characterization of rib cortical bone thickness … · acknowledgement ... distribution of the ages...

Characterization of Rib Cortical Bone Thickness Changes

With Age and Sex

By

Sarah K. Lynch

A Thesis Submitted to the Graduate Faculty of

VIRGINIA TECH – WAKE FOREST UNIVERSITY

SCHOOL OF BIOMEDICAL ENGINEERING & SCIENCES

In Partial Fulfillment of the Requirements

for the Degree of

MASTER OF SCIENCE

Biomedical Engineering

May 2015

Winston-Salem, North Carolina

Approved by:

Joel D. Stitzel, PhD, Advisor, Chair

Examining Committee:

F. Scott Gayzik, PhD

Ashley A. Weaver, PhD

ii

ACKNOWLEDGEMENTS

I would like to start by thanking Dr. Joel D. Stitzel, my advisor and mentor, who

has not only given me the opportunity to pursue higher education but has encouraged me

along the way, both in academics and in life. I can honestly say that I would not be where

I am today without his assistance, understanding, and guidance. I’d like to give a special

thanks to Dr. Ashley Weaver, whose support, contributions, and guidance has been

invaluable, and Dr. Gayzik, for being a great mentor as well. I’d also like to thank Jill

Urban, Elizabeth Davenport, and Samantha Schoell, for their friendship, encouragement,

and support throughout this project, and everyone in the Center for Injury Biomechanics,

for sharing their expertise and support in making this project possible.

I’d finally like to thank my friends and family who have supported me behind the

scenes: offering me encouragement, and understanding as this project came together.

Thanks to my parents, who have always believed in me and offered me motivation when

I needed it most. It is through the efforts of everyone involved, both directly and

indirectly, that this project was made possible.

iii

TABLE OF CONTENTS

List of Tables ............................................................................................................................................ v

List of Figures .......................................................................................................................................... vi

Abstract ................................................................................................................................................ viii

CHAPTER I: INTRODUCTION & BACKGROUND ................................................. 1

Motor Vehicle Crash Thoracic Injuries ...................................................................................................... 1

Thoracic Injury and the Elderly ................................................................................................................. 1

Rib Cortical Bone Thicknesses with Age ................................................................................................... 2

Chapter Summaries .................................................................................................................................. 4 Chapter II: Quantification of Rib Cortical Thickness from Clinical Computed Tomography Scans .................. 4 Chapter III: Characterization and Regression of Rib Cortical Thickness from Clinical Computed Tomography Scans ................................................................................................................................................................ 4 Chapter IV: Summary of Research ................................................................................................................... 4

References ............................................................................................................................................... 5

CHAPTER II: QUANTIFICATION OF RIB CORTICAL THICKNESS FROM

CLINICAL COMPUTED TOMOGRAPHY SCANS ................................................... 8

1. Abstract ............................................................................................................................................... 9

2. Introduction ....................................................................................................................................... 10

3. Methods ............................................................................................................................................. 12

4. Results ............................................................................................................................................... 20

5. Discussion .......................................................................................................................................... 27

6. Conclusion .......................................................................................................................................... 29

7. Acknowledgement ............................................................................................................................. 30

8. References ......................................................................................................................................... 31

9. Appendix ............................................................................................................................................ 34

CHAPTER III: CHARACTERIZATION AND REGRESSION OF RIB

CORTICAL THICKNESS FROM CLINICAL COMPUTED TOMOGRAPHY

SCANS ............................................................................................................................. 36

1. Abstract .............................................................................................................................................. 37

2. Introduction ....................................................................................................................................... 38

3. Methods ............................................................................................................................................. 39

4. Results ............................................................................................................................................... 42

5. Discussion .......................................................................................................................................... 49

6. Conclusion .......................................................................................................................................... 52

iv

7. Acknowledgement ............................................................................................................................. 52

8. References ......................................................................................................................................... 53

CHAPTER IV: SUMMARY OF RESEARCH ............................................................ 56

SCHOLASTIC VITA ..................................................................................................... 57

v

LIST OF TABLES

Table 1. Publication plan for research outlined in this thesis. .......................................... 56

vi

LIST OF FIGURES

Chapter II

Figure 1. Distribution of the ages and sexes of the subjects studied. .............................. 13

Figure 2. A & B) Example illustrating good qualitative agreement between cortical thickness measurements for the microCT and clinical CT scans of the same rib specimen (interior and exterior views shown). ........................................................... 14

Figure 3. The original surface input to the CDM algorithm (A) and the resulting point

cloud of cortical thickness estimations projected onto that surface for a single subject (B).

........................................................................................................................................... 14

Figure 4. Modified cylindrical coordinate system used to partition the thickness

measurements into homologous regions according to longitudinal location along a

centerline (L) and the radial (ρ) and angular (θ) locations within a rib cross-section

normal to the centerline. ................................................................................................... 16

Figure 5. A) Each rib is first broken into segments based on its “Θ” value in relation to

the centroid of the rib (indicated by the green circle). A centroid for each of these

segments is then calculated (yellow circles). B) The segment centroids were then

connected to form a centerline down the length of the rib. .............................................. 17

Figure 6. The number of rings for each rib was determined by the rib level with 10 rings

comprising the first rib, 13 rings in the twelfth rib, and 30 rings making up each of the

second through eleventh ribs. ........................................................................................... 18

Figure 7. Multiple thickness measurements observed at a given angular location (θ) in

original cross sectional slices due to the 3D nature of the rings seen in A) are averaged to

define a single thickness measurement for each θ bin as shown in B). ............................ 20

Figure 8. The CDM estimated cortical thickness measurements (in mm) for a A) 30 year

old male subject and a B) 70 year old male subject. ......................................................... 21

Figure 9. The mean thickness and standard deviation per decade of age for male and

female subjects for the left 9th

rib. These results were typical for all other ribs. .............. 22

Figure 10. Mean thickness by decade for each of the rib levels for both A) females and

B) males. Mean thickness values from the male sternal ribs analyzed in Kemper et al.

(2007) are shown as blue dots in B. .................................................................................. 23

Figure 11. Mean thickness by decade for each of the locations along the rib centerline

for both A) females and B) males. Mean thickness values from lateral and anterior

locations along the sternal ribs analyzed in Kemper et al. (2007) are shown as blue and

black dots in B. ................................................................................................................. 24

vii

Figure 12. Mean thickness changes by decade for the anatomical locations around the

circumference of the ribs for both males and females. Each error bar is constructed using

one standard deviation from the mean. ............................................................................. 25

Figure 13. Mean thickness changes for males and females by decade for each of the

locations around the circumference of the ribs. ................................................................ 26

Figure 14. Mean thickness plotted by location along the rib centerline for four

anatomical locations around the rib circumference. ......................................................... 26

Chapter III

Figure 15. Distribution of the ages and sexes of the subjects included in this study. ...... 40

Figure 16. The organization of A) rings and B) angle measures into anatomical

categories along the length of the rib and around the circumference of the rib,

respectively. ...................................................................................................................... 41

Figure 17. A) An example regression curve for a single sub-section for the males. B)

This sub-section is on the medial aspect of the third ring on the left fifth rib. ................. 43

Figure 18. The resulting cortex thickness for the entire ribcage for both males and

females at ages 20, 40, 60 and 80. .................................................................................... 43

Figure 19. A) The percent change in cortex thickness (average from the entire rib cage)

relative to a 10 year old for both males and females. B) The regressed cortex thickness

with age for both males and females................................................................................. 44

Figure 20. Rib level comparisons for the percent change in cortex thickness compared to

the cortex thickness at age 10 by rib level for A) females and B) males, as well as the

regressed cortical bone thickness with age for C) females and D) males. ........................ 46

Figure 21. The percent change in cortex thickness compared to the cortex thickness at

age 10 by anatomical location down the length of the rib for A) females and B) males, as

well as the regressed cortical bone thickness with age for C) females and D) males....... 48

Figure 22. The percent change in cortex thickness compared to the cortex thickness at

age 10 by anatomical location around the rib circumference for A) females and B) males,

as well as the regressed cortical bone thickness with age for C) females and D) males. . 49

viii

ABSTRACT

Motor vehicle crashes (MVCs) were the leading cause of unintentional fatal

injuries and the fourth leading cause of unintentional nonfatal injuries in the United

States in 2007. Of these injuries, the thoracic injuries rank second in terms of frequency

as well as overall economic cost. Of the thoracic injuries, rib fractures are extremely

common; present in nearly 94% of severely injured belted occupants. Elderly occupants

have increased mortality and morbidity associated with rib fractures. One factor that is

thought to influence rib fracture that changes with age (possibly contributing to increased

injury risk in the elderly population) is the rib cortical bone.

The first aspect of this research outlined novel techniques for estimating rib

cortical bone thickness changes with age and sex from retrospective clinical computed

tomography (CT) scan data. The thicknesses estimated using that technique were then

compared by location within the ribcage and between the different ages and sexes. The

second aspect of this research was to fit a regression curve to the cortex thickness

estimations to characterize the exact cortical thickness changes with age at all of the

different locations within the ribcage for both sexes. These results were also compared by

location within the ribcage and between the different sexes.

1

Chapter I: Introduction & Background

MOTOR VEHICLE CRASH THORACIC INJURIES

In 2009, there were an estimated 10.8 million motor vehicle crashes (MVCs) in

the United States alone, which were responsible for nearly 34,000 deaths in the US.

Worldwide, MVCs kill 1.3 million people. MVCs were the leading cause of

unintentional fatal injuries and the fourth leading cause of unintentional nonfatal injuries

in the United States in 2007. In MVCs, thoracic injury ranks second only to head injury

in terms of frequency, number of fatal and serious injuries, as well as overall economic

cost [1]. Although increases in the number and complexity of safety systems have

decreased the amount of thoracic injuries, rib fractures still remain a common injury

among occupants. Rib fractures have been identified in up to 93.5% of severely or fatally

injured belted occupants [2]. Rib fractures are typically caused by large chest deflections,

inducing bending in the ribs and resulting in fracture.

