News

Using imaging to measure muscle adaptations during injury and recovery

Collaborators

As for any tissue or organ beneath the surface of the skin, techniques for precisely measuring biological health are as elusive as they are vital. In the case of muscle injuries, physiologists, orthopedists, and radiologists combine diagnostic activities to make an educated guess, but when a choice between rest and a return to activity can mean the difference between permanent injury and a full recovery, they need greater accuracy.

Samuel Ward, PT, PhD, is a scientist in Orthopaedic Surgery and Radiology at UC San Diego and a principal investigator for the Wu Tsai Human Performance Alliance – San Diego Innovation Hub, the Triton Center for Performance and Injury Science. In May, Dr. Ward and colleagues published their findings on the application of diffusion tensor imaging to determine the best parameters for identifying different muscle injury modes and severities, with the idea of providing actionable measures clinicians can use to prognosticate injury recovery.

“Interpretation of data from diffusion tensor imaging remains very difficult,” said Dr. Ward. “Our strategy is to create a set of steps that will define the relative health or severity of injury/disease of muscle, so eventually clinicians can better pair patients or athletes with specific treatments and predict the trajectory of recovery.”

Findings from the study led the team to recommend specific MRI pulse sequence parameters when only one single diffusion imaging sequence can be performed, an important step to better-informed care.

Latest News

Model predicts how muscles respond to endurance and resistance training

June 6, 2024

Model predicts how muscles respond to endurance and resistance training

Study challenges cycle syncing, finds metabolism consistent during menstrual cycle

June 4, 2024

Study challenges cycle syncing, finds metabolism consistent during menstrual cycle

Self-supervised learning method boosts data efficiency by 10x for IMU-based analysis of forces during walking

June 3, 2024

Self-supervised learning method boosts data efficiency by 10x for IMU-based analysis of forces during walking

Get Engaged

Join our mailing list to receive the latest information and updates on the Wu Tsai Human Performance Alliance.