Abstract
Untreated rotator cuff tears can progress to a distinct form of shoulder arthritis, and the mechanism of this progression is poorly understood. Biomechanical, molecular and genetic factors may be at play, and a reliable animal model is needed to enable further research. The purpose of this study was to create a reproducible model of posttraumatic shoulder arthritis in the mouse, and to develop a scoring system for this model to enable future research on interventions, the role of various gene products, and the development of therapies to alter the natural course of the disease. Forty-five mice underwent operative ligation of the rotator cuff tendons and were followed for 45 weeks following surgery, with free cage activity post-operatively. Mice were sacrificed at various intervals from 2 to 45 weeks post-injury and histopathologic scoring was developed and tested by blinded reviewers using both quantitative computational analysis of coronal sections of the shoulder joint and semi-quantitative grading. The scoring system revealed a progressive, time-dependent set of tissue changes in the shoulder joint with features similar to human cuff tear arthropathy including acetabularization of the acromion and femoralization of the humeral head. This model establishes that osteoarthritis of the shoulder is distinct from osteoarthritis of the knee or hip, with different stages of degeneration and unique histopathologic features. Using the novel grading procedure and quantitative assessments presented here, future research using this model will enable investigators to test established and novel therapies and evaluate the role of inflammatory factors and gene products in shoulder arthritis. This study provides a reproducible mouse model of shoulder arthritis following isolated injury to the rotator cuff which elucidates characteristics of cuff tear arthropathy and provides a scoring system and venue for future research. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:506-514, 2017.
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