THORACIC INJURY AND THE ELDERLY

Although rib fractures are common, they are associated with an increased risk in

mortality and morbidity in the elderly population [3-5]. Elderly occupants are not only

more likely to be wearing their seatbelts, which puts them at an increased risk for rib

fractures, but rib fractures in the elderly are associated with over two times the mortality

risk of younger patients [3-5]. One study found that 47% of occupants over the age of 64

who died in a frontal collision sustained a fatal thoracic injury [6]. Another study of

occupants from the Crash Injury Research and Engineering Network (CIREN) database

2

found that rib fractures were the worst chest injury sustained in 40% of occupants over

the age of 60 who died of chest injuries [6]. Holcomb et al found increased rib fracture

risk in patients as young as 45 years of age [7].

In 2005, Kent et al describes three ways that the ribs change with age that may

account for the decrease in injury tolerance of rib fractures in the elderly population: 1)

material changes, 2) compositional changes (including cross sectional cortex area), and 3)

thoracic geometry changes. There has been extensive research done to characterize rib

material property changes with age using coupon, whole rib, and whole thorax loading

configurations [8-10]. Rib geometry changes over a large span of ages have also been

quantified [11, 12]. Studies have also been done that examined rib cortical bone thickness

and area variations throughout the ribcage using microscopy estimation and microCT

measurements [13-15].

Kemper et al. (2007) references a study done on seven male cadaver ribs ranging

in age from 42 to 81 years, and Choi’s 2000 paper also used 7 male cadavers, though they

ranged in age from 64 to 75 years [13, 14, 16]. Both of these studies did, however, find

rib cortex thickness variations with rib level (first through twelfth), attachment (true,

false, versus floating), laterality (right versus left), and anatomical region (anterior,

lateral, posterior, superior, inferior, etc.).

RIB CORTICAL BONE THICKNESSES WITH AGE

Another method of obtaining rib cortical thickness data is from clinical computed

tomography (CT) scan measurements. The full-width at half-maximum (FWHM)

technique applied to CT scans estimates the thickness of an object that does not have

3

clearly defined, sharp edges, as is the case with cortical bone in clinical CT scans due to

limited resolution. The FWHM technique, however, tends to overestimate thicknesses of

objects less than 2.5mm thick such as the ribs. A more accurate method for estimating

cortex thickness from clinical CT scans was proposed by Treece et al. which will

henceforth be referred to as the cortical density method (CDM) [17, 18]. The CDM

assumes a constant cortex density to estimate the cortical bone thickness from the clinical

CT scan allowing for accurate estimation of cortex thickness down to approximately 0.3

mm.

Cortical bone varies in thickness based on changes in bone resorption and

formation, which can be influenced by a person’s hormone and activity levels [19-22]. As

a result, there are rib and regional variations in cortex thickness within an individual as

well as variations in cortex thickness between individuals of different ages and sexes.

Many studies have worked to capture the exact changes in cortex thickness and cortical

area with age, though none have looked at the changes with age and sex regionally within

the ribs [23-25].

The first objective of this study is to apply the CDM to a retrospective collection

of clinical CT scans spanning ages 0-100 and both sexes. The second aim of this study is

to compare the resulting estimated cortical thickness variations with age, sex, rib level,

rib attachment, and anatomical location within each rib. The next objective of this study

is to fit a regression curve to cortical thickness estimates throughout the ribcage to

characterize regional cortex thickness changes with age and sex. The final aim of this

study is to compare the resulting regressed cortical thickness variations with age, sex, rib

level, rib attachment, and anatomical location within each rib.

4

CHAPTER SUMMARIES

Chapter II: Quantification of Rib Cortical Thickness from Clinical Computed

Tomography Scans

The objective of this work is to apply the CDM to a retrospective collection of clinical

CT scans spanning ages 0-100 and both sexes. The second aim of this study is to compare

the resulting estimated cortical thickness variations with rib level, rib attachment, age,

sex, and anatomical location within each rib.

Chapter III: Characterization and Regression of Rib Cortical Thickness from

Clinical Computed Tomography Scans

The objective of this study is to fit a regression curve to cortical thickness estimates

throughout the ribcage to characterize regional cortex thickness changes with age and

sex. The second aim of this study is to compare the resulting regressed cortical thickness

variations with age, sex, rib level, and anatomical location within each rib.

Chapter IV: Summary of Research

A brief overview of work presented in this thesis.

5

REFERENCES

1. Ruan, J., et al., Prediction and analysis of human thoracic impact responses and

injuries in cadaver impacts using a full human body finite element model. Stapp

Car Crash J, 2003. 47: p. 299-321.

2. Arajärvi E, S.S., Chest injuries sustained in severe traffic accidents by seatbelt

wearer. J Trauma, 1989(29): p. 37-41.

3. Stawicki, S.P., et al., Rib fractures in the elderly: a marker of injury severity. J

Am Geriatr Soc, 2004. 52(5): p. 805-8.

4. Bergeron, E., et al., Elderly Trauma Patients with Rib Fractures Are at Greater

Risk of Death and Pneumonia. J Trauma, 2003. 54(3): p. 478-485.

5. Bulger, E.M.M.D., et al., Rib Fractures in the Elderly. Journal of Trauma-Injury

Infection & Critical Care, 2000. 48(6): p. 1040-1047.

6. Kent, R., et al., Structural and material changes in the aging thorax and their role

in crash protection for older occupants. Stapp Car Crash J, 2005. 49: p. 231-49.

7. Holcomb, J.B., et al., Morbidity from rib fractures increases after age 45. J Am

Coll Surg, 2003. 196(4): p. 549-55.

8. Golman, A.J., et al., Injury prediction in a side impact crash using human body

model simulation. Accident Analysis & Prevention, 2014. 64: p. 1-8.

9. El-Jawahri, R.E., Laituri, T.R., Ruan, J.S., Rouhana, S.W., Barbat, S.D.,

Development and Validation of Age-Dependent FE Human Models of a Mid-Sized

Male Thorax. Stapp Car Crash Journal, 2010. 54: p. 407-430.

10. Ito, O., Dokko, Y., Ohashi, K. , Development of adult and elderly FE thorax

skeletal models, in Society of Automotive Engineers. 2009.

6

11. Weaver, A.A., S.L. Schoell, and J.D. Stitzel, Morphometric analysis of variation

in the ribs with age and sex. J Anat, 2014. 225(2): p. 246-61.

12. Gayzik, F.S., et al., Quantification of age-related shape change of the human rib

cage through geometric morphometrics. J Biomech, 2008. 41(7): p. 1545-54.

13. Kemper, A.R., et al., The biomechanics of human ribs: material and structural

properties from dynamic tension and bending tests. Stapp Car Crash J, 2007. 51:

p. 235-73.

14. Choi, Y.C. and I. Lee, Thorax FE Model for Older Population. Japanese Scoeity

of Mechanical Engineers, Fukuoka, 2009.

15. Sedlin, E.D. and H.M. Frost, Variations in Cross-section Area of Rib Cortex.

Journal of Gerontology, 1963. 18: p. 9-13.

16. Kemper, A.R., et al., Material properties of human rib cortical bone from

dynamic tension coupon testing. Stapp Car Crash J, 2005. 49: p. 199-230.

17. Treece, G.M., et al., High resolution cortical bone thickness measurement from

clinical CT data. Med Image Anal, 2010. 14(3): p. 276-90.

18. Treece, G.M., K.E. Poole, and A.H. Gee, Imaging the femoral cortex: thickness,

density and mass from clinical CT. Med Image Anal, 2012. 16(5): p. 952-65.

19. Parfitt, A.M., Age-related structural changes in trabecular and cortical bone:

cellular mechanisms and biomechanical consequences. Calcif Tissue Int, 1984.

36 Suppl 1: p. S123-8.

20. Chen, H., et al., Age-related changes in trabecular and cortical bone

microstructure. Int J Endocrinol, 2013. 2013: p. 213234.

7

21. Macdonald, H.M., et al., Age-related patterns of trabecular and cortical bone loss

differ between sexes and skeletal sites: a population-based HR-pQCT study. J

Bone Miner Res, 2011. 26(1): p. 50-62.

22. Thompson, D.D., Age changes in bone mineralization, cortical thickness, and

haversian canal area. Calcif Tissue Int, 1980. 31(1): p. 5-11.

23. Lillie, E.M., et al., Estimation of skull table thickness with clinical CT and

validation with microCT. J Anat, 2015. 226(1): p. 73-80.

24. Urban, J.E., et al., Evaluation of morphological changes in the adult skull with

age and sex. J Anat, 2014.

25. Karlsson, M.K., et al., An Increase in Forearm Cortical Bone Size After

Menopause May Influence the Estimated Bone Mineral Loss-A 28-Year

Prospective Observational Study. J Clin Densitom, 2015.

8

Chapter II: Quantification of Rib Cortical Thickness from

Clinical Computed Tomography Scans

Sarah K. Lynch, Ashley A. Weaver, Samantha L. Schoell, Joel D. Stitzel

Virginia Tech – Wake Forest University Center for Injury Biomechanics,

Winston-Salem, NC

9

1. ABSTRACT

Motor vehicle crashes (MVCs) are responsible for nearly 34,000 deaths in the

United States, with a large number of serious and fatal injuries sustained in MVCs

occurring in the thorax. Thoracic injuries are associated with increased mortality and

morbidity in elderly populations, most likely due to variations that occur within the

ribcage as people age, including geometry, material property, and compositional (cortex)

changes. In this study, cortical bone thickness changes in the ribs were characterized by

applying a cortical thickness estimation algorithm to retrospective clinical computed

tomography (CT) scans of 241 subjects spanning ages 0-100 in both sexes. The rib cortex

thickness estimations were then partitioned into homologous regions and compared with

age, sex, rib level, rib attachment, and anatomical location within each rib. The cortex

was thicker in the manubrial (ribs 1-2) and floating ribs (ribs 8-10) in the females

compared to the female sternal (ribs 3-7) and false (ribs 11-12) ribs, though there was not

much difference in cortex thickness based on rib level for the males. The anterior

portions of the rib cortical bone remained the thinnest for both males and females,

increasing in thickness to a maximum at the lateral portions of the ribs, and then thinning

to the posterior portions. The exterior and interior portions of the ribs were thicker than

the superior and inferior aspects for all locations down the length of the rib for both males

and females for ages 10 and older. Understanding these changes will lead to more

biofidelic thorax models and will lead to enhanced safety for occupants of all ages.

