Four-Dimensional Machine Learning Radiomics for the Pretreatment Assessment of Breast Cancer Pathologic Complete Response to Neoadjuvant Chemotherapy in Dynamic Contrast-Enhanced MRI.

ABSTRACT:

Background

Breast cancer response to neoadjuvant chemotherapy (NAC) is typically evaluated through the assessment of tumor size reduction after a few cycles of NAC. In case of treatment ineffectiveness, this results in the patient suffering potentially severe secondary effects without achieving any actual benefit.

Purpose

To identify patients achieving pathologic complete response (pCR) after NAC by spatio-temporal radiomic analysis of dynamic contrast-enhanced (DCE) MRI images acquired before treatment.

Study type

Single-center, retrospective.

Population

A total of 251 DCE-MRI pretreatment images of breast cancer patients.

Field strength/sequence

1.5 T/3 T, T1-weighted DCE-MRI.

Assessment

Tumor and peritumoral regions were segmented, and 348 radi

SUBMITTER: Caballo M 

PROVIDER: S-EPMC10083908 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature