Applicability of handheld laser scanning for nonmetric skeletal assessment in biological profile estimation: a preliminary two-case study.

Abstract

Background: In forensic anthropology, skeletal materials are commonly assessed through morphological characteristics to estimate components of the biological profile. While traditional analyses relied on physical examination of skeletal remains, digital methodologies offer the potential to supplement or replace direct observations, increasing the accessibility of forensic anthropological consultation, research, and education. However, the reliability of three-dimensional (3D) documentation techniques for nonmetric assessment remained variable and required further investigation. This study provides a preliminary investigation of the applicability of handheld laser scan-derived point-cloud models for nonmetric skeletal assessment in biological profile estimation using a two-case design.

Materials and methods: Two skeletal cases were selected from the George Mason University Forensic Science Program Teaching Collection: a 40-year-old White male and an 80-year-old White female. A total of 53 participants with varying levels of forensic anthropological training and experience were recruited from the Washington metropolitan area. Participants first conducted in-person assessments of skeletal elements and subsequently evaluated 3D models after a washout period.

Results: Inter-observer agreement was generally higher for physical skeletal assessments than for virtual assessments. Skeletal sex estimation (particularly innominate traits) and age estimation via the pubic symphysis showed lower agreement and reduced inter-modality correspondence. Despite this, skeletal sex classification accuracy remained largely stable across modalities. Conversely, population affinity, despite fair inter-modality agreement, showed reduced classification accuracy in the virtual setting.

Conclusion: These findings suggest that handheld laser scans do not fully replicate all aspects of nonmetric skeletal assessment, and their application should be considered trait-dependent and validated further before routine use.