Assessing the utility of 3D modeling with photogrammetry in assigned sex estimation from the greater sciatic notch

Assigned sex estimation via the greater sciatic notch (GSN) is traditionally performed via physical/visual examination and ordinal scoring; however, this relies on the subjective assessment of morphology for typological classification which may not be reflective of human variation. Three-dimensional (3D) photogrammetry may offer a technologically advanced, low cost, and more objective alternative to assess the complex curvature of anatomical landmarks. This research explores the accuracy of photogrammetry derived 3D models by comparing digital measurements to those obtained from the skeletal elements and to streamline the application of curvature analysis for the estimation of assigned sex from the GSN. This study utilizes the left and right os coxae from 15 skeletal individuals (5 females, 10 males) from the Boston University Chobanian & Avedisian School of Medicine. A Fujifilm X-Pro2 and Fujifilm 35 mm prime lens captured 123 images per element, which were processed in Meshroom by AliceVision® to create a 3D textured mesh. The mesh was exported into Blender for cleanup, scaling, measurement, and curvature analysis. The measurements were between 96.54 % and 99.94 % consistent across methods and observations. The consistency between digital metric observations increased by an average of 0.07 % when compared to the consistency of the dry bone measurements. Additionally, curvature analysis of the GSN correctly estimated the assigned sex of all os coxae in the sample. This study demonstrates that photogrammetry is an accurate and reliable method for the digitization of remains that enables analytical techniques to better capture skeletal variation compared to traditional methods.