PURPOSE: To assess the feasibility of using diffusion-weighted imaging (DWI) with the stretched-exponential model (SEM) for glioma grading and determining the correlations among parameters and proliferating cell nuclear antigen and Ki-67 expression. MATERIALS AND METHODS: Mono-exponential model-DWI (MEM-DWI) and SEM-DWI were performed in 104 patients with pathologically proven gliomas. The patients were divided into the training set (n = 72) and test set (n = 32). Apparent diffusion coefficient (ADC), solid tumor distributed diffusion coefficient (DDC), and whole tumor α values were measured. These parameters were applied as cut-off values to determine the predictive accuracy. Proliferating cell nuclear antigen and Ki-67 expression correlated with all parameters. RESULTS: Significant differences between low-grade gliomas (LGG) and high-grade gliomas (HGG) were observed for all parameters (P < 0.05), and significant differences in the ability of DDC to distinguish between any two glioma grades (P < 0.05) were also evident. DDC showed the highest sensitivity and specificity for glioma grading and was negatively correlated with Ki-67 and proliferating cell nuclear antigen expression. DDC also showed greater predictive accuracy than ADC and α. CONCLUSION: SEM-DWI offers a better approach for glioma grading than MEM-DWI, and DDC may be a better imaging biomarker for grading and evaluating the proliferative activity of brain gliomas.
PURPOSE: To assess the feasibility of using diffusion-weighted imaging (DWI) with the stretched-exponential model (SEM) for glioma grading and determining the correlations among parameters and proliferating cell nuclear antigen and Ki-67 expression. MATERIALS AND METHODS: Mono-exponential model-DWI (MEM-DWI) and SEM-DWI were performed in 104 patients with pathologically proven gliomas. The patients were divided into the training set (n = 72) and test set (n = 32). Apparent diffusion coefficient (ADC), solid tumor distributed diffusion coefficient (DDC), and whole tumor α values were measured. These parameters were applied as cut-off values to determine the predictive accuracy. Proliferating cell nuclear antigen and Ki-67 expression correlated with all parameters. RESULTS: Significant differences between low-grade gliomas (LGG) and high-grade gliomas (HGG) were observed for all parameters (P < 0.05), and significant differences in the ability of DDC to distinguish between any two glioma grades (P < 0.05) were also evident. DDC showed the highest sensitivity and specificity for glioma grading and was negatively correlated with Ki-67 and proliferating cell nuclear antigen expression. DDC also showed greater predictive accuracy than ADC and α. CONCLUSION: SEM-DWI offers a better approach for glioma grading than MEM-DWI, and DDC may be a better imaging biomarker for grading and evaluating the proliferative activity of brain gliomas.
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