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脊柱畸形的影像学参数测量及其研究进展
牛升波△,杨桓△,杨明园,陈锴,李明*
0
(海军军医大学(第二军医大学)长海医院骨科, 上海 200433
共同第一作者
*通信作者)
摘要:
脊柱畸形是一种复杂的三维畸形,其相关影像学测量对疾病的诊断分型、治疗选择、疗效评估和进展监测有重要意义。随着科学技术的发展与脊柱畸形研究的不断深入,传统脊柱畸形测量方法与放射成像技术不断改进,EOS影像系统和三维超声成像技术应用于脊柱畸形测量的可行性与有效性已被诸多研究证实,新的测量工具、测量技术及人工智能的应用初见端倪。这些技术共同推动脊柱畸形测量朝着简单安全、高效精准、便于临床推广应用的方向发展。本文在回顾当前脊柱畸形影像学参数测量研究进展的基础上,分析各种测量手段的优势与局限,以期为临床应用与研究选择合适的测量方法提供借鉴。
关键词:  脊柱侧凸  Cobb角  X线放射摄影术  EOS影像系统  三维超声成像  体表形态  人工智能
DOI:10.16781/j.0258-879x.2020.11.1177
投稿时间:2020-01-17修订日期:2020-02-13
基金项目:国家自然科学基金(31870985).
Imaging parameter measurement of spinal deformity: research progress
NIU Sheng-bo△,YANG Huan△,YANG Ming-yuan,CHEN Kai,LI Ming*
(Department of Orthopaedics, Changhai Hospital, Naval Medical University(Second Military Medical University), Shanghai 200433, China
Co-first authors.
* Corresponding author)
Abstract:
Spinal deformity is a complex three-dimensional malformation. The related imaging measurements are vital to its diagnosis and classification, treatment selection, efficacy evaluation and progress monitoring. With the development of science and technology and the deepening of research on spinal deformity, conventional deformity measurement methods and radiographic imaging techniques have been continually improved. The feasibility and effectiveness of the application of EOS imaging system and three-dimensional ultrasound imaging technology in spinal deformity have been confirmed by many studies, and the application of new measurement tools, techniques and artificial intelligence is also emerging. These technologies jointly promote the development of the spinal deformity measurement, making it more simple, safe, efficient and accurate, and convenient for clinical application. In this paper, based on the review of the current research progress in the imaging parameter measurement of spinal deformity, the advantages and limitations are analyzed in order to provide references for clinical application and research.
Key words:  scoliosis  Cobb angle  X-ray radiography  EOS imaging system  three-dimensional ultrasound imaging  surface topography  artificial intelligence