Subject-specific musculoskeletal loading of the tibia: Computational load estimation.

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.

[1]  Xudong Zhang,et al.  Subject-specific finite element modeling of the tibiofemoral joint based on CT, magnetic resonance imaging and dynamic stereo-radiography data in vivo. , 2014, Journal of biomechanical engineering.

[2]  José Manuel García-Aznar,et al.  Comparative analysis of bone remodelling models with respect to computerised tomography-based finite element models of bone , 2010 .

[3]  Marco Viceconti,et al.  An accurate estimation of bone density improves the accuracy of subject-specific finite element models. , 2008, Journal of biomechanics.

[4]  K J Fischer,et al.  Computational method for determination of bone and joint loads using bone density distributions. , 1995, Journal of biomechanics.

[5]  Alejandro F. Frangi,et al.  Patient-Specific Biomechanical Modeling of Bone Strength Using Statistically-Derived Fabric Tensors , 2015, Annals of Biomedical Engineering.

[6]  Gianni Campoli,et al.  Computational load estimation of the femur. , 2012, Journal of the mechanical behavior of biomedical materials.

[7]  José Manuel García-Aznar,et al.  Computational evaluation of different numerical tools for the prediction of proximal femur loads from bone morphology , 2014 .

[8]  H. Koopman,et al.  Prediction of ground reaction forces and moments during various activities of daily living. , 2014, Journal of biomechanics.

[9]  Jack D. Cowan,et al.  Discussion: McCulloch-Pitts and related neural nets from 1943 to 1989 , 1990 .

[10]  J. Favre,et al.  A neural network model to predict knee adduction moment during walking based on ground reaction force and anthropometric measurements. , 2012, Journal of biomechanics.

[11]  Mauricio Reyes,et al.  Biomechanical Role of Bone Anisotropy Estimated on Clinical CT Scans by Image Registration , 2016, Annals of Biomedical Engineering.

[12]  V Carbone,et al.  Evaluation of a morphing based method to estimate muscle attachment sites of the lower extremity. , 2014, Journal of biomechanics.

[13]  R. Müller,et al.  Bone morphology allows estimation of loading history in a murine model of bone adaptation , 2012, Biomechanics and modeling in mechanobiology.

[14]  Nico Verdonschot,et al.  Gait and gait-related activities of daily living after total hip arthroplasty: a systematic review. , 2014, Clinical biomechanics.

[15]  Kenneth J Fischer,et al.  Density-based load estimation using two-dimensional finite element models: a parametric study , 2006, Computer methods in biomechanics and biomedical engineering.

[16]  V Carbone,et al.  TLEM 2.0 - a comprehensive musculoskeletal geometry dataset for subject-specific modeling of lower extremity. , 2015, Journal of biomechanics.

[17]  J. M. García-Aznar,et al.  A bone remodelling model coupling microdamage growth and repair by 3D BMU-activity , 2005, Biomechanics and modeling in mechanobiology.

[18]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[19]  Hui Jin,et al.  Determination of Poisson's ratio of articular cartilage by indentation using different-sized indenters. , 2004, Journal of biomechanical engineering.

[20]  F. Haddad,et al.  Zonal fixation in revision total knee arthroplasty. , 2015, The bone & joint journal.

[21]  Armando Ortiz-Prado,et al.  3D patient-specific model of the tibia from CT for orthopedic use. , 2015, Journal of orthopaedics.

[22]  Rik Huiskes,et al.  Effects of mechanical forces on maintenance and adaptation of form in trabecular bone , 2000, Nature.

[23]  B. Koopman,et al.  A subject-specific musculoskeletal modeling framework to predict in vivo mechanics of total knee arthroplasty. , 2015, Journal of biomechanical engineering.

[24]  J. M. Garcı́a,et al.  Anisotropic bone remodelling model based on a continuum damage-repair theory. , 2002, Journal of biomechanics.

[25]  J Vander Sloten,et al.  Role of subject-specific musculoskeletal loading on the prediction of bone density distribution in the proximal femur. , 2014, Journal of the mechanical behavior of biomedical materials.

[26]  A. Amis,et al.  The effect of muscle loading on the simulation of bone remodelling in the proximal femur. , 2005, Journal of biomechanics.

[27]  Yu Liu,et al.  Lower extremity joint torque predicted by using artificial neural network during vertical jump. , 2009, Journal of biomechanics.

[28]  Zdenek Horak,et al.  Comparison of isotropic and orthotropic material property assignments on femoral finite element models under two loading conditions. , 2007, Medical engineering & physics.

[29]  Amir A. Zadpoor,et al.  Neural network prediction of load from the morphology of trabecular bone , 2012, 1201.6044.

[30]  H. Koopman,et al.  Sensitivity of subject-specific models to errors in musculo-skeletal geometry. , 2012, Journal of biomechanics.

[31]  M Doblaré,et al.  Application of an anisotropic bone-remodelling model based on a damage-repair theory to the analysis of the proximal femur before and after total hip replacement. , 2001, Journal of biomechanics.

[32]  José Manuel García-Aznar,et al.  Numerical stability and convergence analysis of bone remodeling model , 2014 .

[33]  M. Doblaré,et al.  A coupled mechano-biochemical model for bone adaptation , 2014, Journal of mathematical biology.

[34]  Amir A Zadpoor,et al.  Patient-specific bone modeling and analysis: the role of integration and automation in clinical adoption. , 2015, Journal of biomechanics.

[35]  J. García-Aznar,et al.  Accelerating numerical simulations of strain-adaptive bone remodeling predictions , 2014 .

[36]  M M van der Krogt,et al.  A simple controller for the prediction of three-dimensional gait. , 2012, Journal of biomechanics.