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Quantitative Monitoring of Syndesmophyte Growth in Ankylosing Spondylitis Using Computed Tomography

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Computational Methods and Clinical Applications for Spine Imaging

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 17))

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Abstract

Ankylosing Spondylitis, an inflammatory disease affecting mainly the spine, can be characterized by abnormal bone formation (syndesmophytes) along the margins of the intervertebral disk. Monitoring syndesmophytes evolution is challenging because of their slow growth rate, a problem compounded by the use of radiography and qualitative rating systems. To improve sensitivity to change, we designed a computer algorithm that fully quantifies syndesmophyte volume using the 3D imaging capabilities of computed tomography. The reliability of the algorithm was assessed by comparing the results obtained from 2 scans performed on the same day in 9 patients. A longitudinal study on 20 patients suggests that the method will benefit longitudinal clinical studies of syndesmophyte development and growth. After one year, the 3D algorithm showed an increase in syndesmophyte volume in 75 % of patients, while radiography showed an increase in only 15 % of patients.

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Authors and Affiliations

  1. National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, 20892, USA

    Sovira Tan & Michael M. Ward

  2. Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA

    Jianhua Yao & Lawrence Yao

Authors
  1. Sovira Tan
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  2. Jianhua Yao
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  3. Lawrence Yao
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  4. Michael M. Ward
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Corresponding author

Correspondence to Sovira Tan .

Editor information

Editors and Affiliations

  1. Center Drive, National Institutes of Health, Bethesda, Massachusetts, USA

    Jianhua Yao

  2. Innovative Technologies Research Laboratories, Philips Research, Hamburg, Germany

    Tobias Klinder

  3. GE Healthcare and University of Western Ontario, London, Ontario, Canada

    Shuo Li

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© 2014 Springer International Publishing Switzerland

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Tan, S., Yao, J., Yao, L., Ward, M.M. (2014). Quantitative Monitoring of Syndesmophyte Growth in Ankylosing Spondylitis Using Computed Tomography. In: Yao, J., Klinder, T., Li, S. (eds) Computational Methods and Clinical Applications for Spine Imaging. Lecture Notes in Computational Vision and Biomechanics, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-07269-2_12

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  • DOI: https://doi.org/10.1007/978-3-319-07269-2_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07268-5

  • Online ISBN: 978-3-319-07269-2

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