Prediction Accuracy of Femoral and Tibial Stress and Strain Using Statistical Shape and Density Model-Based Finite Element Models in Paediatrics 

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Prediction Accuracy of Femoral and Tibial Stress and Strain Using Statistical Shape and Density Model-Based Finite Element Models in Paediatrics | 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 Research Article Prediction Accuracy of Femoral and Tibial Stress and Strain Using Statistical Shape and Density Model-Based Finite Element Models in Paediatrics Yidan Xu, Laura Carman, Thor F. Besier, Julie Choisne This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6441728/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Oct, 2025 Read the published version in Biomechanics and Modeling in Mechanobiology → Version 1 posted 14 You are reading this latest preprint version Abstract Computed tomography (CT)-based finite element (FE) models cannon-invasively assess bone mechanical properties, but their clinical application in paediatrics is limited due to fewer datasets and models. Predicted FE models using statistically inferred shape and density have application to predict bone fracture, strength, and strains, however, their accuracy in children remains unexplored. This study assessed the accuracy of stress-strain distributions estimated from predicted FE models of paediatric femora and tibiae. CT-based FE models used geometry and densities derived from 330 CT scans from children aged 4 to 18 years. Paediatric statistical shape-density models of the femur and tibia were used to predict bone geometries and densities from participants’ demographics and linear bone measurements. Forces during single leg standing were estimated and applied to each bone. Stress and strain distribution were compared between the predicted FE models and CT-based FE models, which served as the gold standard. The average normalized root-mean-square error (NRMSE) for Von Mises stress was 6% for the femur and 8% for the tibia. Principal strains NRMSE ranged from 1.2% to 5.5%. High correlations between the predicted modelsand CT-based models were observed, with determination coefficients ranging from 0.80 to 0.96. These results illustrate the potential of predictedFE models for paediatric application, such as personalized implant design and surgical planning. Finite element analysis Statistical shape and density model Femur Tibia Paediatric bone biomechanics Full Text Additional Declarations No competing interests reported. Supplementary Files Xu2025SupplementaryInformation.docx Cite Share Download PDF Status: Published Journal Publication published 13 Oct, 2025 Read the published version in Biomechanics and Modeling in Mechanobiology → Version 1 posted Editorial decision: Revision requested 03 Jun, 2025 Reviews received at journal 19 May, 2025 Reviews received at journal 14 May, 2025 Reviews received at journal 09 May, 2025 Reviews received at journal 07 May, 2025 Reviewers agreed at journal 20 Apr, 2025 Reviewers agreed at journal 19 Apr, 2025 Reviewers agreed at journal 18 Apr, 2025 Reviewers agreed at journal 17 Apr, 2025 Reviewers agreed at journal 17 Apr, 2025 Reviewers invited by journal 17 Apr, 2025 Editor assigned by journal 15 Apr, 2025 Submission checks completed at journal 15 Apr, 2025 First submitted to journal 13 Apr, 2025 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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