

660

22.0

0076

125

.667

630

21.0

0058

019

.333

334

12.3

3312

760

120

.333

672

23.0

0038

012

.667

670

22.3

3354

218

.667

571

19.3

3349

116

.667

762

26.0

0012

843

014

.333

600

20.0

0064

121

.667

790

26.3

3346

015

.333

600

20.0

0070

023

.333

680

22.6

6712

950

016

.667

510

17.0

0053

017

.667

720

24.0

0056

018

.667

610

20.3

3357

019

.000

720

24.0

0013

062

020

.667

541

18.3

3355

118

.667

530

17.6

6745

115

.333

431

14.6

6751

017

.000

550

18.3

3313

253

017

.667

541

18.3

3363

021

.000

790

26.3

3369

023

.000

540

18.0

0062

020

.667

840

28.0

0013

363

121

.333

641

21.6

6750

117

.000

811

27.3

3384

028

.000

590

19.6

6759

120

.000

560

18.6

6713

642

014

.000

622

21.3

3337

413

.667

511

17.3

3356

219

.333

441

15.0

0046

216

.000

366

14.0

0020

351

418

.333

683

23.6

6763

021

.000

530

17.6

6771

124

.000

510

17.0

0062

020

.667

710

23.6

6720

470

123

.667

532

18.3

3373

024

.333

701

23.6

6762

020

.667

620

20.6

6760

020

.000

680

22.6

6720

538

113

.000

403

14.3

3374

024

.667

700

23.3

3358

119

.667

622

21.3

3358

019

.333

622

21.3

3320

869

023

.000

654

23.0

0061

120

.667

660

22.0

0065

021

.667

614

21.6

6761

020

.333

591

20.0

0020

942

515

.667

504

18.0

0049

1220

.333

513

18.0

0056

921

.667

573

20.0

0043

616

.333

443

15.6

6721

454

018

.000

540

18.0

0052

017

.333

590

19.6

6762

121

.000

500

16.6

6753

017

.667

490

16.3

3321

632

311

.667

397

15.3

3346

316

.333

294

11.0

0029

511

.333

353

12.6

6738

414

.000

330

11.0

0021

754

018

.000

520

17.3

3356

018

.667

681

23.0

0050

117

.000

521

17.6

6750

016

.667

611

20.6

6721

848

216

.667

680

22.6

6748

517

.667

531

18.0

0054

118

.333

511

17.3

3339

013

.000

460

15.3

3321

944

014

.667

670

22.3

3349

016

.333

620

20.6

6748

116

.333

400

13.3

3340

013

.333

520

17.3

3322

046

015

.333

600

20.0

0043

014

.333

451

15.3

3346

015

.333

480

16.0

0050

016

.667

460

15.3

33

Imax

Ant

Imax

Post

Imin

Med

Imin

Lat

ANTE

RIO

RPO

STER

IOR

MED

IAL

LATE

RAL

158

INDI

V #

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

222

660

22.0

0072

124

.333

630

21.0

0064

021

.333

580

19.3

3356

018

.667

620

20.6

6757

019

.000

224

280

9.33

337

012

.333

590

19.6

6755

018

.333

300

10.0

0032

010

.667

500

16.6

6748

016

.000

225

510

17.0

0060

220

.667

534

19.0

0060

020

.000

582

20.0

0055

118

.667

481

16.3

3357

219

.667

226

510

17.0

0071

023

.667

551

18.6

6767

223

.000

392

13.6

6769

023

.000

661

22.3

3354

018

.000

227

609

23.0

0050

418

.000

688

25.3

3352

218

.000

4011

17.0

0076

326

.333

695

24.6

6774

024

.667

228

413

14.6

6737

112

.667

380

12.6

6746

115

.667

461

15.6

6740

013

.333

462

16.0

0041

013

.667

233

480

16.0

0039

013

.000

5810

22.6

6740

013

.333

400

13.3

3362

221

.333

521

17.6

6744

416

.000

250

610

20.3

3371

425

.000

650

21.6

6767

022

.333

551

18.6

6769

023

.000

640

21.3

3364

121

.667

251

782

26.6

6768

223

.333

741

25.0

0089

531

.333

925

32.3

3371

023

.667

561

19.0

0068

323

.667

252

5311

21.3

3349

116

.667

550

18.3

3355

1021

.667

551

18.6

6744

416

.000

555

20.0

0053

318

.667

253

402

14.0

0033

412

.333

505

18.3

3357

019

.000

630

21.0

0067

624

.333

230

7.66

724

610

.000

255

605

21.6

6757

320

.000

697

25.3

3372

927

.000

628

23.3

3363

021

.000

5110

20.3

3339

815

.667

257

510

17.0

0055

419

.667

682

23.3

3373

225

.000

560

18.6

6754

218

.667

822

28.0

0077

326

.667

301

328

13.3

3346

115

.667

652

22.3

3360

020

.000

473

16.6

6752

218

.000

392

13.6

6752

218

.000

302

643

22.3

3366

323

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26.6

6767

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27.3

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16.3

3365

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6745

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18.6

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18.3

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630

21.0

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31.6

6794

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28.6

6792

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26.6

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319

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18.0

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601

20.3

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13.6

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15.6

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429

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390

13.0

0047

015

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360

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115

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362

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24.3

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018

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650

21.6

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119

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591

20.0

0071

224

.333

Imin

Med

Imin

Lat

ANTE

RIO

RPO

STER

IOR

MED

IAL

LATE

RAL

Imax

Ant

Imax

Post

159

INDI

V #

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

505

620

20.6

6751

117

.333

560

18.6

6771

023

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540

18.0

0061

020

.333

630

21.0

0071

124

.000

506

332

11.6

6736

212

.667

690

23.0

0079

026

.333

502

17.3

3331

110

.667

590

19.6

6771

023

.667

508

370

12.3

3342

014

.000

602

20.6

6763

021

.000

600

20.0

0061

020

.333

480

16.0

0055

118

.667

509

620

20.6

6755

018

.333

680

22.6

6771

023

.667

591

20.0

0046

015

.333

601

20.3

3384

228

