123 Quantitative Volumetric Magnetic Resonance Perfusion Identifies a Distinct Vasculogenic Molecular Subtype of Human Glioblastoma Associated With Worse Clinical Outcomes. Issue Volume 62:Issue CN Supp 1(2015)Supplement 1 (August 2015)

• Record Type: Journal Article
• Authors: Achrol, Achal Singh; Liu, Tiffany; Mitchell, Lex A.; Loya, Joshua J.; Westbroek, Erick M.; Rodriguez, Scott; Feroze, Abdullah; Chang, Steven D.; Rubin, Daniel; Harsh, Griffith R.
• Is Part Of: Neurosurgery. Volume 62:Issue CN Supp 1(2015)Supplement 1
• Publication Date: 2015-08
• Subjects: Nervous system -- Surgery -- Periodicals; 617.48005
• DOI: 10.1227/01.neu.0000467085.78226.37
• Languages: English
• ISSNs: 0148-396X

Abstract

Abstract : INTRODUCTION: Glioblastoma is the most common and aggressive primary human brain cancer. Noninvasive characterization of intratumor blood flow parameters may help guide clinical decision making. Beyond risk stratification and prognostication, tumor perfusion may inform treatment selection and serial monitoring of newer antiangiogenic targeted therapies. In this study, intra- and intertumor variations in blood volume were quantified by using a novel 3-D volumetric, dynamic-susceptibility contrast-enhanced (DSCE), T2*-weighted perfusion magnetic resonance (MR) analysis to determine associations with molecular features and clinical outcomes. METHODS: A total of n = 150 patients underwent preoperative DSCE T2* MR perfusion analysis, including an internal test cohort and external validation cohort. Volumetric quantitative voxel-based data on relative cerebral blood volume (rCBV) were assessed, including mean, median, kurtosis, skewness, and percentage of elevated rCBV (ie, elevated rCBV). Intra- and intertumor heterogeneity in each parameter was characterized by mosaic analysis. Hierarchical clustering was performed to identify subsets of patients with correlated perfusion patterns. Resulting perfusion-based clusters were assessed against molecular features by using integrated PARADIGM genomic pathway-level elastic net logistic regression analyses. Perfusion-based clusters were assessed in univariate Kaplan-Meier (log-rank) and multivariate Cox proportional hazards models for association with overall clinical survival outcomes. Validated MR perfusion parameters discovered in the test cohort were externally validated in the independent validation cohort. RESULTS: Intra- and intertumor heterogeneity was observed in mosaic analyses of quantitative voxel-based MR perfusion data of mean, median, kurtosis, skewness, and elevated rCBV. Hierarchical clustering and random forest analyses identified an elevated rCBV cluster of patients with correlated MR perfusion patterns that demonstrated distinct molecular features of vasculogenesis, gap junction assembly, and endothelial permeability in integrated PARADIGM genomic pathway-level analysis. This elevated rCBV subgroup of patients demonstrated worse overall survival in univariate and multivariate survival analyses (HR 2.9, P = .02), and these findings externally validated in an independent cohort. CONCLUSION: A distinct vasculogenic subtype of glioblastoma identified by quantitative MR perfusion voxel-based analysis was associated with unique molecular features and worse overall survival. Quantitative volumetric MR perfusion holds potential in characterizing intra- and intertumoral heterogeneity, and identifying biologically distinct, clinically relevant subsets of patients for risk stratification and treatment selection.