Research progress of radiomics and deep learning in predicting Ki-67 expression in breast cancer
YANG Xuanying
WANG Yu
WANG Xingyue
JIA Yongmei
HU Yang
OU Hongping
Abstract：The Ki-67 index in breast cancer reflects the proliferative activity of tumor cells.High Ki-67 expression indicates greater proliferative activity,increased invasiveness,higher recurrence risk,and poorer prognosis.Therefore,Ki-67 expression status is essential for molecular subtyping,assessment of treatment efficacy,and prognosis prediction in breast cancer.Radiomics and deep learning have become prominent approaches in intelligent medical imaging,enabling comprehensive,non-invasive,and dynamic assessment of Ki-67 expression in breast cancer by extracting high-throughput imaging features that reflect tumor heterogeneity.This review summarizes recent progress in applying radiomics and deep learning to predict Ki-67 expression status in breast cancer.
Keywords：breast cancerKi-67radiomicsdeep learning
Publication Date：2025-10-20
Online Publishing Date：2025-11-24(First online date of this platform, not the publication date of the document)
Pages：5( 1309-1313 )