.667

511

561

19.0

0076

025

.333

541

18.3

3350

016

.667

460

15.3

3357

019

.000

470

15.6

6773

024

.333

512

432

15.0

0036

313

.000

393

14.0

0043

415

.667

411

14.0

0045

015

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440

14.6

6734

212

.000

513

330

11.0

0033

211

.667

341

11.6

6746

216

.000

361

12.3

3339

213

.667

421

14.3

3345

115

.333

514

550

18.3

3348

116

.333

491

16.6

6759

019

.667

700

23.3

3358

521

.000

552

19.0

0051

017

.000

515

466

17.3

3348

216

.667

513

18.0

0044

315

.667

444

16.0

0058

019

.333

462

16.0

0048

216

.667

516

353

12.6

6744

014

.667

461

15.6

6743

014

.333

363

13.0

0054

118

.333

530

17.6

6751

017

.000

517

510

17.0

0059

120

.000

592

20.3

3370

224

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533

18.6

6743

114

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643

22.3

3375

025

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518

501

17.0

0056

119

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770

25.6

6756

119

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410

13.6

6745

015

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700

23.3

3368

022

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519

361

12.3

3344

014

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850

28.3

3374

024

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440

14.6

6737

213

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721

24.3

3367

022

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520

522

18.0

0062

321

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702

24.0

0079

026

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720

24.0

0057

019

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501

17.0

0066

222

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521

510

17.0

0059

120

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531

18.0

0048

016

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472

16.3

3357

019

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500

16.6

6749

016

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523

502

17.3

3353

017

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521

17.6

6763

021

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490

16.3

3351

017

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600

20.0

0058

019

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524

251

8.66

749

016

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531

18.0

0069

023

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710

23.6

6750

117

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243

9.00

036

112

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800

26.6

6785

329

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575

20.6

6763

021

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910

30.3

3366

122

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551

18.6

6770

023

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604

460

15.3

3346

115

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450

15.0

0050

016

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430

14.3

3332

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490

16.3

3347

015

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610

360

12.0

0040

414

.667

573

20.0

0047

116

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530

17.6

6768

022

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621

21.0

0054

319

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615

440

14.6

6728

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333

503

17.6

6753

118

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490

16.3

3336

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451

15.3

3346

115

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618

680

22.6

6773

024

.333

760

25.3

3380

026

.667

780

26.0

0076

025

.333

590

19.6

6769

023

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619

731

24.6

6762

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.667

660

22.0

0081

127

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680

22.6

6749

016

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630

21.0

0088

029

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620

440

14.6

6748

016

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640

21.3

3362

020

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370

12.3

3374

024

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470

15.6

6766

022

.000

706

470

15.6

6749

016

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610

20.3

3358

019

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431

14.6

6743

014

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410

13.6

6754

018

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715

571

19.3

3365

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650

21.6

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019

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520

17.3

3358

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710

23.6

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17.3

3356

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671

22.6

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802

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17.0

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213

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19.6

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600

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17.3

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574

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806

580

19.3

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711

24.0

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123

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570

19.0

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018

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23.6

6762

