A quantitative radiomic approach to cholesteatoma using histogram analysis

To evaluate the diagnostic accuracy of histogram-based texture analysis on high-resolution computed tomography (HRCT) images for differentiating middle ear cholesteatoma from non-cholesteatomatous lesions. This retrospective study included 96 patients (48 with surgically or histopathologically confirmed cholesteatoma and 48 with non-cholesteatomatous middle ear pathologies) who underwent temporal bone HRCT between 2020 and 2026. Three-dimensional volume of interest (VOI) segmentation was manually performed on axial sections, and histogram-based radiomic features were extracted using LIFEx software. A multivariable binary logistic regression model was constructed using the backward elimination method to identify independent predictors. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Internal validation was performed using five-fold cross-validation, with variable selection repeated independently within each training fold. Inter-observer reliability was assessed via the intraclass correlation coefficient (ICC). The groups were age- and sex-matched. The predictive model incorporated four independent histogram features: Intensity Histogram Mean Absolute Deviation and Minimum Grey Level (both significantly lower in the cholesteatoma group), alongside Intensity Histogram Kurtosis and Range (both significantly higher in the cholesteatoma group). The model demonstrated favorable calibration (Hosmer–Lemeshow p = 0.947) and achieved an AUC of 0.912. Following five-fold cross-validation, the model maintained favorable diagnostic performance, with an AUC of 0.905 and an accuracy of 82.0%. Inter-observer reliability was excellent (ICC = 0.905). Histogram-based radiomic analysis of HRCT images demonstrated high diagnostic performance and excellent inter-observer reproducibility in differentiating cholesteatoma from non-cholesteatomatous middle ear lesions. This approach may serve as a complementary diagnostic tool in the preoperative assessment of middle ear lesions, particularly in patients with diagnostic uncertainty or contraindications to magnetic resonance imaging (MRI).