computed tomography as a supplement for …

COMPUTED TOMOGRAPHY AS A SUPPLEMENT FOR ANALYZING ANTEMORTEM AND PERIMORTEM BLUNT FORCE CRANIAL TRAUMA


by

Felicia MarksA Research Project

Submitted to theForensic Science Forensic Research Committee

George Mason Universityin Partial Fulfillment of

The Requirements for the Degreeof

Master of ScienceForensic Science

Primary Research AdvisorDr. Steven Symes

Forensic AnthropologistMississippi State Medical Examiner’s Office

Secondary Research AdvisorDr. Douglas Ubelaker

Curator of AnthropologySmithsonian Institution

GMU Graduate Research CoordinatorDr. Joseph A. DiZinno

Assistant ProfessorGMU Forensic Science Program

Fall Semester 2019George Mason UniversityFairfax, VA


Acknowledgements

I would like to thank my research advisors, Dr. Symes, Dr. Ubelaker, and Dr. DiZinno

for helping me throughout this process and guiding me to produce original research that could be

applied to the ever-growing field of forensic anthropology.

Thank you to Dr. Falsetti, who assisted me in conducting the statistical analysis and

interpreting the various data produced, in addition to helping me navigate the CT programs.

Thank you to Dr. Hunt and the Smithsonian’s National Museum of Natural History for

allowing me to use the skeletal collections and CT scanner for this research. Also, thank you Dr.

Hunt for taking the time to help me survey the skeletal material and scanning each specimen for

analysis.

Finally, thank you to all of my friends and family for supporting me through this research

project and being there for me every step of the way.

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Table of Contents

List of Tables…………………………………………………………………………………..….3

List of Figures……………………………………………………………………………………..5

List of Definitions/Acronyms..……………………………………………………………….…..7

Abstract………………………………………………………………………………………..…..8

Introduction……………………………………………………………………………………..…9

Overview…………………………………………………………………………………..9

Importance………………………………………………………………………………...9

Background………………………………………………………………………………10

Bone Biomechanics……………………………………………………………...10

Classification of Blunt Force Trauma……………………………………………11

Determination of Fracture Timing……………………………………………….12

Current Imaging Techniques……………………………………………………..13

Previous Research………………………………………………………………………………..14

Materials and Methods…………………………………………………………………………..16

Data Analysis and Interpretation………………………………………………………………...19

Research Results & Discussion………………………………………………………………….37

Conclusion……………………………………………………………………………………….41

References………………………………………………………………………………….…….43

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List of Tables

Table 1. Average number of defects by method (Macro/Photos vs CT)………………..……….24

Table 2. Standard Deviations by Method………………………………………………………..24

Table 3. P-values between methods……………………………………………………………..24

Table 4. Average number of defects by collection………………………………………………25

Table 5. P-values between collections......………………………………………………………26

Table 6. Antemortem defects in Peruvian collection- Macro/Photos.......………………………26

Table 7. P-value for antemortem defects in Peruvian collection-Macro/Photos...………………26

Table 8. Perimortem defects in Peruvian collection- Macro/Photos…………………………….27

Table 9. P-value of perimortem defects in Peruvian collection- Macro/Photos……..……….....27

Table 10. Frequency of antemortem defects in Terry Collection- Macro/Photos.………………28

Table 11. P-value of antemortem defects in Terry collection- Macro/Photos..……….………...28

Table 12. Frequency of perimortem defects in Terry collection- Macro/Photos …………….....29

Table 13. P-value of perimortem defects in Terry collection, Macro/Photos……….…………..29

Table 14. Frequency of antemortem defects in Peruvian collection- CT………………………..29

Table 15. P-value of antemortem defects in Peruvian collection, CT….………………………..29

Table 16. Frequency of perimortem defects in Peruvian collection- CT….……...……………..30

Table 17. P-value of perimortem defects in Peruvian collection- CT……….…………………..31

Table 18. Frequency of antemortem defects in Terry collection- CT……….…………………..31

Table 19 P-value of antemortem defects in Terry collection- CT...……………………………..32

Table 20. Frequency of perimortem defects in Terry collection- CT…..………………...……..32

Table 21. P-value of perimortem defects in Terry collection- CT…......………………………..32

Table 22. P-values between both collections and methods.……………………………………..33

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Table 23. Average number of fracture types by method…….…………………………………..33

Table 24. Standard deviations of fracture types by method……………………………………..34

Table 25. P-values of fracture types by method…………….…….……………………………..34

Table 26. P-values of fracture characteristics by method......….………………………………..35

Table 27. P-values of fracture characteristics by collection……………………………………..36

Table 28. Number of antemortem vs perimortem defects for both methods in Peruvian

collection…………………………………………………………………………………………37

Table 29. Number of antemortem vs perimortem defects for both methods in Terry collection

……………………………………………………………………………………………………38

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List of Figures

Figure 1. Young’s Modulus of Elasticity from Symes, et al. (2013)...……….…………………11

