Volume 56, Issue 5 pp. 1107-1114
PAPER
ANTHROPOLOGY

Virtual Determination of Sex: Metric and Nonmetric Traits of the Adult Pelvis from 3D Computed Tomography Models* ,†

Summer J. Decker Ph.D.

Summer J. Decker Ph.D.

Center for Human Morpho-Informatics Research, Department of Pathology and Cell Biology, University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, MDC 11, Tampa, FL 33612.

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Stephanie L. Davy-Jow Ph.D.

Stephanie L. Davy-Jow Ph.D.

Department of Biological and Earth Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, U.K.

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Jonathan M. Ford M.S.B.E.

Jonathan M. Ford M.S.B.E.

Center for Human Morpho-Informatics Research, Department of Pathology and Cell Biology, University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, MDC 11, Tampa, FL 33612.

Department of Chemical and Biomedical Engineering, University of South Florida College of Engineering, 4202 E. Fowler Avenue, Tampa, FL 33620.

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Don R. Hilbelink Ph.D.

Don R. Hilbelink Ph.D.

Center for Human Morpho-Informatics Research, Department of Pathology and Cell Biology, University of South Florida College of Medicine, 12901 Bruce B. Downs Blvd, MDC 11, Tampa, FL 33612.

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First published: 19 May 2011
Citations: 115
Additional information—reprints not available from author:
Summer J. Decker, Ph.D.
Center for Human Morpho-Informatics Research
Department of Pathology and Cell Biology
University of South Florida College of Medicine
12901 Bruce B. Downs Blvd, MDC 11
Tampa, FL 33612
E-mail: [email protected]

Presented in part at the 62nd Annual Meeting of the American Academy of Forensic Sciences, February 22–27, 2010, in Seattle, WA.

Supported in part by the University of South Florida Clinical and Translational Science Institute.

Abstract

Abstract: Examination of the adult os coxae and sacrum is one of the most common methods of sex estimation from bone. Medical imaging, such as computed tomography (CT), provides the opportunity for three-dimensional (3D) imaging of the skeleton from clinical scans of known individuals in situ. In this study, a randomly selected subset of abdominopelvic CT-derived models were used to evaluate simple, repeatable metric methods of sex estimation based on a combination of obstetric measurements and the traditionally nonmetric Phenice-derived traits. A four-variable discriminant function for sex estimation was developed based on statistical analyses. Overall, the cross-validated accuracy of this method was 100%, with inter-observer error showing an average of only 2.2%. Comparative analysis was run on the data set using FORDISC 3.0. This study shows that current sex determination standards from the pelvis should be updated to include more in vivo data to increase the accuracy of identification.

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