Multiparametric MRI deep learning model based on dynamic Contrast-enhanced and apparent diffusion coefficient map enables accurate prediction of benign and malignant breast lesions.

ABSTRACT:

Objectives

The study aims to develop a deep learning (DL) model based on multiparametric magnetic resonance imaging (MRI) for distinguishing between benign and malignant breast lesions.

Methods

A total of 556 lesions (307 malignant, 249 benign) in 509 patients were pooled in the training/validation datasets between November 2018 and October 2019 in this retrospective study. A combined DL model based on the dynamic contrast enhanced-MRI (DCE-MRI) and apparent diffusion coefficient (ADC) map was developed to characterize breast lesions. Model performance was evaluated by using areas under the receiver operating characteristic curve (AUC) in the validation dataset and an independent testing dataset consisting of 243 lesions in 225 patients, and compared with other combined and

SUBMITTER: Luo C 

PROVIDER: S-EPMC12798014 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature