97323 20230622083321.0 doi 10.29007/lj2j sideral 121379 ART-2020-121379 eng Dejtiar, David Leandro Standard Cruciate-Retaining Total Knee Arthroplasty Implants can Reproduce Native Kinematics 2020 Access copy available to the general public Unrestricted Total knee arthroplasty (TKA) is a common procedure that has become the standard of treatment for severe cases of knee osteoarthritis. Biomechanics and quality of movement similar to healthy were found to improve patient-reported outcomes. In this study, an evaluated musculoskeletal model predicted ligament, contact and muscle forces together with secondary tibiofemoral kinematics. An artificial neural network applied to the musculoskeletal model searched for the optimal implant position in a given range that will minimize the root-mean-square-error (RMSE) between post- TKA and native experimental tibiofemoral kinematics during a squat. We found that, using a cruciate-retaining implant, native kinematics could be accurately reproduced (average RMSE 1.47 mm (± 0.89 mm) for translations and 2.89° (± 2.83°) for rotations between native and optimal TKA alignment). The required implant positions changes maximally 2.96 mm and 2.40o. This suggests that when using pre- operative planning, off-the-shelf CR implants allow for reproducing native knee kinematics post-operatively. info:eu-repo/grantAgreement/EC/H2020/722535/EU/Predictive models and simulations in bone regeneration: a multiscale patient-specific approach/CuraBone This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 722535-CuraBone info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Bartsoen, Laura Wesseling, Mariska Wirix-Speetjens, Roel Vander Sloten, Jos Perez, Maria Angeles Universidad de Zaragoza (orcid)0000-0002-2901-4188 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 4 (2020), 61-64 EPiC ser. health sci. EPiC series in health sciences 2398-5305 437740 http://zaguan.unizar.es/record/97323/files/texto_completo.pdf Versión publicada 315810 http://zaguan.unizar.es/record/97323/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:97323 articulos driver 2023-06-21-15:03:05 ARTICLE