Preoperatively predicting human epidermal growth factor receptor 2-low expression in breast cancer using neural network model based on multiparameter magnetic resonance imaging.

ABSTRACT:

Background

Preoperative prediction of human epidermal growth factor receptor 2 (HER2)-low expression using magnetic resonance imaging (MRI) can enhance the selection of clinical treatment strategies and enhance patient outcomes. Herein, we investigated the value of a neural network model constructed with multiparametric MRI in diagnosing HER2-low breast cancer.

Methods

This retrospective study involved two different centers. A total of 895 breast cancer patients (903 lesions) were enrolled from the Second Hospital of Shandong University (known as "Center 1") between January 2015 to December 2022. They were allocated to the training set (626 cases/632 lesions) and the internal validation set (269 cases/271 lesions). The external validation set included 100 patients (100 lesio

SUBMITTER: Zhao S 

PROVIDER: S-EPMC11652052 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature