Objective: Predicting who will develop osteoarthritis, assessing how rapidly their disease will progress and monitoring early responses to treatment are key to the development of therapeutic agents able to treat this crippling disease and to their future clinical use. Statistical Shape Modelling (SSM) enables quantification of variations in multiple geometric measures describing the whole hip joint to be considered in concert. This prospective study evaluates the responsiveness of SSM to changes in hip-shape within 1 year. Methods: Sixty-two people, mean age 67.1 yrs, were recruited. Dual-energy X-ray Absorptiometry images were taken at three timepoints (baseline, 6 and 12 months). Based on Kellgren–Lawrence grading (KLG) of their baseline images, subjects were classified into control/doubtful OA: KLG < 1 in both hips; moderate OA: KLG = 2; and severe OA: KLG ≥ 3 in their most severe hip. Morphology was quantified using SSM and changes in shape were assessed using generalised estimating equations. Standardized response means (SRMs) were calculated for the first and second 6 month periods, then the full 12 months. Results: Disease severity ranged from KLG0–KLG4 in the 124 hips assessed at baseline. Three SSM modes (Modes 1, 3 and 4) were associated with OA severity. Across the whole cohort, SRM magnitudes ranged from 0.16 to 0.63. The greatest subgroup SRM (magnitude 0.91) was observed over 12 months in those subjects with moderate OA (KLG2). Conclusions: We have demonstrated that SSM can capture changes in hip shape over 6 and 12 months across the entire hip joint providing a sensitive measure of hip OA progression.
- Statistical shape modelling