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Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

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Published on: April 11, 2018

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

N Garijo¹, N Verdonschot², K Engelborghs³

¹Multiscale in Mechanical and Biological Engineering (M2BE), Aragón Institute of Engineering Research (I3A), Mechanical Engineering Department, University of Zaragoza, Spain.

Journal of the Mechanical Behavior of Biomedical Materials

|September 16, 2016

Summary

This study introduces a new method using CT scans, bone remodeling simulations, and artificial neural networks to calculate subject-specific bone forces. The technique accurately estimates key forces, showing potential for personalized bone mechanical analysis.

Keywords:

Artificial neural network Bone density Bone remodelling problem/inverse bone remodelling model Musculoskeletal model Subject-specific

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Area of Science:

Biomechanics
Computational modeling
Medical imaging

Background:

Subject-specific computer models are crucial for personalized treatment analysis.
Finite element models require accurate subject-specific geometries and material properties.
Determining subject-specific forces typically necessitates gait analysis and inverse dynamics simulations.

Purpose of the Study:

To develop a novel methodology for determining subject-specific bone forces.
To utilize computer tomography (CT) images, bone remodeling simulations, and artificial neural networks (ANNs).
To validate the technique by comparing results with traditional gait analysis.

Main Methods:

A methodology combining CT imaging, bone remodeling simulations, and ANNs was proposed.
Subject-specific forces were quantified for five tibias using the novel technique.
Results were compared against those obtained from conventional gait analysis.

Main Results:

The novel technique reliably estimated vertical loads on subject-specific tibias.
The dominant components of bone loading were accurately computed.
Vertical load estimations showed good agreement with gait analysis results.

Conclusions:

The proposed numerical technique shows significant potential for estimating primary forces in subject-specific bone.
This method offers a promising alternative for analyzing the mechanical behavior of individual bones.
Accurate force estimation can enhance personalized treatment strategies in orthopedics.