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A Study of Age-Related Thoracic Injury in Frontal Crashes using Analytic Morphomics
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The purpose of this study was to use detailed medical information to evaluate thoracic injuries in elderly patients in real world frontal crashes. In this study, we used analytic morphomics to predict the effect of torso geometry on rib fracture, a major source of injury for the elderly. Analytic morphomics extracts body features from computed tomography (CT) scans of patients in a semi-automated fashion. Thoracic injuries were examined in front row occupants involved in frontal crashes from the International Center for Automotive Medicine (ICAM) database. Among these occupants, two age groups (age < 60 yr. [Nonelderly] and age ≥ 60 yr. [Elderly]) who suffered severe thoracic injury were analyzed. Regression analyses were conducted to investigate injury outcomes using variables for vehicle, demographics, and morphomics. Compared to the nonelderly group, the elderly group sustained more rib fractures. Logistic regression models were fitted with different configurations of variables predictive of the Maximum Abbreviated Injury Scale of the thoracic region (MAISthx 3+). The performance of models was assessed using area under the receiver operating characteristic curve (AUC). AUC is a widely-used “rating” method to describe the accuracy of prediction models. It represents the probability that a randomly chosen positive subject with higher predicted risk than a randomly chosen negative subject. An area of 1 represents a perfect model; an area of 0.5 represents a worthless model. The model developed based solely on vehicle data had an AUC of 0.58. When demographic data was combined with vehicle data, the model prediction improved to an AUC of 0.66. The AUC associated with vehicle and morphomics data increased to 0.72 and increased again to 0.79 when combining vehicle, demographic, and morphomics variables. The important morphomics variables were the rib’s in-plane shape, rib angle, and spine-to-back skin, which represents fat thickness in the posterior trunk. Morphomics variables such as skeletal geometry and fat distribution can be precisely adjusted in a finite element human body model or anthropomorphic testing device to represent occupants of different body shapes and sizes and are thus more valuable in assessing injury during vehicle crashes.
CitationEjima, S., Holcombe, S., Zhang, P., Derstine, B. et al., "A Study of Age-Related Thoracic Injury in Frontal Crashes using Analytic Morphomics," SAE Technical Paper 2018-01-0549, 2018, https://doi.org/10.4271/2018-01-0549.
Data Sets - Support Documents
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- Hanna, R. and Hershman, L., “Evaluation of Thoracic Injuries Among Older Motor Vehicle Occupants,” . Vol. 811 (Washington, DC, NHTSA, 2009. DOT HS), 101.
- Ridella, S.Rupp, J. ,Poland, K. , and, “Age-Related Difference in AIS 3+ Crash Injury Risk, Types, Causation, and Mechanisms,” Proceeding of IRCOBI Conference, Dublin, Ireland, September 12-14, 2012.
- Bose, D., Segui-Gomez, M., and Crandall, J., “Vulnerability of Female Drivers Involved in Motor Vehicle Crashes: An Analysis of US Population at Risk,” American Journal of Public Health 101:2368-2373, 2011, doi:10.2105/AJPH.2011.300275.
- Shaw, G., Lessley, D., Ash, J., Poplin, J. et al., “Small Female Rib Cage Fracture in Frontal Sled Tests,” Traffic Injury Prevention 18:77-82, 2017, doi:10.1080/15389588.2016.1193599.
- Kent, R., Lee, S.-H., Darvish, K., Wang, S. et al., “Structural and Material Changes in the Aging Thorax and their Role in Crash Protection for Older Occupants,” Stapp Car Crash Journal 49:231-249, 2005.
- Vezin, P. and Berthet, F., “Structural Characterization of Human Rib Cage Behavior under Dynamic Loading,” Stapp Car Crash Journal 53:93-125, 2005.
- Schoell, L., Weaver, A., Vavalle, A. et al., “Development and Validation of an Older Occupant Finite Element Model of a Mid-Sized Male for Investigation of Age-Related Injury Risk,” Stapp Car Crash Journal 59:359-383, 2015.
- Holcombe, S., Wang, S., and Grotberg, J., “The Effect of Age and Demographics on Rib Shape,” Journal of Anatomy 231:229-247, 2017, doi:10.1111/joa.12632229.
- Antona-Makoshi, J., Yamamoto, Y., Kato, R., Sato, F. et al., “Age-Dependent Factors Affecting Thoracic Response: A Finite Element Study Focused on Japanese Elderly Occupants,” Traffic Injury Prevention 16:S66-S74, 2015, doi:10.1080/15389588.2015.1014552.
- Shi, X., Cao, L., Reed, M., Rupp, J.D. et al., “Effects of Obesity on Occupant Responses in Frontal Crashes: A Simulation Analysis Using Human Body Models,” Computer Methods in Biomechanics and Biomedical Engineering 18(12):1280-1292, 2015, doi:10.1080/10255842.2014.900544.
- Kitagawa, Y., Hayashi, S., and Yasuki, T., “Comparison of Impact Kinematics between Non-obese and Obese Occupants in Frontal and Lateral Impacts,” Proceeding of IRCOBI Conference, Antwerp, Belgium, September 13-15, 2017.
