Research Progress on Multiparametric Magnetic Resonance Imaging in the Staging of Liver Fibrosis

肝纤维化是肝脏慢性损伤后的常见病理修复反应，若未能及时干预，可能恶化为肝硬化甚至肝癌。多参数磁共振联合成像(mpMRI)整合多种磁共振技术(如DWI、DCE、MRE等)，从形态、功能、代谢等多维度评估肝脏病理变化，显著提升了肝纤维化分期的客观性和准确性。结合深度学习等人工智能技术，可高效挖掘影像组学特征，增强早期隐匿性病变的识别效能，然而，当前该技术仍面临数据标准化不足、处理流程复杂及成本高等挑战。未来需通过临床多中心研究制定指南及标准，优化算法并降低成本，推动其临床应用。Liver fibrosis is a common pathological repair response following chronic liver damage. If not intervened in a timely manner, it may progress to cirrhosis and even liver cancer. Multiparametric magnetic resonance imaging (mpMRI) integrates various MRI techniques (such as DWI, DCE, MRE, etc.) to reflect and assess liver pathological changes from multiple dimensions, including morphology, function, and metabolism, significantly enhancing the objectivity and accuracy of liver fibrosis staging. When combined with artificial intelligence technologies like deep learning, it can efficiently extract imaging features and improve the detection efficacy of early concealed lesions, further enhancing early diagnostic capabilities. However, this technology currently faces challenges such as insufficient data standardization, complex data processing workflows, and high costs. Future efforts should focus on multi-center clinical studies to establish guidelines and standards, optimize algorithms, and reduce costs to promote its clinical application.