Nichols and collaborators awarded NIH R01 to study the biomechanics contribution to rotator cuff tear symptoms

Jennifer A. Nichols, Ph.D.

The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) has awarded Dr. Jennifer Nichols and Dr. Federico Pozzi a multi-Principal Investigator R01 grant for a research project entitled “Biomechanics Contributions to Symptoms and Joint Health in Individuals with Rotator Cuff Tears.” This project aims to evaluate the influence of musculoskeletal biomechanics on rotator cuff tear symptoms through a combination of experimental and computational methods.

Led by associate professor Dr. Jennifer Nichols (PI) from the Musculoskeletal Biomechanics Laboratory within the J. Crayton Pruitt Family Department of Biomedical Engineering and assistant professor Dr. Federico Pozzi (PI) from the Department of Physical Therapy, the study will look at how muscles and nerves control the shoulder joint in three groups of people: those with painful rotator cuff tears, those with tears that don’t cause pain, and those with healthy shoulders. At University of Florida, Drs. Nichols and Pozzi will work with Dr. Kuang Gong, assistant professor in biomedical engineering, Dr. Jay King, associate professor in orthopaedic surgery, and Dr. Subharup Guha, associate professor in biostatistics. The team also includes Dr. Richard Souza at University of California San Francisco and Dr. Andy Karduna at University of Oregon.

“The proposed multidisciplinary project represents a paradigm shift in rotator cuff research by integrating human movement biomechanics, quantitative medical imaging, and data science,” said Dr. Nichols. “Our goal is to understand the relationship between neuromuscular control, shoulder joint health, and symptoms to design personalized interventions that alleviate pain and maximize functional recovery for the 4.5 million Americans seeking medical care for rotator cuff tears each year.”

Despite the prevalence of asymptomatic rotator cuff tears and the success of conservative exercise interventions for symptomatic tears, the extent to which neuromuscular control changes are adaptive versus pathological remains unknown. This research aims to fill a critical gap by understanding why some individuals with torn rotator cuffs are free of symptoms while others experience pain and dysfunction.

To achieve this, the research team will recruit senior adults to participate in biomechanical assessments within their laboratories, where precise measurements of muscle activation and movement patterns during various functional tasks will be conducted. Participants will subsequently undergo advanced magnetic resonance imaging (MRI) at the AMRIS facility to obtain detailed images of the shoulder musculature. The resulting biomechanics and imaging datasets will be analyzed using state-of-the-art computational simulations and machine learning (ML) algorithms. This integrative approach leverages Dr. Pozzi’s expertise in shoulder biomechanics, Dr. Nichols’ expertise in applying artificial intelligence (AI) and ML methods to biomechanics problems, and Dr. Gong’s proficiency in analyzing imaging using AI and ML.

One notable aspect of this study is the utilization of the same cohort of participants from Dr. Pozzi’s concurrent R01 study, which includes brain imaging and pain assessment data. By synthesizing these diverse modalities, the team aims to comprehensively understand the multifactorial nature of rotator cuff tear symptoms and identify potential avenues for improved therapeutic interventions.

The project will advance prior work through three specific aims:

  1. Aim 1: Elucidate the interrelationship between neuromuscular control and symptom expression by measuring shoulder motion and electromyography (EMG) of shoulder muscles during functional tasks.
  2. Aim 2: Examine the relationship between neuromuscular control, symptom expression, and shoulder joint health using static (MRI) and dynamic (musculoskeletal simulations) measures.
  3. Aim 3: Explore potential treatment targets by leveraging advances in explainable artificial intelligence to evaluate the relative contributions of various organ systems to rotator cuff symptoms.

The multidisciplinary team, led by Nichols and Pozzi, includes experts in biomechanics, musculoskeletal imaging, machine learning, shoulder pathology, clinical care, and biostatistics. This collaboration underscores the University of Florida’s commitment to advancing knowledge and improving patient outcomes in rotator cuff research.

Lead:

  • Jennifer Nichols (PI), Ph.D., Associate Professor & J. Crayton Pruitt Term Fellow, J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida
  • Federico Pozzi (CO-PI), P.T. Ph.D., Assistant professor, Department of Physical Therapy, University of Florida

Co-Investigators:

  • Joseph King, M.D., Associate Professor, Department of Orthopaedic Surgery & Sports Medicine, University of Florida
  • Subharup Guha, Ph.D., Associate Professor, Department of Biostatistics, University of Florida
  • Kuang Gong, Ph.D., Assistant Professor, J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida
  • Andy Karduna, Ph.D., Professor, Department of Human Physiology, University of Oregon
  • Richard Souza, P.T. Ph.D., Professor, Department of Physical Therapy, University of California San Francisco