Machine-learning methods based on the texture and non-texture features of MRI for the preoperative prediction of sentinel lymph node metastasis in breast cancer.

ABSTRACT:

Background

The establishment of an accurate, stable, and non-invasive prediction model of sentinel lymph node (SLN) metastasis in breast cancer is difficult nowadays. The aim of this work is to identify the optimal machine learning model based on the three-dimensional (3D) image features of magnetic resonance imaging (MRI) for the preoperative prediction of SLN metastasis in breast cancer patients.

Methods

A total of 172 patients with histologically proven breast cancer were enrolled retrospectively, including 74 SLN metastasis patients and 98 non-SLN metastasis patients. All of them underwent diffusion-weighted imaging (DWI) magnetic resonance imaging (MRI) scan. Firstly, a total of 10,320 texture and four non-texture features were extracted from the region of interests (RO

SUBMITTER: Wang J 

PROVIDER: S-EPMC10774029 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature