Grading of clear cell renal cell carcinoma by using monoexponential, biexponential, and stretched exponential diffusion-weighted MR imaging - Wang, Wenhui; Wang, Lingdian; Zhou, Jing; Liu, Taiyuan; Bai, Yan; Wang, Meiyun (Frontiers in Oncology, 2024)
ObjectivesTo evaluate the diagnostic accuracy of monoexponential, biexponential and stretched-exponential diffusion-weighted imaging (DWI) models in the grading of clear cell renal cell carcinoma (ccRCC).Materials and MethodsFifty-one patients with pathologically proven ccRCC underwent DWI with fifteen b factors (0, 10, 30, 50, 70, 100, 150, 200, 300, 400, 600, 800, 1000, 1500, 2000 sec/mm²) on a 3.0T MR scanner. The isotropic apparent diffusion coefficient (ADC), true diffusion coefficient (ADCslow), pseudodiffusion coefficient (ADCfast), and fraction of perfusion (f) were derived from DWI using a biexponential model. The water diffusion heterogeneity index (α) and distributed diffusion coefficient (DDC) were derived from DWI using a stretched-exponential model. All values were calculated for the solid area of tumors and compared between high-grade and low-grade ccRCC. The Mann−Whitney U test and receiver operating characteristic (ROC) analysis were used for statistical analysis. The DeLong test was performed to compare the ROC curves.ResultsThe mean ADC, DDC, ADCslow and α values were significantly lower in high-grade ccRCC than in low-grade ccRCC (P< 0.01). However, the ADCfast and f were not significantly different between the two groups (P > 0.05). According to the ROC analyses, the AUC for α was 0.941, which was significantly greater than those of the other parameters, with a sensitivity of 100% and a specificity of 84.2%. The DeLong test showed that there were significant differences in the ROCs among ADCfast/ADC, ADCfast/α, f/ADCslow, ADCfast/ADCslow, f/α, DDC/α, and f/ADC.ConclusionsDiffusion-related parameters (ADC, DDC, ADCslow and α) could be used to distinguish between low- and high-grade ccRCC. The α derived from the stretched-exponential model may be the most promising parameter for grading ccRCC.