Multiparametric MRI Model with DCE-MRI and ADC map Enables Accurate Prediction of Benign and Malignant Breast Lesions

Motivation: No mature neural network model based on multiparametric MRI to predict benign and malignant breast lesions accurately. Goal(s): To develop a deep learning (DL) model based on multiparametric MRI for distinguishing benign and malignant breast lesions Approach: A DL model based on the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and diffusion weighted imaging (DWI) with apparent diffusion coefficient (ADC) map. Results: The DL combined model based on DCE-MRI and ADC achieved the highest diagnostic efficiency with an area under the curve (AUC) of 0.889. Impact: The DL model based on multiparametric MRI achieved high accuracy for distinguishing benign and malignant breast lesions and showed the potential for future application as a new tool for clinical diagnosis.