Monoexponential, biexponential and stretched exponential models of diffusion weighted magnetic resonance imaging in glioma in relation to histopathologic grade and Ki-67 labeling index using high B values.

purposeTo explore the performance of various parameters obtained from monoexponential (Gaussian), biexponential and stretched exponential (non-Gaussian) models of Diffusion Weighted Magnetic Resonance Imaging in differentiating gliomas with correlation to histopathology and Ki-67 labeling index (LI). MATERIALS AND

methodsThis Institute Review Board approved retrospective study included 51 pathologically proven glioma patients (WHO Grade I, n = 1; Grade II, n = 19, Grade III, n = 12; Grade IV, n = 19), and immunohistochemistry for Ki-67 LI was obtained. The conventional Magnetic Resonance (MR) images and Diffusion Weighted (DW) images with 19 non-zero b values (0-4500 s/mm

resultsHighly significant differences were found between HGG and LGG for all the parameters (P < 0.001 for all). In differentiating HGG from LGG, AUC values were 0.955 for Ki-67 LI; 0.926 for α; 0.903 for Dslow; 0.897 for f; 0.863 for DDC; 0.852 for ADC; 0.820 for Dfast (P < 0.001 for all). The parameters ADC, Dslow, Dfast, f, DDC, and α showed moderate to good negative correlation with Ki-67 LI (P < 0.001 for all). The ICCs of all the parameters were found greater than 0.75 (P < 0.05 for all) suggesting good reliability of measurements.

conclusionIn comparison to ADC derived from monoexponential model, the parameters α and Dslow derived from stretched exponential, and biexponential models respectively can efficiently differentiate HGG from LGG with high diagnostic accuracy. Additionally, f and DDC derived from biexponential, and stretched exponential models respectively are also more useful in differentiating HGG from LGG in comparison to ADC.