肝癌病理学的进展和挑战:从诊断到预后分层
Ming-Hui Peng1, Kai-Lun Zhang1, Shi-Wei Guan1
1Department of Hepatobiliary Surgery, The Dingli Clinical Institute of Wenzhou Medical University (Wenzhou Central Hospital), Wenzhou 325000, Zhejiang Province, China.
World journal of clinical oncology
|June 30, 2025
概括
人工智能 (AI) 病理学分析病理图像,以改善肝细胞癌 (HCC) 诊断和治疗. 人工智能增强了瘤分类,复发预测和肝癌的个性化治疗方法.
科学领域:
- 计算病理学计算病理学
- 人工智能在瘤学中的应用
- 数字病理学数字病理学
背景情况:
- 由于其复杂性,肝细胞癌 (HCC) 存在诊断和治疗方面的挑战.
- 病理学,结合AI和定量病理学,从组织图像解码疾病异质性.
研究的目的:
- 审查人工智能驱动的病理学在肝癌管理中的应用.
- 为突出 HCC.全幻灯片图像自动化分析的进步.
主要方法:
- 人工智能和深度学习应用于组织病理特征.
- 整张幻灯片图像的定量分析.
- 整合多组学数据与形态学图案.
主要成果:
- 人工智能使得精确的瘤分类,微血管入侵 (MVI) 检测和生存预测.
- 像MVI-AI和CHOWDER这样的框架显示出预后生物标志物的高准确性.
- 多组学集成将图像特征与分子签名联系起来,例如EZH2表达.
结论:
- 人工智能病理学彻底改变了肝癌管理,提供了精确的诊断和风险分层.
- 挑战包括验证,解释性和临床整合.
- 未来的方向包括多式联接和标准化平台,用于个性化瘤学.
关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.数字病理学数字病理学肝癌是一种肝癌.微血管侵袭是一种微血管侵袭.多种omics集成的整合.病理学是一种病理学.预测生物标志物预测生物标志物瘤复发的情况整个幻灯片成像成像技术更多相关视频
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