Radiomic Analysis of Contrast-Enhanced Mammography With Different Image Types: Classification of Breast Lesions.

ABSTRACT: Objective: A limited number of studies have focused on the radiomic analysis of contrast-enhanced mammography (CEM). We aimed to construct several radiomics-based models of CEM for classifying benign and malignant breast lesions. Materials and Methods: The retrospective, double-center study included women who underwent CEM between November 2013 and February 2020. Radiomic analysis was performed using high-energy (HE), low-energy (LE), and dual-energy subtraction (DES) images from CEM. Datasets were randomly divided into the training and testing sets at a ratio of 7:3. The maximum relevance minimum redundancy (mRMR) method and least absolute shrinkage and selection operator (LASSO) logistic regression were used to select the radiomic features and construct the best classificat

SUBMITTER: Wang S 

PROVIDER: S-EPMC8195270 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature