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Determining skeletal muscle architecture with Laplacian simulations: a comparison with diffusion tensor imaging
Geoffrey G Handsfield1, Bart Bolsterlee2,3, Joshua M Inouye4
1Auckland Bioengineering Institute, University of Auckland, Uniservices Building, Level 6 70 Symonds St., Auckland, 1010, New Zealand. g.handsfield@auckland.ac.nz.
Biomechanics and Modeling in Mechanobiology
|June 4, 2017
Summary
Laplacian flow simulations accurately predict skeletal muscle architecture, including pennation angle and fascicle length. This computational method offers a cost-effective alternative to traditional techniques for muscle modeling.
Area of Science:
- Biomechanics
- Computational modeling
- Anatomy
Background:
- Accurate skeletal muscle architecture determination is crucial for effective muscle behavior modeling.
- Current 3D muscle architecture determination methods are often expensive and time-consuming, limiting clinical and research applications.
- Computational methods like Laplacian flow simulations offer a potential alternative for estimating muscle fascicle orientation.
Purpose of the Study:
- To validate the accuracy of Laplacian flow simulations for determining skeletal muscle architecture.
- To compare muscle architecture data generated by Laplacian simulations with data from diffusion tensor imaging (DTI).
- To assess the feasibility of using Laplacian simulations as a cost-effective tool for in silico muscle architecture analysis.
Main Methods:
- Compared muscle architectures derived from Laplacian flow simulations against those obtained from diffusion tensor imaging (DTI) in eight adult medial gastrocnemius muscles.
- Utilized computational fluid dynamics software to perform Laplacian simulations on training and validation datasets.
- Input parameters included muscle geometry, aponeurosis location, and geometric flow guides.
Main Results:
- Laplacian simulations showed good agreement with DTI-derived muscle architectures in training sets.
- No significant differences were found in pennation angle or fascicle length between the two methods in validation sets.
- The mean difference for pennation angle was [Formula: see text] and for fascicle length was 0.9 mm.
Conclusions:
- Laplacian flow simulation is an effective method for predicting gastrocnemius muscle architecture in healthy volunteers.
- The approach accurately utilizes imaging-derived muscle shape and aponeurosis locations.
- This computational method can serve as a valuable in silico tool and a complement to existing muscle architecture determination techniques.
