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对纤维化进行非侵入性评估技术:进展和前景

Yumeng Tang¹, Yixi Ke², Hualin Ma³

¹Department of Nephrology, Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, Shenzhen, Guangdong, China.

|October 12, 2025

概括

非侵入性方法,包括先进的成像和人工智能 (AI),在检测纤维化方面表现有前途. 这些方法旨在改善慢性病 (CKD) 的早期诊断和管理.

科学领域:

腎臟病學 (nephrology) 是一種醫學專業.
生物医学成像技术生物医学成像技术
人工智能的人工智能

背景情况:

纤维化是慢性病 (CKD) 和末期病 (ESRD) 的关键驱动因素.
传统的脏活检是侵入性的,限制了早期检测和干预.
非侵入性技术对于准确和及时评估纤维化至关重要.

研究的目的:

审查纤维化检测的非侵入性方法的最新进展.
突出人工智能 (AI) 在提高诊断准确性的潜力.
讨论非侵入性纤维化评估的挑战和未来方向.

主要方法:

探索非侵入性生物标志物 (例如TGF-β1,PDGF-D) 的研究.
评估新兴的分子和功能成像技术.
应用人工智能和机器学习算法来整合多模式数据 (临床,成像,生物标志物).

主要成果:

与成像 (超声波,CT,MRI) 集成的AI显示了纤维化预测能力的改善.
由人工智能驱动的多式联通方法提供了增强的非侵入性诊断和监测潜力.
现有的非侵入性生物标志物和成像技术在特异性和早期检测方面面临挑战.

结论:

非侵入性技术,特别是人工智能驱动的多模式策略,对早期纤维化检测和CKD管理具有重大潜力.
需要进一步的研究来应对诸如小样本大小,标准化和AI可解释性等挑战.
非侵入性方法的进步可以改善临床决策和CKD患者的结果.

关键词:

纤维化纤维化纤维化人工智能的人工智能是人工智能.生物标志物生物标志物活组织活检诊断成像诊断成像的使用.脏脏脏是什么?

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