Development and implementation of a coupled computational muscle force optimization bone shape adaptation modeling...

Area of Science:

• Biomechanics
• Computational Biology
• Orthopedics

Background:

• Bone strength adaptation is influenced by muscle forces, but current analysis methods are limited.
• Understanding these influences is crucial for addressing bone loss due to aging, disuse, and reduced gravity.
• Mechanical countermeasures effectiveness varies, necessitating better analytical tools.

Purpose of the Study:

• To develop an advanced computational modeling technique for analyzing muscle-driven bone strength adaptation.
• To quantify individual muscle force magnitudes within a multisegment musculoskeletal system.
• To predict bone strength improvements via simulated material accretion and resorption.

Main Methods:

• Coupling gradient-based and gradientless numerical optimization with finite element methods.
• Developing a performance-based stopping criterion without experimental or system parameters.
• Incorporating direct and indirect muscle effects from the targeted bone and neighboring segments.

Main Results:

• The developed technique quantifies individual muscle force magnitudes in complex musculoskeletal systems.
• It predicts bone strength improvements by simulating cortical material changes.
• The method consistently quantifies shape and strength alterations across various boundary conditions.

Conclusions:

• The new technique provides a robust framework for studying muscle force-bone strength relationships.
• It offers a clearer foundation for understanding bone adaptation mechanisms.
• This approach can lead to improved control over bone adaptive phenomena and the development of targeted interventions.