Fractional Flow Reserve Prediction Using In-House Computational Methods - Validation With Several Patient Cases
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Given the global prevalence and lethality of cardiovascular diseases (CVDs), there has been an increase in the use of numerical tools to aid their diagnosis and treatment stages [1], [2]. A numerical tool is an alternative to invasively obtaining the Fractional Flow Reserve (FFR) in patients with atherosclerosis. A non-invasive approach is a safer and more cost-effective alternative to traditional invasive procedures. Thus, the goal of this study is to predict the numerical FFR of patient-specific coronary arteries with atherosclerosis considering the most accurate physiological conditions as possible. The authors have been developing in-house computational methods to determine a non-invasive FFR. Our approach incorporates the consideration of blood viscoelasticity, a crucial factor in achieving realistic simulations, and the definition of the outlet pressure profiles using Windkessel models to ensure an accurate representation of the physiological conditions. No authors in the literature have considered these two properties simultaneously. To validate our previously developed software, we tested our tool on one representative patient case, and the preliminary results of our approach were promising. Using the 3-element Windkessel model, the relative error between the numerical and invasive FFR values is 2.15%. Using the 5-element Windkessel model, the relative error was reduced to 0.53%. This reduction seems to indicate a higher level of accuracy with the increase of the number of elements. However, further testing with more patients is needed before drawing definitive conclusions. With the increase of the study sample, the goal is to refine our methodology, choose the most appropriate pressure Windkessel model, and validate our non-invasive tool for assessment of the FFR in clinical practice. REFERENCES [1] A. Corti et al. A fully coupled computational fluid dynamics – agent-based model of atherosclerotic plaque development: Multiscale modeling framework and parameter sensitivity analysis in Comput. Biol. Med., 118:103623, 2020. [2] World Heart Federation. World Heart Report 2023: Confronting the World’s Number One Killer, 1–52, 2023.