| Title: | Dual-energy X-ray absorptiometry derived knee shape may provide a useful imaging biomarker for predicting total knee replacement: Findings from a study of 37,843 people in UK Biobank |
| Journal: | Osteoarthritis and Cartilage Open |
| Published: | 9 Apr 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38655015/ |
| DOI: | https://doi.org/10.1016/j.ocarto.2024.100468 |
| Citations: | 1 (1 in last 2 years) as of 8 Aug 2024 |
Publication 9936
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Abstract
Objective: We aimed to create an imaging biomarker for knee shape using knee dual-energy x-ray absorptiometry (DXA) scans and investigate its potential association with subsequent total knee replacement (TKR), independently of radiographic features of knee osteoarthritis and established risk factors.</p>
Methods: Using a 129-point statistical shape model, knee shape (expressed as a B-score) and minimum joint space width (mJSW) of the medial joint compartment (binarized as above or below the first quartile) were derived. Osteophytes were manually graded in a subset of images and an overall score was assigned. Cox proportional hazards models were used to examine the associations of B-score, mJSW and osteophyte score with TKR risk, adjusting for age, sex, height and weight.</p>
Results: The analysis included 37,843 individuals (mean age 63.7 years). In adjusted models, B-score was associated with TKR: each unit increase in B-score, reflecting one standard deviation from the mean healthy shape, corresponded to a hazard ratio (HR) of 2.25 (2.08, 2.43), while a lower mJSW had a HR of 2.28 (1.88, 2.77). Among the 6719 images scored for osteophytes, mJSW was replaced by osteophyte score in the most strongly predictive model for TKR. In ROC analyses, a model combining B-score, osteophyte score, and demographics outperformed a model including demographics alone (AUC = 0.87 vs 0.73).</p>
Conclusions: Using statistical shape modelling, we derived a DXA-based imaging biomarker for knee shape that was associated with kOA progression. When combined with osteophytes and demographic data, this biomarker may help identify individuals at high risk of TKR, facilitating targeted interventions.</p>
12 Authors
- Rhona A. Beynon
- Fiona R. Saunders
- Raja Ebsim
- Monika Frysz
- Benjamin G. Faber
- Jennifer S. Gregory
- Claudia Lindner
- Aliya Sarmanova
- Richard M. Aspden
- Nicholas C. Harvey
- Timothy Cootes
- Jonathan H. Tobias
1 Application
| Application ID | Title |
|---|---|
| 17295 | AUtomated Generation of Musculoskeletal phENotypes from the UK biobank exTended imaging study (AUGMENT Study) |
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