Ai TooLs to chAracterize and identify uNstable aTherosclerotIc plaqueS (ATLANTIS)

Strokes and myocardial infarctions, caused by the rupture of unstable atherosclerotic plaques in the carotid and coronary arteries, are the leading causes of death world-wide. Current clinical guidelines recommend surgical removal of plaques based solely on the degree of artery stenosis. However, stenosis alone is an incomplete determinant of stroke/heart attack risk, leading to suboptimal medical decisions or inappropriate treatment allocation. Although plaque composition is a more accurate indicator of plaque instability and a better predictor of clinical outcomes, no method currently exists for its accurate, quantitative, and non-invasive characterization. We aim to develop artificial intelligence-based platforms to characterize atherosclerotic plaque features from 1) histological and 2) ultrasound plaque images. These platforms will provide a complete and accurate analysis of plaque features and instability, while eliminating bias and inter-individual variability. This method can be used to improve the prediction, treatment, and prevention of heart attacks and strokes.

Faculty Supervisor:

Ioannis Psaromiligkos

Student:

Partner:

Sonaro

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology; Biotechnology; Technology

University:

Research Institute of the McGill University Health Centre

Program: