June 3, 2024
Élodie Labrecque Langlais, Denis Corbin, Olivier Tastet, Ahmad Hayek, Gemina Doolub, Sebastián Mrad, Jean-Claude Tardif, Jean-François Tanguay, Guillaume Marquis-Gravel, Geoffrey H. Tison, Samuel Kadoury, William Le, Richard Gallo, Frederic Lesage & Robert Avram
Evaluation of stenoses using AI video models applied to coronary angiography

Coronary artery disease involves the narrowing of heart blood vessels of the heart, also known as. stenoses, and stands as a major global cause of mortality, requiring accurate evaluation for effective treatment. The existing gold standard for assessing stenosis severity, which relies on visual interpretation of coronary angiography videos by cardiologists, shows significant variability, highlighting the necessity for standardized, objective methods. AI-based algorithms have been developed to overcome this issue, but these methods have inherent limitations which are addressed with DeepCoro.

What is DeepCoro?

DeepCoro, a novel AI-driven pipeline, redefines stenosis severity assessment by leveraging advanced algorithms to analyze coronary angiography videos comprehensively. Unlike previous stenosis assessment methods, DeepCoro is a series of video-based models. It leverages the temporal dimension of an geographic videos, capturing the dynamic nature of the heart and stenoses. This innovative approach allows DeepCoro to surpass the performance of all other similar methods, which lack this crucial consideration of temporal dynamics. Trained on extensive real-world data, DeepCoro offers unparalleled precision in identifying stenoses, enhancing diagnostic reliability in stenosis evaluation.

How DeepCoro Works

DeepCoro integrates cutting-edge algorithms for video alignment, vessel segmentation, coronary structure identification and stenosis severity prediction. By harnessing the temporal dimension of coronary angiography videos, DeepCoromimics cardiologists' comprehensive analysis, ensuring precise stenosis assessment.

Figure 1.DeepCORO Pipeline

Benefits of DeepCoro

DeepCoroout performs existing methods, demonstrating superior precision and reduced variability in stenosis severity prediction. DeepCoro draws insights from a vast dataset of more than 180,000 angiographic videos. This extensive dataset serves as the backbone of DeepCoro's robust performance and reproducibility, ensuring reliable stenosis assessment and enhancing clinical decision-making. Moreover, DeepCoro has shown robust adaptability for assessing stenoses using alternative evaluation techniques such as Quantitative Coronary Angiography. The public access for inference and model weights also facilitates customization for diverse user needs, ensuring its utility across a range of clinical contexts and bolstering diagnostic reliability.

Figure 2.DeepCORO Performance

Table 1.DeepCORO Performance compared to clinical reports performance of stenosis classification and regression against a core lab

DeepCoro significantly outperforms clinical reports in sensitivity, AUROC, and AUPRC, with reduced variability in classification and regression metrics, highlighting its higher accuracy and consistency in evaluating angiograms compared to a single cardiologist's clinical reports, when compared to a core lab adjudication of the exams.


DeepCoro offers a standardized and objective approach to coronary angiography interpretation. Its superior performance and adaptability hold promise for future applications, potentially streamlining clinical workflows and enhancing patient outcomes by facilitating informed treatment decisions. As DeepCoro continues to evolve, its impact on clinical practice and patient care is poised to be transformative.