10

2. INTRODUCTION

In 2009, there were an estimated 10.8 million motor vehicle crashes (MVCs) in

the United States alone, which were responsible for nearly 34,000 deaths. In MVCs,

thoracic injury ranks second only to head injury in terms of frequency, number of fatal

and serious injuries, as well as overall economic cost [1]. Specifically, rib fractures have

been identified in up to 93.5% of severely or fatally injured belted occupants [2].

Although rib fractures are common, they are associated with an increased risk in

mortality and morbidity in the elderly population [3-5]. Elderly occupants are not only

more likely to be wearing their seatbelts, which puts them at an increased risk for rib

fractures, but rib fractures in the elderly are associated with over two times the mortality

risk of younger patients [3-5]. One study found that 47% of occupants over the age of 64

who died in a frontal collision sustained a fatal thoracic injury [6]. Another study of

occupants from the Crash Injury Research and Engineering Network (CIREN) database

found that rib fractures were the worst chest injury sustained in 40% of occupants over

the age of 60 who died of chest injuries [6].

Kent et al. (2005) described three ways that the ribs change with age that may

account for the decrease in injury tolerance of rib fractures in the elderly population: 1)

material changes, 2) compositional changes (including cross sectional cortex area), and 3)

thoracic geometry changes [6]. There has been extensive research done to characterize rib

material property changes with age using coupon, whole rib, and whole thorax loading

configurations [7-9]. Rib geometry changes over a large span of ages have also been

quantified [10, 11]. Accurate quantification of rib cortical bone thickness variation with

age and between the sexes has been limited in previous studies, as this thickness is

11

usually measured using microCT scans of elderly cadaver ribs. Kemper et al. (2007)

references a study done on seven male cadaver ribs ranging in age from 42 to 81 years,

and Choi and Lee (2009) also used 7 male cadavers, though they ranged in age from 64 to

75 years [12-14]. Both of these studies did, however, find rib cortex thickness variations

with rib level (first through twelfth), attachment (true, false, versus floating), laterality

(right versus left), and anatomical region (anterior, lateral, posterior, superior, inferior,

etc.).

Another method of obtaining rib cortical thickness data is from clinical computed

tomography (CT) scan measurements. The full-width at half-maximum (FWHM)

technique applied to CT scans estimates the thickness of an object that does not have

clearly defined, sharp edges, as is the case with cortical bone in clinical CT scans due to

limited resolution. The FWHM technique, however, tends to overestimate thicknesses of

objects less than 2.5mm thick such as the ribs. A more accurate method for estimating

cortex thickness from clinical CT scans was proposed by Treece et al. which will

henceforth be referred to as the cortical density method (CDM) [15, 16]. The CDM

assumes a constant cortex density to estimate the cortical bone thickness from the clinical

CT scan allowing for accurate estimation of cortex thickness down to approximately 0.3

mm. The objective of this study is to apply the CDM to a retrospective collection of

clinical CT scans spanning ages 0-100 and both sexes. The second aim of this study is to

compare the resulting estimated cortical thickness variations with age, sex, rib level, rib

attachment, and anatomical location within each rib.

12

3. METHODS

Scan Collection and Segmentation

Clinical thoracic CT scans were retrospectively obtained for 241 healthy, normal

subjects (124 females and 117 males) from the Wake Forest University radiological

database for ages 0-100 years (Figure 1). Any ribs that were fractured or compromised

structurally were excluded from the analysis. Each of the healthy, uncompromised ribs in

each subject’s rib cage was segmented individually using a semi-automated technique in

Mimics (Materialise, Leuven, Belgium). Segmentation of the ribs involved automated

thresholding and region growing operations, followed by manual editing. Each of the

segmented ribs was exported as an individual stereolithography (STL) geometry model

for later use and a whole rib cage STL was exported as well.

Cortical Thickness Estimation Algorithm Validation and Application

The whole rib cage STL was imported as a surface along with the original

subject’s clinical thoracic CT scan into the validated cortical thickness estimation

program, Stradwin [15, 16]. Stradwin used the bone and surrounding soft tissue greyscale

values to estimate the thickness of the cortical bone at each of the STL vertices using the

CDM. This algorithm, which has been validated previously for application to the femur

and skull, was validated in a similar manner for application to the rib cage [15-17].

Anterior and lateral rib sections were taken from the fourth through seventh ribs of six

cadavers. These sections were scanned both with microCT and clinical CT. Both of the

resulting scans were analyzed using the CDM and after a comparison between the

thickness estimations from microCT and clinical CT (Figure 2), the difference in cortical

13

thickness between the two was well within the error range published by Treece et al.

Following validation, the CDM was then applied to the entire rib cages of the 241

subjects included in the study, to collect an average of 40,000-80,000 thickness

measurements per rib cage (Figure 3).

Figure 1. Distribution of the ages and sexes of the subjects studied.

14

A.

B.

Figure 2. A & B) Example illustrating

good qualitative agreement between

cortical thickness measurements for the

microCT and clinical CT scans of the

same rib specimen (interior and exterior

views shown). C) Histogram of the

cortical thickness differences (in mm)

between clinical and microCT scans of

homologous regions of the specimen

above.

C.

Figure 3. A) The original surface input to the CDM algorithm and B) the resulting point cloud of

cortical thickness estimations projected onto that surface for a single subject.

15

Partitioning Cortical Thickness Measurements into Homologous Regions

To analyze localized thickness variation on each rib, the point clouds of thickness

measurements from each subject’s entire rib cage were partitioned into homologous

regions. Points associated with each individual rib were extracted from the rib cage point

cloud using a density-based clustering algorithm DBSCAN [18] applied using custom

MATLAB code (The MathWorks, Natick, Massachusetts). The previously exported STL

files of each of the individual ribs were overlaid with the rib cage point cloud, and the

more dense overlapping points between the STL and the point cloud were abstracted. The

points (and corresponding cortical thickness estimations) abstracted from the point cloud

were then labeled the same as the STL rib (i.e. points from the point cloud that

overlapped with the points from the “Left Rib 1” STL were then labeled “Left Rib 1

points”).

Each rib was then partitioned into sub-sections based on a modified cylindrical

coordinate system (Figure 4). This modified cylindrical coordinate system was defined

such that each “L” coordinate corresponded to a longitudinal location along the centerline

length of the rib. Then several rib cross-sections normal to the rib centerline were

obtained along this centerline. Within each rib cross-section, a “ρ” coordinate described

the radial location of the thickness measurement while the “θ” coordinate described the

angular location of the thickness measurement.

16

Figure 4. Modified

cylindrical coordinate

system used to

partition the thickness

measurements into

homologous regions

according to

longitudinal location

along a centerline (L)

and the radial (ρ) and

angular (θ) locations

within a rib cross-

section normal to the

centerline.

To establish a centerline for each rib, the rib was first centered about its centroid.

Ribs whose centroid was located on the rib geometry (i.e. ribs 11-12) were instead

centered about an approximated position located medially to the mid-point of the rib’s

longitudinal length. Rays were projected from the “centroid” to partition the rib into

segments defined by a “Θ” polar coordinate as shown in Figure 5A. A centroid was

calculated from the points within each segment of a given “Θ” coordinate, and these

segment centroids were then connected using a spline to create the centerline down the

length of the rib (Figure 5B).

17

A.

B.

Figure 5. A) Each rib is first

broken into segments based on

its “Θ” value in relation to the

centroid of the rib (indicated

by the green circle). A centroid

for each of these segments is

then calculated (yellow

circles). B) The segment

centroids were then connected

to form a centerline down the

length of the rib.

After the centerline was established, cross sectional rings were identified as

sections perpendicular to the centerline at a predetermined number of locations. The ring

locations were determined by both the length of the rib along the centerline and the

number of rings the rib would have. The number of rings per rib was determined by its

level, such that the first ribs had 10 rings, the second through eleventh ribs each had 30

rings, and the twelfth ribs had 13 rings (Figure 6). The number of rings was determined

experimentally as the greatest number of rings each rib could contain without sacrificing

the shape of the ring.

18

Figure 6. The number of rings for each rib was determined by the rib level with 10 rings

comprising the first rib, 13 rings in the twelfth rib, and 30 rings making up each of the second

through eleventh ribs.

The cross-sectional rings were centered about their centroid and a polar

coordinate system was used to define the angular location “θ” of the thickness

measurements within the ring. Thickness measurements were organized into six degree

increment “θ” bins around the ring circumference (60 bins per ring), and the cortex

thicknesses within each bin were averaged. The averaging technique included identifying

points for each bin that represented the inner and outer cortical bone surfaces within that

bin. First, the outer points in each bin were averaged together to get a mean outer cortex

surface location. Next, the thicknesses associated with each of those outer points were

averaged to get a mean cortex thickness for that bin. Finally, the angles formed between

the outer points and their corresponding inner points were averaged to get a mean

direction to project the thickness measurement to the inner surface. Combining these

three parameters, there is a mean outer surface point defined with a thickness and angle at

19

which that thickness ought to be applied, which captures the corresponding mean inner

surface point. These steps effectively averaged the multiple thickness measurements

within each θ bin to define the outer and inner point locations for a single, averaged

thickness measurement within the bin (Figure 7). The “θ” values for each bin for each

ring started superiorly at 0 degrees, increasing first laterally to 90 degrees, then inferiorly

to 180 degrees, then interiorly to the superior position (0 or 360 degrees).

