Contrast enhanced μCT imaging of early articular changes in a pre-clinical model of osteoarthritis.
Osteoarthritis Cartilage. 2018 01;26(1):118-127
Authors: Reece DS, Thote T, Lin ASP, Willett NJ, Guldberg RE
Abstract
OBJECTIVE: The objective of this study was to characterize early osteoarthritis (OA) development in cartilage and bone tissues in the rat medial meniscus transection (MMT) model using non-destructive equilibrium partitioning of an ionic contrast agent micro-computed tomography (EPIC-μCT) imaging. Cartilage fibrillation, one of the first physiological developments in OA, was quantified in the rat tibial plateau as three-dimensional (3D) cartilage surface roughness using a custom surface-rendering algorithm.
METHODS: Male Lewis rats underwent MMT or sham-operation in the left leg. At 1- and 3-weeks post-surgery, the animals (n = 7-8 per group) were euthanized and the left legs were scanned using EPIC-μCT imaging to quantify cartilage and bone parameters. In addition, a custom algorithm was developed to measure the roughness of 3D surfaces. This algorithm was validated and used to quantify cartilage surface roughness changes as a function of time post-surgery.
RESULTS: MMT surgery resulted in significantly greater cartilage damage and subchondral bone sclerosis with the damage increasing in both severity and area from 1- to 3-weeks post-surgery. Analysis of rendered 3D surfaces could accurately distinguish early changes in joints developing OA, detecting significant increases of 45% and 124% in surface roughness at 1- and 3-weeks post-surgery respectively.
CONCLUSION: Disease progression in the MMT model progresses sequentially through changes in the cartilage articular surface, extracellular matrix composition, and then osteophyte mineralization and subchondral bone sclerosis. Cartilage surface roughness is a quantitative, early indicator of degenerative joint disease in small animal OA models and can potentially be used to evaluate therapeutic strategies.
PMID: 29107695 [PubMed – indexed for MEDLINE]
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