Date of Award

5-2023

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Biomedical and Chemical Engineering and Sciences

First Advisor

Peshala Priyadarshana Thibbotuwawa Gamage

Second Advisor

Linxia Gu

Third Advisor

Pengfei Dong

Fourth Advisor

Kenia Pedrosa Nunes

Abstract

Coronary Artery Disease (CAD) affects millions of people worldwide and remains a leading cause of morbidity and mortality. To effectively plan treatment and risk stratification, assessing CAD severity is of paramount importance. Fractional flow reserve (FFR) is a critical clinical parameter used to evaluate CAD severity, measured by the ratio of mean distal coronary pressure to mean aortic pressure during hyperemic conditions. Although non-invasive FFR estimation methods have gained popularity, computational fluid dynamics (CFD) is impractical for routine clinical use due to the time and resources required. To address this issue, a reduced order model is proposed that accurately captures hyperemic conditions and considers the effect of side branch flow on FFR. The model approximates artery sections and branches using Windkessel models and simulates hyperemic conditions by varying microvascular resistance. Preliminary results from this study show that the proposed model effectively captures hyperemic conditions and the impact of side branch flow on FFR, providing critical insights for clinical decision-making. This approach presents a promising way to evaluate CAD severity more efficiently and accurately using non-invasive methods, paving the way for non-invasive assessment of CAD severity. Further studies are necessary to validate the model's accuracy and its potential for clinical translation.

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