To ensure the angle measures were normalized and labeled with the appropriate

anatomical location, each ring on the subject’s ribs were compared with a homologous

ring on an atlas rib which had a known superior point. The atlas ribs were obtained from

the Global Human Body Model Consortium’s (GHBMC) 50th

percentile male’s rib cage

and the partitioning methodology described previously was used to partition the atlas ribs

into cross-sectional rings and angular locations. The superior-most point in each atlas

cross-sectional ring was manually selected and the index number recorded. In a previous

study, the atlas rib landmarks were morphed using image registration to each subject rib

[19]. The angular location of the superior-most atlas point after it was morphed to the

subject rib was labeled as having an angle measure of zero (“superior”), and all other

angle measures were then normalized accordingly.

In total, each subject’s rib cage was partitioned into 38,640 sub-sections defined

by rib level, cross-sectional ring location along a rib centerline, and angular location

within the cross-sectional ring. This partitioning technique was applied to all 241 subjects

so that the thickness measurements at each homologous location within the rib cage could

be obtained for all subjects analyzed.

20

A.

B.

Figure 7. Multiple thickness measurements observed at a given angular location (θ) in original

cross sectional slices due to the 3D nature of the rings seen in A) are averaged to define a single

thickness measurement for each θ bin as shown in B).

4. RESULTS

Cortical thickness measurements obtained from applying the CDM technique to

two subjects (30 year old male and 70 year old male) are shown in Figure 8. The

variation in cortex thickness as well as rib geometry can be visualized.

21

Figure 8. The CDM estimated cortical thickness measurements (in mm) for a A) 30 year old

male subject and a B) 70 year old male subject.

Subjects analyzed were grouped into age decades. Female cortex thickness

increases from decade 10 to decade 20, maintaining a relatively thick composition

through decade 40, then steadily decreasing into the elderly ages (Figure 9). Male cortical

thickness increases from decade 10 to decade 30, then decreases in thickness from decade

30 to decade 50, then plateaus in the elderly ages (Figure 9). Both males and females

have unexpectedly thick cortex averages for the youngest pediatric subjects (decade 0).

This is most likely due to the fact that the CDM has only been validated to accurately

estimate thicknesses greater than 0.3 mm and pediatric rib cortex may be thinner than 0.3

mm.

22

Figure 9. The mean thickness and standard deviation per decade of age for male and female

subjects for the left 9th rib. These results were typical for all other ribs.

Similar trends are observed when comparing cortical thickness by rib level. For

all rib levels, female cortical thickness increases from decade 10 to 20, plateaus at a

maximum thickness from decades 20 to 40, and then decreases rather steadily into the

elderly ages. In females, the manubrial ribs (first and second) and floating ribs (eleventh

and twelfth) tended to be thicker than the sternal ribs (third through seventh) and false

ribs (eighth through tenth), particularly from decade 20 on (Figure 10A, Appendix A).

Males also increased from decade 10 to decade 30, decreasing in thickness steadily until

plateauing at approximately decade 50. The male ribs seemed to maintain thickness

uniformly across rib levels (Figure 10B, Appendix B). There were again large thicknesses

seen at decade 0 for all rib levels for both sexes, still most likely due to overestimation of

extremely thin cortex in the youngest pediatric subjects.

23

A.

B.

Figure 10. Mean thickness by decade for each of the rib levels for both A) females and B) males.

Mean thickness values from the male sternal ribs analyzed in Kemper et al. (2007) are shown as

blue dots in B).

Similar trends were observed when the data was examined based on location

along the rib centerline, from posterior to anterior. Female thicknesses increased from

decade 10 to 20, plateaued at a maximum thickness from decade 20 to decade 40, then

decreased into the elderly ages. There were more dramatic differences in overall

thickness between the different locations along the rib centerline. Going from anterior to

posterior along the rib centerline, rib thickness was thinnest anteriorly, increased in the

lateral portions, and then decreased in thickness posteriorly (Figure 11A, Appendix C).

Males demonstrated increased cortex thickness from decade 10 to decade 30, followed by

decreasing thickness that plateaued at approximately decade 50 (Figure 11B, Appendix

D).

0 20 40 60 80 1000

0.5

1

1.5

2

2.5

Mean T

hic

kness (

mm

)

Decade (years)

Female Thickness by Rib Level

Manubrial

Sternal

False

Floating

0 20 40 60 80 1000

0.5

1

1.5

2

2.5

Mean T

hic

kness (

mm

)

Decade (years)

Male Thickness by Rib Level

Manubrial

Sternal

False

Floating

Kemper et al, 2007

24

A.

B.

Figure 11. Mean thickness by decade for each of the locations along the rib centerline for both

A) females and B) males. Mean thickness values from lateral and anterior locations along the

sternal ribs analyzed in Kemper et al. (2007) are shown as blue and black dots in B).

Thickness measurements were compared around the circumference of the rib, i.e.

the superior, interior, inferior, versus exterior portions of the rib (Figure 12). For all ages

except decade 0, the ribs were thicker along the exterior and interior portions and thinner

at the superior and inferior portions. Figure 13 also shows the mean thickness for all of

the ribs by decade at four generalized locations around the circumference of the ribs

(superior, exterior, inferior, interior). It can again be seen that the exterior and interior

portions are consistently thicker than the superior and inferior portions of the ribs for all

ages, except for decade 10. Lastly, Figure 14 compares the thickness variations both

along the rib centerline and around the circumference. The thicknesses tended to

uniformly increase from posterior to lateral, and then decrease from lateral to anterior,

similar to what is demonstrated in Figure 11.

0 20 40 60 80 1000

0.5

1

1.5

2

2.5

Mean T

hic

kness (

mm

)

Decade (years)

Female Thickness by Location Along Rib Centerline

Posterior

Posteriolateral

Lateral

Anteriolateral

Anterior

0 20 40 60 80 1000

0.5

1

1.5

2

2.5

Mean T

hic

kness (

mm

)

Decade (years)

Male Thickness by Location Along Rib Centerline

Posterior

Posteriolateral

Lateral

Anteriolateral

Anterior

Kemper, 2007 - Lateral

Kemper, 2007 - Anterior

25

Figure 12. Mean thickness changes by decade for the anatomical locations around the circumference of the ribs for both males and females. Each

error bar is constructed using one standard deviation from the mean.

26

Figure 13. Mean thickness changes for males and females by decade for each of the locations

around the circumference of the ribs.

Figure 14. Mean thickness plotted by location along the rib centerline for four anatomical

locations around the rib circumference.

27

5. DISCUSSION

The CDM method applied to clinical CT scans obtained cortical thickness

estimates similar to the thicknesses measured from the same specimens using microCT

scans, thus validating the CDM method for application to the rib cage. Cortical bone

changes in thickness with age because the rates at which the bone is broken down and

reformed changes throughout life, based on factors such as hormone and activity levels

[20-23]. This study allowed for analysis of the thicknesses at precise locations

throughout the rib cage for comparison with literature values and also between subjects

(based on age and sex) and locations within a single subject’s rib cage.

Cortex increases in thickness for both males and females from age 10 until the

middle ages, with females reaching a thickness plateau from decade 20 to 40 and males

reaching a maximum thickness at decade 30. Cortex then thins steadily into the elderly

ages for both sexes (Figure 9). Both males and females have unexpectedly thick cortex

averages for the youngest subjects (decade 0). This is most likely due to the fact that the

CDM has only been validated to accurately estimate thicknesses greater than 0.3 mm and

pediatric rib cortex is most likely thinner than 0.3 mm.

Thickness trends from decades 10+ are similar to the trends seen in both the

lumbar and femoral cortical bone area measurement data from the National Health and

Nutrition Examination Survey (NHANES) for both males and females [24]. The female

data has a very similar shape, but reaches a maximum thickness later in life (age 45) than

would be expected from the NHANES cross sectional area trends calculated from DXA

which reach a maximum at age 40 (for the lumbar spine). This may indicate that there is

increasing bone formation of the endosteal surface of the bone with increased bone

28

resorption on the periosteal surface, allowing for increasing thickness with decreasing

area. Cross-sectional area in male NHANES data does not decrease after reaching a

maximum at approximately age 50, which is contrary to the rib cortical thickness trends

in this study. This may indicate that males have increased resorption on the endosteal

surface and increased bone formation on the periosteal surface, allowing for decreasing

thickness while maintaining a constant cortical area, if the ribs have the same trends as

the lumbar spine. Further studies should look into exactly where the cortical bone is

being lost from (endosteal versus periosteal surfaces).

The sternal rib thicknesses in Figure 10B are comparable to the results published

by Kemper et al. (2007), which examined cortical thickness measurements of a series of

sternal ribs (ribs 4-7) from 6 male cadavers [13]. Choi and Lee (2009) only reported very

specific thickness measurements for an 8th

and 9th

rib, so his results cannot be compared

broadly [14]. When examining the same locations (the 9th

rib compared around the

circumference at a lateral aspect), however, the middle 80% of our thicknesses (range:

0.45 – 1.29 mm) matches almost perfectly with the thickness ranges presented by Choi

and Lee (range: 0.4 – 1.3 mm).

The thicknesses variations along the rib centerline, seen in Figure 11 and Figure

14, match closely with the Kemper et al. (2007) location-based thickness results, as well

as the variations published by Choi and Lee (2009). Kemper’s location-based results are

shown as the blue and black dots in Figure 11 [13]. Choi and Lee (2009) only reported

the linear regression of thickness change from anterior to posterior, though our data does

corroborate an increase in thickness from approximately 0.4 mm anteriorly to about 0.8

mm posteriorly [14].

29

For all decades except decade 0, the ribs were thicker in both sexes along the

interior and exterior portions of the rib as compared to the superior and inferior portions,

which supports results found by previous studies [13, 14]. For decade 0, both sexes show

little regional variation, and this is most likely due to the fact that the CDM is

overestimating the cortex thickness equally in all locations.

In general, male and female cortical thickness tended to increase during young

adulthood, and then decrease as the subjects approached middle and elderly age. Age-

based regression equations would need to be produced for exact correlation between

cortical thickness and age and sex, and this is a topic of future investigation. One

limitation of this study is that the thickness is estimated. Although the estimation

technique was validated, it was professed to be unable to capture thicknesses less than 0.3

mm, and therefore limited the ability to accurately characterize thickness variations in the

youngest pediatric subjects.

