Investigating Rotator Cuff Muscle Function Through Experimental Biomechanics and Imaging

Developing novel approaches for musculoskeletal injuries risk assessments

Our research focuses on improving the understanding of shoulder function and rotator cuff pathology by combining cadaveric biomechanical testing, in-vivo ultrasound shear wave elastography (SWE), and imaging-based muscle analysis. We aim to characterize the mechanical behavior and functional roles of distinct sub-regions within the rotator cuff muscles – a concept that highlights the heterogeneous nature of these muscles and their contribution to shoulder stability and movement. Through cadaveric biomechanical experiments, we assess the mechanical load-sharing properties of individual muscle sub-regions under different loading and repair conditions. Complementing this work, SWE imaging in-vivo and in cadavers allows us to quantify muscle stiffness and mechanical integrity, offering real-time insights into muscle quality and contractile function both pre- and post-operatively. By integrating these experimental techniques, our research aims to establish muscle sub-region-specific functional profiles and identify key mechanical indicators associated with rotator cuff repair failure (re-tears). Ultimately, this work will advance our ability to predict surgical outcomes, personalize rehabilitation strategies, and optimize treatment approaches based on the functional health of rotator cuff muscle sub-regions.

Our research is centered on improving vertebral fracture risk prediction by integrating quantitative computed tomography (QCT)-based finite element analysis (FEA) with musculoskeletal (MSK) whole-body modeling. This innovative approach aims to move beyond traditional bone mineral density (BMD) assessments by incorporating subject-specific bone strength estimates and loading conditions experienced during activities of daily living. Using QCT imaging, we develop detailed, patient-specific vertebral models for FEA, enabling us to evaluate accurate vertebral mechanical properties. Loads derived from MSK modeling, which simulates whole-body movement and calculates internal forces acting on the spine during activities of daily living (ADLs), such as lifting, bending, and walking, are used together with the QCT/FEA models to better predict fracture risk based on ADLs. By coupling these computational techniques, we aim to provide a more comprehensive and physiologically relevant assessment of fracture risk. This integrated framework will enhance our ability to identify individuals at high risk for fragility fractures, even when BMD alone appears normal. Ultimately, our goal is to develop personalized risk assessment tools that better reflect real-life loading conditions, improving clinical decision-making and preventative strategies for patients at risk of vertebral fractures.