Abstract
Bicuspid aortic valve (BAV), the most common congenital valvular abnormality, generates asymmetric flow patterns and increased stresses on the leaflets that expedite valvular calcification and structural degeneration. Recently adapted for use in BAV patients, TAVR demonstrates promising performance, but post-TAVR complications tend to get exacerbated due to BAV anatomical complexities. Utilizing patient-specific computational modeling, we address some of these complications. The degree and location of post-TAVR PVL was assessed, and the risk of flow-induced thrombogenicity was analyzed in 3 BAV patients — using older generation TAVR devices that were implanted in these patients, and compared them to the performance of the newest generation TAVR devices using in silico patient models. Significant decrease in PVL and thrombogenic potential was observed after implantation of the newest generation device. The current work demonstrates the potential of using simulations in pre-procedural planning to assess post-TAVR complications, and compare the performance of different devices to achieve better clinical outcomes.
Graphical abstract
Patient-specific computational framework to assess post-transcatheter bicuspid aortic valve replacement paravalvular leakage and flow-induced thrombogenic complications and compare device performances.
Similar content being viewed by others
Abbreviations
- BAV:
-
Bicuspid aortic valve
- CFD:
-
Computational fluid dynamics
- FE :
-
Finite element
- LCL:
-
Left coronary leaflet
- LVOT:
-
Left ventricular outflow tract
- NCL:
-
Non-coronary leaflet
- PPI:
-
Permanent pacemaker Implantation
- PVL:
-
Paravalvular leak
- RCL:
-
Right coronary leaflet
- SAVR:
-
Surgical aortic valve replacement
- TAVR:
-
Transcatheter aortic valve replacement
References
Braverman, A. C., et al. (2005). The bicuspid aortic valve. Curr Problems in Cardiology, 30, 470–522. https://doi.org/10.1016/j.cpcardiol.2005.06.002
Losenno, K. L., Goodman, R. L., & Chu, M. W. A. (2012). Bicuspid aortic valve disease and ascending aortic aneurysms: Gaps in knowledge. Cardiology Research and Practice, 2012, 145202. https://doi.org/10.1155/2012/145202
Ward, C. (2000). Clinical significance of the bicuspid aortic valve. Heart, 83, 81. https://doi.org/10.1136/heart.83.1.81
Pibarot, P., & Clavel, M.-A. (2017). Outcome of aortic valve replacement in aortic stenosis: The number of valve cusps matters. European Heart Journal - Cardiovascular Imaging, 19, 9–11. https://doi.org/10.1093/ehjci/jex258
Depboylu, B. C., Yazman, S., & Harmandar, B. (2018). Complications of transcatheter aortic valve replacement and rescue attempts. Vessel Plus, 2, 26. https://doi.org/10.20517/2574-1209.2018.39
Braghiroli, J., Kapoor, K., Thielhelm, T. P., Ferreira, T., & Cohen, M. G. (2020). Transcatheter aortic valve replacement in low risk patients: a review of PARTNER 3 and Evolut low risk trials. Cardiovascular diagnosis and therapy, 10, 59–71. https://doi.org/10.21037/cdt.2019.09.12
O’Riordon, M. (2020). Positive early data for TAVR in low-risk patients with bicuspid valves. https://www.tctmd.com/news/positive-early-data-tavr-low-risk-patients-bicuspid-valves
Spears, J., Al-Saiegh, Y., Goldberg, D., Manthey, S., & Goldberg, S. (2020). TAVR: A review of current practices and considerations in low-risk patients. Journal of Interventional Cardiology, 2020, 2582938. https://doi.org/10.1155/2020/2582938
Vincent, F., et al. (2021). Transcatheter aortic valve replacement in bicuspid aortic valve stenosis. Circulation, 143, 1043–1061. https://doi.org/10.1161/CIRCULATIONAHA.120.048048
Yoon, S.-H., Makkar, R. R. (2018) TAVR for severe bicuspid aortic valve stenosis. American College of Cardiology. https://www.acc.org/latest-in-cardiology/articles/2018/01/19/08/14/tavr-for-severe-bicuspid-aortic-valve-stenosis
Conte, S. M., et al. (2019). Plugging paravalvular leak in transcatheter aortic valves. JACC: Case Reports, 1(696), 702. https://doi.org/10.1016/j.jaccas.2019.10.013
Halim, S. A., et al. (2020). Outcomes of transcatheter aortic valve replacement in patients with bicuspid aortic valve disease. Circulation, 141, 1071–1079. https://doi.org/10.1161/CIRCULATIONAHA.119.040333
Mauri, V., et al. (2020). Impact of device landing zone calcification patterns on paravalvular regurgitation after transcatheter aortic valve replacement with different next-generation devices. Open Heart, 7, e001164. https://doi.org/10.1136/openhrt-2019-001164
Jimenez Diaz, V. A., et al. (2019). Assessment of platelet REACtivity after transcatheter aortic valve replacement: The REAC-TAVI trial. JACC Cardiovascular Interventions, 12(22), 32. https://doi.org/10.1016/j.jcin.2018.10.005
Bianchi, M., et al. (2019). Patient-specific simulation of transcatheter aortic valve replacement: Impact of deployment options on paravalvular leakage. Biomechanics and Modeling in Mechanobiology, 18, 435–451. https://doi.org/10.1007/s10237-018-1094-8
Huded, C. P., et al. (2019). Association between transcatheter aortic valve replacement and early postprocedural stroke. JAMA, 321, 2306–2315. https://doi.org/10.1001/jama.2019.7525
Makkar, R. R., et al. (2019). Association between transcatheter aortic valve replacement for bicuspid vs tricuspid aortic stenosis and mortality or stroke. JAMA, 321, 2193–2202. https://doi.org/10.1001/jama.2019.7108
