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Updated: Oct 27, 2025

Obtaining Quality Extended Field-of-View Ultrasound Images of Skeletal Muscle to Measure Muscle Fascicle Length
Published on: December 14, 2020
Architectural model for muscle growth during maturation
Stefan Papenkort1, Markus Böl2, Tobias Siebert3
1Department of Motion and Exercise Science, University of Stuttgart, Stuttgart, Germany. stefan.papenkort@inspo.uni-stuttgart.de.
This study developed a 3D muscle architecture model to predict fascicle architecture changes during growth. The model accurately forecasts muscle dimensions and mass, aiding future biomechanical simulations.
Area of Science:
- Biomechanics
- Skeletal Muscle Physiology
- Computational Modeling
Background:
- Skeletal muscle mechanical properties are significantly influenced by muscle architecture parameters like fascicle length and pennation angle.
- Muscle architecture must adapt to the growth of an organism during maturation.
- Predicting these adaptations is crucial for understanding muscle function across different ages.
Purpose of the Study:
- To develop a predictive model for 3D fascicle architecture in unipennate muscles across various ages.
- To incorporate age-related changes in muscle belly length, fascicle length, and pennation angle into the model.
- To validate the model's predictions using experimental data and existing literature.
Main Methods:
- Collected novel 3D muscle architecture data for the rabbit M. plantaris in animals aged 29 to 106 days.
- Developed a computational model integrating experimental data on muscle growth and architectural parameter changes.
- Validated model predictions against literature data for rabbit M. soleus and M. gastrocnemius medialis.
Main Results:
- Observed significant increases in M. plantaris muscle belly length (73%), mean fascicle length (39%), and mean pennation angle (14%) with age.
- The developed model demonstrated good accuracy, with a -1.0 ± 8.6% error in predicting aponeurosis length, width, muscle height, and mass.
- Model predictions aligned well with interindividual variations found in literature data.
Conclusions:
- The developed 3D muscle architecture model effectively predicts age-related changes in unipennate muscles.
- The model's accuracy in predicting key architectural parameters and mass supports its utility.
- This predictive model can generate realistic architectural datasets for future biomechanical simulation studies.
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