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

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https://doi.org/10.13020/zk0a-1e27
https://hdl.handle.net/11299/211384

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2017

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Title

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

Published Date

2020-01-24

Authors

Ellingson, Arin M

Kage, Craig C

Group

Minnesota Rehabilitation Biomechanics Laboratory

Author Contact

Ellingson, Arin M
ellin224@umn.edu

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Dataset
Experimental Data

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 0.42-1.80º and the lumbar spine ranged between 0.35-1.17mm and 0.49-1.06º. The RMSE associated with RSA ranged between 0.14-0.69mm and 0.96-2.33º for bead centroid identification and 0.25-1.19mm and 1.69-4.06º 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.

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https://doi.org/10.1371/journal.pone.0228594

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CC0 1.0 Universal Public Domain Dedication
http://creativecommons.org/publicdomain/zero/1.0/

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Data Repository for U of M (DRUM)

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Eunice Kennedy Shriver National Institute of Child Health and Human Development K12HD073945 Eunice Kennedy Shriver National Institute of Child Health and Human Development F31HD087069 National Institute of Arthritis and Musculoskeletal and Skin Diseases T32 AR050938 Foundation for Physical Therapy Minnesota Partnership for Biotechnology and Medical Genomics MHP IF #14.02

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Ellingson, Arin M; Kage, Craig C. (2020). Validation of an automated shape-matching algorithm for biplane radiographic spine osteokinematics and radiostereometric analysis error quantification. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/zk0a-1e27.

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