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15 March 2019 Quantitative cartilage imaging using spectral photon-counting detector based computed tomography
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Glycosaminoglycans (GAG) in the extracellular matrix of the articular cartilage are biomarkers of cartilage health. Loss of GAG has been associated with early stage osteoarthritis, with zonal depletion of intra-articular GAG levels occurring prior to cartilage degeneration. Detecting this biochemical change in articular cartilage may facilitate early diagnosis of osteoarthritis. GAG is negatively-charged and repels anionic contrast media. Increased uptake of anionic contrast agents could be correlated with depleted GAG levels in the cartilage. Photon-counting detector (PCD) based computed tomography (CT) offers high-resolution imaging and x-ray energy discrimination capabilities. This allows delineation of finer anatomical structures, and the generation of quantitative material maps using energy-resolved CT data. In this study, we demonstrate quantitative GAG imaging in porcine cartilage using a research whole-body PCD-CT system and an anionic contrast agent. Hind knee joints were harvested from euthanized pigs. GAG depletion mimicking early-OA was induced using trypsin treatment. Both the control group and the trypsin-treated group were incubated in an anionic gadolinium contrast prior to PCD-CT scanning. The specimens were scanned at ultra-high resolution using the PCD-CT system at 120kV, 330mAs, and [25, 51] keV energy thresholds. An image-domain material decomposition was employed to generate the mass density map for gadolinium in cartilage using energy-resolved PCD-CT data. The results showed significantly higher gadolinium uptake (p < 0.0001) in the trypsin-treated specimens, compared to the control specimens. We demonstrated high-resolution ex vivo cartilage imaging using PCD-CT to quantify gadolinium uptake in articular cartilage as an inverse marker of GAG.
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Kishore Rajendran, Shengzhen Tao, Amy Benike, Shuai Leng, and Cynthia McCollough "Quantitative cartilage imaging using spectral photon-counting detector based computed tomography", Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109531A (15 March 2019);

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