A three-component multi-b-value diffusion-weighted imaging might be a useful biomarker for detecting microstructural features in gliomas with differences in malignancy and IDH-1 mutation status

The purpose of the study was to explore the performance of a three-component diffusion model in evaluating the degree of malignancy and isocitrate dehydrogenase 1 (IDH-1) gene type of gliomas. Overall, 60 patients with gliomas were enrolled. The intermediate and perfusion-related diffusion coefficients (D${}_{int}$ and D${}_p$) and fractions of strictly limited, intermediate, and perfusion-related diffusion (F${}_{very-slow}$, F${}_{int}$, and F${}_p$) were obtained with a three-component diffusion model. Parameters were also obtained from a diffusion kurtosis model and mono- and biexponential models. All parameters were compared between different tumor grades and IDH-1 gene types. Diagnostic performance and logistic regression analyses were performed. High-grade gliomas (HGGs) had significantly higher F${}_{int}$, F${}_{very-slow}$, and D${}_p$ values but significantly lower F${}_p$ and D${}_{int}$ values than low-grade gliomas (LGGs), and F${}_{int}$ and F${}_p$ differed significantly among grade II, III, and IV gliomas (p < 0.05 for all). F${}_{int}$ achieved the highest AUC of 0.872 in differentiating between LGGs and HGGs. Logistic regression analysis revealed that in each model, F${}_{int}$, diffusion coefficient (D), apparent diffusion coefficient (ADC), mean diffusivity (MD), and mean kurtosis (MK) were associated with glioma grading. After multiple regression analysis, F${}_{int}$ remained the only differentiator. Additionally, F${}_{int}$ and F${}_p$ showed significant differences between IDH-1 mutated and IDH-1 wild-type gliomas (p = 0.007 and 0.01, respectively). The three-component DWI model served as a useful biomarker for detecting microstructural features in gliomas with different grades and IDH-1 mutation statuses.