[Applications and challenges of pathomics technique in the management of hepatocellular carcinoma]

Zhonghua Wai Ke Za Zhi. 2024 Jul 1;62(7):665-670. doi: 10.3760/cma.j.cn112139-20240103-00003.
[Article in Chinese]

Abstract

The incidence and mortality rate of hepatocellular carcinoma rank among the top of all cancer types,seriously threatening the life and health of human beings. In recent years,the rapid development of artificial intelligence and the deepening of the concept of precision medicine have led to a boom in interdisciplinary research. Pathomics,as an emerging omics technology driven by artificial intelligence,can mine massive information from high-resolution whole slide images,and shows broad application prospects in the diagnosis,treatment and prognosis assessment of hepatocellular carcinoma. However, pathomics research in hepatocellular carcinoma is still in its infancy, and its research patterns and clinical applications still face several controversies and challenges, including data security, ethics, and "black box" issues. Future research should focus on conducting prospective studies, integrating multimodal data, improving computational technologies, and establishing professional standards to promote the high-quality development of pathomics technology in both clinical and basic research of hepatocellular carcinoma.

肝癌的发病率和死亡率在众多癌种中的排名均居前列,严重威胁人类的生命和健康。近年来,人工智能的飞速发展和精准医学理念的深化,使得医工融合研究呈现井喷趋势。病理组学作为一种人工智能驱动的新兴组学技术,可从高分辨率的全视野病理学图像中挖掘海量信息,在肝癌的诊断、治疗和预后评估等方面都展现出了广阔的应用前景。然而,肝癌的病理组学研究尚处于起步阶段,其科研范式及临床实际应用仍存在数据安全、伦理、“黑箱”问题等诸多争议和挑战。未来的研究应聚力开展前瞻性研究、整合多模态数据、改善计算性能以及制定行业标准,从而让病理组学技术更好地助力肝癌的精准诊疗。.

Publication types

  • English Abstract

MeSH terms

  • Artificial Intelligence
  • Carcinoma, Hepatocellular* / diagnosis
  • Carcinoma, Hepatocellular* / therapy
  • Humans
  • Liver Neoplasms* / diagnosis
  • Liver Neoplasms* / therapy
  • Precision Medicine
  • Prognosis