Published in:
14-07-2023 | Computed Tomography | Technical Report
Sex determination by linear measurements of the bony labyrinth in cone-beam and computed tomography: a practical method
Authors:
Stéphane Gargula, Justin Michel, Denis Ayache, Pascal Adalian, Mary Daval
Published in:
Forensic Science, Medicine and Pathology
|
Issue 1/2024
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Abstract
Purpose
The determinism of the sex is of most importance for reconstruction of the biological profile of deceased individuals. In this study, we aim to implement a technique to improve the accessibility of sex determination by the study of the bony labyrinth on cone-beam computed tomography (CBCT) and computed tomography (CT) scans.
Methods
CBCT and CT scans of temporal bones performed between 2014 and 2022 were collected with demographic information. The width of the lateral (LSCw), posterior (PSCw), and anterior semicircular canal (ASCw) was measured. The primary outcome was the diagnostic performance of the individual linear measures and the product of these measures. This analysis is supplemented by establishing thresholds using ROC curves. Inter-judge and intra-judge reliability evaluation was performed blinded in randomly selected exams.
Results
One hundred forty-one petrous bones were included for analysis of their imaging. The analysis of the PSCw, ASCw, and ASCw*PSCw for sex determination was associated with area under curves of 0.88 ± 0.11, 0.82 ± 0.14, and 0.84 ± 0.10 respectively and accuracies of 0.74 ± 0.13, 0.78 ± 0.11, and 0.79 ± 0.13 respectively. In ROC-curve analysis, a PSCw*ASCw product > 48.5 allows to determine a male sex with > 95% specificity and a sensitivity of 50.1%. A PSCw*ASCw product ≤ 43 allows to determine a female sex with 88% specificity and 64% sensitivity. Reproducibility analyses showed good to excellent intra-judge and inter-judge reproducibility for ASCw and PSCw.
Conclusion
Linear measurement of the semicircular canals of the vestibule on CBCT or CT could provide easy-to-use sex determination of the majority of females and males with a good predictive value.