Are Magnetic Resonance Imaging Technologies Crucial to Our Understanding of Spinal Conditions?
Are Magnetic Resonance Imaging Technologies Crucial to Our Understanding of Spinal Conditions?
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DOI：
10.2519/jospt.2019.8793
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发表时间：
2019-05-01
影响因子：
6.1
通讯作者：
Elliott, James M.
中科院分区：
文献类型：
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作者：
Crawford, Rebecca J.;Fortin, Maryse;Elliott, James M.
持续的脊柱（创伤性和非创伤性）疼痛是常见的，并在全球范围内造成了高昂的社会和个人成本。人们公认迫切需要新的跨学科方法来治疗这种疾病，软组织，包括骨骼肌、脊髓和大脑，作为重要的生物学贡献者，正受到越来越多的关注。为了回应最近对基于成像的发现的怀疑和质疑价值，本文旨在认识到成像技术的技术发展，特别是磁共振成像，正在允许表征以前不太可见的形态。我们强调量化的价值和数据分析的几个贡献者在生物心理社会模型的理解脊柱疼痛。此外，我们强调了有关肌肉成分变化（如萎缩、脂肪浸润）的病理生物学的新证据，以及这些重要软组织的神经成像和肌肉骨骼成像技术（如脂肪水成像、功能磁共振成像、扩散成像、磁化转移成像）的进展。这些非侵入性和客观的数据来源可以补充已知的预后因素，如恢复不良、患者自我报告、诊断测试和“组学”领域。结合起来，先进的“大数据”分析可以帮助识别以前没有考虑到的关联。我们的临床评论得到了实证研究结果的支持，这可能会使未来的努力朝着协作对话、假设生成、跨学科研究和跨多个健康领域的翻译方向发展。我们的重点是，磁共振成像技术和研究是至关重要的进步，我们的理解脊柱条件的复杂性。
Persistent spinal (traumatic and nontraumatic) pain is common and contributes to high societal and personal costs globally. There is an acknowledged urgency for new and interdisciplinary approaches to the condition, and soft tissues, including skeletal muscles, the spinal cord, and the brain, are rightly receiving increased attention as important biological contributors. In reaction to the recent suspicion and questioned value of imaging-based findings, this paper serves to recognize the promise that the technological evolution of imaging techniques, and particularly magnetic resonance imaging, is allowing in characterizing previously less visible morphology. We emphasize the value of quantification and data analysis of several contributors in the biopsychosocial model for understanding spinal pain. Further, we highlight emerging evidence regarding the pathobiology of changes to muscle composition (eg, atrophy, fatty infiltration), as well as advancements in neuroimaging and musculoskeletal imaging techniques (eg, fat-water imaging, functional magnetic resonance imaging, diffusion imaging, magnetization transfer imaging) for these important soft tissues. These noninvasive and objective data sources may complement known prognostic factors of poor recovery, patient self-report, diagnostic tests, and the "-omics" fields. When combined, advanced "big-data" analyses may assist in identifying associations previously not considered. Our clinical commentary is supported by empirical findings that may orient future efforts toward collaborative conversation, hypothesis generation, interdisciplinary research, and translation across a number of health fields. Our emphasis is that magnetic resonance imaging technologies and research are crucial to the advancement of our understanding of the complexities of spinal conditions.