Diffusion coefficient calculated with intravoxel incoherent motion modeling of diffusion-weighted MR imaging demonstrated superior performance compared with the apparent diffusion coefficient in di... PurposeTo compare the association of intravoxel incoherent motion (IVIM)–derived parameters and apparent diffusion coefficient (ADC) with the histologic grade of hepatocellular carcinoma (HCC) and ...

Background: Until now, several investigators have explored the value of diffusion-weighted magnetic resonance imaging (DWI) for the preoperative tumor grading of endometrial cancer. However, the diagnostic value of DWI with quantitative analysis of apparent diffusion coefficient (ADC) has been controversial. Purpose: To explore the role of histogram analysis of ADC maps based on entire tumor volume in determining the grade of endometrial cancer. Material and Methods: This study was IRB-approved with waiver of informed consent. Thirty-three patients with endometrial cancer underwent DWI (b = 0, 600, 1000 s/mm²), and corresponding ADC maps were acquired. Regions of interest (ROIs) were drawn on all slices of the ADC map in which the tumor was visualized including areas of necrosis to derive volume-based histographic ADC data. Histogram parameters (5th–95th percentiles, mean, standard deviation, skewness, kurtosis) were correlated with histological grade using one-way ANOVA with Tukey-Kramer test for post hoc comparisons, and were compared between high (grade 3) and low (grades 1/2) grade using Student t-test. ROC curve analysis was performed to determine the optimum threshold value for each parameter, and their corresponding sensitivity and specificity. Results: The standard deviation, quartile, 75th, 90th, and 95th percentiles of ADC showed significant differences between grades ( P ≤ 0.03 for all) and between high and low grades ( P ≤ 0.024 for all). There were no significant correlations between tumor grade and other parameters. ROC curve analysis yielded sensitivities and specificities of 75% and 96%, 62.5% and 92%, 100% and 52%, 100% and 72%, and 100% and 88%, using standard deviation, quartile, 75th, 90th, and 95th percentiles for determining high grade with corresponding areas under the curve (AUCs) of 0.787, 0.792, 0.765, 0.880, and 0.925, respectively. Conclusion: Histogram analysis of ADC maps based on entire tumor volume can be useful for predicting the histological grade of endometrial cancer. The 90th and 95th percentiles of ADC were the most promising parameters for differentiating high from low grade.