Feasibility of a Deep Learning-based Algorithm for Non-invasive Assessment of Vulnerable Coronary Plaque

The primary objective of this study is to assess the accuracy in terms of sensitivity, specificity, negative and positive predicted values of the DL-based algorithm with respect to correct identification of the plaque and associated vulnerability grade.

Data collected in this study will be used for technology development, scientific evaluation, education, and regulatory submissions for future products. This is a pre-market, open label, prospective, non-randomized clinical research study conducted at one site in Italy. The product being researched is the Deep Learning-based (DL) algorithm for non-invasive detection of vulnerable coronary plaque.