Prediction of Isocitrate Dehydrogenase Genotype in Brain Gliomas with MRI: Single-Shell versus Multishell Diffusion Models

Abstract

A recent update of the World Health Organization (WHO) classification of brain tumors introduced molecular markers that add greater prognostic accuracy than histopathologic findings alone (1,2). Isocitrate dehydrogenase (IDH) genotype and epigenetic 1p/19q codeletion are two key molecular markers. Patients with IDH wildtype gliomas have a worse prognosis than those with IDHmutant gliomas. Patients with 1p/19q uncodeleted gliomas have a worse prognosis than those with codeleted IDH-mutant gliomas (3). The establishment of in vivo biomarkers that enable prediction of IDH and 1p/19q status would thus be relevant for patient management (4) and clinical trials. Diffusion MRI is a potential method for providing such in vivo biomarkers. It enables assessment of the microstructure of the whole tumor at a relatively high spatial resolution and is easily accessible. Diffusion-tensor imaging (DTI) is currently the most used method (5). DTI parameters such as mean diffusivity (MD) and fractional anisotropy (FA) correlate with changes in cellular density and in extracellular matrix features induced by glioma infiltration and growth. Several studies aimed to grade gliomas with use of DTI. Most of these have demonstrated significantly lower MD values in high-grade gliomas (6-12), but the majority failed to differentiate WHO grade II gliomas from grade III gliomas due to overlapping MD and FA values. A limitation of the above studies is that the authors did not stratify patients according to IDH

Regional and Volumetric Parameters for Diffusion-Weighted WHO Grade II and III Glioma Genotyping: A Method Comparison

“…Specifically for IDH wild-type glioblastoma, no difference in diffusivity may exist between grades II and IV. 29 Villaneuva-Meyer et al 30 previously assessed ROI-derived minimum, mean, and maximum in WHO grade II gliomas: A minimum ADC threshold of 0.9 Â 10 À3 seconds /mm 2 provided the greatest sensitivity (91%) and specificity (76%) for IDH typing, with an AUC of 0.901. 19 ROI-based minimum ADC analysis was also performed by Wasserman et al 15 with a proposed cutoff point of 0.95Â 10 À3 seconds /mm 2 (sensitivity of 76.9%, specificity of 65.2%, and AUC ¼ 0.711) 13 and by Xing et al 14 with a suggested minimum ADC threshold of 1.01Â 10 À3 seconds /mm 2 (sensitivity of 76.9%, specificity of 82.6%, AUC ¼ 0.87).…”

<p>Neurite orientation and dispersion density imaging: clinical utility, efficacy, and role in therapy</p>

“…After the discovery of unique contrast of NODDI maps within gliomas with a 7-T MRI scanner, 45 Maximov et al 46 reported the reliable and feasible differentiation of glioma grading by NODDI parameters. Additionally, although there is no significant additional utility of NODDI for detecting isocitrate dehydrogenase-1 (IDH-1) mutation status in gliomas, 47,48 quantitative NODDI metrics in tumoral and peritumoral regions are suggested to be useful for glioma grading. 48 ND seems to have the best discriminative power for distinguishing normal, tumoral, and peritumoral edematous areas.…”

Prediction of Lower Grade Insular Glioma Molecular Pathology Using Diffusion Tensor Imaging Metric-Based Histogram Parameters

“…Moreover, Figini et al. ( 34 ) found lower FA and higher MD values in glioma patients with IDH mutations; however, there were no significant result regarding the prediction of 1p19q codeletion.…”