Computed Tomographic Assessment of Paranasal Sinuses for Age and Gender Estimation: A Retrospective Study

Background: The paranasal sinuses are unique anatomical structures that exhibit considerable individual variation in shape, size, and volume. These variations are influenced by multiple factors including genetic, developmental, and environmental influences. Because sinus morphology remains relatively stable after maturation and is well visualized on computed tomography (CT), it has been increasingly explored as a potential marker for personal identification in forensic investigations. Studying the correlation of sinus dimensions with age and gender can therefore provide valuable insight into their diagnostic and forensic relevance. Although paranasal sinus measurements have been explored for forensic identification, comparative evaluation of frontal, sphenoid and maxillary sinus dimensions using regression-based models remains limited. Objective: To evaluate the relationship between paranasal sinus dimensions and age and gender using CT, and to assess their potential applicability in forensic identification. Methods: A retrospective cross-sectional study was conducted using CT data from 250 patients obtained from the institutional radiology archives. CT scans were analyzed using RadiAnt DICOM Viewer 2023.1. The height, width, and depth of the frontal, maxillary, and sphenoid sinuses were measured bilaterally. Volumes were calculated using a standard mathematical formula. Data were tabulated and analyzed to assess variations of sinus dimensions with age and gender. Linear regression analysis was performed to identify the most significant parameters associated with age estimation, while logistic regression was applied to predict gender differences. A significance level of P < 0.05 was considered statistically significant. Results: Linear regression analysis identified the parameters most strongly associated with age: right sphenoid sinus height, width, volume, and right frontal sinus depth. A regression formula was derived to estimate age, explaining 29.1% of age variation. Logistic regression analysis for gender prediction showed that right maxillary sinus height, width, depth, volume; right sphenoid sinus height, width, volume; and left frontal sinus depth were statistically significant, with the right sphenoid sinus exhibiting the highest odds ratio. Conclusion: Paranasal sinus dimensions demonstrate a statistically significant relationship with both age and gender. This combined sinus-based approach highlights the differential predictive role of individual paranasal sinuses in age and gender estimation.