Predicting glioma histo-molecular diagnosis and prognosis: preoperative dynamic contrast-enhanced magnetic resonance imaging insights

Background: The preoperative prediction of glioma, integrated histological/molecular classification, and prognosis are critical for personalized patient management and treatment optimization. This study aimed to explore whether preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), an advanced MRI technique, can comprehensively and noninvasively evaluate gliomas. Methods: ) and 1p/19q status, was evaluated using receiver operating characteristic (ROC) analysis. The prognostic predictive value was assessed using Cox or logistic regression analysis to build models visualized by nomograms. The area under the curve (AUC), calibration curves, and decision curves were used to evaluate the performance of these models. Results: ) status. Tumor Ktrans.max emerged as an independent prognostic risk factor for glioma patients [AUCs for 1-, 3-, and 5-year survival, 0.75 (0.58-0.92), 0.64 (0.47-0.82), and 0.66 (0.43-0.89), respectively]. Conclusions: status, and prognosis, thereby offering a comprehensive preoperative evaluation framework. This approach enables clinicians to accurately stratify patients, thus optimizing treatment strategies.