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Measurement of vertebral kinematics using noninvasive image matching method-validation and application.

Publication ,  Journal Article
Wang, S; Passias, P; Li, G; Li, G; Wood, K
Published in: Spine (Phila Pa 1976)
May 15, 2008

STUDY DESIGN: In vitro and in vivo laboratory study. OBJECTIVE: To validate a dual fluoroscopic image matching technique for measurement of in vivo spine kinematics. SUMMARY OF BACKGROUND DATA: Accurate knowledge of the spinal structural functions is critical to understand the biomechanical factors that affect spinal pathology. Many studies have investigated vertebral motion both in vitro and in vivo. However, determination of in vivo motion of the vertebrae under physiologic loading conditions remains a challenge in biomedical engineering because of the limitations of current technology and the complicated anatomy of the spine. METHODS: In in vitro validation, an ovine spine was moved to a known distance in a known speed by an MTS machine. The dual fluoroscopic system was used to capture the spine motion and reproduce the moving distance and speed. In in vivo validation, a living subject moved the spine in various positions under weightbearing. The fluoroscopes were used to reproduce the in vivo spine positions 5 times. The standard deviations in translation and orientation of the 5 measurements were used to evaluate the repeatability of technique. RESULTS: The translation positions of the ovine spine could be determined with a mean accuracy less than 0.40 mm for the image matching technique using magnetic resonance image-based vertebral models. The spine speed could be reproduced within an accuracy of 0.2 mm/s. The repeatability of the method in reproducing in vivo human spine 6DOF kinematics was less than 0.3 mm in translation and less than 0.7 degrees in orientation. CONCLUSION: The image matching technique was accurate and repeatable for noninvasive measurement of spine vertebral motion. The technique could be a useful tool for determination of vertebral positions and orientations before and after surgical treatment of spinal pathology to evaluate and improve the efficacy of the various surgical methods in restoring normal spine function.

Duke Scholars

Published In

Spine (Phila Pa 1976)

DOI

EISSN

1528-1159

Publication Date

May 15, 2008

Volume

33

Issue

11

Start / End Page

E355 / E361

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Spine
  • Sheep
  • Research Design
  • Orthopedics
  • Magnetic Resonance Spectroscopy
  • Image Processing, Computer-Assisted
  • Humans
  • Biomechanical Phenomena
  • Animals
 

Citation

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Wang, S., Passias, P., Li, G., & Wood, K. (2008). Measurement of vertebral kinematics using noninvasive image matching method-validation and application. Spine (Phila Pa 1976), 33(11), E355–E361. https://doi.org/10.1097/BRS.0b013e3181715295
Wang, Shaobai, Peter Passias, Gang Li, Guoan Li, and Kirkham Wood. “Measurement of vertebral kinematics using noninvasive image matching method-validation and application.Spine (Phila Pa 1976) 33, no. 11 (May 15, 2008): E355–61. https://doi.org/10.1097/BRS.0b013e3181715295.
Wang S, Passias P, Li G, Wood K. Measurement of vertebral kinematics using noninvasive image matching method-validation and application. Spine (Phila Pa 1976). 2008 May 15;33(11):E355–61.
Wang, Shaobai, et al. “Measurement of vertebral kinematics using noninvasive image matching method-validation and application.Spine (Phila Pa 1976), vol. 33, no. 11, May 2008, pp. E355–61. Pubmed, doi:10.1097/BRS.0b013e3181715295.
Wang S, Passias P, Li G, Wood K. Measurement of vertebral kinematics using noninvasive image matching method-validation and application. Spine (Phila Pa 1976). 2008 May 15;33(11):E355–E361.

Published In

Spine (Phila Pa 1976)

DOI

EISSN

1528-1159

Publication Date

May 15, 2008

Volume

33

Issue

11

Start / End Page

E355 / E361

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Spine
  • Sheep
  • Research Design
  • Orthopedics
  • Magnetic Resonance Spectroscopy
  • Image Processing, Computer-Assisted
  • Humans
  • Biomechanical Phenomena
  • Animals