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静息态功能磁共振在轻微型肝性脑病机制及智能诊断中的研究进展

姜茂 李文博 樊丽华 杨紫媛 郑运松

分子影像学杂志2026,Vol.49Issue(4):549-556,8.
分子影像学杂志2026,Vol.49Issue(4):549-556,8.DOI:10.12122/j.issn.1674-4500.2026.04.19

静息态功能磁共振在轻微型肝性脑病机制及智能诊断中的研究进展

Research progress on resting-state functional magnetic resonance imaging in the mechanisms and intelligent diagnosis of minimal hepatic encephalopathy

姜茂 1李文博 1樊丽华 2杨紫媛 1郑运松3

作者信息

  • 1. 陕西中医药大学医学技术学院,陕西 咸阳 712046
  • 2. 陕西中医药大学附属医院医学影像科,陕西 咸阳 712000
  • 3. 陕西中医药大学医学技术学院,陕西 咸阳 712046||陕西中医药大学附属医院医学影像科,陕西 咸阳 712000
  • 折叠

摘要

Abstract

Minimal hepatic encephalopathy(MHE),as the early occult stage of hepatic encephalopathy,often presents with unremarkable clinical manifestations and routine blood biochemical parameters.Its diagnosis primarily relies on neurophysiological or neuropsychological tests.Without timely intervention,MHE can progress to overt hepatic encephalopathy,significantly impairing patients'quality of life.In recent years,resting-state functional magnetic resonance imaging(rs-fMRI),with its non-invasive and precise advantages,has provided crucial neuroimaging tools for unraveling the neural mechanisms of MHE.However,existing reviews have predominantly focus on the conventional applications of rs-fMRI in MHE,lacking a systematic synthesis of multi-dimensional brain functional metrics and their integration with artificial intelligence techniques.This review systematically summarizes the latest advancements in utilizing rs-fMRI-based brain functional metrics to investigate the mechanisms of cognitive impairment in MHE.It first elucidates the neuropathological basis of MHE from the perspective of functional connectivity abnormalities,particularly within networks such as the default mode network and the executive control network.Building on this foundation,it further synthesizes the progress in model construction and validation for intelligent MHE diagnosis using machine learning and deep learning methods(e.g.,support vector machines and graph neural networks).Furthermore,it explores the emerging trend of integrating multimodal imaging with artificial intelligence,addressing the gaps present in previous reviews.This article aims to provide a systematic imaging basis for elucidating the neural mechanisms of MHE and to offer new research directions for achieving quantitative and precise diagnosis of MHE.Future research endeavors should focus on multi-center,large-sample validation,multimodal data fusion,and in-depth exploration of pathways for clinical translation.

关键词

轻微型肝性脑病/静息态功能磁共振/肝硬化/人工智能

Key words

minimal hepatic encephalopathy/resting-state functional magnetic resonance imaging/cirrhosis/artificial intelligence

引用本文复制引用

姜茂,李文博,樊丽华,杨紫媛,郑运松..静息态功能磁共振在轻微型肝性脑病机制及智能诊断中的研究进展[J].分子影像学杂志,2026,49(4):549-556,8.

基金项目

陕西省科学技术厅陕西省重点研发计划项目(2024SF-YBXM-524) (2024SF-YBXM-524)

陕西中医药大学研究生质量提升工程专项研究生创新实践能力提升项目(CXSJ202526) (CXSJ202526)

咸阳市科技局重点研发计划项目(S2025-ZDYF-JBFZ-4274) (S2025-ZDYF-JBFZ-4274)

分子影像学杂志

1674-4500

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