Prediction of bladder cancer grade based on biparametric MRI radiomics: comparison with traditional MRI

Abstract Background: To compare biparametric (bp) MRI radiomics signatures and traditional MRI model for the preoperative prediction of bladder cancer (BCa) grade. Methods: This retrospective study included 255 consecutive patients with pathologically confirmed 113 low-grade and 142 high-grade BCa who underwent preoperative MRI, including T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC). The traditional MRI nomogram model was developed using univariate and multivariate logistic regression by the mean apparent diffusion coefficient (mADC), vesical imaging reporting and data system (VI-RADS) scoring, tumor size and number of tumors. Volumes of interest were manually drawn on T2WI and ADC maps by two radiologists. Using ANOVA, correlation and LASSO methods to select features. Then, a logistic regression (LR) classifier was used to develop the radiomics signatures in the training set and assessed in the validation set. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic abilities of the radiomics and traditional MRI models by the DeLong test. Finally, decision curve analysis (DCA) was performed by estimating the clinical usefulness of the two models in both the training and validation sets. Results: The areas under the ROC curves (AUCs) of the traditional MRI model were 0.841 in the training cohort and 0.806 in the validation cohort. The AUCs of the three groups of radiomics model [ADC, T2WI, bp-MRI (ADC and T2WI)]-based logistic regression analysis algorithms were 0.888, 0.875 and 0.899 in the training cohort and 0.863, 0.805 and 0.867 in the validation cohort, respectively. The combined radiomics model achieved higher AUCs than the traditional MRI model and was compared using the DeLong test (P = 0.026 and 0.023 in the training and validation cohorts, respectively). DCA indicated that the radiomics model had higher net benefits than the traditional MRI model. Conclusions: The bp-MRI radiomics model may be helpful for distinguishing high-grade and low-grade BCa and outperformed the traditional MRI model. Multicenter validation is needed to acquire high-level evidence for its clinical application.