Figure 2. Spectrum of fracture timing classifications across anthropology and forensic

pathology…………………………………………………………………………………………13

Figure 3. 3D reconstruction produced by Horos DICOM program…...……...…………………14

Figure 4. Snapshot of spreadsheet used for classifications…...…………………………………17

Figure 5. Snapshot of spreadsheet used for defects...………………...…………………………18

Figure 6. Top to bottom: A) anterior view with catalog #, B) close-up of defect, C) close-up with

scale, D) anterior view from CT, E) close-up of defect from CT..………………………………19

Figure 7. Chart of fracture characteristics from Kranioti (2015)…...………………………...…20

Figure 8. A) hinging, B) sharp edges, C) uniform in color, D) smooth surface texture, E)

bridging………………………………………………………………………………………..…20

Figure 9. Chart of common BFT fractures from Kranioti (2015)………..……………………...21

Figure 10. A) Depressed/comminuted/coup fractures, B) Hairline, C) Diastatic, D) Linear…...22

Figure 11. Distribution curve of defects by method...…………………………………………..23

Figure 12. Distribution curve of defects by collection…………………………………………..25

Figure 13. Distribution of antemortem defects in Peruvian collection- Macro/Photos...…...…..27

Figure 14. Distribution of perimortem defects in Peruvian collection- Macro/Photos...………..28

Figure 15. Distribution of antemortem defects in Peruvian collection- CT……………………..30

Figure 16. Distribution of perimortem defects in Peruvian collection- CT……………………..31

Figure 17. Distribution of fracture types by method…………………………...………………..34

Figure 18. Distribution of fracture types by collection………...………………………………..35

Figure 19. Distribution curve of fracture characteristics by method.…………………….……..36

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Figure 20. Distribution curve of fracture characteristics by collection.………………..………..37

Figure 21. Average number of antemortem and perimortem defects by Macro/Photos………...38

Figure 22. Average number of antemortem and perimortem defects by CT……………………38

Figure 23. Frequency of fracture types- Peru……………………..……………………………..39

Figure 24. Frequency of fracture types- Terry…………………………………………………..39

Figure 25. Frequency of fracture characteristics between methods- Peru…………………..…..40

Figure 26. Frequency of fracture characteristics between methods- Terry…………….………..40

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List of Definitions/Acronyms

Antemortem Prior to deathBlunt force trauma (BFT) Low-velocity impact from an object with a

blunt surfaceCT Computed tomographyElastic deformation Bone can return to its original shape after an

outside force is removedFracture point Point at which bone fracturesμCT (Micro-CT) Captures fine-detail of small specimensPerimortem Around the time of death/ displays similar

biomechanical properties as living bonePlastic deformation Bone is permanently altered once outside

force is removedPostmortem Alteration to bone after deathStrain Bone responseStress Force per unit of areaYield point Point at which bone enters the plastic

deformation phase

Abstract

Within the field of forensic anthropology, skeletal trauma analysis plays a critical role in

reconstructing the events surrounding the life and death of an individual. For example, analyzing

cranial blunt force trauma (BFT) could provide insight into a history of abuse based on the

amount of healing present. Blunt force trauma to the skull has been researched extensively in the

past, but to date has not focused on interpreting the timing of fractures to differentiate early

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antemortem from perimortem stages of healing. The goal of this research was to examine the

fracture characteristics present by traditional macroscopic assessment, then enhancing the details

of cranial injuries through computed tomography (CT) in order to have better visualization and

aid in determining the timing of fractures. A total of 23 antemortem and 20 perimortem BFT

injuries were initially observed within a sample of 30 skulls from skeletal collections at the

Smithsonian’s Museum Support Center and National Museum of Natural History. The skeletal

collections consisted of the Robert J. Terry Anatomical Collection, and the Peruvian skeletal

collection created by Aleš Hrdlička in the early 1900s. This study revealed that by using

computed tomography for analyzing cranial blunt force trauma, there was no significant

difference in the further classification of fracture timing for early antemortem and perimortem

defects.

Keywords: Forensic anthropology, computed tomography (CT), antemortem, perimortem, blunt

force trauma, cranial

Introduction

Overview

In the field of forensic anthropology, research involving analyzing cranial blunt force

trauma with the use of advancing technologies has been rapidly increasing. With new technology

comes greater ability to widen the field and update current guidelines for traditional trauma

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analysis. One of these aspects of technology, computed tomography (CT), has sparked interest in

researchers for determining the depths at which current methods can be expanded upon. In

particular, one method that calls for further research involves the determination of fracture

timing from cranial blunt force trauma, especially in relation to antemortem and perimortem

classifications. Questions that were asked throughout this research consisted of:

1. Will using CT increase the quality of fracture characteristics to better categorize the

timing of fractures?

2. Can CT pick up on additional defects not seen during macroscopic analysis?

From these questions, it could be hypothesized that the use of CT will provide greater

detail of fracture characteristics to aid in determining antemortem versus perimortem blunt force

cranial trauma than traditional macroscopic methods.

