Gait Analysis Methods for Rodent Models of Arthritic Disorders- Reviews and Recommendations EH Lakes- KD Allen - Osteoarthritis and Cartilage- 2016

Authors
Lakes EH, Allen KD

Lab
Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA; Institute for Cell & Tissue Science and Engineering, University of Florida, Gainesville, FL, USA.

Journal
Osteoarthritis Cartilage.

Abstract
Gait analysis is a useful tool to understand behavioral changes in preclinical arthritis models. While observational scoring and spatiotemporal gait parameters are the most widely performed gait analyses in rodents, commercially available systems can now provide quantitative assessments of spatiotemporal patterns. However, inconsistencies remain between testing platforms, and laboratories often select different gait pattern descriptors to report in the literature. Rodent gait can also be described through kinetic and kinematic analyses, but systems to analyze rodent kinetics and kinematics are typically custom made and often require sensitive, custom equipment. While the use of rodent gait analysis rapidly expands, it is important to remember that, while rodent gait analysis is a relatively modern behavioral assay, the study of quadrupedal gait is not new. Nearly all gait parameters are correlated, and a collection of gait parameters is needed to understand a compensatory gait pattern used by the animal. As such, a change in a single gait parameter is unlikely to tell the full biomechanical story; and to effectively use gait analysis, one must consider how multiple different parameters contribute to an altered gait pattern. The goal of this article is to review rodent gait analysis techniques and provide recommendations on how to use these technologies in rodent arthritis models, including discussions on the strengths and limitations of observational scoring, spatiotemporal, kinetic, and kinematic measures. Recognizing rodent gait analysis is an evolving tool, we also provide technical recommendations we hope will improve the utility of these analyses in the future.