ArticleBioengineering (Basel, Switzerland)2025
Hemodynamics of Proximal Coronary Lesions in Patients Undergoing Transcatheter Aortic Valve Implantation: Patient-Specific In Silico Study.
Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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