6. CONCLUSION

The objective of this work was to estimate the rib cortical bone thickness for a

population of subjects spanning ages 0 to 100 and for both sexes. The cortical thickness

was estimated from clinical CT scans using the CDM technique, which estimates cortical

thicknesses less than 2.5 mm better than traditional methods such as FWHM. The cortex

is thicker in the manubrial and floating ribs in the females compared to the female sternal

and false ribs, though there was not much difference in cortex thickness based on rib

level for the males. The anterior portions of the rib cortical bone remained the thinnest for

both males and females, increasing in thickness to a maximum at the lateral portions of

30

the ribs, and then thinning to the posterior portions. The exterior and interior portions of

the ribs remained thicker than the superior and inferior aspects for all locations along the

rib centerline for both males and females. The methodology presented in this paper has

already been applied to characterize the cortical bone thickness of the skull, and could be

applied to characterize cortical thickness of other bones from normal or diseased subjects.

Accurately characterizing the cortical bone thickness variations in the ribs with age and

sex will allow for a more biofidelic model of the ribcage for any age, which in turn

provides accurate injury information allowing for increased safety for all ages.

7. ACKNOWLEDGEMENT

Funding was provided by the National Highway Traffic Safety Administration under

Cooperative Agreement Number DTN22-09-H-00242. Views expressed are those of the

authors and do not represent the views of NHTSA.

31

8. REFERENCES



Car Crash J, 2003. 47: p. 299-321.


wearer. J Trauma, 1989(29): p. 37-41.


Am Geriatr Soc, 2004. 52(5): p. 805-8.





6. Kent, R., et al., Structural and material changes in the aging thorax and their

role in crash protection for older occupants. Stapp Car Crash J, 2005. 49: p.

231-49.




Development and Validation of Age-Dependent FE Human Models of a Mid-

Sized Male Thorax. Stapp Car Crash Journal, 2010. 54: p. 407-430.



32

10. Weaver, A.A., S.L. Schoell, and J.D. Stitzel, Morphometric analysis of variation

in the ribs with age and sex. J Anat, 2014. 225(2): p. 246-61.






properties from dynamic tension and bending tests. Stapp Car Crash J, 2007.

51: p. 235-73.

14. Choi, Y.C. and I. Lee, Thorax FE Model for Older Population. Japanese Scoeity of

Mechanical Engineers, Fukuoka, 2009.







18. Daszykowski, M., B. Walczak, and D.L. Massart, Density-based clustering for

exploration of analytical data. Anal Bioanal Chem, 2004. 380(3): p. 370-2.



36 Suppl 1: p. S123-8.

33



21. Macdonald, H.M., et al., Age-related patterns of trabecular and cortical bone

loss differ between sexes and skeletal sites: a population-based HR-pQCT study.

J Bone Miner Res, 2011. 26(1): p. 50-62.



34

9. APPENDIX A. The mean, standard deviation (STD), and interquartile range (IQR) for the rib cortical

thickness values in mm for the different rib levels by decade for female subjects.

Females Manubrial Sternal False Floating

Decade Mean STD IQR Mean STD IQR Mean STD IQR Mean STD IQR

0 0.83 0.54 0.78 0.64 0.45 0.45 0.71 0.45 0.57 0.91 0.47 0.67

10 0.50 0.31 0.31 0.49 0.21 0.25 0.50 0.20 0.24 0.73 0.39 0.50

20 1.12 0.55 0.68 1.00 0.46 0.66 1.03 0.50 0.77 1.17 0.53 0.75

30 1.18 0.55 0.66 1.03 0.38 0.45 1.05 0.51 0.60 1.14 0.51 0.54

40 1.10 0.56 0.61 0.97 0.34 0.43 1.00 0.42 0.54 1.16 0.53 0.65

50 0.95 0.50 0.56 0.82 0.30 0.41 0.82 0.42 0.50 0.82 0.36 0.48

60 0.90 0.49 0.58 0.83 0.33 0.44 0.81 0.38 0.50 0.83 0.38 0.50

70 1.05 0.54 0.70 0.89 0.37 0.44 0.82 0.42 0.54 0.87 0.45 0.52

80 0.77 0.38 0.41 0.72 0.31 0.34 0.69 0.33 0.37 0.74 0.41 0.46

90 0.93 0.48 0.58 0.79 0.31 0.37 0.69 0.30 0.37 0.71 0.30 0.38

B. The mean, standard deviation (STD), and interquartile range (IQR) for the rib cortical

thickness values in mm for the different rib levels by decade for male subjects.

Males Manubrial Sternal False Floating

Decade Mean STD IQR Mean STD IQR Mean STD IQR Mean STD IQR

0 0.70 0.48 0.64 0.50 0.33 0.30 0.59 0.37 0.38 0.91 0.44 0.67

10 0.56 0.39 0.39 0.58 0.25 0.32 0.57 0.25 0.30 0.57 0.26 0.30

20 0.81 0.69 0.65 0.82 0.48 0.66 0.80 0.45 0.65 0.88 0.49 0.64

30 1.00 0.46 0.45 1.03 0.35 0.44 1.02 0.37 0.47 1.08 0.41 0.54

40 0.91 0.43 0.44 0.91 0.34 0.45 0.93 0.37 0.49 0.93 0.34 0.44

50 0.86 0.46 0.44 0.84 0.29 0.38 0.83 0.33 0.42 0.79 0.31 0.37

60 0.86 0.49 0.50 0.83 0.33 0.39 0.83 0.34 0.48 0.80 0.37 0.44

70 0.89 0.45 0.51 0.84 0.32 0.38 0.80 0.33 0.42 0.72 0.29 0.37

80 1.02 0.50 0.59 0.91 0.33 0.40 0.87 0.33 0.40 0.83 0.35 0.43

90 0.99 0.45 0.49 0.93 0.29 0.37 0.90 0.33 0.46 0.78 0.28 0.38

35

C. The mean, standard deviation (STD), and interquartile range (IQR) for the rib cortical

thickness values in mm for the different ring levels by decade for female subjects.

Females Posterior Posteriolateral Lateral Anteriolateral Anterior

Decade Mean STD IQR Mean STD IQR Mean STD IQR Mean STD IQR Mean STD IQR

0 0.56 0.36 0.35 0.85 0.53 0.71 0.82 0.50 0.66 0.74 0.46 0.61 0.56 0.41 0.49

10 0.53 0.20 0.25 0.60 0.20 0.22 0.57 0.22 0.21 0.55 0.31 0.23 0.36 0.28 0.21

20 1.07 0.46 0.66 1.18 0.45 0.61 1.15 0.51 0.60 1.04 0.49 0.55 0.75 0.44 0.53

30 1.11 0.42 0.48 1.22 0.42 0.51 1.24 0.48 0.47 1.03 0.39 0.37 0.72 0.35 0.38

40 1.04 0.37 0.47 1.13 0.36 0.40 1.16 0.45 0.44 1.00 0.42 0.43 0.73 0.38 0.42

50 0.88 0.31 0.43 0.92 0.36 0.43 0.95 0.44 0.46 0.81 0.34 0.38 0.57 0.29 0.32

60 0.83 0.32 0.44 0.91 0.33 0.43 0.99 0.41 0.49 0.83 0.36 0.42 0.60 0.31 0.37

70 0.82 0.34 0.45 1.04 0.42 0.50 1.10 0.48 0.56 0.84 0.36 0.41 0.61 0.31 0.34

80 0.69 0.28 0.33 0.80 0.36 0.34 0.85 0.39 0.39 0.71 0.30 0.33 0.53 0.27 0.30

90 0.71 0.27 0.36 0.82 0.34 0.35 0.89 0.36 0.42 0.74 0.31 0.37 0.62 0.30 0.38

D. The mean, standard deviation (STD), and interquartile range (IQR) for the rib cortical

thickness values in mm for the different ring levels by decade for female subjects.

MALES Posterior Posteriolateral Lateral Anteriolateral Anterior

Decade Mean STD IQR Mean STD IQR Mean STD IQR Mean STD IQR Mean STD IQR

0 0.48 0.30 0.26 0.69 0.42 0.45 0.67 0.41 0.45 0.63 0.41 0.47 0.49 0.38 0.40

10 0.62 0.30 0.36 0.66 0.23 0.30 0.64 0.26 0.31 0.55 0.24 0.26 0.40 0.24 0.24

20 0.87 0.58 0.68 0.92 0.43 0.62 0.93 0.46 0.69 0.81 0.53 0.61 0.54 0.38 0.45

30 1.08 0.38 0.50 1.10 0.32 0.39 1.14 0.37 0.44 1.03 0.34 0.39 0.79 0.37 0.42

40 0.99 0.41 0.54 1.02 0.33 0.45 1.01 0.35 0.43 0.89 0.28 0.33 0.68 0.29 0.31

50 0.87 0.35 0.48 0.87 0.28 0.37 0.91 0.34 0.38 0.85 0.33 0.32 0.64 0.27 0.32

60 0.86 0.34 0.48 0.91 0.33 0.43 0.94 0.37 0.45 0.82 0.34 0.31 0.60 0.30 0.31

70 0.84 0.35 0.46 0.86 0.32 0.41 0.94 0.35 0.40 0.81 0.29 0.35 0.62 0.31 0.34

80 0.84 0.32 0.44 0.96 0.32 0.38 0.99 0.34 0.40 0.92 0.37 0.37 0.75 0.37 0.36

90 0.88 0.33 0.47 0.96 0.29 0.38 0.98 0.33 0.39 0.94 0.30 0.36 0.81 0.33 0.40

36

Chapter III: Characterization and Regression of Rib Cortical

Thickness from Clinical Computed Tomography Scans

Sarah K. Lynch, Ashley A. Weaver, Samantha L. Schoell, Joel D. Stitzel

Virginia Tech – Wake Forest University Center for Injury Biomechanics,

Winston-Salem, NC

37

1. ABSTRACT

Motor vehicle crashes (MVCs) are responsible for nearly 1.3 million deaths

worldwide, with a large number of serious and fatal injuries sustained in MVCs occurring