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20.6

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600

20.0

0058

019

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642

22.0

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016

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582

20.0

0061

020

.333

812

612

21.0

0058

019

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850

28.3

3371

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760

25.3

3363

121

.333

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29.3

3373

124

.667

813

556

20.3

3348

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732

25.0

0068

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640

21.3

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511

17.3

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123

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814

560

18.6

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222

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700

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640

21.3

3360

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701

23.6

6770

023

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651

22.0

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011

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470

15.6

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451

15.3

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450

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17.0

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400

13.3

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17.3

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550

18.3

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420

14.0

0053

318

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594

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480

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17.6

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242

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330

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433

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3342

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230

7.66

731

110

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820

281

9.66

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114

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19.3

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114

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10.6

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2713

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440

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326

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19.3

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550

18.3

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540

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902

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19.6

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670

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3366

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610

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3375

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440

14.6

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217

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21.6

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540

18.0

0058

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19.6

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551

18.6

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213

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19.0

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023

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577

21.3

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18.3

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600

20.0

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225

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611

20.6

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660

22.0

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21.6

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340

11.3

3341

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15.3

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400

13.3

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374

13.6

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590

19.6

6762

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531

18.0

0055

018

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351

12.0

0045

115

.333

ANTE

RIO

RPO

STER

IOR

MED

IAL

LATE

RAL

Imax

Ant

Imax

Post

Imin

Med

Imin

Lat

160

INDI

V #

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

Ost

eons

Frag

sO

PD

910

390

13.0

0043

114

.667

340

11.3

3334

011

.333

471

16.0

0040

013

.333

350

11.6

6739

213

.667

913

473

16.6

6738

012

.667

521

17.6

6758

320

.333

550

18.3

3352

017

.333

420

14.0

0058

019

.333

916

523

18.3

3358

220

.000

620

20.6

6776

125

.667

591

20.0

0053

017

.667

530

17.6

6780

127

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421

14.3

3351

017

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480

16.0

0044

014

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481

16.3

3357

019

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341

11.6

6760

020

.000

922

478

18.3

3349

417

.667

529

20.3

3388

731

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742

25.3

3375

225

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498

19.0

0055

018

.333

923B

292

10.3

3344

215

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440

14.6

6742

014

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470

15.6

6752

017

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282

10.0

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010

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925

560

18.6

