A team of experts determined that correlating masses initially detected on MRI are significantly more likely to result in a cancer diagnosis than other common findings.
The model incorporates specific data from MRI exams with patient risk factors to predict whether a person is likely to develop clinically significant prostate cancer.
Contextualized reports differ from structured reports in that they focus on specific clinical indications, rather than a basic standardized checklist of anatomical regions that does not always address a particular concern.
This week at the International Society for Magnetic Resonance in Medicine’s annual meeting, a team of experts presented new data on the technologist’s role in MRI safety events.
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.