Importance of Research

While research has been done regarding the determination of perimortem in comparison

to postmortem fractures, there has not been research specifically focused on antemortem versus

perimortem, as it is commonly assumed to be an easier classification. However, within the

determination of antemortem trauma is a range of possible timeframes for which the injuries

could have occurred and healed. In particular, cranial trauma that shows signs of “early”

antemortem healing could be confused for perimortem trauma as little to no healing is present

and can be difficult to see to the untrained eye. Additionally, the primary goal of this research is

to aid in forensic anthropological investigations involving cranial blunt force trauma using CT in

order to enhance the determination of antemortem versus perimortem fractures.

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Background Information

Bone Biomechanics

Bone is classified heterogeneous material due to having both organic and inorganic

properties that contribute to how bone reacts to outside forces. The organic component that

comprises 65-70% of bone is collagen, which provides elasticity, flexibility and strength in

tension, while the inorganic components such as hydroxyapatite contribute to the rigidity,

hardness and break due to compression (Kranioti 2015, Symes et. al 2013).

When examined as a material, bone is not only heterogeneous, but also anisotropic and

viscoelastic. The anisotropic aspect of bone implies that the way in which a particular bone

breaks, the fractures that occur are dependent on the strength of the mechanical load, location of

impact, as well as in what direction it is coming from (Kranioti 2015, Symes et. al 2013). As for

bone being viscoelastic, this typically refers to how the bone responds to an external force at

varying speeds and amount of time (Symes, et al. 2013). Additionally, the viscoelasticity of bone

means that it is typically stronger in compression than in tension. In other words, when an

extrinsic force is impacting the bone surface, it will fracture first as a result of tension (Berryman

& Symes). For example, when a baseball bat is impacting the skull, the side where tension is

applied will break first, and if enough force is applied to where plastic deformation occurs, then

the bone will fail under compression.

In order to further understand how extrinsic forces and/or stresses impact bone in terms

of trauma analysis, Young’s Modulus of Elasticity is routinely used. As shown in Figure 1,

stress/strain curves are produced which relate the force applied per unit area and how the bone

responds to said force (i.e. deformation response). As of a result of blunt force trauma to the

skull, more severe injuries will occur due to the small surface area of the skull having contact

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with the blunt object. From this, plastic deformation, otherwise described as a permanent

alteration to bone, causes the bone to fracture.

Figure 1, Young’s Modulus of Elasticity from Symes, et al. (2013)

Classification of Blunt Force Trauma

According to the Scientific Working Group for Forensic Anthropology, blunt force

trauma is created from a low velocity impact from an object with a “blunt” surface (SWGANTH,

2011). Examples of the types of events that ultimately cause blunt force trauma injuries consist

of a car accident, an individual falling from a height, or being struck with an object such as a

baseball bat or hammer. When determining if certain fractures are a result of blunt force trauma,

Berryman & Symes (1996) discussed the correlating fracture characteristics depend on “extrinsic

factors such as magnitude, area, and duration of the blow, and such intrinsic factors as the ability

of bone to absorb the blow, bone elasticity, plasticity, and density.”

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Determination of Fracture Timing

In order to determine the timing of fractures, it is imperative to understand the difference

between antemortem trauma, perimortem trauma, and postmortem breakage. Antemortem trauma

is any alteration to the bone that occurred during life and is commonly identified through signs of

healing. According to Cunha & Pinheiro (2016), the “evidence of bone repair is the basis for the

antemortem diagnosis in anthropology.” Additionally, several remodeling phases have been

noted when determining the extent of antemortem trauma. These can include an initial

inflammatory response, soft callus stage, hard callus stage, and a remodeling stage typically seen

after 3 months from when the injury occurred (Cunha & Pinheiro 2016). Furthermore, Ubelaker

(2015) discussed the issues surrounding the determination of early antemortem bone response,

which consist of the generalized “criteria for recognizing the earliest evidence of bone response

and how long prior to death fractures could occur without any evidence of bone response.”

Defining perimortem trauma varies across several areas of forensic science, where

forensic pathologists would describe it as trauma that occurred around the time of death and

could have directly contributed to the cause of death. This can be better understood by the chart

created by Cunha & Pinheiro in Figure 2. In forensic pathology, “perimortem” most commonly

refers to the event being at or around the time of death (Passalacqua & Bartelink 2015).

Figure 2, Spectrum of fracture timing classifications across anthropology and forensic pathology

For the purposes of this research the forensic anthropological definition is used, which

describes perimortem trauma as occurring at or around the time of death with lack of healing

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and “is determined on the basis of evidence of the biomechanical characteristics of fresh bone

and does not take into consideration the death event” (SWGANTH 2011, Dirkmaat et al. 2008).

Additionally, common fracture characteristics observed from perimortem trauma can consist of

the following: sharp and smooth fracture margins, radiating fracture lines, hinging, peeling or

lifting of fracture margins, bending, uniformity in color (Loe, 2016). As for any alteration of

bone occurring after death, it is not considered to be trauma due to the absence of wet/fresh bone

response and is termed postmortem breakage.

