The roles of real-world shoulder biomechanics in rotator cuff tendinopathy rehabilitation

About This Grant

PROJECT SUMMARY Rotator cuff tendinopathy is a prevalent chronic disease that is painful, debilitating, and reduces the quality of life. Physical therapy (PT) is an effective first-line treatment, but the non-response rate to PT is still high. Long- term recovery is further limited, and the reason for pain recurrence is poorly explained. It is possible that the in- clinic gains of PT fail to translate to good real-world mechanics and are overwhelmed by the pathomechanical shoulder movements in activities of daily living. Clinical and basic science both suggest shoulder overuse and motion-driven pathomechanics are causal factors of rotator cuff pathology. These biomechanical mechanisms are unconfirmed in patients partly due to the complex interplays among pathology, mechanics, and treatment, in addition to a paucity of methods to quantify the highly variable real-world motion and in-vivo tendon loading. My overall goal is to discover how real-world shoulder biomechanics interact with the clinical outcomes of PT in rotator cuff tendinopathy. This research progresses from a cross-sectional [K99] to a longitudinal cohort study [R00]. My cross-sectional Aim 1 [K99] will use 1) wearable sensors to track 7-day bilateral shoulder cumulative motion in daily living; 2) motion analysis and musculosketeal models to identify motion-driven pathomechanics specific to daily living functional tasks; and 3) machine learning to combine sensor-detected activities with motion-driven biomechanics to quantify real-world cumulative rotator cuff tendon loading. My mentored K99 will validate research tools and define how patient shoulder motion and tendon loading deviate from normal status. The longitudinal Aim 2 [R00] will link the real-world biomechanics established in Aim 1 with changes in clinical outcomes, including pain, shoulder function, and tendon structure, through a 3-month PT protocol followed by the first 6 months after PT completion. These Aims will clarify the mechanical mechanisms on how real-world shoulder motion and loading alter the course of PT clinical outcomes in rotator cuff tendinopathy. Findings will inform data-driven continuous rehabilitation paradigms that monitor and modify daily living activities to maintain long-term shoulder health. This research will also serve as the foundation of Dr. Ke Song's career development plan to acquire 2 years of mentored training [K99] and prepare for transition into independence [R00]. Through the guidance of his experienced and interdisciplinary mentoring team, Dr. Song will perform hands-on training with field-leading experts in shoulder biomechanics, physical therapy, orthopaedics, wearable sensors, data science, and biostatistics to maximize the impact of his proposed research. Dr. Song will also learn from formal courses and professional training activities to ensure his career progress, develop clinical research proficiency, improve grant writing, mentoring, and leadership skills, and secure an independent tenure-track faculty position at a clinical research-intensive institution. The scientific training, professional development, and research plans will guide Dr. Song through a pathway to independent research in translational musculoskeletal biomechanics that help patients with rotator cuff tendinopathy and related shoulder diseases improve long-term outcomes.