人工智能驱动的代谢功能障碍相关脂肪性肝炎病理量化与精准评估进展

摘要/Abstract

摘要： 代谢功能障碍相关脂肪性肝炎(MASH)已成为全球肝病相关死亡的重要原因,其发病率持续上升,对全球公共健康构成严重威胁。肝活检病理是MASH诊断与分期的金标准,在评估肝纤维化进展方面至关重要。近年来,人工智能(AI)技术在病理领域快速发展,视觉-语言大模型等多模态AI系统显著提高了肝脏病理的连续化量化、一致性与预测能力,能够提供客观、标准化、可追踪的诊断和疗效评估。主流AI系统如AI-based histologic measurement of NASH(AIM-MASH)、FibroNest、MorphoQuant和HistoIndex等,在脂肪变性、炎症及纤维化等关键病理特征的量化分析中展现出明显优势,有效克服了传统人工判读具有主观性和结果异质性的不足。然而,当前AI在MASH病理领域的应用仍面临标准化、数据整合和临床相关性验证等挑战。未来需加强技术与平台标准统一、多模态信息整合及前瞻性临床研究,不断完善AI模型的个体化风险预测能力。总体来看,AI驱动的病理量化分析正在推动MASH精准诊疗的发展,有望提升肝脏疾病的管理水平与改善远期预后。

张岑, 赵新颜. 人工智能驱动的代谢功能障碍相关脂肪性肝炎病理量化与精准评估进展[J]. 肝脏, 2025, 30(11): 1451-1454.

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