Stature estimation by semi-automatic measurements of 3D CT images of the femur.

Journal: International journal of legal medicine
PMID:

Abstract

Stature estimation is one of the most basic and important methods of personal identification. The long bones of the limbs provide the most accurate stature estimation, with the femur being one of the most useful. In all the previously reported methods of stature estimation using computed tomography (CT) images of the femur, laborious manual measurement was necessary. A semi-automatic bone measuring method can simplify this process, so we firstly reported a stature estimation process using semi-automatic bone measurement software equipped with artificial intelligence. Multiple measurements of femurs of adult Japanese cadavers were performed using automatic three-dimensional reconstructed CT images of femurs. After manually setting four points on the femur, an automatic measurement was acquired. The relationships between stature and five femoral measurements, with acceptable intraobserver and interobserver errors, were analyzed with single regression analysis using the standard error of the estimate (SEE) and the coefficient of determination (R). The maximum length of the femur (MLF) provided the lowest SEE and the highest R; the SEE and R in all cadavers, males and females, respectively, were 3.913 cm (R = 0.842), 3.664 cm (R = 0.705), and 3.456 cm (R = 0.686) for MLF on the right femur, and 3.837 cm (R = 0.848), 3.667 cm (R = 0.705), and 3.384 cm (R = 0.699) for MLF on the left femur. These results were non-inferior to those of previous reports regarding stature estimation using the MLF. Stature estimation with this simple and time-saving method would be useful in forensic medical practice.

Authors

  • Kei Kira
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba, 260-8670, Japan.
  • Fumiko Chiba
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba, 260-8670, Japan.
  • Yohsuke Makino
    Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8654, Japan.
  • Suguru Torimitsu
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba, 260-8670, Japan.
  • Rutsuko Yamaguchi
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba, 260-8670, Japan.
  • Shigeki Tsuneya
    Department of Forensic Medicine, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8654, Japan.
  • Ayumi Motomura
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba, 260-8670, Japan.
  • Maiko Yoshida
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-Ku, Chiba, Chiba Prefecture, 260-8670, Japan.
  • Naoki Saitoh
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-Ku, Chiba, Chiba Prefecture, 260-8670, Japan.
  • Go Inokuchi
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba, 260-8670, Japan.
  • Yumi Hoshioka
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-Ku, Chiba, Chiba Prefecture, 260-8670, Japan.
  • Hisako Saitoh
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-Ku, Chiba, Chiba Prefecture, 260-8670, Japan.
  • Daisuke Yajima
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba, 260-8670, Japan.
  • Hirotaro Iwase
    Department of Legal Medicine, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chuo-ku, Chiba, 260-8670, Japan.