CT Histogram Analysis for Predicting Malignancy in Anterior Mediastinal Masses

Anterior mediastinal masses encompass a broad spectrum from benign thymic hyperplasia to malignant thymomas and thymic complementary computed tomography (CT) histogram and texture analysis have emerged as complementary, non-invasive quantitative biomarkers for malignancy prediction. This study investigates whether CT histogram-derived parameters, particularly mean attenuation and first-order metrics, can differentiate benign from malignant anterior mediastinal masses to support preoperative risk stratification.

We retrospectively analyzed data from 102 patients who underwent surgical resection of anterior mediastinal masses. Non-contrast CT scans were evaluated, and mean Hounsfield unit (HU), standard deviation, skewness, and kurtosis values were extracted using region-of-interest-based histogram analysis. Histopathological diagnosis is considered the gold standard for classification. Group comparisons were performed using appropriate parametric or non-parametric tests, and the diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.

Of the 102 patients, 60 (58.8%) had malignant and 42 (41.2%) had benign pathologies. The mean CT attenuation was higher in malignant lesions than in benign lesions (63.3±16.9 HU vs. 48.3±39.0 HU; P = 0.023), whereas the standard deviation was similar between the groups (P = 0.810). Skewness and kurtosis were higher in malignant lesions (P < 0.05), indicating denser and more peaked attenuation distributions. ROC analysis of mean HU demonstrated moderate discriminative performance (area under the curve: 0.64), with high sensitivity (96.7%) and limited specificity (50.0%).

CT histogram analysis, particularly mean attenuation, may serve as a complementary biomarker for differentiating benign from malignant anterior mediastinal masses. Given its high sensitivity but limited specificity, it should be used as an adjunct to clinical and morphologic assessment rather than as a determinant of surgical management. Prospective validation incorporating volumetric and advanced radiomic parameters is required.