An Efficient Modelling-Simulation-Analysis Workflow to Investigate Stump-Socket Interaction Using Patient-Specific,...

Area of Science:

• Biomechanics
• Medical Imaging
• Computational Modeling

Background:

• Simulation-based analysis of socket-stump interaction is hindered by inefficient modeling workflows.
• Detailed, subject-specific computational models are crucial for accurate biomechanical simulations.

Purpose of the Study:

• To develop and validate an efficient modeling-simulation-analysis workflow for subject-specific residual limb models.
• To predict deep tissue injury in residual limbs using finite element (FE) simulations.
• To compare the accuracy of detailed multi-muscle models against fused-muscle models.

Main Methods:

• Generated detailed 3D finite element models of residual limbs from Diffusion Tensor MRI images in under 20 minutes.
• Implemented a nonlinear hyperelastic, transversely isotropic skeletal muscle constitutive law with a deep tissue injury model in LS-DYNA.
• Performed implicit dynamic FE simulations of 2-hour bipedal stance with optimally-fitted and misfitted prosthetic sockets.

Main Results:

• The multi-muscle model predicted significantly higher peak stresses compared to the fused-muscle model (4x lower in fused-muscle).
• Peak interface stress in the individual-muscle model was 2.63 times lower than in deep stump tissues.
• A misfitted socket predicted 16.03% injured residual limb volume with the detailed model, versus 7.65% with the fused-muscle model.

Conclusions:

• The proposed workflow enables rapid generation of subject-specific residual limb models for biomechanical analysis.
• Detailed, anatomically realistic multi-muscle models provide superior prediction of deep tissue injury compared to fused-muscle models.
• This approach has broad applications, including prosthetic fitting optimization, plastic surgery impact prediction, and musculoskeletal system simulations.