Invited Talk ESA-SRB-ANZBMS 2024 in conjunction with ENSA

Microstructural imaging and the biomechanics of cartilage and joint structures (#58)

Kathryn Stok 1
  1. The University of Melbourne, Parkville, VIC, Australia

Early detection and treatment of arthritis activity goes beyond understanding mechanisms of disease, and also relies on advances in biological measurement techniques, medical imaging technology, medical image analysis, and evidence of clinical sensitivity. In the Integrative Cartilage Research Group, our strategy is to explore microstructural tissue remodelling as a key contributor to both early disease activity and tissue regeneration. With improved definition of this activity across the breadth of degenerative joint disease new links to peripheral sensitisation and future targets for drug development may be identified.

 

In this talk, new multiscale approaches for exploring bone, cartilage and joint health will be presented. This will include our novel imaging and mechanical platforms for quantitative measurement of biological tissues and joints: the Felix (ex vivo tissue) and MAXIS (in vivo joint) systems. These systems permit time-lapse image-guided mechanical evaluation of tissue development and degeneration, which allows further exploration of the influence of external loading on internal stresses and strains that trigger cell signalling pathways. Validation of the Felix system as a tool to tune tissue engineered constructs to meet functional demands is explored. While demonstration of the MAXIS system for assessing in vivo joint mechanics is provided. Acquisition protocols and analysis solutions for quantification of tissue development and degeneration is described, and evidence for their reproducibility and sensitivity to change for time-lapse imaging - in the same subject - is demonstrated.

 

Prioritising a need to translate these developments for clinical relevance, our current efforts with key collaborators in rheumatology, bone biology, and radiology, to define arthritis remodelling activity from high-resolution CT and deep learning is presented. Challenges around the importance of validation and reproducibility testing of these tools, while relinquishing clinician time back to patients (and away from datasets) are discussed.

 

In summary, this talk will present new quantitative approaches to longitudinal acquisition and analysis for preclinical and clinical disease detection, the role of mechanics in tissue development and degeneration, and future perspectives on taking advantage of high-resolution, low-radiation computed tomography technology combined with deep learning in a clinical setting.