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. 2022 Apr:216:106674.
doi: 10.1016/j.cmpb.2022.106674. Epub 2022 Feb 1.

Real time reduced order model for angiography fractional flow reserve

Javad Hashemi  1 , Bhavesh Patel  1 , Yiannis S Chatzizisis  2 , Ghassan S Kassab  3
Affiliations

Real time reduced order model for angiography fractional flow reserve

Javad Hashemi et al. Comput Methods Programs Biomed. 2022 Apr.

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.

Keywords: Anatomical parameters; Coronary artery stenosis; Physiological parameters; Reduced order method; Response surface method.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no conflict of interest.

Figures

Figure 1.
Figure 1.
Overall chart describing the method to derive and validate a ROM to calculate FFR.
Figure 2.
Figure 2.
Sample hyperemic boundary conditions: (a) pressure inlet (b) volume flow rate outlet.
Figure 3.
Figure 3.
schematic of different stenosis shapes and different factors.
Figure 4.
Figure 4.
(a) Interaction AB for concentric and (b) eccentric stenosis and (c) interaction BD for concentric and (d) eccentric stenosis in first design.
Figure 4.
Figure 4.
(a) Interaction AB for concentric and (b) eccentric stenosis and (c) interaction BD for concentric and (d) eccentric stenosis in first design.
Figure 5.
Figure 5.
(a) Interaction AB for concentric and (b) eccentric stenosis and (c) interaction BD for concentric and (d) eccentric stenosis in the second design.
Figure 5.
Figure 5.
(a) Interaction AB for concentric and (b) eccentric stenosis and (c) interaction BD for concentric and (d) eccentric stenosis in the second design.
Figure 6.
Figure 6.
(a) Interaction AB for concentric and (b) eccentric stenosis and (c) interaction BD for concentric and (d) eccentric stenosis in third design.
Figure 6.
Figure 6.
(a) Interaction AB for concentric and (b) eccentric stenosis and (c) interaction BD for concentric and (d) eccentric stenosis in third design.
Figure 7.
Figure 7.
(a) Interaction AB for concentric and (b) eccentric stenosis and (c) interaction BD for concentric and (d) eccentric stenosis in the fourth design.
Figure 7.
Figure 7.
(a) Interaction AB for concentric and (b) eccentric stenosis and (c) interaction BD for concentric and (d) eccentric stenosis in the fourth design.
Figure 8.
Figure 8.
(a) ROM-FFR and pressure-wire FFR for 100 coronary arteries, (b) Receiver operator characteristic (ROC) curve analysis for predicted-FFR against pressure-wire FFR (area under curve=0.947), (c) Bland-Altman analysis, and (d) visualization of ROM-FFR for patient A with FFR 0.9 and patient B with FFR 0.62.
Figure 8.
Figure 8.
(a) ROM-FFR and pressure-wire FFR for 100 coronary arteries, (b) Receiver operator characteristic (ROC) curve analysis for predicted-FFR against pressure-wire FFR (area under curve=0.947), (c) Bland-Altman analysis, and (d) visualization of ROM-FFR for patient A with FFR 0.9 and patient B with FFR 0.62.
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