in the thorax. Thoracic injuries are more likely to kill or disable elderly occupants due to

variations that occur within the ribcage as people age, including geometry, material

property, and compositional (cortex) changes. In this study, cortical bone thickness

changes in the ribs were characterized by applying a cortical thickness estimation

algorithm to retrospective clinical computed tomography (CT) scans of 222 subjects

spanning ages 10-100 within both sexes. The rib cortex thickness estimations were then

partitioned into homologous regions and compared with age, sex, rib level, rib

attachment, and anatomical location within each rib and the thickness measurements

within each homologous region was averaged. The subject-specific thickness data for

each homologous region was then fit with a regression curve to characterize the thickness

variation at each region with age and sex. Although the cortex showed variations in the

thickness trends (percent change) with age based on rib level, analysis of the regressed

thickness values showed much smaller rib level based variation. The anterior portions of

the rib cortical bone remained the thinnest for both males and females, increasing in

thickness to a maximum at the lateral portions of the ribs, and then thinning to the

posterior portions (although the anterior portion was much thinner than the posterior

portion throughout the lifespan). The exterior and interior portions of the ribs were

thicker than the superior and inferior aspects for all locations around the circumference of

the rib for both males and females for ages 10 and older, though the trends as the

thicknesses changed with age were uniform for all sections. Applying these regression

38

functions for cortical rib thickness will lead to more biofidelic thorax models and

enhanced safety for occupants of all ages.

2. INTRODUCTION

Motor vehicle crashes (MVCs) kill 1.3 million people worldwide every year, with

34,000 of those from the United States alone. In MVCs, the thorax is one of the most

commonly injured body regions, ranking second only to head injuries in terms of

frequency, number of fatal and serious injuries, as well as overall economic cost [1].

Sirmali et al found that almost 40% of hospital patients with thoracic injury have rib

fractures, and Arajärvi et al identified rib fractures in nearly 94% of severely or fatally

injured belted occupants [2, 3]. Unfortunately, rib fractures are not only common, but

they pose an almost doubled risk of mortality and morbidity in the elderly population

than in younger occupants [4-6]. In a study of subjects over the age of 60 who had fatal

chest injuries, it was shown that for 40% of those fatalities, the worst chest injury

sustained was rib fractures, according to the Crash Injury Research and Engineering

Network (CIREN) database [7].

Three factors have been proposed to explain the changes in thoracic injury

tolerance that occur with age: 1) material changes, 2) compositional changes (including

cross sectional cortex area), and 3) thoracic geometric changes [7]. Rib material property

variations have been characterized extensively through the use of whole thorax, whole

rib, and coupon testing [8-12]. Weaver et al and Gayzik et al also characterized three

dimensional rib geometry changes with age and sex [13, 14]. Studies have also examined

rib cortical bone thickness and area variations throughout the ribcage using microscopy

39

estimation, clinical computed tomography (CT) estimation, and microCT measurements

[12, 15, 16, Lynch Chapter II].

Cortical bone varies in thickness based on changes in bone resorption and

formation, which can be influenced by a person’s hormone and activity levels [17-20]. As

a result, there are regional variations in rib cortex thickness within an individual as well

as variations in cortex thickness between individuals of different ages and sexes. Several

studies have quantified changes in cortex thickness and cortical area with age, though

none have fully quantified cortical thickness variation with age and sex regionally within

the ribs [13, 21, 22]. The objective of this study is to develop regression equations to

quantify regional cortex thickness changes with age and sex from a population of 222

subjects. The second aim of this study is to compare the resulting regressed cortical

thickness variations with age, sex, rib level, rib attachment, and anatomical location

within each rib.

3. METHODS

Scan Collection and Segmentation

Clinical thoracic CT scans were retrospectively obtained for 222 healthy, normal

subjects (114 females and 108 males) from the Wake Forest Radiological database for

ages 10-100 years (Figure 15). Any ribs that were fractured or compromised structurally

were excluded from analysis. Each of the healthy, uncompromised ribs in each subject’s

ribcage was segmented individually using Mimics (Materialise, Leuven, Belgium).

40

Cortical Thickness Estimation Algorithm Application

The whole ribcage segmentations were imported as a surface along with the

original subject’s clinical thoracic CT scan into the validated cortical thickness estimation

program, Stradwin [21, 23, 24][Lynch, 2015]. Stradwin, which utilizes the cortical

density method (CDM), assumes a constant cortex density to estimate the cortical bone

thickness from the clinical CT scan allowing for accurate estimation of cortex thickness

down to approximately 0.3 mm. The CDM was applied to the entire ribcages of the 222

subjects to collect an average of 40,000-80,000 thickness measurements per ribcage.

Figure 15. Distribution of the ages and sexes of the subjects included in this study.

After the CDM was applied to all of the subjects, each of the thickness estimates

for the subjects were partitioned into homologous regions outlined in Lynch et al, 2015.

Each subject’s ribcage was sub-sectioned into homologous regions based on rib level,

distance along the rib length (defined by cross-sectional rings shown in Figure 16A), and

location around the rib circumference (60 angle measures shown in Figure 16B). For each

41

subject, the thickness values within each homologous region were averaged to obtain a

single average thickness measurement within the homologous region.

A.

B.

Figure 16. The organization of A) rings and B) angle measures into anatomical categories along

the length of the rib and around the circumference of the rib, respectively.

The average thickness measurements within a particular homologous region for

all subjects of a given sex were regressed with age using Equation 1. This equation was

chosen because it fit the subject data well, capturing the cortical thickening through the

young adult ages, a maximum thickness reached in the middle ages, and then the cortical

thinning into the elderly ages.

𝑦 = 𝑎 + 𝑏𝑥𝑙𝑛(𝑥) + 𝑐𝑙𝑛(𝑥) [1]

Where a, b, and c are the regression coefficients, x is subject age in years, and y is the

cortical thickness in mm.

42

Comparisons were made for the regressed cortical thicknesses for both sexes with

age based on rib level (first through twelfth), attachment (manubrial, sternal, false,

floating), and anatomical region (anterior, lateral, posterior, superior, inferior, etc.).

4. RESULTS

A sample regression curve for a single sub-section of the male ribcage can be seen

in Figure 17. Equation 1, shown as the red curve in Figure 17A, is fit to the original

subject thickness estimations for all ages at that sub-section (blue circles). Based on the

regression equation, the thickness of the rib cortical bone is seen to increase steeply

through the younger ages for this particular sub-section, reach a maximum during the

middle ages, and then decrease fairly steadily into the elderly ages. These trends were

generally typical for all sub-sections. Cortical thickness variation trends for the entire

ribcage for both males and females are shown in Figure 18 where the regression

equations are evaluated for ages 20, 40, 60, and 80 years. The cortex thickness for both

sexes increased from age 20 to 40, reached a maximum between 40 and 60 and then

decreased from 60 to 80. There was slight thickening with age seen in some portions of

the first rib for both males and females. Variations in thickness throughout the ribcage

can be visualized too, with thinner cortex at the anterior and posterior portions of each

rib. There are also visible variations between the different ribs and around the rib

circumference.

43

A.

B.

Figure 17. A) An example regression curve for a

single sub-section for the males. B) This sub-section

is on the medial aspect of the third ring on the left

fifth rib.

Figure 18. The resulting cortex thickness for the entire ribcage for both males and females at

ages 20, 40, 60 and 80.

The average cortical thickness of the entire rib cage for each age decade was used

to compute the percent change in thickness relative to a 10 year old (Figure 19A).

10 20 30 40 50 60 70 80 90 1000

0.5

1

1.5

2

Age (years)

Thic

kness (

mm

)

Rib:5, Ring:3, Angle: 270

44

Females tended to increase in percent thickness almost equivalently with the males, until

the maximum thickness is reached (at approximately age 45 for females and 55 for

males). Then females decrease in thickness much more dramatically than males into the

elderly ages. The average maximum thickness for both males and females is

approximately 200% of the cortex thickness at age 10. In elderly age, male and female

cortical thickness decreased to approximately 180% and 140%, respectively. The

regressed cortex thicknesses for the different ages for both sexes show that females begin

with thicker ribs and actually have thicker average cortical bone until approximately age

70 (Figure 19B).

A.

B.

Figure 19. A) The percent change in cortex thickness (average from the entire rib cage) relative

to a 10 year old for both males and females. B) The regressed cortex thickness with age for both

males and females.

Looking specifically at rib level, females had similar trends in the percentage of

cortical thickening for the manubrial (ribs 1-2), sternal (ribs 3-7), and floating (ribs 8-10)

ribs, increasing up to approximately 200% of the thickness at age 10 and decreasing to

about 150% at age 100 (Figure 20A). The female false ribs (ribs 11-12) did not undergo

as much change, increasing only to about 150% of the thickness at age 10 and decreasing

45

to nearly 80% at age 100. Although the female false ribs did not change in thickness as

much, they in the younger ages they were much thicker that the other rib levels.

However, by the elderly ages, the false rib thicknesses are similar to the other rib levels

(Figure 20C). Males had more thickening in their manubrial ribs, up to 225% relative to a

10 year old, which then decreased to 200% in elderly age (Figure 20B). The male

manubrial ribs tended to be thinner than the rest of the ribs in the younger ages (Figure

20D). The male’s sternal and floating ribs mimicked the trends for the females,

increasing to nearly 200% and decreasing to approximately 175% relative to the 10 year

old thickness. The false ribs in males showed the least change in cortex thickness,

increasing only to about 175% then decreasing to about 110% relative to the 10 year old

thickness.

46

Females Males

A.

B.

C.

D.

Figure 20. Rib level comparisons for the percent change in cortex thickness compared to the

cortex thickness at age 10 by rib level for A) females and B) males, as well as the regressed

cortical bone thickness with age for C) females and D) males.