- Iwamoto, M., Nakahira, Y., Kimpara, H. et al., “Development of a Finite Element Model of 5th Percentile Female with Multiple Muscle and Its Application to Investigation on Impact Response of Elderly Females,” Proceeding of the 23rd International Techinical Conference on the Enhanced Safety of Vehicle, Paper No. 13-0366, 2013.
- Schoell, S., Weaver, A., Vavalle, N., and Stitzel, J.D., “Age- and Sex-Specific Thorax Finite Element Model Development and Simulation,” Traffic Injury Prevention 16:S57-S65, 2015, doi:10.1080/15389588.2015.1005208.
- Parenteau, C., Zhang, P., Holcombe, S. et al., “Analysis of Morphomics Parameters by Gender and BMI Groups: Thorax Shape and H-Point Location,” Proceedings of IRCOBI Conference, Gothenburg, Sweden, September 11-13, 2013.
- Parenteau, C., Zhang, P., Holcombe, S. et al., “The Effect of Age on Fat and Bone Properties along the Vertebral Spine,” SAE Int. J. Trans. Safety 1(2):226-240, 2013, doi:10.4271/2013-01-1244.
- Parenteau, C., Zhang, P., Holcombe, S., Kohoyda-inglis, C. et al., “Can Anatomical Morphomic Variables Help Predict Abdominal Injury Rates in Frontal Vehicle Crashes,” Traffic Injury Prevention 15:619-626, 2014, doi:10.1080/15389588.2013.852665.
- Holcombe, S., Kindig, M., Zhang, P. et al., “Age-Based Predictive Model of the Pediatric Ribcage,” International Journal of Automotive Engineering 5:15-22, 2014, doi:10.20485/jsaeijae.5.1_15.
- RAMP, “Reference Analytic Morphomic Population - University of Michigan Health System,” http://www.med.umich.edu/surgery/morphomics/ramp, accessed December 2016
- Zhang, P., Parenteau, C., Wang, L. et al., “Prediction of Thoracic Injury Severity in Frontal Impacts by Selected Anatomical Morphomic Variables through Model-averaged Logistic Regression Approach,” Accident Analysis and Prevention 5:172-180, 2013, doi:10.1016/j.aap.2013.08.020.
- Holcombe, S., Wang, S., and Grotberg, J., “Modeling Female and Male Rib Geometry with Logarithmic Spirals,” Journal of Biomechanics 49:2995-3003, 2016, doi:10.1016/j.jbiomech.2016.07.0212995.
- Holcombe, S., Wang, S., and Grotberg, J., “Age-Related changes in Thoracic Skeletal Geometry of Elderly Females,” Traffic Injury Prevention 18(S1):S122-S128, 2017, doi:10.1080/15389588.2017.1309526.
- Ejima, S., Holcombe, S., Zhang, P. et al., “Application of Analytic Morphomics for Belted Elderly Occupants in Frontal Crashes,” Proceedings of IRCOBI Conference, Malaga, Spain, September 14-16, 2016.
- Gennarelli, T.A. and Wodzin, E. (Editors), “Abbreviated Injury Scale 2005,” 2005, 2007 Updated Edition, 2005, Barrington, IL: AAAM and Medicine, A.f.t.A.o.A. 167.
- Stitzel, J., Kilgo, P., Weaver, A., Martin, R.S. et al., “Age Thresholds for Increased Mortality of Predominant Crash Induced Thoracic Injuries,” Annals of Advances in Automotive Medicine 54:41-50, 2010.
- MATLAB, Natick, MA, USA, The Mathworks Inc., 2016a.
- Ritchie, N., Schneider, L., Wang, S. et al., “A Method for Documenting Location of Rib Fractures for Occupants in Real-World Crashes Using Medical Computed Tomography (CT) Scans,” SAE Technical paper 2006-01-0250, 2006, doi:10.4271/2006-01-0250.
- Lee, E., Craig, M., and Scarboro, M., “Real-World Rib Fracture Patterns in Frontal Crashes in Different Restraint Conditions,” Traffic Injury Prevention 16:115-123, 2015, doi:10.1080/15389588.2015S115.
- Zhou, Q., Rouhana, S., and Melvin, J., “Age Effect of Thoracic Injury Tolerance,” SAE Technical paper 962421, 1996, doi:10.4271/962421.
- Viano, D.C., Parenteau, C.S., and Edwards, M.L., “Crash Injury Risks for Obese Occupants Using a Matched-Pair Analysis,” Traffic Injury Prevention 9:59-64, 2008.
- Kent, R., Forman, J., and Bostrom, O., “Is There Really a “Cushion Effect”? A Biomechanical Investigation of Crash Injury Mechanisms in the Obese,” Obesity 18:749-753, 2010.
- Forman, J., Lopez-Valdes, F.J., Lessley D. et al., “The Effect of Obesity on the Restraint of Automobile Occupants,” in Annual Proceeding of Association for the Advancement of Automotive Medicine, 53, 25-40, 2009.
- Stein, I.D. and Granik, G., “Rib Structure and Bending Strength: An Autopsy Study,” Calcified Tissue Research 20:61-73, 1976.
- Wuermser, L.-A., Achenbach, S.J., Amin, S., Khosla, S. et al., “What Accounts for Rib Fractures in Older Adults?” Journal of Osteoporosis 2011:1-6, 2011.