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双平面放射学脊柱运动学的自动形状匹配算法验证及放射立体分析误差量化。

Validation of an automated shape-matching algorithm for biplane radiographic spine osteokinematics and radiostereometric analysis error quantification.

机构信息

Division of Rehabilitation Science, Department of Rehabilitation Medicine, University of Minnesota, Minneapolis, Minnesota, United States of America.

Rehabilitation Medicine Research Center, Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, Minnesota, United States of America.

出版信息

PLoS One. 2020 Feb 14;15(2):e0228594. doi: 10.1371/journal.pone.0228594. eCollection 2020.

Abstract

Biplane radiography and associated shape-matching provides non-invasive, dynamic, 3D osteo- and arthrokinematic analysis. Due to the complexity of data acquisition, each system should be validated for the anatomy of interest. The purpose of this study was to assess our system's acquisition methods and validate a custom, automated 2D/3D shape-matching algorithm relative to radiostereometric analysis (RSA) for the cervical and lumbar spine. Additionally, two sources of RSA error were examined via a Monte Carlo simulation: 1) static bead centroid identification and 2) dynamic bead tracking error. Tantalum beads were implanted into a cadaver for RSA and cervical and lumbar spine flexion and lateral bending were passively simulated. A bead centroid identification reliability analysis was performed and a vertebral validation block was used to determine bead tracking accuracy. Our system's overall root mean square error (RMSE) for the cervical spine ranged between 0.21-0.49mm and 0.42-1.80° and the lumbar spine ranged between 0.35-1.17mm and 0.49-1.06°. The RMSE associated with RSA ranged between 0.14-0.69mm and 0.96-2.33° for bead centroid identification and 0.25-1.19mm and 1.69-4.06° for dynamic bead tracking. The results of this study demonstrate our system's ability to accurately quantify segmental spine motion. Additionally, RSA errors should be considered when interpreting biplane validation results.

摘要

双翼 X 线摄影和相关的形状匹配提供了非侵入性、动态的 3D 骨和关节运动分析。由于数据采集的复杂性,每个系统都应该针对感兴趣的解剖结构进行验证。本研究的目的是评估我们系统的采集方法,并相对于放射立体分析(RSA)验证定制的自动 2D/3D 形状匹配算法,用于颈椎和腰椎。此外,通过蒙特卡罗模拟检查了 RSA 的两种误差源:1)静态珠心标识和 2)动态珠跟踪误差。将钽珠植入尸体中进行 RSA,被动模拟颈椎和腰椎屈伸和侧屈。进行了珠心标识可靠性分析,并使用椎验证块确定珠跟踪精度。我们系统的颈椎总体均方根误差(RMSE)范围为 0.21-0.49mm 和 0.42-1.80°,腰椎范围为 0.35-1.17mm 和 0.49-1.06°。RSA 与珠心标识相关的 RMSE 范围为 0.14-0.69mm 和 0.96-2.33°,与动态珠跟踪相关的 RMSE 范围为 0.25-1.19mm 和 1.69-4.06°。本研究的结果表明,我们的系统能够准确地量化节段性脊柱运动。此外,在解释双翼验证结果时应考虑 RSA 误差。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/72f7/7021291/9f64a8749eba/pone.0228594.g001.jpg

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