A Narrative Review of Personalized Musculoskeletal Modeling Using the Physiome and Musculoskeletal Atlas Projects

Area of Science:

• Biomechanics
• Medical Imaging
• Computational Biology

Background:

• Personalized computational musculoskeletal models are crucial for understanding human movement.
• Existing models often lack patient-specific anatomical detail.
• Advancements in imaging and computational techniques enable greater personalization.

Purpose of the Study:

• To review recent developments in computational musculoskeletal model personalization.
• To highlight the role of statistical shape modeling in this process.
• To discuss the application of these methods across various anatomical regions.

Main Methods:

• Review of literature focusing on computational musculoskeletal modeling and personalization techniques.
• Exploration of statistical shape modeling for anatomical segmentation and classification.
• Analysis of projects like the Physiome and Musculoskeletal Atlas Projects.

Main Results:

• Model geometry personalization significantly impacts segmentation, classification, and model creation.
• Successful applications demonstrated in joints (trapeziometacarpal, tibiofemoral), tendons (Achilles), muscles (gastrocnemius), and pediatric bones.
• A novel multiscale personalization approach using scaffolds is proposed.

Conclusions:

• Statistical shape modeling is a powerful tool for creating patient-specific musculoskeletal models.
• Personalization techniques are advancing rapidly, with broad applicability in musculoskeletal research.
• The concept of multiscale personalization offers a promising direction for future model development.