Prediction of Survival in Surgically Treated Glioblastoma Multiforme Utilizing DTI and Contrast-Enhanced MRI.

Introduction  Glioblastoma multiforme (GBM) is a highly malignant brain tumor with poor prognosis, despite maximal safe resection and chemoradiotherapy. Predicting survival outcomes is crucial for optimizing treatment strategies. While conventional magnetic resonance imaging (MRI) reveals tumor characteristics, advanced sequences like diffusion tensor imaging (DTI) and susceptibility-weighted imaging (SWI) may enhance prognostic accuracy. Materials and Methods  A retrospective study reviewed 45 newly diagnosed GBM patients treated with maximal safe resection, adjuvant radiotherapy, and temozolomide between 2016 and 2022. Preoperative MRI data, including conventional sequences, DTI, and SWI, were analyzed. Radiological parameters-tumor volume, edema:tumor volume ratio, necrosis, enhancement, fractional anisotropy (FA), and microhemorrhage-were assessed for survival prediction. Kaplan-Meier survival analysis and Cox regression evaluated their prognostic significance. Results  Among the 45 patients, the median follow-up was 58.3 weeks, with 30 deaths reported. Significant differences were observed in FA, edema:tumor volume ratio, necrosis, enhancement, and microhemorrhage between survivors and nonsurvivors. Higher edema:tumor volume ratio (cutoff ≥ 0.905, area under the curve [AUC] = 0.895) and higher FA (cutoff ≥ 0.655, AUC = 0.8) correlated with mortality and survival, respectively. Multivariate Cox regression identified edema:tumor volume ratio (hazard ratio [HR] = 7.4, p  < 0.05) and microhemorrhage > 25% (HR = 45.9, p  < 0.05) as independent predictors of mortality. Conclusion  Tumor-related edema and necrosis significantly influence mortality, with edema:tumor volume ratio emerging as a stronger predictor than individual tumor or edema volumes. FA values reflect tumor aggressiveness, correlating with survival. Incorporating advanced imaging parameters like DTI and SWI alongside conventional MRI enhances prognostic precision in GBM management.