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Proceedings Paper

Bone density quantification via material decomposition in an arthritic mouse model using photon counting spectral CT
Author(s): Nathaniel R. Fredette; Chandra Mohan; Mini Das
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Paper Abstract

Accurate quantitation of bone density variation would allow monitoring changes due to aging, disease progression, therapy outcomes or drug response. We present results from our material decomposition method using spectral computed tomography (CT) with a photon counting detector (PCD) for estimating quantitative bone density variations in healthy and arthritic mice. Limited samples of healthy mice and collagen antibody-induced arthritis (CAIA) mice were imaged on our home-built benchtop micro CT system with a wide area photon counting detector with a high resolution 55 micrometer pixel size. A material decomposition algorithm was applied in the image domain to separate and quantify bone and soft tissue variations. The resulting bone densities were quantified globally and locally for both mice. Higher bone densities were seen in the control mice over their arthritis counterparts by about 6-12%. Based on our preliminary results, material decomposition of multi-energy CT images collected with a PCD appears promising for bone density quantification. Our results show that these methods could be successfully applied to arthritis diagnosis and treatment monitoring in a mouse model. We will further investigate the utility of our methods to simultaneously quantify bone density as well as tagged contrast agents. These investigations are expected to help with longitudinal imaging studies to understand disease progression in animal models.

Paper Details

Date Published: 16 March 2020
PDF: 6 pages
Proc. SPIE 11312, Medical Imaging 2020: Physics of Medical Imaging, 113121G (16 March 2020); doi: 10.1117/12.2550543
Show Author Affiliations
Nathaniel R. Fredette, Univ. of Houston (United States)
Chandra Mohan, Univ. of Houston (United States)
Mini Das, Univ. of Houston (United States)

Published in SPIE Proceedings Vol. 11312:
Medical Imaging 2020: Physics of Medical Imaging
Guang-Hong Chen; Hilde Bosmans, Editor(s)

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