Machine learning prediction of axillary lymph node metastasis in breast cancer: 2D versus 3D radiomic features.

ABSTRACT:

Purpose

The purpose of this study was to distinguish axillary lymph node (ALN) status using preoperative breast DCE-MRI radiomics and compare the effects of two-dimensional (2D) and three-dimensional (3D) analysis.

Methods

A retrospective study including 154 breast cancer patients all confirmed by pathology; 80 with ALN metastasis and 74 without. All MRI scans were achieved at a 3.0 Tesla scanner with 7 post-contrast MR phases sequentially acquired with a temporal resolution of 60 s. MRI radiomic features were extracted separately from a 2D single slice (i.e., the representative slice) and the 3D tumor volume. Several machine learning classifiers were built and compared using 2D or 3D analysis to distinguish positive vs negative ALN status. We performed independent test and

SUBMITTER: Arefan D 

PROVIDER: S-EPMC8581816 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature