New AI Can Automatically Detect a Serious Heart Condition the Utilizing intravascular optical coherence tomography images, a new technique made it easier to identify plaque erosion
Researchers have created a brand-new artificial intelligence (AI) technique that uses optical coherence tomography (OCT) images to automatically detect plaque erosion in the arteries of the heart. Monitoring arterial plaque is crucial because, if it disintegrates, it may obstruct blood flow to the Heart Condition, triggering a heart attack or other dangerous problems. “If cholesterol plaque lining arteries starts to erode it can lead to a sudden reduction in blood flow to the Heart Condition known as acute coronary syndrome, which requires urgent treatment,” said research team leader Zhao Wang from the University of Electronic Science and Technology of China. “Our new method could help improve the clinical diagnosis of plaque erosion and be used to develop new treatments for patients with heart disease.”
OCT is an optical imaging technique with micron-scale resolution that may be utilized within blood vessels to produce 3D pictures of the coronary arteries, which carry blood to the heart. Although intravascular OCT is being used by doctors more frequently to check for plaque erosion, there is a substantial level of interobserver variability because of the volume of data generated and the difficulty of visually interpreting the images. In order to address this issue, Wang collaborated with a team of engineers from his institution and medical professionals from The 2nd Affiliated Hospital of Harbin Medical University under the direction of Bo Yu to create an automated, objective method that uses AI to identify plaque erosion based on OCT images. They explain the new method in the Optica Publishing Group journal Biomedical Optics Express and demonstrate that it is accurate enough to possibly serve as the foundation for clinical diagnosis. “Our new AI-based method can automatically detect the presence of plaque erosion using the original OCT images without any additional input,” said Wang. “The ability to detect plaque erosion objectively and automatically will reduce the laborious manual assessment associated with diagnosis.”
Source: This news is originally published by scitechdaily