@inproceedings{f488b9865cc140b5801735e6a758c08d,
title = "Quantitative cartilage imaging using spectral photon-counting detector based computed tomography",
abstract = "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.",
keywords = "Photon-counting detectors, computed tomography, glycosaminoglycans, multi-energy, trypsin digestion, ultra-high resolution",
author = "Kishore Rajendran and Shengzhen Tao and Amy Benike and Shuai Leng and Cynthia McCollough",
note = "Publisher Copyright: {\textcopyright} 2019 SPIE.; Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging ; Conference date: 19-02-2019 Through 21-02-2019",
year = "2019",
doi = "10.1117/12.2512627",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Barjor Gimi and Andrzej Krol",
booktitle = "Medical Imaging 2019",
}