医学
腰椎
肌肉萎缩
背部肌肉
腰椎
解剖
物理医学与康复
放射科
外科
骨骼肌
作者
Wei Wang,Weishi Li,Zhongqiang Chen
出处
期刊:PubMed
日期:2020-11-15
卷期号:34 (11): 1462-1467
标识
DOI:10.7507/1002-1892.201912120
摘要
To review the evaluation method of paraspinal muscle and its role in lumbar spine diseases, and offer reference for further research on paraspinal muscles.The related literature of paraspinal muscle measurement and its role in lumbar spine diseases was reviewed. The evaluation methods of paraspinal muscle were analyzed from the advantages and disadvantages and the role of paraspinal muscle in lumbar spine diseases was summarized.Radiographic methods are often used to evaluate the atrophy of paraspinal muscle, mainly including CT and MRI. The cross-sectional area and fatty infiltration of paraspinal muscle are two key parameters. Radiographic methods are reproducible and widely applied, but CT has the disadvantage of radiation exposure, while the cost of MRI is high. Besides, more and more researchers focus on the functional evaluation of paraspinal muscle, which mainly includes surface electromyogram analysis and back muscle strength test. The surface electromyogram analysis can quantitatively measure neuromuscular function, but the results could be affected by many influencing factors. The back muscle strength test is simple, but it lacks standardized posture. The atrophy of paraspinal muscle is related to many lumbar spine diseases, while the results of different researches are different.There are many methods to evaluate paraspinal muscles, but there is no unified standard. The role of paraspinal muscle in lumbar spine diseases need to be further studied.对椎旁肌评价方法及其与腰椎疾病发生发展的关系进行综述,为进一步开展椎旁肌相关研究提供参考。.广泛查阅国内外关于椎旁肌评价方法及椎旁肌在腰椎疾病中作用的相关文献,对常用的椎旁肌评价方法优点和局限性、椎旁肌与腰椎疾病的关系等方面进行总结。.临床常用 CT、MRI 评估椎旁肌退变,检测指标包括椎旁肌横截面积及脂肪浸润程度。影像学测量方法可重复性好,但是 CT 存在辐射暴露缺点,MRI 花费较高。此外,椎旁肌功能也逐渐得到学者关注,主要评价方法有表面肌电信号分析以及腰背肌力量测试。表面肌电信号分析能够定量反映神经肌肉功能,但是测量结果影响因素较多;腰背肌力量测试简单,但缺乏标准化动作。研究表明椎旁肌退变与多种腰椎疾病相关,但不同研究结果之间存在差异。.椎旁肌评价方法多样,但缺乏统一标准,椎旁肌退变对腰椎疾病的影响有待进一步研究。.
科研通智能强力驱动
Strongly Powered by AbleSci AI