肝纤维化逆转的临床评估：基于组织学、血清学与影像学的多模态精准策略

刘逸舟; 姜倩楠; 尤红; 吴晓宁

doi:10.12449/JCH260727

肝纤维化逆转的临床评估：基于组织学、血清学与影像学的多模态精准策略

DOI: 10.12449/JCH260727

首都医科大学附属北京友谊医院肝病中心，北京 100050

基金项目:

“十四五”国家重点研发计划病原学与防疫技术体系研究专项 (2023YFC2306900)

利益冲突声明：本文不存在任何利益冲突。

作者贡献声明：刘逸舟负责文章撰写；姜倩楠负责资料收集；尤红负责论文审阅；吴晓宁负责论文修改。

详细信息

通信作者:
吴晓宁， wuxiaoningbs@126.com （ORCID： 0000-0001-5416-712X）

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出版历程
- 收稿日期: 2025-11-17
- 录用日期: 2026-02-11
- 出版日期: 2026-07-25

Clinical evaluation of liver fibrosis regression: A multimodal precision strategy based on histology, serology, and imaging

Liver Research Center，Beijing Friendship Hospital，Capital Medical University，Beijing 100050，China

Research funding:

Special Project of Pathogenology and Epidemic Prevention Technology System Research under the National Key R&D Program during the 14th Five-Year Plan Period (2023YFC2306900)

More Information

Corresponding author: Wu Xiaoning， wuxiaoningbs@126.com （ORCID： 0000-0001-5416-712X）

摘要

摘要: 肝纤维化是慢性肝病进展至肝硬化的关键病理阶段，在有效病因控制或治疗干预后，部分肝纤维化可发生不同程度的逆转。如何准确评估肝纤维化的逆转程度，逐渐成为临床管理及新药研发中关注的重要问题。传统评估方法多侧重于纤维化分期，在反映组织结构重塑及动态变化方面仍存在一定局限。本文系统综述了近年来肝纤维化逆转评估的研究进展，重点从组织学与数字病理、血清学及多组学标志物、功能与分子影像学等多个维度，分析其在逆转评估中的优势与局限。在此基础上，探讨基于人工智能的多模态整合评估策略，以期为肝纤维化逆转的精准评估、个体化治疗监测及临床试验终点优化提供新的思路。
- 肝纤维化 /
- 组织学 /
- 血清学 /
- 影像学
Abstract: Liver fibrosis is a key pathological stage in the progression of chronic liver diseases to liver cirrhosis， and effective etiological control or therapeutic interventions can help to achieve varying degrees of liver fibrosis regression in some patients. Accordingly， accurate assessment of the degree of liver fibrosis regression has gradually become an important concern in clinical management and the development of novel therapeutic agents. Conventional assessment methods mainly focus on fibrosis staging and have certain limitations in reflecting structural remodeling and dynamic changes of the liver. This article systematically reviews the recent research advances in the assessment of liver fibrosis regression from various aspects such as histological and digital pathology， serological and multi-omics biomarkers， and functional and molecular imaging modalities and discusses their respective advantages and limitations in assessing liver fibrosis regression. On this basis， this article discusses a multimodal integrated evaluation strategy based on artificial intelligence， in order to provide new ideas for accurate assessment of liver fibrosis regression， individualized therapeutic monitoring， and optimization of clinical trial endpoints.
- Hepatic Fibrosis /
- Histology /
- Serology /
- Imaging

HTML全文

注： PIR，进展型、不确定型和逆转型分类；SHG/TPEF，双光子荧光显微技术；M2BP，紫藤凝集素阳性Mac-2结合蛋白；CHI3L1，壳多糖酶3样蛋白1；APRI，天冬氨酸氨基转移酶与血小板比值指数；FIB-4，纤维化-4指数；LSM，肝硬度值；MRE，磁共振弹性成像；FAPI-PET，成纤维细胞激活蛋白抑制剂正电子发射断层扫描；AI，人工智能。

图 1 多模态联合评估肝纤维化逆转

Figure 1. Multimodal joint evaluation of liver fibrosis reversal

下载: 全尺寸图片幻灯片

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