Diffusion model-enhanced patella shape analysis predicts knee osteoarthritis progression and surgical replacement risk
Abstract
Patellofemoral osteoarthritis (OA) is a significant contributor to knee OA symptoms and functional impairments, with early morphological changes often originating in the patellofemoral joint. To facilitate early interventions in knee OA management, there is a pressing need for prognostic artificial intelligence (AI) models that can accurately forecast and explain the risk of disease deterioration. Recent studies have demonstrated the benefits of incorporating image generative models as an intermediate step in predicting knee OA progression from radiographs. Building on the remarkable advancements in image generation quality of diffusion models, this study presents a novel approach to knee OA prognosis using synthetic follow-up patella shapes for patella shape analysis. Our pipeline commences with a two-step patella segmentation model, achieving high accuracy (Dice score: 0.973, IoU: 0.947) in extracting precise patella masks from lateral knee radiographs. We then employ a diffusion model to predict patella shape trajectories over a 60-month period, conditioned on baseline patella masks. This model generates synthetic follow-up patella shapes that capture future morphological changes associated with OA progression. To predict knee OA outcomes, we developed a specialized 2-channel 1D-CNN with circular padding, incorporating both baseline and synthetic follow-up patella shapes to predict key outcomes of disease onset and end-stage. Our results demonstrate the significant…
Read the paper
Related studies
- Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2)
- Commentary on the clinical and preclinical dosage limits of interstitially administered magnetic fluids for therapeutic hyperthermia based on current practice and efficacy models
- Prosthesis: New Technological Opportunities and Innovative Biomedical Devices
- The history and future of neural modeling for cochlear implants
- Ryanodine receptors: waking up from refractoriness
- Novel Transgenic Rabbit Model Sheds Light on the Puzzling Role of Matrix Metalloproteinase-12 in Atherosclerosis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.