A novel semi-automated classifier of hip osteoarthritis on DXA images shows expected relationships with clinical outcomes in UK Biobank

Objective
Conventional scoring methods for radiographic hip osteoarthritis (rHOA) are subjective and show inconsistent relationships with clinical outcomes. To provide a more objective rHOA scoring method, we aimed to develop a semi-automated classifier based on dual-energy X-ray absorptiometry (DXA) images, and confirm its relationships with clinical outcomes.

Methods
Hip DXAs in UK Biobank (UKB) were marked up for osteophyte area from which acetabular, superior and inferior femoral head osteophyte grades were derived. Joint space narrowing (JSN) grade was obtained automatically from minimum joint space width (mJSW) measures.

Clinical outcomes related to rHOA comprised hip pain, hospital diagnosed OA (HES OA) and total hip replacement (THR). Logistic regression and Cox proportional hazard modelling were used to examine associations between overall rHOA grade (0-4; derived from combining osteophyte and JSN grades), and the clinical outcomes.

Results
40,340 individuals were included in the study (mean age 63.7), of whom 81.2% had no evidence of rHOA, while 18.8% had grade ≥1 rHOA. Grade ≥1 osteophytes at each location and JSN were associated with hip pain, HES OA and THR. Associations with all three clinical outcomes increased progressively according to rHOA grade, with grade 4 rHOA and THR showing the strongest association [57.70 (38.08-87.44)].

Conclusions
Our novel semi-automated tool provides a useful means for classifying rHOA on hip DXAs, given its strong and progressive relationships with clinical outcomes. These findings suggest DXA scanning can be used to classify rHOA in large DXA-based cohort studies supporting further research, with the future potential for population-based screening.