This study evaluates the reliability of osteometric data commonly used in forensic case analyses, with specific reference to the measurements in Data Collection Procedures 2.0 (DCP 2.0). Four observers took a set of 99 measurements four times on a sample of 50 skeletons (each measurement was taken 200 times by each observer). Two-way mixed ANOVAs and repeated measures ANOVAs with pairwise comparisons were used to examine interobserver (between-subjects) and intraobserver (within-subjects) variability. Relative technical error of measurement (TEM) was calculated for measurements with significant ANOVA results to examine the error among a single observer repeating a measurement multiple times (e.g. repeatability or intraobserver error), as well as the variability between multiple observers (interobserver error). Two general trends emerged from these analyses: (1) maximum lengths and breadths have the lowest error across the board (TEM<0.5), and (2) maximum and minimum diameters at midshaft are more reliable than their positionally-dependent counterparts (i.e. sagittal, vertical, transverse, dorso-volar). Therefore, maxima and minima are specified for all midshaft measurements in DCP 2.0. Twenty-two measurements were flagged for excessive variability (either interobserver, intraobserver, or both); 15 of these measurements were part of the standard set of measurements in Data Collection Procedures for Forensic Skeletal Material, 3rd edition. Each measurement was examined carefully to determine the likely source of the error (e.g. data input, instrumentation, observer's method, or measurement definition). For several measurements (e.g. anterior sacral breadth, distal epiphyseal breadth of the tibia) only one observer differed significantly from the remaining observers, indicating a likely problem with the measurement definition as interpreted by that observer; these definitions were clarified in DCP 2.0 to eliminate this confusion. Other measurements were taken from landmarks that are difficult to locate consistently (e.g. pubis length, ischium length); these measurements were omitted from DCP 2.0. This manual is available for free download online (https://fac.utk.edu/wp-content/uploads/2016/03/DCP20_webversion.pdf), along with an accompanying instructional video (https://www.youtube.com/watch?v=BtkLFl3vim4).

Although knee measurements yield high classification rates in metric sex estimation, there is a paucity of studies exploring the knee in artificial intelligence-based sexing. This proof-of-concept study aimed to develop deep learning algorithms for sex estimation from radiographs of reconstructed cadaver knee joints belonging to the Terry Anatomical Collection. A total of 199 knee radiographs were obtained from 100 skeletons (46 male and 54 female cadavers; mean age at death 64.2 years, range 50-102 years) whose tibiofemoral joints were reconstructed in standard anatomical position. The AIDeveloper software was used to train, validate, and test neural network architectures in sex estimation based on image classification. Of the explored algorithms, an MhNet-based model reached the highest overall testing accuracy of 90.3%. The model was able to classify all females (100.0%) and most males (78.6%) correctly. These preliminary findings encourage further research on artificial intelligence-based methods in sex estimation from the knee joint. Combining radiographic data with automated and externally validated algorithms may establish valuable tools to be utilized in forensic anthropology.

This study used 155 computed tomography (CT) scans of Finns (81 males, 74 females) for creating population-specific sectioning points from femoral and humeral head diameters for the purposes of sex estimation. The study included four measurements: vertical and transverse diameter of the femoral head and vertical and transverse diameter of humeral head. All the measured dimensions were sexually dimorphic and the following sectioning points were calculated: Femur: vertical diameter 46.2 mm, transverse diameter 46.3 mm; Humerus: vertical diameter 46.8 mm, transverse diameter 43.6 mm. These sectioning points correctly classified sexes with overall classification rates over 92%. The female diameters were classified more often correctly than males. Discriminant function analysis was also used but it did not improve the classification rates. This study gives new standards for humeral and femoral head dimensions for Finnish population and can be used for sex estimation in forensic cases if only major long bones, femur or humerus with a proximal end, are present or the skeletal remains are commingled.

Sex estimation is an important part of osteological analysis of skeletons and forensic identification process. Traditionally cranial and pelvic traits are utilized for accurate sex estimation. However, post-cranial measurements have also been proven to accurately estimate sex especially from robust bones such as the femur. In this study, we investigated the potential of knee breadth dimensions in sex estimation in a Finnish population. To conduct this study we utilized a study sample (n = 1654) belonging to the Northern Finland Birth Cohort 1966. All individuals were 46 years of age at the time of the examination. Three knee breadth dimensions were measured from subjects' knee posteroanterior radiographs: femoral biepicondylar breadth (FBEB), mediolateral breadth of the femoral condyles (FCML), and mediolateral breadth of the tibial plateau (TPML). Sex estimation was performed using logistic regression. The study clearly demonstrated that all three measurements were different between males and females. Sectioning points for individual knee breadth measurements were 82.9 mm for FBEB, 76.6 mm for FCML and 75.4 mm for TPML. The classification rates ranged from 90.9% to 93.6%. The less commonly used measurements of FCML and TPML showed higher accuracy than FBEB in sex estimation. Our study confirmed that knee breadths can be successfully utilized to improve sex estimation in cases where the skeleton is only partially preserved and other major components of sex estimation are absent. We can also provide new standards for sex estimation from the knee joint in a Finnish population.