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. 2025 Mar 26;12(4):339.
doi: 10.3390/bioengineering12040339.

Hemodynamics of Proximal Coronary Lesions in Patients Undergoing Transcatheter Aortic Valve Implantation: Patient-Specific In Silico Study

Yahia Bellouche  1   2   3 , Sirine Abdelli  1   2 , Sinda Hannachi  1   2 , Clement Benic  1   2   3 , Florent Le Ven  1   2   3 , Romain Didier  1   2   3
Affiliations

Hemodynamics of Proximal Coronary Lesions in Patients Undergoing Transcatheter Aortic Valve Implantation: Patient-Specific In Silico Study

Yahia Bellouche et al. Bioengineering (Basel). .

Abstract

Aortic stenosis (AS) frequently coexists with coronary artery disease (CAD), complicating revascularization decisions. The use of coronary physiology indices, such as the fractional flow reserve (FFR), instantaneous wave-free ratio (iFR), and coronary flow reserve (CFR), in AS patients remains debated, particularly after transcatheter aortic valve implantation (TAVI). In this study, we employ computational fluid dynamics (CFD) to evaluate coronary hemodynamics and assess changes in the wall shear stress (WSS) before and after TAVI. Our analysis demonstrates strong agreement between CFD-derived and invasive FFR measurements, confirming CFD's reliability as a non-invasive tool for coronary physiology assessment. Furthermore, our results show no significant changes in FFR (p=0.92), iFR (p=0.67), or CFR (p=0.34) post-TAVI, suggesting that these indices remain stable following aortic valve intervention. However, a significant reduction in high WSS exposure (59% to 40.8%, p<0.001) and the oscillatory shear index (OSI: 0.32 to 0.21, p<0.001) was observed, indicating improved hemodynamic stability. These findings suggest that coronary physiology indices remain reliable for revascularization guidance post-TAVI and highlight a potential beneficial effect of aortic stenosis treatment on plaque shear stress dynamics. Our study underscores the clinical utility of CFD modeling in CAD management, paving the way for further research into its prognostic implications.

Keywords: aortic stenosis (AS); computational fluid dynamics (CFD); coronary artery disease (CAD); fractional flow reserve (FFR); instantaneous wave-free ratio (iFR); transcatheter aortic valve implantation (TAVI); wall shear stress (WSS).

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Pathophysiology of microvascular dysfunction in aortic stenosis patients.
Figure 2
Figure 2
Examples of computational fluid dynamics applications in cardiovascular medicine.
Figure 3
Figure 3
Study flowchart.
Figure 4
Figure 4
Simvascular platform pipeline for vascular simulations.
Figure 5
Figure 5
Problem specification of the inlet, ascending thoracic aorta, and coronary outlets for simulations of blood flow (Details in text).
Figure 6
Figure 6
Metrics used for wall shear stress (WSS) analysis.
Figure 7
Figure 7
Study detailed workflow.
Figure 8
Figure 8
Bland–Altman analysis of invasive FFR vs. CFD-derived FFR. Agreement between invasive and CFD-derived FFR, with the x-axis representing their average and the y-axis showing the percentage difference. The solid black line indicates the mean bias, while the dotted blue lines represent the Limits of Agreement (LOA: −5.277% to 2.305%). CFD: Computational fluid dynamics.
Figure 9
Figure 9
iFR variation by patient before and after AVR. AVR: Aortic valve replacement.
Figure 10
Figure 10
FFR variation by patient before and after AVR. AVR: Aortic valve replacement.
Figure 11
Figure 11
CFR variation by patient before and after AVR. AVR: Aortic valve replacement.
Figure 12
Figure 12
Examples of time average wall shear stress distribution (TAWSS) (in pascal) in two patients before and after aortic valve replacement (AVR).
See this image and copyright information in PMC

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