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Application of statistical shape modeling to the human hip joint: a scoping review protocol
Luke G Johnson1, Colleen Pawliuk2
1School of Biomedical Engineering, Faculty of Applied Science, University of British Columbia, Vancouver, BC, Canada.
Objective:
This review aims to identify all examples of the application of statistical shape models to the human hip joint, with a focus on methodology, validation, and applications.
Introduction:
Abnormal hip joint morphology (eg, deformity secondary to Legg-Calvé-Perthes disease) is an important precursor to osteoarthritis. Clinical radiographs are often used to characterize deformity and provide indication for surgical correction, but it is unclear whether radiographs can adequately describe three-dimensional deformity. Statistical shape modeling, a method of describing a population of shapes using a small number of variables, has been identified as a potential tool that will allow clinicians and researchers to validate current and novel radiographic measurements of hip deformity. In identifying all previous examples of statistical shape modeling applied to the hip joint, this review will determine its prevalence, strengths, and weaknesses, and identify gaps in the literature.
Inclusion Criteria:
Peer-reviewed and gray literature focusing on the development and/or application of statistical shape models to the human hip joint will be included.
Methods:
Several relevant databases, including Ovid MEDLINE, Embase, and IEEE, will be searched for literature published from 1992, and for a title and abstract that can be searched in English. After removal of duplicates, two reviewers will independently screen papers by title and abstract, then screen the full text of selected or uncertain papers. The same reviewers will then independently chart data from the final selection. At each stage, disagreements will be resolved through discussion or third-party arbitration.
