Assessment of MGMT and TERT Subtypes and Prognosis of Glioblastoma by Whole Tumor Apparent Diffusion Coefficient Histogram Analysis - Ling Chen; Min Wu; Yao Li; Lifang Tang; Chuyun Tang; Lizhao Huang; Tao Li; Li Zhu (Brain and Behavior)
Abstract Background: Adult glioblastomas (GBMs) are associated with high recurrence and mortality. Personalized treatment based on molecular markers may help improve the prognosis. We aimed to evaluate whether apparent diffusion coefficient (ADC) histogram analysis can better predict MGMT and TERT molecular characteristics and to determine the prognostic relevance of genetic profile in patients with GBM. Materials and Methods: MRI, clinical, and pathological data of 79 patients with GBM were retrospectively collected. The ADC values based on histogram analysis were described using 10th percentile (p10), 90th percentile (p90), mean, median, minimum, maximum, skewness, kurtosis, and entropy. The independent‐sample t test, linear correlation analysis, receiver operating characteristics (ROC) curve analysis, Kaplan–Meier analysis, and Cox proportional hazard regression were performed. Results: MGMT promoter methylation and TERT promoter mutation were detected in 53.2% and 44.3% of GBM patients, respectively. The ADCp10 in MGMT promoter unmethylated group was significantly lower than that in the MGMT promoter methylated group (p = 0.005). There were significant differences in ADCmin, ADCp10, ADCmean, and entropy between TERT promoter mutant and wild‐type groups. Entropy showed the best diagnostic performance in differentiating between positive and negative TERT groups (AUC = 0.722, p = 0.001). Overall survival (OS) showed a positive correlation with ADCmin. The TERT promoter mutation was the only independent prognostic factor for GBM. Conclusions: ADC histogram analysis may be a potential noninvasive biomarker for differentiating MGMT and TERT molecular markers and providing prognostic information for GBM patients.