Current Imaging Techniques

Computed tomography, otherwise known as CT, is considered to be a series of

radiographs taken from various angles to produce cross-sectional images which can then be

“stacked” to create 3D reconstruction (Garvin & Stock, 2016). An example of how the

radiographs are turned into a 3D reconstruction can be seen in Figure 3.In forensic anthropology,

computed tomography has been used in various applications such as the preservation of fragile

remains, creation of biological profiles, analyzing the structure of bone as a non-destructive

method, as well as trauma analysis (Christensen et. al, 2016). However, its current use is limited

due to the high cost associated to obtaining access to the scanner as well as overall availability of

CT scanners to anthropologists. Additionally, if access to CT technology is available, those who

would be working with CT images need to have specialized software and experience using the

associated programs (Garvin & Stock, 2016).

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Figure 3, 3D reconstruction produced by Horos DICOM program

Previous Research

Fleming-Farrell, et al. (2013) conducted a study to investigate the potential use of 3D

multi-detector CT to help distinguish between perimortem and postmortem cranial trauma by

looking at specific criteria found in both types of fractures. The overall sample size used was 45

crania and the criteria examined to determine fracture timing were as follows: preponderant

texture, preponderant outline, edge morphology, fracture angle, fracture relationship to the path

of least resistance, plastic deformation, and hinging. They were able to identify 27 of the 31

cranial fractures in CT reconstruction and found limitations based on observer experience as well

as a limited sample size.

While a study conducted by Rubin & Spock (2018) focused on fracture repair of the

human rib cage, they discussed the issue of comparing antemortem and perimortem trauma due

to their similarities and the need for further research to be done in this area. For determining the

presence of perimortem in skeletal material, the authors noted that the “anthropological

perimortem interval may span several days to weeks in either direction of time of death” (Rubin

& Spock, 2018). They further explain the need for more research to be conducted for examining

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antemortem versus perimortem by discussing how that boundary can be blurred “when an

individual sustains a fracture prior to/unrelated to death but dies before signs of healing manifest

in dry bone, or conversely, when fractures display early signs of healing but are directly related

to cause of death” (Rubin & Spock, 2018).

Moraitis, Eliopoulos & Spiliopoulou (2009) analyzed perimortem fractures of bone based

on the morphological characteristics present and focused on such injuries resulting from blunt

force trauma. Trauma was interpreted based on a visual examination of patterns, where each

fracture was thoroughly described and photographed for reference. Additionally, fracture edges

were further examined by using a low-powered stereomicroscope. Within the study, the authors

noted that fracture patterns, morphology of fracture edges, and the presence of certain attributes

indicated the presence of perimortem trauma (Moraitis, Eliopoulos & Spiliopoulou, 2009). They

concluded that certain characteristics such as the type of fracture pattern and lack of an

osteogenic response help anthropologists with determining presence of perimortem trauma. Also,

they summarized that the combination of the types of fractures present and their corresponding

fractured edge characteristics was the most useful method for assessing perimortem skeletal

trauma.

Brown, et. al (2010) applied μCT (Micro-CT) technology to identify and analyze a skull

fracture resulting from blunt force trauma in a forensic case. They focused on μCT as a result of

regular CT not always having the ability to detect extremely fine fracture lines due to the type of

resolution used. During autopsy, the fracture lines were examined using photography and a

dissection microscope, where they found that the photographs taken were only able to pick up on

two of the fracture lines that were able to be seen macroscopically. μCT analysis was able to

identify most of the fine fracture lines, but the resolution used was not high enough to pick up

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smaller hairline fractures. That being said, the authors discussed the value of overall CT use in

the field of forensic science, as it is a non-destructive method for examining bone fragments and

can create a simple way to explain findings to the average layperson.

Materials and Methods

Materials

1. Microsoft Excel

2. Notebook

3. Magnifying glass

4. Pen

5. Nikon D3000

6. Flash

7. AA batteries

8. Tripod

9. Skull ring

10. Siemens SOMATOM Emotion 6 CT Scanner with Syngo CT 2006A software

11. Horos DICOM viewer for Mac

12. PostDICOM viewer for PC

Methods

In order to create the sample size, potential samples were surveyed within the Peruvian

and Terry skeletal collections, where each cranium was examined macroscopically for evidence

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of blunt force trauma. These collections were housed at the Smithsonian’s Museum Support

Center in Suitland, Maryland as well as at the National Museum of Natural History in

Washington, DC. If blunt force trauma was present, then the types of fractures and the

corresponding fracture characteristics seen were noted in Excel. The location of each fracture,

preliminary timing classification, as well as any additional observations were also noted next to

each specimen number in Figure 4. The total number of defects observed and their initial

classification of antemortem versus perimortem were also noted in a separate spreadsheet shown

in Figure 5. This process was completed for both the Peruvian and Terry collections to create the

initial sample size, and each specimen noted on the spreadsheet was re-examined to determine

the final sample size (n=30).

