Radiomics model to classify mammary masses using breast DCE-MRI compared to the BI-RADS classification performance.

ABSTRACT:

Background

Recent advanced in radiomics analysis could help to identify breast cancer among benign mammary masses. The aim was to create a radiomics signature using breast DCE-MRI extracted features to classify tumors and to compare the performances with the BI-RADS classification.

Material and methods

From September 2017 to December 2019 images, exams and records from consecutive patients with mammary masses on breast DCE-MRI and available histology from one center were retrospectively reviewed (79 patients, 97 masses). Exclusion criterion was malignant uncertainty. The tumors were split in a train-set (70%) and a test-set (30%). From 14 kinetics maps, 89 radiomics features were extracted, for a total of 1246 features per tumor. Feature selection was made using Boruta algor

SUBMITTER: Debbi K 

PROVIDER: S-EPMC10102264 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature