Stature Estimation from Radiographic Measurements in Adult Anatolian Population

Abstract

The purpose of the present study was to create a regression equation for measuring stature using measurements obtained from the long bone radiographs of adult individuals in Anatolian population. In this study, the maximum length measurements of the six long bones in the upper and lower limbs of 167 healthy individuals were determined from radiographic images. Single and multiple regression equations were created to predict the stature of the individuals from the maximum bone stature. From these equations, the standard error of estimate was determined in the range of 1.68-4.09 cm. As a result of this study, the obtained regression equations resulted in highly reliable and successful results in terms of predicting stature. These equations will provide convenient and predictive accuracy in the estimation of stature from skeletal remains obtained from societies that lived and living in Anatolia. Besides, we anticipate that it will guide researchers working in the fields of Forensic Anthropology, Forensic Medicine and Anatomy.

Developing an automated skeletal phenotyping pipeline to leverage biobank-level medical imaging databases

“…Stature regression plots (Figure 6) indicate that the automated skeletal measurements reflect realistic body proportions, and that there is reasonable concordance between manually recorded stature and 2D image-derived measurements. Comparisons with previously published data reflecting the relationships between stature and lower limb lengths in South Asian populations appear consistent with those presented here (Açikgöz et al, 2021, Pomeroy et al, 2018; Shobha et al, 2019) (Table 3, Figure 6). With the exception of Pomeroy et al’s tibia equation, there is considerable overlap between published regression lines and our data points (Figure 6).…”

“…Circles and solid lines represent Bangladeshi (purple), Indian (blue), and Pakistani (green) standing height (cm) (UKB UDI 50-0.0) and automated skeletal measurements (mm). Dashed lines and + symbols represent the linear regression equations and descriptive statistics presented by Açikgöz et al, 2021 (pink), Pomeroy et al, 2018 (yellow), and Shobha et al, 2019 (orange). Only maximum femur length was reported by Shobha et al…”

“…Additionally, relationships between lower limb lengths and stature are well characterized and can provide a frame of reference for assessing the utility and validity of our automated skeletal measurements. Therefore, univariate regression equations for stature were calculated using maximum femur length and tibia length and were visually compared with published stature regression equations from Açikgöz et al, 2021, Pomeroy et al, 2018, and Shobha et al, 2019 (Table 3). The aforementioned publications present univariate stature regression equations derived from skeletal measurements taken from antero-posterior (AP) DXA scans or radiographic images from contemporary populations in or near South Asia.…”

Developing an automated skeletal phenotyping pipeline to leverage biobank‐level medical imaging databases

“…Circles and solid lines represent Bangladeshi (burgundy), Indian (orange), and Pakistani (yellow) standing height (cm) (UKB UDI 50–0.0) and automated skeletal measurements (mm). Dashed lines and + symbols represent the linear regression equations and descriptive statistics presented by Açıkgöz et al (2021) (dark blue), Pomeroy et al (2018) (light blue), and Shobha et al (2019) (green). Only maximum femur length was reported by Shobha et al…”

Femur morfometrisi ve proksimal ile distal parçalar arasındaki korelasyon

“…For this reason, the femur is frequently used for stature estimation in identification in anthropology and forensic medicine applications. Various formulas have also been developed for the estimation of the total length of fractured and fragmented long bones 18,19 . In total hip arthroplasty, the design of the femoral component and the dimensions of the proximal part of the femur must be compatible with each other.…”