NASHVILLE, Tenn.--(BUSINESS WIRE)--Bay Labs, a medical technology company at the forefront of applying artificial intelligence (AI) to cardiovascular imaging, today announced its EchoMD AutoEF deep learning software has less variability in evaluating left ventricular ejection fraction (EF) than the average variability of cardiologists reported in literature, as demonstrated in a study conducted with the Minneapolis Heart Institute. Results of the study were presented today at the 2018 American Society of Echocardiography (ASE) Annual Scientific Sessions.
Literature shows that the average variability of cardiologist readers using the Simpson’s biplane method in estimating EF is 9.2%. The observed variability of EchoMD AutoEF was superior at 8.29% (p = 0.002). The study also demonstrated that EchoMD AutoEF is an accurate and fully automated method of calculating EF from complete echocardiographic patient studies without user intervention. In addition to normal patients, it performed well on obese patients and on patients with a range of normal and abnormal EF.
“Historically there have been challenges with variability and reproducibility in reporting of the ejection fraction, especially when the EF is not normal; our study showed that the EchoMD AutoEF algorithms can aid interpretation enormously and have less variability than cardiologists reported in literature,” said Richard Bae, MD, FACC, Director of the Echocardiography Laboratory at the Minneapolis Heart Institute and co-author of the study. “By supporting fast, efficient and accurate AI-assisted echocardiogram analysis, the algorithms can allow physicians to focus on putting results into context for the patient - guiding prognosis and course of management.”
The study included 405 echocardiographic patient studies from Minneapolis Heart Institute representing a wide range of body mass index, EF values and of ultrasound systems. For each patient study, the Bay Labs’ software automatically selected optimal apical four chamber and apical two chamber digital video clips and used them to perform an EF calculation. These calculations were compared to the standard Simpson’s biplane method.
“Bay Labs EchoMD AutoEF was shown to automatically provide accurate EF calculations, and our hope is that this will assist cardiologists in their decision making,” said Charles Cadieu, co-founder and CEO of Bay Labs. “At Bay Labs, we are reimagining the detection, monitoring and timing of treatment for cardiovascular disease with our unique applications of AI.”
About the EchoMD AutoEF Software Algorithms
EchoMD AutoEF automatically reviews all the relevant digital video clips from a patient’s echocardiography study, rates them according to image quality, and selects the best ones to calculate EF. EchoMD AutoEF eliminates the need to manually select views, choose the best clips, and manipulate them for quantification, an often time-consuming and highly variable process. EchoMD AutoEF was trained on a carefully curated dataset of over 4,000,000 images, representing 9,000 patients. The software product recently received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for the fully automated clip selection and calculation of left ventricular EF. EchoMD AutoEF can be integrated into any DICOM PACS medical imaging environment and provides cardiologists with results as a seamless part of routine diagnostic workflow. To learn more about Bay Labs’ EchoMD AutoEF software and how AI-assisted interpretation could benefit medical practices and patients, visit www.baylabs.io/.
About Bay Labs
Bay Labs is a San Francisco-based privately held company focused on increasing quality, value and access to medical imaging by combining AI and ultrasound. Founded in 2013, Bay Labs applies artificial intelligence to cardiovascular imaging, and its deep learning technology is designed to help medical professionals of all skill levels perform and interpret high-quality echocardiography to ultimately benefit their patients. There are over 10 million echoes performed annually in the United States, and according to the Centers for Disease Control, over 600,000 people in the U.S. die from cardiovascular disease each year making it the cause of one in four deaths. Bay Labs is funded by Khosla Ventures, Data Collective, and other leading venture capital firms. For more information about Bay Labs, visit www.baylabs.io/.