Figure 4, Snapshot of spreadsheet used for classifications

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Figure 5, Snapshot of spreadsheet used for defects

Once the macroscopic evaluation was complete, each sample was then photographed

using a Nikon D3000 camera and documented on a photography log. The sequence of photos

taken were:

1) side/overall view of crania with catalog number

2) close-up of defect

3) close-up with scale.

The settings for the camera used were manual mode, auto-focus, ISO 400, metering was

set to matrix, and the flash was set to manual mode. After photographing each specimen, the

samples located at MSC were transported to NMNH to be scanned by Dr. David Hunt, a physical

anthropologist and curator at the Smithsonian, using the Siemens SOMATOM Emotion 6 CT

Scanner. The settings used were as follows: slice thickness and rotation set at 0.63mm, recons

set at 0.3mm, kernels used were U90 Osteo (Ultra Sharp), B50 Osteo (Medium Sharp), and U90

Inner Ear. After each specimen was scanned, the same process described for the macroscopic

examination was repeated and then the observations from the CT scans were compared to what

was previously seen from the macroscopic exam/photo documentation, as noted in Figure 6.

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A. B. C.

D. E.Figure 6, Top to bottom: A) anterior view with catalog #, B) close-up of defect, C) close-up with

scale, D) anterior view from CT, E) close-up of defect from CT

Data Analysis and Interpretation

The overall data was generated through photography and 3D imaging from CT scans of

each cranial sample containing either antemortem and/or perimortem blunt force trauma

fractures and characteristics. Then, it was analyzed using classification charts from a study

conducted by Kranioti (2015), which listed fracture characteristics for antemortem and

perimortem trauma as well as types of cranial fractures that result from blunt force trauma as

shown in Figures 7-10 alongside examples of how they were used. For example, in Figure 8, the

macroscopic exam/photographic documentation led to classifying the defect as perimortem and

19


was re-classified as early antemortem after CT analysis due to the imaging technology being able

to pick up on the presence of hinging.

Figure 7. Chart of fracture characteristics from Kranioti (2015)

Figure 8, A )hinging, B) sharp edges, C) uniform in color, D) smooth surface texture, E) bridging (only seen on CT image)

20


Figure 9, Chart of common BFT fractures from Kranioti (2015)

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Figure 10, A) Depressed/comminuted/coup fractures, B) Hairline, C) Diastatic, D) Linear

Once observations were noted for each of the 30 specimens, the following were then

analyzed: A) the number of defects observed between methods, B) the number of defects

observed between collections, C) average of antemortem and perimortem fractures between

methods, D) average of antemortem and perimortem fractures between collections, E) frequency

of fracture types between methods, F) frequency of fracture types between collections, G)

frequency of fracture characteristics between methods, H) frequency of fracture characteristics

between collections.

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For each of the above categories, statistical analyses were performed consisting of either

T-tests or Chi-square analysis. T-tests are traditionally used in order to determine if there is a

significant difference present between means of two groups, such as two types of methods and/or

two collections. This statistical test was used for determining the difference in the number of

defects between both methods and collections, the frequency of fracture types present for both

methods and collections, as well as the frequency of fracture characteristics present for both

methods and collections. In order to interpret the relative means of antemortem and perimortem

fractures, Chi-square tests were performed, which are used to test if the null hypothesis can show

that the variables are independent.

When examining the number of defects present between both methods, there was no

significant difference as seen in Figure 11, which shows the two methods to have nearly identical

results. Tables 1-3 show that within the 30 samples, the average amount of defects were 1.4667

and 1.3667, and the respective P-values were 0.7549 which indicates a lack of statistical

significance due to being greater than 0.05. Also, it is important to note that in Table 1, “M&P”

refers to the “Macroscopic/Photo” method of examination.

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Distribution of Defects

KernelNormal

ct

M&P

Met

hod

0

20

40

60

80

Perc

ent

0

20

40

60

80

Perc

ent

ct

0

20

40

60

80

Perc

ent

0

20

40

60

80

Perc

ent

M&P

-5 0 5 10

Defects

Figure 11, Distribution curve of defects by method

Method Method N Mean Std Dev Std Err Minimum Maximum

M&P 30 1.4667 1.2521 0.2286 1.0000 7.0000

ct 30 1.3667 1.2172 0.2222 1.0000 7.0000

Diff (1-2) Pooled 0.1000 1.2348 0.3188

Diff (1-2) Satterthwaite 0.1000 0.3188

Table 1, Average number of defects by method

Method Method Mean 95% CL Mean Std Dev 95% CL Std Dev

M&P 1.4667 0.9991 1.9342 1.2521 0.9972 1.6833

ct 1.3667 0.9122 1.8212 1.2172 0.9694 1.6363

Diff (1-2) Pooled 0.1000 -0.5382 0.7382 1.2348 1.0453 1.5089

Diff (1-2) Satterthwaite 0.1000 -0.5382 0.7382

Table 2, Standard deviations by method

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Method Variances DFt Val

ue Pr > |t|

Pooled Equal 58 0.31 0.7549

Satterthwaite Unequal 57.954 0.31 0.7549

Table 3, P-values between methods

As for the number of defects observed between the Peruvian and Terry collections (seen

in Figure 12 and Tables 4-5), the P-values were also above 0.05 which indicate no significant

difference.

