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

Abstract

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 (IDHmut/1p19qcodel), IDH-mutant and 1p/19q-intact (IDHmut/1p19qint), or IDH-wildtype (IDHwt). For IDHwt 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 IDHmut/1p19qint, and all seven with 25–50% mismatch. Well-defined margins correlated with IDHmut/1p19qint 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 IDHwt status (especially “molecular glioblastoma”). Calcification correlated with IDHmut/1p19qcodel 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 IDHmut/1p19qint even with a lower threshold of ≥ 25% mismatch and outweighs other features. Secondary features include enhancement, necrosis and hemorrhage (predicting IDHwt, especially “molecular glioblastoma”), and calcification (predicting IDHmut/1p19qcodel).

AdvancedMRTechniques for Preoperative Glioma Characterization: Part 2

“…Lasocki et al examined multiple conventional MRI features for the prediction of the three key molecular subtypes, IDH‐mutant and 1p/19q co‐deleted, IDH‐mutant and 1p/19q intact, and IDH‐wildtype in grade 2 and 3 gliomas using multivariate logistic regression analysis, and reported T2‐FLAIR mismatch as the most predictive feature across the three genotypes 101 . Additionally, contrast enhancement, hemorrhage, and necrosis were observed to be correlated with IDH wild‐type status, while calcification was found to be correlated with IDH mutant and 1p/19q co‐deleted status.…”

Rapid detection of isocitrate dehydrogenase 1 mutation status in glioma based on Crispr-Cas12a

“…With sharp boundaries and T2/FLAIR-mismatch sign features, astrocytoma is more likely to diagnosis, and all tumors in T2w and Flair high signal areas need to be removed as much as possible 34 . If the IDH1-R132H mutation is not detected, and the tumor boundary is blurred and the invasive and growth characteristics are prominent, IDH wild-type adult diffuse glioma should be diagnosed, and more radical surgical resection may be required 35 . It is worth mentioning that, for some non-neoplastic lesions, such as inflammatory pseudotumors, they often do not have the molecular characteristics of IDH mutation 36 .…”

Conventional MRI-Derived Biomarkers of Adult-Type Diffuse Glioma Molecular Subtypes: A Comprehensive Review

“…Indeed, a homogeneous T2w signal has been demonstrated to be related to IDH-MUT 1p/19q non-codeleted tumors [ 24 ]. The evaluation of T2w images, particularly the use of a quantitative approach through T2 mapping sequences, has recently shown how the T2 signal is significantly increased in IDH-MUT gliomas compared to the wild-type; this may be due to an accumulation of 2HG and modified tumor metabolism [ 35 ]. On the contrary, calcifications within IDH-MUT are more likely related to IDH-MUT 1p/19q codeleted tumors [ 24 ], which bear a heterogeneous signal intensity in T2w images with a significantly higher micro-vascularity and higher vascular heterogeneity ( Figure 3 ) [ 36 ].…”