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In a recent video interview, David Ouyang, M.D., shared insights from two recent studies he co-authored on the use of artificial intelligence (AI) to improve initial assessment of left ventricular ejection fraction (LVEF) on echocardiography and ascertain cardiac risks associated with changes in the left ventricle sphericity index seen on magnetic resonance imaging (MRI).

New ACR Guidelines Emphasize Earlier Breast Cancer Screening for High-Risk Women

While calling for a universal breast cancer risk assessment by the age of 25, the American College of Radiology (ACR) emphasized that ascertaining screening needs prior to the age of 40 is particularly important in high-risk populations such as Black women, who are 42 percent more likely to die from breast cancer in comparison to non-Hispanic White women.

TeraRecon Launches AI-Powered Neuro Suite

The artificial intelligence (AI)-powered Neuro Suite reportedly enables radiologists to access leading neurological AI algorithm solutions in the field, including the brain magnetic resonance imaging (MRI) segmentation capabilities of the Combinostics’ algorithm that can help differentiate degenerative pathologies such as Alzheimer’s disease and dementia.

In the study of 119 patients who had endovascular treatment for intracranial atherosclerotic stenosis, multivariable analysis revealed that post-op ischemic brain lesions on diffusion-weighted magnetic resonance imaging (MRI) were 3.6 times more likely to occur in patients who smoke cigarettes and 2.9 times more likely in patients who had multiple operative attempts.