Machine learning–derived acetabular dysplasia and cam morphology are features of severe hip osteoarthritis: findings from UK Biobank
Machine learning–derived acetabular dysplasia and cam morphology are features of severe hip osteoarthritis: findings from UK Biobank
The contribution of shape changes to hip osteoarthritis (HOA) remains unclear, as is the extent to which these vary according to HOA severity. In the present study, we used statistical shape modeling (SSM) to evaluate relationships between hip shape and HOA of different severities using UK Biobank DXA images. We performed a cross-sectional study in individuals with left hip dual-energy X-ray absorptiometry (DXA) scans. Statistical shape modeling (SSM) was used to quantify hip shape. Radiographic HOA (rHOA) was classified using osteophyte size and number and joint space narrowing. HOA outcomes ranged in severity from moderate (grade 2) to severe (grade ≥3) rHOA, hospital-diagnosed HOA, and subsequent total hip replacement (THR). Confounder-adjusted logistic regression between the top 10 hip shape modes (HSMs) and OA outcomes was performed. Further models adjusted for alpha angle (AA) and lateral center-edge angle (LCEA), reflecting acetabular dysplasia and cam morphology, respectively. Composite HSM figures were produced combining HSMs associated with separate OA outcomes. A total of 40,311 individuals were included (mean 63.7 years, 47.8% male), of whom 5.7% had grade 2 rHOA, 1.7% grade ≥3 rHOA, 1.3% hospital-diagnosed HOA, and 0.6% underwent THR. Composite HSM figures for grade 2 rHOA revealed femoral neck widening, increased acetabular coverage, and enlarged lesser and greater trochanters. In contrast, grade ≥3 rHOA, hospital-diagnosed HOA, and THR were suggestive of cam morphology and reduced acetabular coverage. Associations between HSMs depicting cam morphology and reduced acetabular coverage and more severe HOA were attenuated by AA and LCEA adjustment, respectively. Relationships between hip shape and HOA differed according to severity. Notably, cam morphology and acetabular dysplasia were features of severe HOA, but unrelated to moderate disease, suggesting possible prognostic utility
1720–1732
Frysz, Monika
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Faber, Benjamin G.
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Ebsim, Raja
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Saunders, Fiona R.
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Lindner, Claudia
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Gregory, Jennifer S.
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Aspden, Richard M.
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Aspden, Richard M.
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Harvey, Nicholas C.
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Cootes, Tim
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Tobias, Jon H.
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1 September 2022
Frysz, Monika
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Faber, Benjamin G.
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Ebsim, Raja
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Saunders, Fiona R.
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Lindner, Claudia
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Gregory, Jennifer S.
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Aspden, Richard M.
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Aspden, Richard M.
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Harvey, Nicholas C.
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Cootes, Tim
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Tobias, Jon H.
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Frysz, Monika, Faber, Benjamin G., Ebsim, Raja, Saunders, Fiona R., Lindner, Claudia, Gregory, Jennifer S., Aspden, Richard M., Aspden, Richard M., Harvey, Nicholas C., Cootes, Tim and Tobias, Jon H.
(2022)
Machine learning–derived acetabular dysplasia and cam morphology are features of severe hip osteoarthritis: findings from UK Biobank.
Journal of Bone and Mineral Research, 37 (9), .
(doi:10.1002/jbmr.4649).
Abstract
The contribution of shape changes to hip osteoarthritis (HOA) remains unclear, as is the extent to which these vary according to HOA severity. In the present study, we used statistical shape modeling (SSM) to evaluate relationships between hip shape and HOA of different severities using UK Biobank DXA images. We performed a cross-sectional study in individuals with left hip dual-energy X-ray absorptiometry (DXA) scans. Statistical shape modeling (SSM) was used to quantify hip shape. Radiographic HOA (rHOA) was classified using osteophyte size and number and joint space narrowing. HOA outcomes ranged in severity from moderate (grade 2) to severe (grade ≥3) rHOA, hospital-diagnosed HOA, and subsequent total hip replacement (THR). Confounder-adjusted logistic regression between the top 10 hip shape modes (HSMs) and OA outcomes was performed. Further models adjusted for alpha angle (AA) and lateral center-edge angle (LCEA), reflecting acetabular dysplasia and cam morphology, respectively. Composite HSM figures were produced combining HSMs associated with separate OA outcomes. A total of 40,311 individuals were included (mean 63.7 years, 47.8% male), of whom 5.7% had grade 2 rHOA, 1.7% grade ≥3 rHOA, 1.3% hospital-diagnosed HOA, and 0.6% underwent THR. Composite HSM figures for grade 2 rHOA revealed femoral neck widening, increased acetabular coverage, and enlarged lesser and greater trochanters. In contrast, grade ≥3 rHOA, hospital-diagnosed HOA, and THR were suggestive of cam morphology and reduced acetabular coverage. Associations between HSMs depicting cam morphology and reduced acetabular coverage and more severe HOA were attenuated by AA and LCEA adjustment, respectively. Relationships between hip shape and HOA differed according to severity. Notably, cam morphology and acetabular dysplasia were features of severe HOA, but unrelated to moderate disease, suggesting possible prognostic utility
Text
Machine Learning Derived Acetabular Dysplasia
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Accepted/In Press date: 7 July 2022
e-pub ahead of print date: 10 July 2022
Published date: 1 September 2022
Additional Information:
Medical Research Council. Grant Numbers: MR/S00405X/1, MR/S021280/1
Wellcome Trust. Grant Numbers: 209233, 223267/Z/21/Z
Identifiers
Local EPrints ID: 474772
URI: http://eprints.soton.ac.uk/id/eprint/474772
ISSN: 0884-0431
PURE UUID: bbdfeb9d-59f2-4e54-abc8-8d2e2c5a3eb0
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Date deposited: 02 Mar 2023 17:46
Last modified: 17 Mar 2024 02:59
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Author:
Monika Frysz
Author:
Benjamin G. Faber
Author:
Raja Ebsim
Author:
Fiona R. Saunders
Author:
Claudia Lindner
Author:
Jennifer S. Gregory
Author:
Richard M. Aspden
Author:
Richard M. Aspden
Author:
Tim Cootes
Author:
Jon H. Tobias
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