title: Subject-specific musculoskeletal loading of the tibia: Computational load estimation.
abstract: The systematic development of subject-specific computer models for the analysis of personalized treatments is currently a reality. In fact, many advances have recently been developed for creating virtual finite element-based models. These models accurately recreate subject-specific geometries and material properties from recent techniques based on quantitative image analysis. However, to determine the subject-specific forces, we need a full gait analysis, typically in combination with an inverse dynamics simulation study. In this work, we aim to determine the subject-specific forces from the computer tomography images used to evaluate bone density. In fact, we propose a methodology that combines these images with bone remodelling simulations and artificial neural networks. To test the capability of this novel technique, we quantify the personalized forces for five subject-specific tibias using our technique and a gait analysis. We compare both results, finding that similar vertical loads are estimated by both methods and that the dominant part of the load can be reliably computed. Therefore, we can conclude that the numerical-based technique proposed in this work has great potential for estimating the main forces that define the mechanical behaviour of subject-specific bone.
authors.affiliation: Multiscale in Mechanical and Biological Engineering (M2BE), Aragón Institute of Engineering Research (I3A), Mechanical Engineering Department, University of Zaragoza, Spain.
authors.forename: N
authors.initials: N
authors.lastname: Garijo
authors.affiliation: Laboratory for Biomechanical Engineering, University of Twente, Enschede, The Netherlands; Radboud University Medical Center, Radboud Institute for Health Sciences, Orthopaedic Research Laboratory, Nijmegen, The Netherlands.
authors.forename: N
authors.initials: N
authors.lastname: Verdonschot
authors.affiliation: Biomedical Engineering Department, Materialise NV, Leuven, Belgium.
authors.forename: K
authors.initials: K
authors.lastname: Engelborghs
authors.affiliation: Multiscale in Mechanical and Biological Engineering (M2BE), Aragón Institute of Engineering Research (I3A), Mechanical Engineering Department, University of Zaragoza, Spain.
authors.forename: J M
authors.initials: JM
authors.lastname: García-Aznar
authors.affiliation: Multiscale in Mechanical and Biological Engineering (M2BE), Aragón Institute of Engineering Research (I3A), Mechanical Engineering Department, University of Zaragoza, Spain. Electronic address: angeles@unizar.es.
authors.forename: M A
authors.initials: MA
authors.lastname: Pérez
mesh_terms: D015519:Bone Density; D016723:Bone Remodeling; D003198:Computer Simulation; D020342:Finite Element Analysis; D005684:Gait; D006801:Humans; D008954:Models, Biological; D016571:Neural Networks, Computer; D013977:Tibia / Q000502:physiology*; D016474:Weight-Bearing
keywords: Artificial neural network; Bone density; Bone remodelling problem/inverse bone remodelling model; Musculoskeletal model; Subject-specific