In vivo human lower limb muscle architecture dataset obtained using diffusion tensor imaging.

Area of Science:

• Biomechanics
• Human Anatomy
• Medical Imaging

Background:

• Current human muscle architecture data relies on elderly cadavers, limiting generalizability.
• Musculoskeletal models use this data for muscle force properties, potentially impacting accuracy for younger, healthier populations.
• Individualized in vivo muscle architecture data is challenging to obtain.

Purpose of the Study:

• To establish a reference set of human lower limb muscle architecture using in vivo imaging.
• To investigate the relationship between muscle architecture, force, and anthropometry in healthy adults.
• To assess the suitability of diffusion tensor imaging (DTI) for capturing in vivo muscle architecture.

Main Methods:

• Diffusion tensor magnetic resonance imaging (DTI) was employed to collect data from 10 healthy adults.
• Muscle architecture data, including fiber lengths, was acquired for 20 lower limb muscles.
• Analysis focused on muscle fiber lengths and maximum isometric force in relation to subject anthropometry.

Main Results:

• Diffusion tensor imaging (DTI) successfully provided detailed muscle architecture data for 20 lower limb muscles.
• Maximum isometric force and muscle fiber lengths did not consistently scale with subject anthropometry.
• Significant anatomical variation in lower limb muscle architecture was observed among individuals.

Conclusions:

• Diffusion tensor imaging (DTI) is a valid method for obtaining individualized in vivo muscle architecture.
• The lack of scaling suggests limitations in predicting muscle properties via simple algorithms.
• Subject-specific muscle properties are essential for enhancing the accuracy of musculoskeletal models in clinical applications.