Deciphering Osteoarthritis Progression and Knee Replacement Biomarkers: A Digital Twin Analysis via qMRI

Deciphering Osteoarthritis Progression and Knee Replacement Biomarkers: A Digital Twin Analysis via qMRI | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Deciphering Osteoarthritis Progression and Knee Replacement Biomarkers: A Digital Twin Analysis via qMRI Gabrielle Hoyer, Gabrielle Hoyer, Kenneth Gao, Felix Gassert, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4317958/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Osteoarthritis (OA), a prevalent and debilitating condition, poses substantial diagnostic and therapeutic challenges. Our study leverages advanced quantitative MRI to construct a sophisticated 100-dimensional space mapping known risk factors, unveiling unique imaging biomarkers for early detection and causal analysis in OA incidence and knee replacement (KR) cohorts. This methodological innovation enables a data-driven exploration of OA pathophysiology. We identified distinctive imaging features that differentiate between individuals at risk of OA and controls, elucidating protective factors and risk enhancers. Specifically, our analysis revealed that variations in cartilage thickness and T2 relaxation times are associated with reduced OA risk, whereas alterations in the medial meniscus shape increase susceptibility. Additionally, we pinpointed biomarkers for KR candidates, including tibial bone shape and cartilage characteristics, with significant implications for understanding OA’s progression. Our findings provide a promising foundation for future research, tailored clinical trials, and personalized therapeutic approaches, marking a significant stride toward combating OA. Health sciences/Biomarkers/Prognostic markers Biological sciences/Computational biology and bioinformatics/Image processing Biological sciences/Computational biology and bioinformatics/Statistical methods Biological sciences/Computational biology and bioinformatics/Machine learning Health sciences/Diseases/Rheumatic diseases/Osteoarthritis Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ExtendedFigures.pdf SupplementaryInformation.pdf SupplementaryTables.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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