AI Algorithm Flags and Triages Suspected Abdominal Aortic Aneurysms from CTA Images

An abdominal aortic aneurysm (AAA) denotes a bulge in the abdominal aorta, the chief artery that transfers blood from the heart to other parts of the body. If not detected and treated in time, AAA can cause a rupture, which frequently results in fatality. The majority of individuals affected by AAA do not exhibit any symptoms, and many remain oblivious to their condition until a rupture occurs. Now, a novel artificial intelligence (AI) algorithm flags and triages suspected AAA cases, facilitating healthcare providers in swiftly identifying and detecting individuals with AAA, while also automatically directing those at imminent risk of rupture for further evaluation and care.

Viz AAA from Viz.ai, Inc. (San Francisco, CA, USA) is the first FDA-cleared AI-powered solution for the detection and triage of suspected AAA. Viz AAA leverages the power of AI to automatically scan computed tomography angiography (CTA) images from any scanner in a hospital network to identify the presence of an AAA. The new AI algorithm and clinical workflow solution are part of the Viz AORTIC Module, an AI-based system devised to expedite treatment decisions for all types of aortic pathology. The software can be seamlessly integrated into existing hospital workflows, allowing physicians to swiftly and effortlessly detect patients exhibiting signs of a suspected AAA and initiate appropriate measures to prevent a rupture. Viz.ai is collaborating with prominent hospitals and healthcare providers to implement Viz AAA into their clinical workflows.

“AAA is an important and actionable incidental finding that is too-often missed,” said Jayme Strauss, chief clinical officer at Viz.ai. “The vision behind Viz AAA is to automatically catch and follow abdominal aortic disease, no matter the patient’s location. We believe that this product will enable care teams to prevent catastrophic aortic emergencies, such as aortic rupture, by increasing the surveillance of these patients.”

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