Faculty Bibliography

PURPOSE: Lower grade gliomas (WHO grade II/III) have been classified into clinically-relevant molecular subtypes based on IDH and 1p/19q mutation status. The purpose was to investigate whether T2/FLAIR MRI features could distinguish between lower grade glioma molecular subtypes

Experimental Design: MRI scans from the TCGA/TCIA lower grade glioma database (n=125) were evaluated by 2 independent neuroradiologists to assess: 1) presence/absence of homogenous signal on T2WI; 2) presence/absence of "T2-FLAIR mismatch" sign; 3) sharp or indistinct lesion margins; 4) presence/absence of peritumoral edema. Metrics with moderate-substantial agreement underwent consensus review, and were correlated with glioma molecular subtypes. Somatic mutation, DNA copy number, DNA methylation, gene expression, and protein array data from the TCGA lower grade glioma database were analyzed for molecular-radiographic associations. A separate institutional cohort (n=82) was analyzed to validate the T2-FLAIR mismatch sign.

Results: Among TCGA/TCIA cases, inter-reader agreement was calculated for lesion homogeneity (k=0.234 [0.111-0.358]), T2-FLAIR mismatch sign (k=0.728 [0.538-0.918]), lesion margins (k=0.292 [0.135-0.449]), and peritumoral edema (k=0.173 [0.096-0.250]). All 15 cases that were positive for the T2-FLAIR mismatch sign were IDH-mutant, 1p/19q-non-codeleted tumors (p<0.0001; PPV=100%, NPV=54%). Analysis of the validation cohort demonstrated substantial inter-reader agreement for the T2-FLAIR mismatch sign (k=0.747 [0.536 - 0.958]); all 10 cases positive for the T2-FLAIR mismatch sign were IDH-mutant, 1p/19q non-codeleted tumors (p<0.00001; PPV=100%, NPV=76%).

Conclusion: Among lower grade gliomas, T2-FLAIR mismatch sign represents a highly specific imaging biomarker for the IDH-mutant, 1p/19q-non-codeleted molecular subtype.

BACKGROUND: Brain imaging in diffuse glioma is used for diagnosis, treatment planning, and follow-up. PURPOSE: In this meta-analysis, we address the diagnostic accuracy of imaging to delineate diffuse glioma. DATA SOURCES: We systematically searched studies of adults with diffuse gliomas and correlation of imaging with histopathology. STUDY SELECTION: Study inclusion was based on quality criteria. Individual patient data were used, if available. DATA ANALYSIS: A hierarchic summary receiver operating characteristic method was applied. Low- and high-grade gliomas were analyzed in subgroups. DATA SYNTHESIS: Sixty-one studies described 3532 samples in 1309 patients. The mean Standard for Reporting of Diagnostic Accuracy score (13/25) indicated suboptimal reporting quality. For diffuse gliomas as a whole, the diagnostic accuracy was best with T2-weighted imaging, measured as area under the curve, false-positive rate, true-positive rate, and diagnostic odds ratio of 95.6%, 3.3%, 82%, and 152. For low-grade gliomas, the diagnostic accuracy of T2-weighted imaging as a reference was 89.0%, 0.4%, 44.7%, and 205; and for high-grade gliomas, with T1-weighted gadolinium-enhanced MR imaging as a reference, it was 80.7%, 16.8%, 73.3%, and 14.8. In high-grade gliomas, MR spectroscopy (85.7%, 35.0%, 85.7%, and 12.4) and 11C methionine-PET (85.1%, 38.7%, 93.7%, and 26.6) performed better than the reference imaging. LIMITATIONS: True-negative samples were underrepresented in these data, so false-positive rates are probably less reliable than true-positive rates. Multimodality imaging data were unavailable. CONCLUSIONS: The diagnostic accuracy of commonly used imaging is better for delineation of low-grade gliomas than high-grade gliomas on the basis of limited evidence. Improvement is indicated from advanced techniques, such as MR spectroscopy and PET.