Computed tomography-based age and sex estimation through hyoid bone anthropometry and radiodensity analysis.

In forensic investigations of skeletal remains, age and sex estimation are crucial for identification. This retrospective study evaluates anthropometric measurements, fusion degrees, and radiodensity of the hyoid bone in a large sample. It analyzed cervical vertebrae CT scans from 660 randomly selected cases (330 males, 330 females) aged 15-80 years (2021-2024), based on specific exclusion criteria. We reconstructed data into 3D models using 3D Slicer™ software to perform osteometric measurements, fusion staging, and volume and radiodensity analyses. Statistical analyses included independent t-tests for sexual dimorphism, intra-class correlation coefficients (ICC) for observer reliability, binary logistic regression for sex estimation, and stepwise multiple linear regression to derive age-estimation models. Morphometric and volume measurements were significantly higher in males. Females had lower radiodensity values across all ages, particularly in older groups. The multivariate stepwise binary logistic regression model correctly classified sex with 93.8% accuracy. In age estimation, multivariate stepwise linear regression models explained 51.2% of the variance in females and 45.4% in males. This multiparametric CT-based study demonstrates that the hyoid bone exhibits pronounced sexual dimorphism in a Turkish population. Because age-estimation models have limited explanatory power, an estimated age range is more reliable than an exact age. CT-based multidimensional analysis of the hyoid bone is a robust method for sex estimation and a supportive tool for age estimation.