Statistical shape modeling of skeletal muscles improves the prediction of muscle strength
Motivation: Decline in muscle mass does not explain decline in muscle strength related to aging providing a compelling gap to investigate contribution of shape features in muscle strength. Goal(s): Our goal was to use statistical shape modeling (SSM) to investigate shape features of quadriceps muscles associated with muscle strength. Approach: We used SSM to extract dominant shape features of quadriceps. Extracted shape features were used to predict muscle strength. Results: Muscle shape features increased muscle strength prediction compared to muscle volume alone. These shape features may reflect architecture rearrangement of the quadriceps as a result of aging. Impact: Shape features of quadriceps muscles extracted from statistical shape modeling demonstrated a higher prediction of muscle strength of the rectus femoris, the vastus lateralis and the vastus medialis muscles in healthy subjects.
Authors
- Valentina Mazzoli (ORCID: https://orcid.org/0000-0002-6700-8424)
- Salim Bin Ghouth
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/2214
- Primary Topic
- Sports Performance and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00