Conventional MRI features can predict the molecular subtype of adult grade 2–3 intracranial diffuse gliomas

PURPOSE: Molecular biomarkers are important for classifying intracranial gliomas, prompting research into correlating imaging with genotype (“radiogenomics”). A limitation of the existing radiogenomics literature is the paucity of studies specifically characterizing grade 2–3 gliomas into the three key molecular subtypes. Our study investigated the accuracy of multiple different conventional MRI features for genotype prediction. METHODS: Grade 2–3 gliomas diagnosed between 2007 and 2013 were identified. Two neuroradiologists independently assessed nine conventional MRI features. Features with better inter-observer agreement (κ ≥ 0.6) proceeded to consensus assessment. MRI features were correlated with genotype, classified as IDH-mutant and 1p/19q-codeleted (IDH(mut)/1p19q(codel)), IDH-mutant and 1p/19q-intact (IDH(mut)/1p19q(int)), or IDH-wildtype (IDH(wt)). For IDH(wt) tumors, additional molecular markers of glioblastoma were noted. RESULTS: One hundred nineteen patients were included. T2-FLAIR mismatch (stratified as > 50%, 25–50%, or < 25%) was the most predictive feature across genotypes (p < 0.001). All 30 tumors with > 50% mismatch were IDH(mut)/1p19q(int), and all seven with 25–50% mismatch. Well-defined margins correlated with IDH(mut)/1p19q(int) status on univariate analysis (p < 0.001), but this related to correlation with T2-FLAIR mismatch; there was no longer an association when considering only tumors with < 25% mismatch (p = 0.386). Enhancement (p = 0.001), necrosis (p = 0.002), and hemorrhage (p = 0.027) correlated with IDH(wt) status (especially “molecular glioblastoma”). Calcification correlated with IDH(mut)/1p19q(codel) status (p = 0.003). A simple, step-wise algorithm incorporating these features, when present, correctly predicted genotype with a positive predictive value 91.8%. CONCLUSION: T2-FLAIR mismatch strongly predicts IDH(mut)/1p19q(int) even with a lower threshold of ≥ 25% mismatch and outweighs other features. Secondary features include enhancement, necrosis and hemorrhage (predicting IDH(wt), especially “molecular glioblastoma”), and calcification (predicting IDH(mut)/1p19q(codel)).