Coronary Artery Disease Automatic Classification
Abstract
Atherosclerosis represents the restriction of blood flow in the heart muscle and is one of the main causes of death in the world. The assessment of atherosclerosis is challenging and is currently evaluated by the Fractional Flow Reserve (FFR) and the Quantitative Flow Ratio (QFR). Both exams are based on angiography, which is the gold standard for geometrical assessment. This study presents a pipeline to automatically determine the presence of narrowing in the right coronary artery (RCA) angiography exams, segmenting the artery silhouette, selecting regions of interest (ROIs) followed by a classification model. Initial results suggest a valid sequence of steps to classify the lesion, but require some improvements in the network architecture for better classification accuracy.References
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Chakladar, A., Gan, J., and Edsell, M. (2017). Angiograa arterial coronária. Anaesthesia Tutorial of the Week.
Cong, C., Kato, Y., Vasconcellos, H. D., Ostovaneh, M. R., Lima, J. A., and AmbaleVenkatesh, B. (2021). Deep learning-based end-to-end automated stenosis classication and localization on catheter coronary angiography. medRxiv.
Guyton, A. and Hall, J. (2006). Textbook of Medical Physiology. Elsevier Saunders.
Hideo-Kajita, A., Garcia, H., Schlofmitz, E., and Campos, C. (2019). Atualização sobre tecnologias siológicas baseadas em angiograa coronariana update on coronary angiography-based physiology technologies.
Johnson, N. P., Gould, K. L., Di Carli, M. F., and Taqueti, V. R. (2016). Invasive FFR and Noninvasive CFR in the Evaluation of Ischemia: What Is the Future? Journal of the American College of Cardiology, 67(23):2772–2788.
Loewe, C. (2019). Hemodynamically signicant coronary stenosis: Detection with CT Myocardial Perfusion Imaging versus Machine Learning Coronary CT Fractional Flow Reserve. Radiology, 293(2):315–316.
Moon, J. H., Lee, D. Y., Cha, W. C., Chung, M. J., Lee, K.-S., Cho, B. H., and Choi, J. H. (2021). Automatic stenosis recognition from coronary angiography using convolutional neural networks. Computer Methods and Programs in Biomedicine, 198:105819.
World Health Organization, W. (2020). Cardiovascular diseases. [link].
Published
2021-08-26
How to Cite
FREITAS, Samuel A.; COSTA, Cristiano A. da; RAMOS, Gabriel de O..
Coronary Artery Disease Automatic Classification. In: REGIONAL SCHOOL OF APPLIED COMPUTING FOR HEALTH (ERCAS), 8. , 2021, São Paulo.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 26-29.
DOI: https://doi.org/10.5753/ercas.2021.17431.