Distribution of Defects

KernelNormal

T

P

Col

lect

ion

0

20

40

60

80

Perc

ent

0

20

40

60

80

Perc

ent

T

0

20

40

60

80

Perc

ent

0

20

40

60

80

Perc

ent

P

-5 0 5 10 15

Defects

Figure 12, Distribution curve of defects by collection

Collectio Method N Mean Std Dev Std Err Minimum Maximum

25


n

P 19 1.5789 1.5024 0.3447 1.0000 7.0000

T 11 1.2727 0.6467 0.1950 1.0000 3.0000

Diff (1-2) Pooled 0.3062 1.2651 0.4793

Diff (1-2) Satterthwaite 0.3062 0.3960

Table 4, Average number of defects by collection

Method Variances DF t Value Pr > |t|



Table 5, P-values between collections

In order to determine the mean of antemortem versus perimortem classifications, the

number of defects were compared from both collections to determine normality. In Tables 6-9,

14-17 and Figures 13-16, the Peruvian collection varied in normality based on each method,

while the Terry collection displayed no significant difference (Tables 10-13, 18-21).

Antemortem Frequency PercentCumulativeFrequency

CumulativePercent

1 5 71.43 5 71.43

4 1 14.29 6 85.71

5 1 14.29 7 100.00

Frequency Missing = 12

Table 6, Antemortem defects in Peruvian Collection- Macro/Photos

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Chi-Square Testfor Equal Proportions

Chi-Square 4.5714

DF 2

Pr > ChiSq 0.1017

WARNING: The table cells have expected counts lessthan 5. Chi-Square may not be a valid test.

Table 7, P-Value for Antemortem defects in Peruvian Collection - Macro/Photos

-0.5

0.0

0.5

1.0

Rel

ativ

e D

evia

tion

1 4 5

Antemortem

Deviations of Antemortem

-0.5

0.0

0.5

1.0

Rel

ativ

e D

evia

tion

1 4 5

Antemortem

0.1017Pr > ChiSq


Figure 13, Distribution of antemortem defects in Peruvian collection- Macro/Photos

Perimortem Frequency PercentCumulativeFrequency

CumulativePercent

1 11 84.62 11 84.62

2 2 15.38 13 100.00


Table 8, Perimortem defects in Peruvian collection- Macro/Photos

27



Chi-Square 6.2308

DF 1

Pr > ChiSq 0.0126

Table 9, P-value of perimortem defects in Peruvian collection- Macro/Photos

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

Rel

ativ

e D

evia

tion

1 2

Perimortem

Deviations of Perimortem

-0.75

-0.50

-0.25

0.00

0.25

0.50

0.75

Rel

ativ

e D

evia

tion

1 2

Perimortem

0.0126Pr > ChiSq


Figure 14, Distribution of perimortem defects in Peruvian collection- Macro/Photos


CumulativePercent

1 9 100.00 9 100.00


Table 10, Frequency of antemortem defects in Terry collection- Macro/Photos

28



Chi-Square 0.0000

DF 0

Pr > ChiSq .

Table 11, P-value of antemortem defects in Terry collection- Macro/Photos


CumulativePercent

2 1 50.00 1 50.00

3 1 50.00 2 100.00


Table 12, Frequency of perimortem defects in Terry Collection, Macro/Photos


Chi-Square 0.0000

DF 1

Pr > ChiSq 1.0000


Table 13, P-value of perimortem defects in Terry Collection, Macro/Photos


CumulativePercent

1 8 80.00 8 80.00

2 1 10.00 9 90.00

4 1 10.00 10 100.00


Table 14, Frequency of antemortem defects in Peruvian collection- CT

29



Chi-Square 9.8000

DF 2

Pr > ChiSq 0.0074


Table 15, P-value of antemortem defects in Peruvian collection, CT

-0.5

0.0

0.5

1.0

1.5

Rel

ativ

e D

evia

tion

1 2 4

Antemortem


-0.5

0.0

0.5

1.0

1.5

Rel

ativ

e D

evia

tion

1 2 4

Antemortem

0.0074Pr > ChiSq


Figure 15, Distribution of antemortem defects in Peruvian collection- CT


CumulativePercent

1 8 80.00 8 80.00

2 1 10.00 9 90.00

3 1 10.00 10 100.00


Table 16, Frequency of perimortem defects in Peruvian collection- CT

30



Chi-Square 9.8000

DF 2

Pr > ChiSq 0.0074


Table 17, P-value of perimortem defects in Peruvian collection- CT

-0.5

0.0

0.5

1.0

1.5

Rel

ativ

e D

evia

tion

1 2 3

Perimortem


-0.5

0.0

0.5

1.0

1.5

Rel

ativ

e D

evia

tion

1 2 3

Perimortem

0.0074Pr > ChiSq


Figure 16, Distribution of perimortem defects in Peruvian collection- CT


CumulativePercent

1 10 100.00 10 100.00


Table 18, Frequency of antemortem defects in Terry collection- CT

31



Chi-Square 0.0000

DF 0

Pr > ChiSq .

