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人工智能在胃癌病理学中的应用

英文原题:Artificial Intelligence in the Pathology of Gastric Cancer.

查看英文原题

Artificial Intelligence in the Pathology of Gastric Cancer.

PubMed 2023/07/01(内容时间) J Gastric Cancer Q1 · IF 5.1(JCR 2025)

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中文摘要

近年来,人工智能(AI)的进展为快速、精准的病理诊断提供了新型工具。数字病理学的引入使得获取扫描切片图像成为可能,而这些图像对于AI的应用至关重要。AI在改进病理诊断方面的应用包括:对可能被忽略的微小病灶进行无差错检测,例如淋巴结中微小转移肿瘤细胞灶;对可能存有争议的组织学表现进行准确诊断,例如酷似正常上皮组织的高分化癌;以及对癌症进行病理亚型分类。

此外,利用AI算法能够精确判定靶向治疗相关免疫组化标志物的评分,例如人表皮生长因子受体2和程序性死亡配体1。研究表明,AI辅助可减少病理学家之间判读的不一致性,并更准确地预测临床结局。已有多种方法被用于利用AI从组织学图像中开发新型生物标志物。

此外,AI辅助的癌症微环境分析显示,TIL(肿瘤浸润淋巴细胞)的分布与免疫检查点抑制剂治疗的应答相关,强调了其作为生物标志物的价值。随着大量研究证实AI辅助判读和生物标志物开发的重要意义,基于AI的方法将推动诊断病理学的发展。

展开英文摘要原文

Recent advances in artificial intelligence (AI) have provided novel tools for rapid and precise pathologic diagnosis. The introduction of digital pathology has enabled the acquisition of scanned slide images that are essential for the application of AI.

The application of AI for improved pathologic diagnosis includes the error-free detection of potentially negligible lesions, such as a minute focus of metastatic tumor cells in lymph nodes, the accurate diagnosis of potentially controversial histologic findings, such as very well-differentiated carcinomas mimicking normal epithelial tissues, and the pathological subtyping of the cancers.

Additionally, the utilization of AI algorithms enables the precise decision of the score of immunohistochemical markers for targeted therapies, such as human epidermal growth factor receptor 2 and programmed death-ligand 1. Studies have revealed that AI assistance can reduce the discordance of interpretation between pathologists and more accurately predict clinical outcomes. Several approaches have been employed to develop novel biomarkers from histologic images using AI.

Moreover, AI-assisted analysis of the cancer microenvironment showed that the distribution of tumor-infiltrating lymphocytes was related to the response to the immune checkpoint inhibitor therapy, emphasizing its value as a biomarker. As numerous studies have demonstrated the significance of AI-assisted interpretation and biomarker development, the AI-based approach will advance diagnostic pathology.

论文信息

作者
Choi S、Kim S
第一作者单位
Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.South Korea
通讯作者单位
Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea. seokhwikim@ajou.ac.kr.South Korea
文献类型
综述
期刊
Journal of gastric cancer2023 Jul
原文标识
PubMed 37553129 · DOI 10.5230/jgc.2023.23.e25