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119

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460

15.3

3375

225

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16.3

3352

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360

12.0

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022

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927

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26.6

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29.3

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24.0

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670

22.3

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120

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19.3

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219

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550

18.3

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17.6

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18.0

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116

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19.3

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015

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610

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16.3

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440

14.6

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15.0

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16.0

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.333

1021

570

19.0

0064

121

.667

670

22.3

3386

028

.667

570

19.0

0069

223

.667

561

19.0

0080

026

.667

1023

550

18.3

3358

420

.667

520

17.3

3369

123

.333

640

21.3

3349

016

.333

430

14.3

3340

013

.333

1026

964

33.3

3392

030

.667

670

22.3

3365

322

.667

931

31.3

3354

018

.000

522

18.0

0055

018

.333

1103

510

17.0

0055

118

.667

630

21.0

0069

023

.000

570

19.0

0070

023

.333

540

18.0

0066

122

.333

1109

500

16.6

6754

218

.667

460

15.3

3361

221

.000

470

15.6

6765

021

.667

530

17.6

6750

117

.000

1119

600

20.0

0039

013

.000

551

18.6

6755

018

.333

660

22.0

0043

014

.333

570

19.0

0054

018

.000

1121

522

18.0

0043

114

.667

572

19.6

6769

023

.000

560

18.6

6763

021

.000

540

18.0

0051

418

.333

1122

381

13.0

0048

417

.333

624

22.0

0081

328

.000

563

19.6

6750

719

.000

730

24.3

3382

027

.333

1123

450

15.0

0046

115

.667

470

15.6

6746

517

.000

445

16.3

3345

115

.333

376

14.3

3346

115

.667

1124

562

19.3

3359

019

.667

550

18.3

3361

221

.000

461

15.6

6746

015

.333

612

21.0

0073

024

.333

1203

510

17.0

0062

321

.667

601

20.3

3365

021

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522

18.0

0063

522

.667

521

17.6

6762

221

.333

1213

721

24.3

3381

528

.667

570

19.0

0087

029

.000

720

24.0

0069

023

.000

580

19.3

3385

128

.667

1214

630

21.0

0063

121

.333

540

18.0

0066

022

.000

520

17.3

3357

019

.000

610

20.3

3354

118

.333

1215

480

16.0

0039

013

.000

410

13.6

6755

018

.333

510

17.0

0044

115

.000

460

15.3

3362

321

.667

1218

650

21.6

6793

231

.667

751

25.3

3378

226

.667

760

25.3

3381

027

.000

781

26.3

3367

223

.000

1305

500

16.6

6759

120

.000

691

23.3

3379

026

.333

104

135

.000

694

24.3

3370

023

.333

690

23.0

0013

0645

015

.000

520

17.3

3348

116

.333

561

19.0

0045

115

.333

390

13.0

0052

218

.000

543

19.0

0013

0827

912

.000

420

14.0

0054

018

.000

561

19.0

0045

416

.333

602

20.6

6730

612

.000

343

12.3

3313

1137

012

.333

642

22.0

0057

019

.000

662

22.6

6743

014

.333

563

19.6

6754

018

.000

680

22.6

6713

1257

119

.333

440

14.6

6768

123

.000

670

22.3

3365

222

.333

624

22.0

0052

017

.333

560

18.6

6713

1342

214

.667

500

16.6

6744

014

.667

554

19.6

6748

216

.667

461

15.6

6752

820

.000

500

16.6

6713

1458

019

.333

600

20.0

0066

022

.000

640

21.3

3351

017

.000

671

22.6

6759

019

.667

621

21.0

0013

1960

220

.667

500

16.6

6773

024

.333

760

25.3

3360

020

.000

471

16.0

0070

023

.333

630

21.0

0013

2534

212

.000

392

13.6

6734

111

.667

345

13.0

0039

1116

.667

451

15.3

3332

010

.667

562

19.3

3314

0142

014

.000

391

13.3

3363

121

.333

480

16.0

0044

115

.000

544

19.3

3335

011

.667

422

14.6

6714

0244

014

.667

375

14.0

0054

018

.000

690

23.0

0064

021

.333

571

19.3

3360

120

.333

580

19.3

3314

0462

321

.667

744

26.0

0049

016

.333

630

21.0

0076

426

.667

540

18.0

0064

021

.333

692

23.6

6714

0552

418

.667

640

21.3

3357

019

.000

560

18.6

6761

120

.667

530

17.6

6754

118

.333

511

17.3

3314

0652

418

.667

7114

28.3

3370

023

.333

832

28.3

3353

318

.667

711

24.0

0061

020

.333

760

25.3

3314

1040

314

.333

398

15.6

6755

219

.000

520

17.3

3346

416

.667

582

20.0

0043

716

.667

423

15.0

0014

1248

417

.333

550

18.3

3372

325

.000

694

24.3

3363

121

.333

610

20.3

3365

222

.333

741

25.0

0014

1450

117

.000

412

14.3

3346

015

.333

520

17.3

3353

017

.667

583

20.3

3341

114

.000

471

16.0

0014

1667

223

.000

723

25.0

0067

022

.333

702

24.0

0072

124

.333

710

23.6

6762

723

.000

630

21.0

0014

1952

418

.667

611

20.6

6758

220

.000

602

20.6

6751

017

.000

580

19.3

3353

118

.000

601

20.3

3314

2045

115

.333

332

11.6

6769

123

.333

502

17.3

3361

120

.667

520

17.3

3358

220

.000

480

16.0

0014

2151

117

.333

514

18.3

3344

115

.000

413

14.6

6742

114

.333

462

16.0

0042

214

.667

500

16.6

6714

2459

220

.333

530

17.6

6777

126

.000

740

24.6

6762

020

.667

690

23.0

0067

022

.333

650

21.6

6714

2669

023

.000

490

16.3

3358

019

.333

720

24.0

0070

123

.667

570

19.0

0061

020

.333

751

25.3

33

Imin

Med

Imin

Lat

ANTE

RIO

RPO

STER

IOR

MED

IAL

LATE

RAL

Imax

Ant

Imax

Post

161

Appendix F: Research Sample Remodeling Data Images

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211