Paranasal Sinus Morphometry for Forensic Sex Estimation: A Computed Tomography Study of 499 Individuals with a Cross-Validated, Transparently Reported Machine Learning Model.
Authors
Affiliations (3)
Affiliations (3)
- Department of Forensic Medicine, Faculty of Medicine, Balikesir University, 10145 Balikesir, Türkiye.
- Forensic Medicine Division, Balıkesir Atatürk City Hospital, 10100 Balıkesir, Türkiye.
- Department of Radiology, Defne Hospital, 31000 Hatay, Türkiye.
Abstract
<b>Background/Objectives:</b> Paranasal sinus morphometry on computed tomography (CT) is of interest for forensic sex estimation, but many published predictive models rely on in-sample formulas without cross-validation, external testing, or release of model parameters. We aimed to characterize sex differences, pneumatization patterns, asymmetry, and age relationships of the paranasal sinuses in a Turkish adult population, and to develop, cross-validate, and transparently report a predictive model for sex estimation, explicitly benchmarked against the single best morphometric feature. <b>Methods:</b> In this single-center, STROBE-compliant retrospective cross-sectional study, maxillary, frontal, and sphenoid sinus volumes were measured by semi-automated active-contour segmentation in ITK-SNAP on CT scans of 499 adults (282 male, 217 female; 18-65 years). Between-sex differences were tested with the Mann-Whitney U test with Bonferroni correction; effect sizes used Cliff's delta and the probability of superiority. L1-regularized logistic regression, random forest, and gradient boosting were trained with 10-fold stratified cross-validation and a held-out 20% test set, and compared with a univariate frontal-volume benchmark. <b>Results:</b> All three sinus volumes were larger in males (all Bonferroni-adjusted <i>p</i> < 0.001), with the largest effect among the individual sinuses for the frontal sinus (Cliff's delta = 0.53; probability of male superiority = 0.77). The best classifier was L1-regularized logistic regression (10-fold cross-validated AUC 0.79 ± 0.07; held-out test AUC 0.80; accuracy 70%). Because the area under the ROC curve of a single continuous marker equals its probability of superiority, frontal volume alone reached an AUC of approximately 0.77; the multivariable model therefore added little beyond this single feature. Age could not be reliably estimated (test mean absolute error ≈ 10.8 years; R<sup>2</sup> ≈ 0). <b>Conclusions:</b> Paranasal sinus volumes show robust sex dimorphism, concentrated in the frontal sinus, but provide only moderate sex discrimination-appropriate as one corroborating input in a forensic identification workflow rather than a stand-alone determinant. Age cannot be reliably estimated from sinus morphometry in this cohort. Full model coefficients are reported to permit independent replication.