Table 19, P-value of antemortem defects in Terry collection- CT


CumulativePercent

4 1 100.00 1 100.00


Table 20, Frequency of perimortem defects in Terry collection- CT


Chi-Square 0.0000

DF 0

Pr > ChiSq .

Table 21, P-value of perimortem defects in Terry collection- CT

When looking at the combined p-values between methods and classifications, as seen in

Table 22, there was no significant difference in fracture timing determinations between both

methods and both collections. However, there was a significant difference when examining the

presence of antemortem versus perimortem trauma within the Peruvian collection for both

methods. Additionally, N/A in Table 22 refers to the sample not being large enough to calculate

the frequency. This was seen primarily within the Terry collection, as there was a total of 11

specimens examined while there were 19 from the Peruvian collection. As a result, there was not

enough data to generate deviation graphs for the Terry collection and displayed as “0” and “.” In

Table 21.

32


Macro/Photos CT

Antemortem (Peru) 0.1017 0.0074

Perimortem (Peru) 0.0126 0.0074

Antemortem

(Terry)

N/A N/A

Perimortem (Terry) 1.0000 N/A

Table 22, P-values between both collections and methods

From examining the frequency of fracture types, there was not a significant difference

between macroscopic/photography and CT methods, as shown in Tables 23-25. In Figure 17,

there was a wider range of fractures observed from the macroscopic/photography method.

However, there was a significant difference seen between collections which is shown in Figure

18.

Method Method N Mean Std Dev Std Err Minimum Maximum

ct 18 2.6111 2.4287 0.5725 0 7.0000

mp 18 3.1111 3.2519 0.7665 0 11.0000

Diff (1-2) Pooled -0.5000 2.8700 0.9567

Diff (1-2) Satterthwaite -0.5000 0.9567

Table 23, Average number of fracture types by method

Method Method Mean 95% CL Mean Std Dev 95% CL Std Dev

ct 2.6111 1.4033 3.8189 2.4287 1.8225 3.6410

mp 3.1111 1.4940 4.7283 3.2519 2.4402 4.8751

Diff (1-2) Pooled -0.5000 -2.4442 1.4442 2.8700 2.3215 3.7603

Diff (1-2) Satterthwaite -0.5000 -2.4500 1.4500

Table 24, Standard deviations of fracture types by method

33



Pooled Equal 34 -0.52 0.6046

Satterthwaite Unequal 31.464

-0.52 0.6049

Table 25, P-values of fracture types by method

Distribution of Number1

KernelNormal

mp

ct

Met

hod

0

10

20

30

40

Perc

ent

0

10

20

30

40

Perc

ent

mp

0

10

20

30

40

Perc

ent

0

10

20

30

40

Perc

ent

ct

-5 0 5 10 15

Number1

Figure 17, Distribution of fracture types by method

34



KernelNormal

t

p

Col

lect

ion

0

10

20

30

40

50

Perc

ent

0

10

20

30

40

50

Perc

ent

t

0

10

20

30

40

Perc

ent

0

10

20

30

40

Perc

ent

p

-5 0 5 10 15

Number1

Figure 18, Distribution of fracture types by collection

In regard to comparing the frequency of fracture characteristics between methods, there

was no significant difference seen as both p-values were 1.0000, shown in Table 26. As for the

frequency between collections, there was almost a significant difference noted, since the P-

values were only slightly above the 0.05 threshold and the relative means were fairly close

together, as seen in Table 27 and Figure 19. Additionally, there was a slight overlap in ranges

which was observed in Figure 19.




Table 26, P-values of fracture characteristics by method

35





Table 27, P-values of fracture characteristics by collection


KernelNormal

mp

ct

Met

hod

0

10

20

30

Perc

ent

0

10

20

30

Perc

ent

mp

0

10

20

30

40

Perc

ent

0

10

20

30

40

Perc

ent

ct

-10 0 10 20

Number2

Figure 19, Distribution curve of fracture characteristics by method

36



KernelNormal

t

p

Col

lect

ion

0

10

20

30

40

Perc

ent

0

10

20

30

40

Perc

ent

t

0

10

20

30

40

Perc

ent

0

10

20

30

40

Perc

ent

p

-10 0 10 20

Number2

Figure 20, Distribution curve of fracture characteristics by collection

Results & Discussion

As shown during the data analysis, certain characteristics were able to be seen from the

CT images that were not originally observed through traditional macroscopic

examination/photography. Unfortunately, not enough of those characteristics were observed to

show overall statistical significance. For classifying antemortem versus perimortem defects in

particular, there was a slight variance seen between both methods but not enough to warrant the

need for CT, as shown in Tables 28-29 and Figures 21-22.

