Orthopedic imaging relies on X-ray, MRI and CT to diagnose disorders and injuries affecting the bones, muscles, ligaments, tendons, cartilage, and spine. Orthopedists also use these test results to create an effective treatment plan.
The goal of the study is to obtain quantitative data on how daily training and competing affect players’ musculoskeletal health. The information will be used to inform training, rest and recovery periods.
Although gadolinium-based contrast agents are largely considered safe and are routinely used for MRI exams, experts suggest that providers should still utilize GBCAs sparingly for musculoskeletal studies.
Many decision support tools catered to knee osteoarthritis have emerged in recent years, but external validation that ensures these algorithms can operate in a clinical setting has been lacking.
Reperforming lateral knee radiographs is common practice but consumes unnecessary resources and exposes patients to added radiation, experts explained in Radiography.
Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.
Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.
"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.