Females did not tend to have much variation in cortical thickening or thinning

trends between the anatomical locations within the ribs, both along the length of the rib

and around the circumference. Thicknesses values increased to approximately 200%

relative to a 10 year old, then decreased to approximately 140% in elderly age (Figure

21A and Figure 22A). However, there were some distinct differences in the regressed

thickness values with age for these locations for females. The female rib cortex increased

in thickness from the anterior portions of the rib to the lateral sections, then decreased in

thickness from lateral to posterior portions. The anterior portion remained the thinnest

47

region of all (Figure 21C). Around the circumference of the rib, it is evident that the

superior and inferior portions remain thinner than the exterior and interior locations

(Figure 22A and C).

Males had less thinning in the anterior portion of the rib compared to both females

and the other rib portions after reaching age 50, increasing to nearly 260% relative to the

10 year old thickness and then decreasing to only 220% at age 100 (Figure 21B). The

anterior portions of the ribs were thinner than other regions for the younger ages, and by

the elderly ages, reached a maximum thickness similar to the rest of the rib. The posterior

and anterolateral rib thicknesses did not vary as much down the rib. Thicknesses in these

regions increased with age to about 190% and then decreased with age to approximately

175% of the thickness at age 10. However, the posterior portion did thin at a faster rate

than all of the other locations. The lateral and posterolateral sections increased to

approximately 175% and then decreased to about 150%. Males also had cortex

thickening from the anterior region to the lateral region, and then thinning posteriorly,

with the anterior aspect remaining the thinnest across all ages (Figure 21D). Similar to

females, males did not seem to have any differences in cortex thickening or thinning

trends in relation to the anatomical location around the circumference of the rib. All four

anatomical regions studied increased to approximately 200% relative to the 10 year old

thickness, and then decreased to approximately 180% at age 100 (Figure 22B). The

regressed thickness values for males did show increased thickness at the exterior and

interior portions of the ribs compared to the superior and inferior sections (Figure 22D).

48

Females Males

A.

B.

C.

D.

Figure 21. The percent change in cortex thickness compared to the cortex thickness at age 10 by

anatomical location down the length of the rib for A) females and B) males, as well as the

regressed cortical bone thickness with age for C) females and D) males.

49

Females Males

A.

B.

C.

D.

Figure 22. The percent change in cortex thickness compared to the cortex thickness at age 10 by

anatomical location around the rib circumference for A) females and B) males, as well as the

regressed cortical bone thickness with age for C) females and D) males.

5. DISCUSSION

Regression equations were fit to subject-specific rib cortical thickness data

obtained using the CDM method on 222 male and female subjects ranging in age from 10

to 100 years. The resulting regressions showed general cortical thickening during the

early adult years, with ribs reaching a maximum thickness during the middle ages, and

then thinning in the elderly ages. Females on average reached their maximum thickness at

approximately age 45, while males reached their maximum thickness, approximately a

decade later, at about 55. Females experienced a much steeper slope of cortex thickening

50

up until their maximum thickness as opposed to males (Figure 19B). Females also had

more dramatic cortex thinning into the elderly ages compared to males, who have slighter

thinning of the cortex after age 55 (Figure 19).

These sex-specific trends, particularly of the cortical thinning into the elderly

ages, presents as expected based on aging bone literature. As bone ages, it has been

shown to have a reduction in new osteoblasts (bone forming cells) as well as a shorter

lifespan for mature osteoblasts [25]. There have also been variations in bone loss

associated with estrogen levels and Frost et al identified increased bone loss in women

after the onset of menopause, which would agree with the increased cortical thinning

trends in women versus men after the maximum thickness is reached [26].

In female rib level analyses, the false ribs changed the least with age (Figure

20A). The female false ribs had the thickest cortex in the younger ages and achieved

similar thicknesses to the rest of the rib levels into the elderly ages (Figure 20C). The

male false ribs also changed the least percent with age, but started out only slightly

thicker than the other ribs and by the elderly ages were much thinner than the rest. The

male and female ribs tended to have similar trends between locations along the rib length

(Figure 21A and B). This data matches well with the data presented in Kemper et al. 2007

work that noted that, at least on the exterior side, the lateral portions of the rib (ranging in

thickness from 1.05 to 1.39 mm) were thicker than the anterior portions (ranging from

0.55 to 0.97 mm) [12]. Looking specifically at male subjects (since Kemper only

included male cadaver ribs from ages 42-81), the regressed values for the lateral section

ranges from approximately 0.60 to approximately 1.0 mm, and the regressed values for

the anterior portion range from about 0.20 mm to about 0.65 mm. Although our ranges

51

include much thinner cortex estimates than Kemper’s data, our data is averaged for the

entire rib (including more than simply the exterior section), which may decrease our

average thicknesses. Our range is also for thicknesses of all ages 10-100, which includes

the thicknesses from the much thinner pediatric and elderly ribs.

Males and females had very similar trends in age-related thickness changes

between the different locations around the circumference of the rib. However, the

superior and inferior portions were thinner than the exterior and inferior portions in both

sexes. These comparisons are similar comparatively to the circumferential variations

found by Choi and Lee (2009) [15]. Choi and Lee fit a curve to raw cortical thickness

measurements taken from lateral cross sections of seven elderly (ages 64-75) Korean

male subjects’ ninth ribs, which ranged from approximately 0.3mm in the superior and

inferior portions to approximately 1.2 mm in the interior portion and 1.0 in the exterior

portion. Our data does not show nearly as much variation for a single rib cross section,

but does show approximately 0.1 mm of variation between the superior/inferior portion

and the interior/exterior portion. These variations may be explained by the fact that

increased bone formation has been identified at locations of increased loading, and the

exterior and interior portions of the rib are the aspects that are under tension and

compression during rib bending [27].

These variations in rib cortical bone thickness with age and sex provide an ideal

basis for comparing normal cortex with diseased cortex (irradiated, cancerous,

osteoporotic, etc.). These regressions can also be used for calculating the approximate

cortical thickness for use in subject-specific finite element models, which can in turn

52

better predict rib fracture in subjects of all ages. Better predictive models for rib fracture

will allow for improved mitigation of thoracic injuries, which in turn saves lives.

6. CONCLUSION

This study used data from 222 subjects to develop functions to quantify rib

cortical thickness variation within the rib cage and with age (10-100 years) and sex. In

general, rib cortex thickens through the young adult ages and reaches a maximum

thickness in the middle ages that is approximately double the cortical thicknesses of a 10

year old. From middle to elderly age, rib cortical thickness decreases steadily to about

180% (males) and 140% (females), relative to the 10 year old cortical thickness.

Thickness variations were observed between different rib levels, locations along the rib

length, and locations around the rib circumference. These regression curves can be used

in the future for comparison with diseased bones as well as for incorporation of variable

cortical thickness into personalized finite element thoraxes.

7. ACKNOWLEDGEMENT

Funding was provided by the National Highway Traffic Safety Administration under

Cooperative Agreement Number DTN22-09-H-00242. Views expressed are those of the

authors and do not represent the views of NHTSA.

53

8. REFERENCES



Car Crash J, 2003. 47: p. 299-321.


wearer. J Trauma, 1989(29): p. 37-41.

3. Sirmali, M., et al., A comprehensive analysis of traumatic rib fractures:

morbidity, mortality and management. Eur J Cardiothorac Surg, 2003. 24(1): p.

133-8.


Am Geriatr Soc, 2004. 52(5): p. 805-8.





7. Kent, R., et al., Structural and material changes in the aging thorax and their role

in crash protection for older occupants. Stapp Car Crash J, 2005. 49: p. 231-49.




Development and Validation of Age-Dependent FE Human Models of a Mid-Sized

Male Thorax. Stapp Car Crash Journal, 2010. 54: p. 407-430.

54






properties from dynamic tension and bending tests. Stapp Car Crash J, 2007. 51:

p. 235-73.

13. Urban, J.E., et al., Evaluation of morphological changes in the adult skull with

age and sex. J Anat, 2014.



15. Choi, Y.C. and I. Lee, Thorax FE Model for Older Population. Japanese Scoeity

of Mechanical Engineers, Fukuoka, 2009.

16. Sedlin, E.D. and H.M. Frost, Variations in Cross-section Area of Rib Cortex.

Journal of Gerontology, 1963. 18: p. 9-13.



36 Suppl 1: p. S123-8.



19. Macdonald, H.M., et al., Age-related patterns of trabecular and cortical bone loss

differ between sexes and skeletal sites: a population-based HR-pQCT study. J

Bone Miner Res, 2011. 26(1): p. 50-62.

55





22. Karlsson, M.K., et al., An Increase in Forearm Cortical Bone Size After

Menopause May Influence the Estimated Bone Mineral Loss-A 28-Year

Prospective Observational Study. J Clin Densitom, 2015.





25. Rejtarova, O., et al., Costal cartilages--a clue for determination of sex. Biomed

Pap Med Fac Univ Palacky Olomouc Czech Repub, 2004. 148(2): p. 241-3.

56

Chapter IV: Summary of Research

The research presented in this thesis has yielded important contributions to the

field of injury biomechanics. Through the application of a cortical thickness estimation

algorithm and subsequent analysis of the estimated cortex thicknesses by age and sex, the

following objectives have been completed in this thesis:

1. Compare cortex thicknesses variations with rib level, rib attachment, age, sex, and

anatomical location within each rib.

2. Fit a regression curve to cortical thickness estimates throughout the ribcage to

characterize regional cortex thickness changes with age and sex.

3. Compare the resulting regressed cortical thickness variations with age, sex, rib

level, rib attachment, and anatomical location within each rib.

Quantification of the changes in rib cortical bone thickness with age and sex will

not only allow for personalized finite element models to be created with increased

biofidelity, but can also be used as a basis for comparison with disease states. The

methodology presented here can also be used in a number of applications. Research

presented in Chapter II and Chapter III is expected to be published in scientific journals

listed in Table 1.

Table 1. Publication plan for research outlined in this thesis.

