Featuring a combination of automated measurement capabilities and workflow enhancements, the new AI-powered cardiovascular ultrasound platform also provides automated assessment of regional wall motion abnormalities.
Industry firsts for automated segmental wall motion scoring and automated 3D quantification of mitral regurgitation are among the new Philips cardiac ultrasound artificial intelligence (AI) applications granted 510(k) clearance by the Food and Drug Administration (FDA).
For patients with heart valve disease, Philips said the fully automated quantification of mitral regurgitation facilitates improved assessments and management of this patient population. Another benefit with the newly FDA-cleared AI ultrasound applications is improved accuracy in the detection of regional wall motion abnormalities (RWMAs) that are associated with adverse cardiovascular risks among patients with myocardial infarction and congenital heart disease, according to Philips.
Newly FDA-cleared cardiac ultrasound artificial intelligence (AI) applications from Phillips include automated 3D quantification of mitral regurgitation and AI-enhanced detection of regional wall motion abnormalities (RWMAs). (Image courtesy of Philips.)
Phillips noted that the AI applications, trained on patient data sets from real-world clinical environments, bolster the quality and reproducibility of cardiac imaging, enabling radiologists and other health-care providers with varying ultrasound experience to enhance the accuracy and speed of their imaging assessments.
“As clinical cases get more complex and patient volumes increase, we read hundreds of echocardiography exams daily with thousands of data points. With the integration of AI into echocardiography solutions, we can now automate some of the steps to support clinicians' decision-making, allowing them to detect, diagnose, and monitor various cardiac conditions with greater confidence and efficiency in seconds,” said Roberto Lang, M.D., the director of the Noninvasive Cardiac Imaging Lab at the University of Chicago Medicine, who will be lecturing on AI detection of RWMAs later this month at the American Society of Echocardiography (ASE) conference in Portland, Oregon.
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