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Richard Aspden

and Jenny Gregory

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date: 23 June 2021

The study of joint morphology can help us to understand the risk factors for osteoarthritis (OA), how it progresses, and aids in developing imaging biomarkers for study of the disease. OA results in gross structural changes in affected joints. Growth of osteophytes, deformation of joint components, and loss of joint space where cartilage has broken down are all characteristics of the disorder. Certain bone shapes as well as malalignment predispose people to future OA, or may be a marker for early OA. Geometrical measures, such as the alpha angle or Wiberg’s CE angle, used to be the primary tool for investigating morphology. In recent years, however, statistical shape modelling (SSM) has become increasingly popular. SSM can be used with any imaging modality and has been successfully applied to a number of musculoskeletal conditions. It uses sets of landmark points denoting the anatomy of one or more bones to generate new variables (modes) that describe and quantify the shape variation in a set of images via principal components analysis. With the aid of automated search algorithms for point placement, the use of SSMs is expanding and provides a valuable and versatile tool for exploration of bone and joint morphometry. Whilst the majority of research has focused on hip and knee OA, this chapter provides an overview of joint morphology through the whole skeleton and how it has helped our ability to understand and quantify the risk and progression of osteoarthritis.

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