Radiomics-based comparison of MRI and CT for differentiating pleomorphic adenomas and Warthin tumors of the parotid gland: a retrospective study

Objective The objective of this study was to compare the diagnostic performance of magnetic resonance imaging (MRI) and computed tomography (CT) in differentiating pleomorphic adenomas from Warthin tumors using radiomics. Study Design We retrospectively reviewed 626 patients who underwent preoperative MRI or CT for parotid tumor diagnosis. Patient groups were balanced by propensity score matching (PSM) and 123 radiomic features were extracted from tumor images. Radiomic signatures (rad-scores) were generated using a least absolute shrinkage and selection operator logistic regression model. The Canny edge detector was used to define tumor borders (border index). The diagnostic performance of rad-score and border index before and after PSM was evaluated with area under the receiver operating characteristic curve analysis. Results For differentiation of pleomorphic adenomas and Warthin tumors, rad-score and border index areas under the curve for MRI after PSM were 0.911 (95% confidence interval [CI], 0.871-0.951) and 0.716 (95% CI, 0.646-0.787), respectively; those for CT were 0.876 (95% CI, 0.829-0.923) and 0.608 (95% CI, 0.527-0.690), respectively. Tumor border index on MRI, but not CT, had superior diagnostic performance (P < .05); MRI- and CT-based rad-scores showed similar performance (P >.05). Conclusions MRI is superior to CT for tumor margin examination; however, the radiomics features of both modalities showed no difference. The objective of this study was to compare the diagnostic performance of magnetic resonance imaging (MRI) and computed tomography (CT) in differentiating pleomorphic adenomas from Warthin tumors using radiomics. We retrospectively reviewed 626 patients who underwent preoperative MRI or CT for parotid tumor diagnosis. Patient groups were balanced by propensity score matching (PSM) and 123 radiomic features were extracted from tumor images. Radiomic signatures (rad-scores) were generated using a least absolute shrinkage and selection operator logistic regression model. The Canny edge detector was used to define tumor borders (border index). The diagnostic performance of rad-score and border index before and after PSM was evaluated with area under the receiver operating characteristic curve analysis. For differentiation of pleomorphic adenomas and Warthin tumors, rad-score and border index areas under the curve for MRI after PSM were 0.911 (95% confidence interval [CI], 0.871-0.951) and 0.716 (95% CI, 0.646-0.787), respectively; those for CT were 0.876 (95% CI, 0.829-0.923) and 0.608 (95% CI, 0.527-0.690), respectively. Tumor border index on MRI, but not CT, had superior diagnostic performance (P < .05); MRI- and CT-based rad-scores showed similar performance (P >.05). MRI is superior to CT for tumor margin examination; however, the radiomics features of both modalities showed no difference.