Abstract
AbstractObjectiveWe developed a novel imaging biomarker derived from knee dual-energy x-ray absorptiometry (DXA) to predict subsequent total knee replacement (TKR). The biomarker is based on knee shape, determined through statistical shape modelling. It was developed and evaluated using data and scans from the UK Biobank cohort.MethodsUsing a 129-point statistical shape model (SSM), knee shape (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 DXA images. Cox proportional hazards models were used to examine the associations of B-score, mJSW and osteophyte score with the risk of TKR, adjusted for age, sex, height and weight.ResultsThe analysis included 37,843 individuals (mean 63.7 years). In adjusted models, B-score and mJSW were associated with TKR: a standard deviation increase in B-score was associated with a hazard ratio (HR) of 2.32 (2.13, 2.54), and a lower mJSW with a HR of 2.21 (1.76, 2.76). In the 6,719 images scored for osteophytes, mJSW was replaced by osteophyte score in the most strongly predictive model for TKR. In subsequent ROC analyses, a model combining B-score, osteophyte score, and demographic variables had superior discrimination (AUC=0.87) in predicting TKR at five years compared with a model with demographic variables alone (AUC=0.73).ConclusionsAn imaging biomarker derived from knee DXA scans reflecting knee shape and osteophytes, in conjunction with demographic factors, could help identify those at high risk of TKR, in whom preventative strategies should be targeted.
Publisher
Cold Spring Harbor Laboratory