Artificial Intelligence Helps Detect Plaque Erosion in Heart Arteries

In what may lead to the development of new treatments for heart diseases, researchers have created a novel artificial intelligence (AI) technique that can detect plaque erosion in heart arteries. The technique uses optical coherence tomography (OCT) images to monitor arterial plaque. The finding is crucial as the disintegration of the plaque can serve as a prelude to a heart attack or other severe heart diseases. The OCT, which is an optical imaging technique, can be used within blood vessels to produce 3D pictures of the coronary arteries that carry blood to the heart muscles.

The OCT technique has been in use for spotting plaque erosion. But, the volume of data generated and the difficulty in interpreting the images causes substantial interobserver variability. In a bid to solve this, researchers introduced AI in the OCT technique to identify plaque erosion.

“If cholesterol plaque lining arteries starts to erode it can lead to a sudden reduction in blood flow to the heart known as acute coronary syndrome, which requires urgent treatment. Our new method could help improve the clinical diagnosis of plaque erosion and be used to develop new treatments for patients with heart disease,” said Zhao Wang from the University of Electronic Science and Technology of China. Wang is also the lead author of the study published in Biomedical Optics Express.

The new AI method consists of two primary steps where first an AI model known as neural network analyses the original image and two pieces of shape information to predict the regions of plaque erosion.

This prediction is then refined through a post-processing algorithm that mimics the knowledge of professional physicians to do the diagnosis. “We had to develop a new AI model that incorporates explicit shape information, the key feature used to identify plaque erosion in OCT images. The underlying intravascular OCT imaging technology is also crucial because it is currently the highest resolution imaging modality that can be used to diagnose plaque erosion in living patients,” said Wang.

The researchers tested the new technique and found that the automated method could predict 80 per cent of the plaque erosion cases with 73 per cent positive predictive value. Moreover, the diagnosis done using AI technique matched well with those conducted by experienced physicians.