LAUSR

Background/Objectives: This study evaluates the diagnostic efficacy of the apparent diffusion coefficient (ADC) and T1-weighted contrast-enhanced (T1W + C) and T2-weighted (T2W) imaging modalities in differentiating vestibular schwannomas (VSs) and cerebellopontine angle meningiomas (CPAMs), aiming to optimize clinical imaging protocols for these tumors. Methods: A retrospective analysis was conducted on 97 surgically and pathologically confirmed cases (65 VS, 32 CPAM) from Nanjing Drum Tower Hospital. Imaging features from ADC, T1W + C, and T2W sequences were extracted using medical imaging software. A support vector machine (SVM) model was trained to classify tumors based on these features, focusing on first-, second-, and third-order radiomic characteristics. Results: The ADC images demonstrated the highest classification efficiency, particularly with third-order features (AUC = 0.9817). The T2W images achieved the best accuracy (87.63%) using second-order features. Multimodal analysis revealed that ADC alone outperformed combinations with T1W + C or T2W sequences, suggesting limited added value from multi-sequence integration. Conclusions: Diffusion-weighted imaging (DWI) sequences, particularly ADC maps, exhibit superior diagnostic utility compared to T1W + C and T2W sequences in distinguishing VS and CPAM. The findings advocate prioritizing DWI in clinical imaging workflows to enhance diagnostic accuracy and streamline protocols.