Acupuncture is effective for the management and treatment of pain related diseases. At present, the patients'subjective evaluations were often used to measure the effect of acupuncture analgesia in clinical research, but it lacks objectivity and accuracy. In recent years, some studies had tried to analyze the magnetic resonance images of patients' brains using magne-tic resonance imaging and machine learning methods before and after acupuncture intervention, so as to identify specific neural markers. These markers not only helped explain the brain mechanism of acupuncture analgesia, but also provided objective indicators for the analgesic effect of acupuncture. This article analyzes the significance and feasibility of pain biomarkers research based on magnetic resonance imaging and machine learning technology, summarizes its research status in acupuncture analgesia, and makes suggestions in the future study.
针刺治疗疼痛类疾病疗效显著，患者的主观评价是目前临床研究中衡量针刺镇痛效果的常用标准，但缺乏客观性和精准性。近年来，有研究尝试应用磁共振成像和机器学习方法，分析针刺治疗前后患者大脑的磁共振影像，识别具有特异性的神经标志物。这些标志物不仅有助于阐释针刺镇痛的脑机制，且有望发展为研究针刺镇痛效应的客观指标。本文从基于磁共振成像和机器学习技术的疼痛生物标志物的研究意义和可行性分析切入，总结其在针刺镇痛领域的研究现状，并对目前研究中存在的相关问题提出建议。.
Keywords: Acupuncture analgesia; Biomarker; Machine learning; Magnetic resonance imaging.