首页|基于深度学习的计算病理学在结直肠癌预后预测和疗效评估中的研究进展

基于深度学习的计算病理学在结直肠癌预后预测和疗效评估中的研究进展

Research progress on deep learning-based computational pathology in prognostic prediction and therapeutic response evaluation of colorectal cancer

扫码查看
结直肠癌是最常见的恶性肿瘤之一,已严重威胁人们的生命健康.目前临床上以肿瘤淋巴结转移(TNM)分期系统作为结直肠癌风险分层和预后预测的主要参考标准,但具有相同病理分期患者间的预后仍有较大差异.因此,迫切需要更加精准的预后预测模型.计算病理学是借助计算机和人工智能(AI)分析组织病理学图像的新领域.AI可以对组织病理学图像进行全面、定量的分析,在结直肠癌的预后预测中显示出重要的价值和潜力.本文对计算病理学在结直肠癌预后预测和疗效评估中的应用进行综述,并总结了该技术在预后预测过程中存在的问题以及未来的发展方向.
Colorectal cancer is one of the most common malignant tumors and has become a serious threat to people's lives and health.The clinics currently use the tumor-lymph node-metastasis(TNM)staging system as the main reference standard for risk stratification and prognostic prediction in colorectal cancer,but there are still large differences in prognosis between patients with the same pathologic stage.Therefore,there is an urgent need for more accurate prognostic prediction models.Computational pathology is a new field that utilizes computers and artificial intelligence(AI)to analyze histopathological images.AI enables comprehensive and quantitative analysis of histopathological images,which shows significant value and potential in prognostic prediction of colorectal cancer.This article reviews the application of computational pathology in prognostic prediction and therapeutic response evaluation of colorectal cancer,and summarizes the problems of this technique in the prognostic prediction process as well as the future development direction.

computational pathologydeep learningcolorectal cancerprognostic predictiontherapeutic response evaluation

陆艺展、周学志

展开 >

新乡医学院医学工程学院智能医学工程教研室,河南 新乡 453003

河南省神经传感与控制工程研究中心,河南 新乡 453003

计算病理学 深度学习 结直肠癌 预后预测 疗效评估

国家自然科学基金资助项目河南省科技攻关项目

82302298232102310009

2024

新乡医学院学报
新乡医学院

新乡医学院学报

CSTPCD
影响因子:0.999
ISSN:1004-7239
年,卷(期):2024.41(7)