Radiomics Nomogram Based on High--Value Diffusion-Weighted Imaging for Distinguishing the Grade of Bladder Cancer.

Background: The aim was to evaluate the feasibility of radiomics features based on diffusion-weighted imaging (DWI) at high -values for grading bladder cancer and to compare the possible advantages of high--value DWI over the standard -value DWI.

Methods: Seventy-four participants with bladder cancer were included in this study. DWI sequences using a 3 T MRI with -values of 1000, 1700, and 3000 s/mm were acquired, and the corresponding ADC maps were generated, followed with feature extraction. Patients were randomly divided into training and testing cohorts with a ratio of 8:2. The radiomics features acquired from the ADC, ADC, and ADC maps were compared between low- and high-grade bladder cancers by using the Wilcox analysis, and only the radiomics features with significant differences were selected. The least absolute shrinkage and selection operator method and a logistic regression were performed for the feature selection and establishing the radiomics model. A receiver operating characteristic (ROC) analysis was conducted to assess the diagnostic performance of the radiomics models.

Results: In the training cohorts, the AUCs of the ADC, ADC, and ADC model for discriminating between low- from high-grade bladder cancer were 0.901, 0.920, and 0.901, respectively. In the testing cohorts, the AUCs of ADC, ADC, and ADC were 0.582, 0.745, and 0.745, respectively.

Conclusions: The radiomics features extracted from the ADC maps could improve the diagnostic accuracy over those extracted from the conventional ADC maps.