Computational Methods to Predict the Fractional Flow Reserve in Coronary Arteries - a Literature Review
Palavras-chave:
Fractional Flow Reserve, Coronary Artery Disease, Stenosis, Numerical Methods, Non-Invasive AssessmentResumo
Coronary artery disease (CAD), characterized by the buildup of plaque in arteries restricting blood flow to the heart, requires an accurate diagnosis with the Fractional Flow Reserve (FFR) assessment. Traditional FFR measurement involves invasive procedures, but non-invasive computational methods have been explored to mitigate risks and costs. This study reviews recent literature on computational approaches to predict FFR in coronary arteries. Researchers have investigated the use of advanced hemodynamic simulations considering patient-specific real conditions in the non-invasive prediction of the FFR. This approach aims to deliver accurate FFR results for on-site diagnosis in hospitals. The integration of these non-invasive tools could improve the effectiveness of FFR assessment and diagnosis.
