Real time reduced order model for angiography fractional flow reserve. (April 2022)

• Record Type: Journal Article
• Authors: Hashemi, Javad; Patel, Bhavesh; Chatzizisis, Yiannis S.; Kassab, Ghassan S.
• Is Part Of: Computer methods and programs in biomedicine. Volume 216(2022)
• Publication Date: 2022-04
• Subjects: Anatomical parameters -- Physiological parameters -- Response surface method -- Coronary artery stenosis -- Reduced order method; 3D Three Dimonsional -- CCTA Coronary CT Angiography -- CFD Computational Fluid Dynamics -- DOE Design of Experiments -- FFR Fractional Flow Reserve -- LAD Left Anterior Descending -- LCx Left Circumflex -- OM Obtuse Marginal -- RCA Right Coronary Artery -- ROM Reduced Order Model -- RSM Response Surface Method; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2022.106674
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: The ROM can be used to reliably calculate FFR in patients with intermediate coronary stenosis. The ROM can replace time-consuming CFD-based FFR estimation and provide instead a real-time calculation method. The ROM-FFR is validated against in One hundred arteries from ninety patients who had undergone FFR measurements. Abstract: Background and Objectives: Fractional flow reserve (FFR) is the gold standard for quantification of coronary stenosis and pressure wire is the gold standard for measuring FFR. Recently, computational fluid dynamics (CFD) methods have been used to compute FFR less invasively using images obtained from coronary angiography. This approach is, however, computationally intensive and solutions to reduce computation time are clearly required. Methods: We hypothesized that FFR can be calculated instantly using a reduced order model (ROM) derived using response surface method (RSM) for simulation modeling in lieu of the computationally intensive CFD. Specifically, eleven physiological and anatomical factors known to affect FFR were selected as input variables, and Plackett–Burman analysis was performed in conjunction with CFD on model arteries to identify set of variables affecting FFR the most. Based on the Box–Behnken design, a mathematical model was developed to compute FFR using the retained set of variables. Results: The model fidelity was tested on a cohort of 90 patients (100 coronary arteries) with known pressure-wire FFR. FFR derived from this ROM had a strong correlation with pressure-wire FFR with sensitivity of 89.4%, specificity of 100% and area under curve of 0.947 ( p < 0.05). Conclusions: The ROM method can be used to reliably calculate FFR in patients with coronary stenosis and able to replace time-consuming CFD-based FFR estimation and provide instead a real-time calculation method.