Morphological Sex Estimation from Low-Dose X-Ray Scans – An Exploratory Study

Abstract

Technological advancements in forensic imaging have promoted the use of radiographs for skeletal sex estimation, minimising the need to macerate human remains. Radiographs have been shown to yield sex classification accuracies similar to those achieved through dry bone analyses method. This study investigated the observability, repeatability, and sex classification accuracy of skull and postcranial traits for morphological sex estimation using Lodox® Statscan™ radiographs of white European adult individuals (n = 150 scans; 72 males, 78 females). The skull and eight postcranial elements, in association with 32 morphological traits, were assessed for observability and scorability, followed by sex classification, to assess accuracy. The skeletal elements were observed first, followed by the observations of associated skeletal traits, given the observability of respective skeletal elements from Lodox scans. Nominal and ordinal traits were scored on two-point nominal and five-point ordinal scales, respectively. Intra- and inter-observer repeatability were assessed using Cohen's Kappa statistics. Eight skeletal elements were observed in over 88% of scans, with cranium and pelvic bones each achieving 99% observability. High observability and scorability frequencies were noted for four skull traits (80-93% and 76-93%, respectively), eight pelvic traits (87-97% and 82-93%, respectively), and select traits of the scapula and distal humerus (78-82% and 72% and 80%, respectively), with varying repeatability agreements. Sex classification accuracies ranged from moderate (53-81% for skull and pelvic traits) to low (15-54% for non- pelvic traits). Sex accuracies of the non-pelvic postcranial traits were low (15-54%). Lodox scans demonstrated limited trait observability and moderate sex classification, proving less effective than dry bone analysis. Limitations included interference from soft tissue, distortion, superimposition, and reliance on anteroposterior scans. Alternative metric sex estimation approaches are recommended, leveraging the observable traits identified despite Lodox® Statscan™ limitations.