Progress of MRI-based artificial intelligence technology in evaluating the response to neoadjuvant chemotherapy for breast cancer
WANG Mengyao
ZHANG Xueli
TANG Xiangbing
YANG Zhihao
ZHAO Ming
Abstract：Breast cancer remains one of the leading causes of cancer-related mortality among women worldwide.Neoadjuvant chemotherapy(NAC)has become an essential component of contemporary breast cancer treatment.However,conventional methods for assessing NAC efficacy are often limited by subjectivity and suboptimal accuracy,underscoring the urgent need for more objective and reliable evaluation strategies.In recent years,AI,particularly radiomics and deep learning,has driven significant advances in medical imaging analysis.MRI-based radiomics combined with DL has demonstrated the ability to extract high-dimensional features from imaging data that are invisible to the human eye.These features can capture subtle microstructural alterations within tumors,characterize biological phenotypes,and quantify intratumoral heterogeneity,thereby substantially improving the precision of treatment response evaluation.This review highlights recent progress in the application of MRI-based AI technologies for predicting NAC response in breast cancer,aiming to facilitate the translation of these techniques from theory to clinical practice and to provide a scientific foundation for advancing precision and personalized oncology care.
Keywords：radiomicsdeep learningbreast cancerneoadjuvant chemotherapymagnetic resonance imaging
Publication Date：2025-11-20
Online Publishing Date：2025-12-16(First online date of this platform, not the publication date of the document)
Pages：7( 1439-1445 )