Abstract
Our objective was to determine the efficacy and feasibility of a new approach for identifying candidate biomarkers for knee osteoarthritis (OA), based on selecting promising candidates from a range of high-frequency acoustic emission (AE) measurements generated during weight-bearing knee movement. Candidate AE biomarkers identified by this approach could then be validated in larger studies for use in future clinical trials and stratified medicine applications for this common health condition. A population cohort of participants with knee pain and a Kellgren-Lawrence (KL) score between 1-4 were recruited from local NHS primary and secondary care sites. Focusing on participants’ self-identified worse knee, and using our established movement protocol, sources of variation in AE measurement and associations of AE markers with other markers were explored. Using this approach we identified 4 initial candidate AE biomarkers, of which “number of hits” showed the best reproducibility, in terms of within-session, day to day, week to week, between-practitioner, and between-machine variation, at 2 different machine upper frequency settings. “Number of hits” was higher in knees with KL scores of 2 than in KL1, and also showed significant associations with pain in the contralateral knee, and with body weight. “Hits” occurred predominantly in 2 of 4 defined movement quadrants. The protocol was feasible and acceptable to all participants and professionals involved. This study demonstrates how AE measurement during simple sit-stand-sit movements can be used to generate novel candidate knee OA biomarkers. AE measurements probably reflect a composite of structural changes and joint loading factors. Refinement of the method and increasing understanding of factors contributing to AE will enable this approach to be used to generate further candidate biomarkers for validation and potential use in clinical trials.
Highlights
Knee osteoarthritis (OA) is a common degenerative joint condition, amongst older people
Variability between participants was higher than variability due to day of measurement, NHS research practitioner (RP) and Joint Acoustic Analysis System’ (JAAS) machine
Our acoustic emission (AE) technique focuses on capture and analysis of high frequency acoustic signals (20 to 400 kHz) emitted from knees during weight bearing movement
Summary
Knee osteoarthritis (OA) is a common degenerative joint condition, amongst older people. The recent development of techniques to measure high-frequency acoustic emission (AE) from knees offers the possibility of identifying AE features which reflect the integrity of interactions between joint components during weight bearing movement [4,5,6,7,8,9]. Such features would be regarded as "biomarkers" in the sense adopted by the NIH/FDA BEST resource [3], where molecular, histologic, radiographic, or physiologic characteristics (including, potentially, AE signatures) are types of biomarker. This approach has face validity with a clear rationale for enabling the identification and development of new knee OA biomarkers
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