Chapter Topic Journal

II Application of CDM and Subsequent

Organization of Cortex Thickness

Estimates

Journal of Anatomy

III Regression and Analysis of

Regionally Organized Cortex

Thickness Estimates by Age and Sex

Journal of Anatomy

†Published

*Submitted

57

Scholastic Vita

SARAH LYNCH Research Engineer, Injury Biomechanics

EDUCATION

Virginia Tech – Wake Forest University, Winston-Salem, NCM.S. in Biomedical Engineering (May 2015) Center for Injury Biomechanics, Advisor: Dr. Joel D. Stitzel North Carolina State University, Raleigh, NC B.S. in Biomedical Engineering (Dec. 2012)

RESEARCH EXPERIENCE Biomechanics Consultant, Crash Injury Research and Engineering Network Jan. 2013 – Present Principal Investigator: Joel D. Stitzel, PhD Virginia Tech-Wake Forest University Center for Injury Biomechanics National Highway Traffic Safety Administration The CIREN process combines prospective data collection with professional multidisciplinary analysis of medical and engineering evidence to determine injury causation to improve the prevention, treatment, and rehabilitation of motor vehicle crash injuries to reduce deaths, disabilities, and human and economic costs.

Researcher, CIREN Head Injury Biomechanics Research Jan. 2013 – Present Research Intern, CIREN Head Injury Biomechanics Research May 2012 – Aug. 2012 Principal Investigator: Joel D. Stitzel, PhD Virginia Tech-Wake Forest University Center for Injury Biomechanics NHTSA/Crash Injury Research and Engineering Network This study combines medical image analysis and biomechanics to quantify the volume, extent, and distribution of head injuries with respect to crash characteristics and occupant parameters to better predict occupant injury following a motor vehicle crash.

Researcher, NHTSA Chest Morphometrics Data Collection and Model Development Jan. 2013 – Present Principal Investigator: Joel D. Stitzel, PhD Virginia Tech-Wake Forest University Center for Injury Biomechanics National Highway Traffic Safety Administration This study analyzes medical images to quantify the changes in geometry and cortical thickness of the ribcage in relation to age and sex of the subjects. These changes combined with literature reported changes in rib material property results in age- and sex-specific finite element models.

Researcher, Ethicon Abdominal and Pelvic Anatomy Study Nov. 2014 – Present Principal Investigator: Joel D. Stitzel, PhD Virginia Tech-Wake Forest University Center for Injury Biomechanics Ethicon, Inc. This study uses image segmentation, registration, and geometrical modeling techniques to produce 3D geometries of the bony pelvis and several abdominal and pelvic organs from male subjects of approximately the same height and weight as the 50th percentile male. These geometries combined with specific anatomical measurements will allow for an accurate representation of the average male’s bony and soft tissue anatomy for use in colorectal surgery device design and testing. Researcher, CIREN Bone Mineral Density Study Aug. 2013 – Present Principal Investigator: Joel D. Stitzel, PhD Virginia Tech-Wake Forest University Center for Injury Biomechanics National Highway Traffic Safety Administration This study made a correlation between DXA bone density measurements and clinical CT scan greyscale values so that bone mineral density measurements could be estimated from clinical CT scans, allowing for a reduction in radiation, time, and number of tests run on patients.

Research Intern, Human Physiology of Wearable Robots July 2011 – May 2012 Principal Investigator: Gregory Sawicki, PhD UNC Chapel Hill-North Carolina State University Joint Department of Biomedical Engineering This study examined muscle fiber dynamics of hemiparetic walking using an ultrasound probe, as well as associated joint dynamics using Vicon motion capture systems.

(910) 617-2985

Winston-Salem, NC 27103

[email protected]

58

DESIGN EXPERIENCE

Design Engineer, Raptor Hand Prosthetic Aug. 2012 – Oct. 2013

Project Lead: Philip Brown

Design Engineer, Suture Needle Holder Sep. 2013 – Nov. 2013

Project Lead: Philip Brown

Design Engineer, Femoral Artery Patency Device Aug. 2012 – Dec. 2012

Supervisor: Andrew Dimeo, PhD

Project Manager, Design Engineer, Infant Respiratory Monitor Aug. 2011 – May. 2012

Supervisor: Andrew Dimeo, PhD

TEACHING EXPERIENCE

Wake Forest University, Winston-Salem, NC Feb. 2015

Guest Lecturer, Seminar Course

Characterization of Cortical Bone Thickness Changes with Age and Sex

Wake Forest University, Winston-Salem, NC Jan. 2015

Guest Lecturer, Injury Biomechanics

Crash Injury Research and Engineering Network (CIREN)

Davie County High School, Mocksville, NC Sep. 2013 – Jan. 2015

Tutor, Mathematics

Algebra II, Integrated II, A.P. Calculus AB, A.P. Calculus BC

Ravenscroft School, Raleigh, NC Sep. 2012 – Jan. 2013

Tutor/Mentor, Accelerated Learning

Environmental Science, Biology, Astronomy, Basic Mathematics SKILLS

Computer: MATLAB, Microsoft Office, SolidWorks, AutoCad, Mimics, ADAMS, Stradwin, LS PrePost, LS DYNA, Geomagic Studio, Hypermesh, JMP, TeraRecon, PSPICE PUBLICATIONS AND PAPERS

Papers in Refereed Journals

1. Weaver AA, Schoell SL, Nguyen CM, Lynch SK, Stitzel JD. “Morphometric Analysis of Variation in the Sternum with Sex and Age.” Journal of Morphology, 2014 Nov; 275(11): 1284-99. doi: 10.1002/jmor.20302.

Papers in Refereed Conference Publications

1. Lillie EM, Urban JE, Lynch SK, Whitlow CT, Stitzel JD. "Evaluation of the Extent and Distribution of Diffuse Axonal Injury from Real World Motor Vehicle Crashes." Rocky Mountain Bioengineering Proceedings, April 2013.

Other Conference Papers (abstract style or non-refereed)/Scientific Exhibits

1. Lynch SK, Weaver AA, Schoell S, Stitzel JD. “The Characterization of Cortical Bone Thickness Changes in the Thoracic Skeleton with Age and Sex.” 2014 Biomedical Engineering Society Annual Meeting, San Antonio, TX, October 2014.

2. Lillie EM, Urban JE, Lynch SK, Weaver AA, Stitzel JD. "Skull Cortical Thickness Changes in the Adult Skull Measured from Clinical Computed Tomography Scans." World Congress of Biomechanics, Boston, MA, July 2014

3. Lynch SK, Weaver AA, Stitzel JD. “Characterization of Cortical Bone Thickness Changes in the Thoracic Skeleton with Age and Gender.” Virginia Tech-Wake Forest University School of Biomedical Engineering and Sciences Graduate Student Research Symposium, Winston Salem, NC, May 2014.

4. Lillie EM, Urban JE, Lynch SK, Weaver AA, Powers AK, Stitzel JD. "Validation and Evaluation of Full and Cortical Skull Thickness Changes with Age and Sex." Virginia Tech-Wake Forest University School of Biomedical Engineering and Sciences Graduate Student Research Symposium, Winston Salem, NC, May 2014.

59

5. Urban JE, Weaver AA, Schoell S, Lillie EM, Lynch SK, Stitzel JD. "Variation in Anthropometry of the Head and Chest with Age for Application to Human Injury Prediction." SAE 2014 Government/Industry Meeting, Washington, DC, January 2014.

6. Urban JE, Lynch SK, Stitzel JD. "Evaluation of Head Injury: Extent and Distribution of Lesions from Motor Vehicle Crashes." Fortieth International Workshop on Human Subjects for Biomechanical Research, Savannah, GA, October 2012.

Additional Presentations at Professional Meetings/Conferences

1. Lynch, SK, Weaver AA, Schoell SL, Stitzel JD. “Rib Cortical Bone Thickness Changes; A Three-Minute Thesis”, Wake Forest Graduate Student and PostDoc Research Day, March 2015.

2. Weaver AA, Schoell SL, Urban JE, Lynch SK, Lillie EM, Gayzik FS, Stitzel JD. “Development of an Older Occupant FE Model Incorporating Geometry, Material Property, and Cortical Thickness Variation”, Society of Automotive Engineers Government Industry Meeting, January 2015.

3. Stitzel JD, Weaver AA, Lynch SK, Hightower C, Miller AN, Beavers K. “Measurement of Bone Quality for CIREN and Correlation with Age and Fracture Incidence.” CIREN Public Meeting, Charlottesville, VA, September 2014.

4. Urban JE, Lynch SK, Melyiani M, Lillie, EM, Whitlow CT, Maldjian JA, Powers AK, Meredith W, Hardy W, Takhounts E, Stitzel JD. “Understanding Brain Injury Mechanism: Integrating Real-World Lesions, ATD Response and Finite Element Modeling.” CIREN Public Meeting, Washington, DC, September 2013.

5. Urban JE, Lynch SK, Whitlow CT, Maldjian JA, Powers AK, Meredith W, Hardy W, Takhounts E, Stitzel JD. “Understanding Brain Injury Mechanism: Integrating Real-World Lesions, ATD Response and Finite Element Modeling.” CIREN Public Meeting, Washington, DC, September 2012.

Technical Reports

1. Stitzel JD, Duma S, Hardy W, Weaver AA, Urban JE, Schoell S, Lynch SK, Jones DA, Rowson S, Fievisohn E. “Year 5, Annual Report. Head and Thoracic Injury: Epidemiological, Experimental, and Computational Approaches to Injury Reduction.” Report to the National Highway Traffic Safety Administration, Washington, DC, August 2014. 2. Stitzel JD, Duma S, Hardy W, Weaver AA, Urban JE, Schoell S, Lillie EM, Lynch SK, Rowson S, Fievisohn E. “Year 4, Annual Report. Head and Thoracic Injury: Epidemiological, Experimental, and Computational Approaches to Injury Reduction.” Report to the National Highway Traffic Safety Administration, Washington, DC, August 2013.

characterization of rib cortical bone thickness … · acknowledgement ... distribution of the ages...

Documents