The University of California, San Francisco is developing and training an AI model that could help diagnose tears in knee cartilage, or the meniscus. A meniscus tear can lead to long-term health challenges and lifestyle changes, ranging from debilitation to limits on activity. One of the keys to mitigating the consequences of meniscus tears is identifying and treating tears in the meniscus early. Here’s an interesting look at the research currently going on.
While this goal is pretty simple, the path forward is rather complicated. To diagnose a torn meniscus, clinicians need to review and interpret hundreds of high-resolution 3D magnetic resonance imaging (MRI) slices showing a patient’s knee from different angles. Radiologists then assign a numerical score to indicate the presence of a tear and its severity. This labor-intensive, time-consuming process relies heavily on the skills and availability of clinical specialists, and the interpretation of the images themselves can be rather subjective.