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

Craig C. Kage, Mohsen Akbari-Shandiz, Mary H. Foltz, Rebekah L. Lawrence, Taycia L. Brandon, Nathaniel E. Helwig, Arin M. Ellingson

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article numbere0228594
JournalPloS one
Volume15
Issue number2
DOIs
StatePublished - Feb 1 2020

Bibliographical note

Funding Information:
This work was supported by NIH/NICHD (National Institute of Child Health and Human Development): K12HD073945 (AE), F31HD087069 (RL), NIH/NIAMS (National Institute of Arthritis and Musculoskeletal and Skin Diseases) T32 AR050938, Musculoskeletal Training Grant (CK, RL), the Foundation for Physical Therapy (RL), and the Minnesota Partnership for Biotechnology and Medical Genomics (MHP IF #14.02) (AE). The authors appreciate the technical assistance of Conrad Lindquist, particularly for the design, construction, and implementation of the radiographic attenuator and validation block. The authors would also like to acknowledge the assistance of Hana Boudlali and Eric Twohey. The authors wish to thank the individuals who donated their bodies to the University of Minnesota?s Anatomy Bequest Program for the advancement of education and research.

Publisher Copyright:
© 2020 Kage et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Validation Study

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