Noninvasive differentiation of molecular subtypes of adult nonenhancing glioma using MRI perfusion and diffusion parameters

Ilanah J Pruis; Stephan R Koene; Sebastian R van der Voort; Fatih Incekara; Arnaud J P E Vincent; Martin J van den Bent; Geert J Lycklama À Nijeholt; Rishi D S Nandoe Tewarie; Sophie E M Veldhuijzen van Zanten; Marion Smits

doi:10.1093/noajnl/vdac023

Noninvasive differentiation of molecular subtypes of adult nonenhancing glioma using MRI perfusion and diffusion parameters

Neurooncol Adv. 2022 Feb 21;4(1):vdac023. doi: 10.1093/noajnl/vdac023. eCollection 2022 Jan-Dec.

Affiliations

¹ Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
² Department of Neurosurgery, Erasmus MC, Rotterdam, The Netherlands.
³ Department of Neurology, Erasmus MC, Rotterdam, The Netherlands.
⁴ Department of Radiology and Nuclear Medicine, Haaglanden MC, Den Haag, The Netherlands.
⁵ Department of Neurosurgery, Haaglanden MC, Den Haag, The Netherlands.

Abstract

Background: Nonenhancing glioma typically have a favorable outcome, but approximately 19-44% have a highly aggressive course due to a glioblastoma genetic profile. The aim of this retrospective study is to use physiological MRI parameters of both perfusion and diffusion to distinguish the molecular profiles of glioma without enhancement at presentation.

Methods: Ninety-nine patients with nonenhancing glioma were included, in whom molecular status (including 1p/19q codeletion status and IDH mutation) and preoperative MRI (T2w/FLAIR, dynamic susceptibility-weighted, and diffusion-weighted imaging) were available. Tumors were segmented semiautomatically using ITK-SNAP to derive whole tumor histograms of relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC). Tumors were divided into three clinically relevant molecular profiles: IDH mutation (IDHmt) with (n = 40) or without (n = 41) 1p/19q codeletion, and (n = 18) IDH-wildtype (IDHwt). ANOVA, Kruskal-Wallis, and Chi-Square analyses were performed using SPSS.

Results: rCBV (mean, median, 75^th and 85^th percentile) and ADC (mean, median, 15^th and 25^th percentile) showed significant differences across molecular profiles (P < .01). Posthoc analyses revealed that IDHwt and IDHmt 1p/19q codeleted tumors showed significantly higher rCBV compared to IDHmt 1p/19q intact tumors: mean rCBV (mean, SD) 1.46 (0.59) and 1.35 (0.39) versus 1.08 (0.31), P < .05. Also, IDHwt tumors showed significantly lower ADC compared to IDHmt 1p/19q codeleted and IDHmt 1p/19q intact tumors: mean ADC (mean, SD) 1.13 (0.23) versus 1.27 (0.15) and 1.45 (0.20), P < .001).

Conclusions: A combination of low ADC and high rCBV, reflecting high cellularity and high perfusion respectively, separates IDHwt from in particular IDHmt 1p/19q intact glioma.

Keywords: ADC; MRI; molecular profile; nonenhancing glioma; rCBV.