Preoperative prediction of axillary lymph node metastasis in breast invasive ductal carcinoma patients using a deep learning model based on dynamic contrast-enhanced magnetic resonance imaging: a multicenter study.

ABSTRACT:

Background

Invasive ductal carcinoma (IDC) is the most common histological subtype of breast cancer, and axillary lymph node metastasis (ALNM) is a pivotal factor in clinical staging, prognostic assessment, and treatment planning. This study aims to develop and validate a deep learning (DL) model based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the prediction of ALNM in IDC patients.

Methods

This multicenter study conducted a retrospective analysis of DCE-MRI images from 520 patients diagnosed with IDC of the breast. The training and internal validation sets consisted of 411 patients from The First Hospital of Qinhuangdao, while the external testing set included 109 patients from the Maternal and Child Health Hospital of Qinhuangdao. Radiomics and

SUBMITTER: Gu C 

PROVIDER: S-EPMC12685781 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature