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Spinal Imaging and Image Analysis pp 67–93Cite as

Osteoporosis

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Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 18))

Abstract

Osteoporosis is defined as a skeletal disorder characterized by compromised bone strength predisposing an individual to an increased risk for fracture. Osteoporotic fractures, in particular spine fractures, are associated with a high mortality and generate immense financial costs. Osteoporotic vertebral fractures frequently occur in absence of a specific trauma and may be asymptomatic. Since a prevalent vertebral fracture increases the risk of a subsequent fracture, the diagnosis of osteoporotic vertebral fractures is highly important to initiate appropriate therapy. Computer-assisted diagnostic tools for spine radiographs, dual-energy X-ray absorptiometry (DXA) and multi-detector computed tomography (MDCT) images have been developed to support radiologists to correctly diagnose and report osteoporotic vertebral fractures. The assessment of fracture risk at the spine has traditionally relied on the measurements of bone mineral density (BMD) by using DXA. However, BMD values of subjects with versus without osteoporotic fractures overlap. Bone strength reflects the integration of BMD and bone quality. The latter can be partly determined by measurements of bone microstructure. High-resolution MDCT allows for the assessment of trabecular bone microstructure at the spine. MDCT-based trabecular bone microstructure parameters and finite element models have shown to improve the prediction of bone strength beyond DXA-based BMD and revealed pharmacotherapy effects, which were partly not captured by BMD. Furthermore, recent studies demonstrated that quantitative magnetic resonance imaging (MRI) including proton single-voxel magnetic resonance spectroscopy (1H-MRS) and chemical shift-based water-fat imaging techniques quantifying bone marrow fat content at the spine may provide complementary information for diagnosing osteoporosis and assessing vertebral fracture risk.

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Authors and Affiliations

  1. Department of Radiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany

    Thomas Baum, Dimitrios C. Karampinos, Stefan Ruschke, Hans Liebl & Peter B. Noël

  2. Section of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany

    Jan S. Bauer

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  1. Thomas Baum
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  2. Dimitrios C. Karampinos
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  3. Stefan Ruschke
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  4. Hans Liebl
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  5. Peter B. Noël
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  6. Jan S. Bauer
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Correspondence to Thomas Baum .

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Editors and Affiliations

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

    Shuo Li

  2. Clinical Center, National Institutes of Health, Bethesda, Maryland, USA

    Jianhua Yao

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Baum, T., Karampinos, D.C., Ruschke, S., Liebl, H., Noël, P.B., Bauer, J.S. (2015). Osteoporosis. In: Li, S., Yao, J. (eds) Spinal Imaging and Image Analysis. Lecture Notes in Computational Vision and Biomechanics, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-319-12508-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-12508-4_3

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