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Abstract #2214

Statistical shape modeling of skeletal muscles improves the prediction of muscle strength

Salim G. Bin Ghouth1 and Valentina Mazzoli1
1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University, New York, NY, United States

Synopsis

Keywords: Muscle, Quantitative Imaging, Statistical Shape Modeling (SSM), Muscle Strength, Aging, and Sarcopenia

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.

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Keywords