Abstract
Objectives: To compare the efficacy of parameters from multiple diffusion magnetic resonance imaging (dMRI) for prediction of isocitrate dehydrogenase 1 (IDH1) genotype and assessment of cell proliferation in gliomas.Methods: Ninety-one patients with glioma underwent diffusion weighted imaging (DWI), multi-b-value DWI, and diffusion kurtosis imaging (DKI)/neurite orientation dispersion and density imaging (NODDI) on 3.0T MRI. Each parameter was compared between IDH1-mutant and IDH1 wild-type groups by Mann–Whitney U test in lower-grade gliomas (LrGGs) and glioblastomas (GBMs), respectively. Further, performance of each parameter was compared for glioma grading under the same IDH1 genotype. Spearman correlation coefficient between Ki-67 labeling index (LI) and each parameter was calculated.Results: The diagnostic performance was better achieved with apparent diffusion coefficient (ADC), slow ADC (D), fast ADC (D∗), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), mean kurtosis (MK), and intracellular volume fraction (ICVF) for distinguishing IDH1 genotypes in LrGGs, with statistically insignificant AUC values from 0.750 to 0.817. In GBMs, no difference between the two groups was found. For IDH1-mutant group, all parameters, except for fractional anisotropy (FA) and D∗, significantly discriminated LrGGs from GBMs (P < 0.05). However, for IDH1 wild-type group, only ADC statistically discriminated the two (P = 0.048). In addition, MK has maximal correlation coefficient (r = 0.567, P < 0.001) with Ki-67 LI.Conclusion: dMRI-derived parameters are promising biomarkers for predicting IDH1 genotype in LrGGs, and MK has shown great potential in assessing glioma cell proliferation.
Highlights
In 2016, the World Health Organization classified levels of Central Nervous System tumors based on molecular features, the isocitrate dehydrogenase 1 (IDH1) genotype (Karsy et al, 2017)
The diagnostic performance was better achieved with apparent diffusion coefficient (ADC), slow ADC (D), fast ADC (D∗), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), mean kurtosis (MK), and intracellular volume fraction (ICVF) for distinguishing IDH1 genotypes in lowergrade gliomas (LrGGs), with statistically insignificant area under the curve (AUC) values from 0.750 to 0.817
Patients were included in the study if they met the following inclusion criteria: (a) pathologically confirmed primary gliomas; (b) preoperative diffusion weighted imaging (DWI), multi-b-value DWI, and diffusion kurtosis imaging (DKI)/neurite orientation dispersion and density imaging (NODDI) acquisition were performed; (c) IDH1 genotype measured by genetic screening or immunohistochemistry was available
Summary
In 2016, the World Health Organization classified levels of Central Nervous System tumors based on molecular features, the isocitrate dehydrogenase 1 (IDH1) genotype (Karsy et al, 2017). Many studies have indicated a better prognosis of IDH1-mutant gliomas than IDH1 wild-type gliomas (Turkalp et al, 2014; Shen et al, 2020). Accurate identification of glioma IDH1 genotype facilitates the formulation of treatment plans and assessment of patient prognosis. The higher Ki-67 labeling index (LI) indicates faster tumor growth and poorer tissue differentiation. To obtain tumor pathology information and Ki-67 LI via surgery or pathological biopsy is not applicable for all gliomas, such as those in the brainstem and basal ganglia regions. An imaging approach to obtain anatomical details and tissue characteristics is essential for clinic diagnosis
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