Macro/Photos CT

Antemortem 14 14

Perimortem 15 13Table 28, Number of antemortem vs perimortem defects for both methods in Peruvian collection

Macro/Photos CT

37


Antemortem 9 10Perimortem 5 4

Table 29, Number of antemortem vs perimortem defects for both methods in Terry collection

Peru Terry02468

10121416

Macro/Photos

Antemortem Perimortem

Figure 21, Average number of antemortem and perimortem defects by Macro/Photos

Peru Terry02468

10121416

CT

Antemortem Perimortem

Figure 22, Average number of antemortem and perimortem defects by CT

As for the frequency of fracture types, there was no statistical difference between both

methods, but as shown in Figures 23-24, there was a difference between the Peruvian and Terry

collections.

38


Basila

r

Commin

uted

Conce

ntric

Coup

Depres

sed

Diastat

ic

Hairlin

e

Linea

r

Radiat

ing

0

4

8

12Peru

Macro/Photo CT

Figure 23, Frequency of fracture types- Peru

Basila

r

Commin

uted

Conce

ntric

Coup

Depres

sed

Diastat

ic

Hairlin

e

Linea

r

Radiat

ing

02468

1012

Terry

Macro/Photo CT

Figure 24, Frequency of fracture types- Terry

For the frequency of fracture characteristics, there was a wider range observed within the

Peruvian collection than the Terry collection, as demonstrated in Figures 25-26. Despite this,

there was no statistical difference seen from using either the macroscopic/photography method or

CT between both collections.

39


Beveli

ng

Bone f

lakes

Bridgin

g

Callus

Hingi

ng

Plastic

defo

rmati

on

Sharp ed

ges

Smooth

edges

Smooth s

urface

Unifo

rm in

colo

r0

6

12

Peru

Macro/Photos CT

Figure 25, Frequency of fracture characteristics between methods- Peru

Beveli

ng

Bone f

lakes

Bridgi

ng

Callus

Hingi

ng

Plastic

defo

rmati

on

Sharp

edges

Smooth e

dges

Smooth s

urfac

e

Uniform

in co

lor

0

4

8

12

16

Terry

Macro/Photos CT

Figure 26, Frequency of fracture characteristics between methods- Terry

To summarize, there was no significant difference observed using either the macroscopic/

photography method or CT to determine the number of defects that were present, the frequency

of fracture types, as well as the frequency of fracture characteristics. However, there was a

significant difference noted in the frequency of fracture types by collection, in addition to the

40


frequency of antemortem versus perimortem classifications by method within the Peruvian

collection.

Conclusion

Due to the results between both methods being similar, the use of CT is not needed as an

aid in the determination of fracture timing or the types of fractures present if there are sufficient

photographs taken and/or a thorough macroscopic examination is possible. Since CT is not

always necessary for antemortem versus perimortem blunt force trauma classification, this could

save anthropologists both time and money when assessing the potential value of this method for

analyzing dry skeletal material. As for limitations within the study, only one observer was used

for both methods and collections, which could potentially create either inconsistencies or

inaccuracies in the observations noted. Additionally, inexperience in using both the Horos Dicom

and PostDicom viewers is another factor to consider. Both programs were free to download, but

their accompanying user manuals and tutorials required additional payment.

For future directions of this research, multiple users should be implemented to ensure the

observations made are accurate and consistent. As noted in previous research related to this

topic, microscopic examination of fracture characteristics could yield additional information

useful for further classifying the timing of fractures as early antemortem versus perimortem

(Moraitis, Eliopoulos & Spiliopoulou 2009). In regard to sample size, having the same amount of

specimens if pulling from multiple collections could show regulated trends as well. In this

research, the scanned samples were observed at the U90 Osteo (Ultra Sharp) kernel, which

produced the highest quality image. That being said, future directions could include comparing

41


CT scans at the varying kernels in order to determine if one might display certain defects or

characteristics not seen in one versus another.

References

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Christensen, A., Smith, M., Gleiber, D., Cunningham, D., & Wescott, D. (2018). The Use of X-ray Computed Tomography Technologies in Forensic Anthropology. Forensic Anthropology, 1(2), 124–140. doi: 10.5744/fa.2018.0013

Cunha, E. & Pinheiro, J. (2016). Antemortem Trauma. In: S. Blau & D. Ubelaker (Eds.), Handbook of Forensic Anthropology and Archaeology (2nd ed., pp. 322- 345). New York: Taylor & Francis.

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Passalacqua, N., & Bartelink, E. (2015). Blunt force trauma patterns in the human skull and thorax: A case study from northern California. Skeletal Trauma Analysis: Case Studies in Context (1 ed., pp. 56-69). John Wiley & Sons, Ltd.

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