Abstract
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 one year.
Methods
Sixty-two people, mean age 67.1 yrs, were recruited. Dual-energy X-ray Absorptiometry images were taken at three timepoints (baseline, six and twelve 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 (SRM) 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.
Original language | English |
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Pages (from-to) | 783-789 |
Number of pages | 7 |
Journal | Osteoarthritis and Cartilage |
Volume | 26 |
Issue number | 6 |
Early online date | 16 Apr 2018 |
DOIs | |
Publication status | Published - Jun 2018 |
Bibliographical note
AcknowledgementsWe are grateful to all the study participants. We thank Lana Gibson and Jennifer Scott for their expertise with the iDXA scanner as well as iDXA precision data.
Funding source
This study was supported by an award (Ref: WHMSB_AU068/071) from the Translational Medicine Research Collaboration – a consortium made up of the Universities of Aberdeen, Dundee, Edinburgh and Glasgow, the four associated NHS Health Boards (Grampian, Tayside, Lothian and Greater Glasgow & Clyde), Scottish Enterprise and initially Wyeth, now Pfizer.
The funder had no involvement in the collection, analysis and interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.
Dr J.S. Gregory was the holder of an MRC New Investigator award (Ref: G0901242).
Keywords
- osteoarthritis
- statistical shape modelling
- morphology
- hip
- radiographic
- DXA
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Jenny Gregory
- School of Medicine, Medical Sciences & Nutrition, Medical Education - Senior Lecturer
- School of Medicine, Medical Sciences & Nutrition, MRC/Versus Arthritis Centre for Musculoskeletal Health and Work
- School of Medicine, Medical Sciences & Nutrition, Institute of Medical Sciences
- School of Medicine, Medical Sciences & Nutrition, Aberdeen Centre for Arthritis and Musculoskeletal Health (ACAMH)
Person: Academic Related - Scholarship