4.6 Article

Quantitative morphometric patterns in cartilage and bone from the humeral heads of end-stage osteoarthritis patients

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OSTEOARTHRITIS AND CARTILAGE
卷 23, 期 8, 页码 1377-1387

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ELSEVIER SCI LTD
DOI: 10.1016/j.joca.2015.04.009

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Shoulder; Arthritis; Osteoporosis; Morphometry; Micro-computed tomography; Magnetic resonance imaging

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Objective: The purpose of this work is to investigate in a quantitative manner, the gross and regional structural patterns in cartilage and bone from the humeral head of end-stage OA patients, with the goal of identifying patterns of disease. Since the prevalence of primary OA of the shoulder is increasing as the population ages and the non-traumatic degenerative changes leading to this disease are poorly understood, a site-specific morphometric analysis speaks to the structure-function remodelling relationship of the pathological anatomy. Methods: Humeral heads were harvested from twenty-one patients undergoing shoulder arthroplasty for end-stage primary OA. The samples were scanned with micro-computed tomography and magnetic resonance imaging (MRI), and registered to provide reconstructed 3D datasets of the cartilage, cortical and trabecular bone tissues. Gross visual examination of the datasets allowed samples to be classified as OA-like, osteoporosis (OP)-like or OA/OP-like. Results: Volumes of interest (VOI) separating the OA-like samples into five distinct regions showed positive correlations between bone and cartilage morphometric parameters; specifically in areas where more cartilage has been lost, the underlying subchondral cortical bone was more porous and thicker, while the subchondral trabecular bone was more dense, including more connections and trabeculae. These differences were site-specific, where the central humeral head saw the greatest destruction of cartilage and bone sclerosis, followed by the anterior aspects. Conclusion: The ability to correlate bone and cartilage changes is valuable, as these structural cuesmay allow a more targeted diagnostic approach and a better classification of the disease, leading to improved therapies. (C) 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

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