机器学习基于MRI预测乳腺癌对新辅助化疗反应的研究进展

Research progress of machine learning for predicting breast cancer response to neoadjuvant chemotherapy based on MRI

新辅助化疗(neoadjuvant chemotherapy,NAC)是乳腺癌治疗方案中的重要组成部分。乳腺癌经NAC后会出现不同程度的缓解,准确的疗效预估手段有助于治疗方案的调整和术式的选择,能够使患者最大限度地受益。机器学习(machine learning,ML)可以提取MR图像的高通量信息反映肿瘤的异质性,在NAC早期甚至是治疗前预测肿瘤的反应。本文就ML结合乳腺MRI预判NAC疗效的研究进展予以综述。

Neoadjuvant chemotherapy(NAC) is the essential component of breast cancer treatment plan.Breast cancer will show varying degrees of remission after NAC.An accurate method of efficacy prognosis can help in the adjustment of treatment plan and the selection of surgical modality that can benefit patients to the maximum extent.Machine learning(ML) can extract high-throughput information from MR images to reflect tumor heterogeneity and predict tumor response early in NAC or even before therapy.This article reviews the progress of research on ML combined with breast MRI to predict the efficacy of NAC.