Statistical shape modeling of the hip and the association with hip osteoarthritis: a systematic review

Statistical shape modeling of the hip and the association with hip osteoarthritis: a systematic review.

M.M.A. van Buuren, N.K. Arden, S.M.A. Bierma-Zeinstra, W.M. Bramer, N.C. Casartelli, D.T. Felson, G. Jones, N.E. Lane, C. Lindner, N.A. Maffiuletti, J.B.J. van Meurs, A.E. Nelson, M.C. Nevitt, P.L. Valenzuela, J.A.N. Verhaar, H. Weinans, R. Agricola.

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Summary

Objective

To summarize available evidence on the association between hip shape as quantified by statistical shape modeling (SSM) and the incidence or progression of hip osteoarthritis.

Design

We conducted a systematic search of five electronic databases, based on a registered protocol (available: PROSPERO CRD42020145411). Articles presenting original data on the longitudinal relationship between radiographic hip shape (quantified by SSM) and hip OA were eligible. Quantitative meta-analysis was precluded because of the use of different SSM models across studies. We used the Newcastle–Ottawa Scale (NOS) for risk of bias assessment.

Results

Nine studies (6,483 hips analyzed with SSM) were included in this review. The SSM models used to describe hip shape ranged from 16 points on the femoral head to 85 points on the proximal femur and hemipelvis. Multiple hip shape features and combinations thereof were associated with incident or progressive hip OA. Shape variants that seemed to be consistently associated with hip OA across studies were acetabular dysplasia, cam morphology, and deviations in acetabular version (either excessive anteversion or retroversion).

Conclusions

Various radiographic, SSM-defined hip shape features are associated with hip OA. Some hip shape features only seem to increase the risk for hip OA when combined together. The heterogeneity of the used SSM models across studies precludes the estimation of pooled effect sizes. Further studies using the same SSM model and definition of hip OA are needed to allow for the comparison of outcomes across studies, and to validate the found associations.