FDA clears new AI model for MAC detection in routine imaging results
San Francisco-based Bunkerhill Health has received U.S. Food and Drug Administration (FDA) clearance for its new advanced artificial intelligence (AI) algorithm designed to detect and evaluate mitral annular calcification (MAC) on routine, non-gated CT scans.
According to Bunkerhill Health, the AI model—known as Bunkerhill MAC—is the first AI model cleared by the FDA to identify signs of MAC, a known cardiovascular disease risk factor. It was developed and tested using data from more than 25 academic medical centers.
“MAC may be missed on imaging, but it carries prognostic value for cardiovascular risk and procedural outcomes,” Alexander Sandhu, MD, MS, assistant professor in the division of cardiology at Stanford University School of Medicine, said in a statement. Stanford is one of the schools that provided data for the development of Bunkerhill MAC. “A tool that can automatically identify and quantify MAC on routine chest CT scans gives us a way to capture this information consistently and at scale, which could help guide decision-making and research across cardiology and structural heart care.”
“FDA clearance of this algorithm is a landmark not just for Bunkerhill, but for how we use routine data to advance cardiac care,” added Nishith Khandwala, co-founder and CEO of Bunkerhill Health. “By making MAC quantification available at scale through routine CT scans, we’re giving clinicians a new tool to better understand risk and tailor patient care, all embedded seamlessly into the workflows they already use.”
Bunkerhill MAC is now officially part of Carebricks, Bunkerhill Health’s generative AI platform designed to help clinicians apply various AI models to patient data. Carebricks was built to take on referral prioritization, address actionable incidents and much more. It is already being used by a variety of U.S. health systems, including Cleveland Clinic and Mayo Clinic.
Bunkerhill Health was founded in 2021 by Khandwala and David Eng, two researchers from Stanford University’s Center for Artificial Intelligence in Medicine and Imaging. The company has received funding from Sequoia Capital, Optum Ventures, SciFi VC and other big-name investors.
Michael has more than 19 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.