Mao, W., Wang, Q., Kodali, S., & Sun, W. (2018). Numerical parametric study of paravalvular leak following a transcatheter aortic valve deployment into a patient-specific aortic root. Journal of Biomechanical Engineering, 140, 1010071–10100711. https://doi.org/10.1115/1.4040457
Qin, T., et al. (2020). The role of stress concentration in calcified bicuspid aortic valve. Journal of The Royal Society Interface, 17, 20190893. https://doi.org/10.1098/rsif.2019.0893
de Jaegere, P., et al. (2016). Patient-specific computer modeling to predict aortic regurgitation after transcatheter aortic valve replacement. JACC Cardiovascular Interventions, 9(508), 512. https://doi.org/10.1016/j.jcin.2016.01.003
Wang, Q., Kodali, S., Primiano, C., & Sun, W. (2015). Simulations of transcatheter aortic valve implantation: Implications for aortic root rupture. Biomechanics and modeling in mechanobiology, 14, 29–38. https://doi.org/10.1007/s10237-014-0583-7
Bosi, G. M., et al. (2020). A validated computational framework to predict outcomes in TAVI. Scientific Reports, 10, 9906. https://doi.org/10.1038/s41598-020-66899-6
Lavon, K., et al. (2019). Biomechanical modeling of transcatheter aortic valve replacement in a stenotic bicuspid aortic valve: Deployments and paravalvular leakage. Medical & biological engineering & computing, 57, 2129–2143. https://doi.org/10.1007/s11517-019-02012-y
Pasta, S., et al. (2020). Simulation study of transcatheter heart valve implantation in patients with stenotic bicuspid aortic valve. Medical & Biological Engineering & Computing, 58, 815–829. https://doi.org/10.1007/s11517-020-02138-4
Dowling, C., Firoozi, S., & Brecker, S. J. (2020). First-in-human experience with patient-specific computer simulation of TAVR in bicuspid aortic valve morphology. JACC: Cardiovascular Interventions, 13, 184–192. https://doi.org/10.1016/j.jcin.2019.07.032
Bianchi, M., et al. (2016). Effect of balloon-expandable transcatheter aortic valve replacement positioning: A patient-specific numerical model. Artificial Organs, 40, E292-e304. https://doi.org/10.1111/aor.12806
Martin, C., & Sun, W. (2012). Biomechanical characterization of aortic valve tissue in humans and common animal models. Journal of Biomedical Materials Research Part A, 100A, 1591–1599. https://doi.org/10.1002/jbm.a.34099
Emendi, M., et al. (2021). Patient-specific bicuspid aortic valve biomechanics: A magnetic resonance imaging integrated fluid–structure interaction approach. Annals of Biomedical Engineering, 49, 627–641. https://doi.org/10.1007/s10439-020-02571-4
Xenos, M., et al. (2010). Device thrombogenicity emulator (DTE) — Design optimization methodology for cardiovascular devices: A study in two bileaflet MHV designs. Journal of Biomechanics, 43, 2400–2409.
Girdhar, G., et al. (2012). Device thrombogenicity emulation: A novel method for optimizing mechanical circulatory support device thromboresistance. PLoS One, 7, e32463.
Chiu, W. C., et al. (2014). Thromboresistance comparison of the heartmate II ventricular assist device with the device thrombogenicity emulation-optimized heartassist 5 VAD. Journal of Biomechanical Engineering, 136, 021014. https://doi.org/10.1115/1.4026254
Pibarot, P., Hahn Rebecca, T., Weissman Neil, J., & Monaghan Mark, J. (2015). Assessment of paravalvular regurgitation following TAVR. JACC: Cardiovascular Imaging, 8, 340–360. https://doi.org/10.1016/j.jcmg.2015.01.008
Forrest, J. K., et al. (2020). Transcatheter aortic valve replacement in bicuspid versus tricuspid aortic valves from the STS/ACC TVT Registry. JACC Cardiovascular Interventions, 13, 1749–1759. https://doi.org/10.1016/j.jcin.2020.03.022
Mas-Peiro, S., Fichtlscherer, S., Walther, C., & Vasa-Nicotera, M. (2020). Current issues in transcatheter aortic valve replacement. Journal of thoracic disease, 12, 1665–1680. https://doi.org/10.21037/jtd.2020.01.10
Jones, B. M., et al. (2016). Prognostic significance of mild aortic regurgitation in predicting mortality after transcatheter aortic valve replacement. Journal of Thoracic and Cardiovascular Surgery, 152, 783–790. https://doi.org/10.1016/j.jtcvs.2016.05.023
Mack, M. J., et al. (2015). 5-year outcomes of transcatheter aortic valve replacement or surgical aortic valve replacement for high surgical risk patients with aortic stenosis (PARTNER 1): A randomised controlled trial. Lancet, 385, 2477–2484. https://doi.org/10.1016/s0140-6736(15)60308-7
Yoon, S.-H., et al. (2020). Bicuspid aortic valve morphology and outcomes after transcatheter aortic valve replacement. Journal of the American College of Cardiology, 76, 1018–1030. https://doi.org/10.1016/j.jacc.2020.07.005
Acknowledgements
We would like thank SeaWulf Cluster at Stony Brook University for providing computational resources and Simulia Living Heart Project and Ansys for academic collaborations and providing Abaqus and Ansys software.
Funding
This project was supported by National Institutes of Health-National Institute of Biomedical Imaging and Bioengineering U01EB026414-01 (DB).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethical Approval and Informed Consent
All procedures involving human participants followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national research) and with the Helsinki Declaration of 1975, as revised in 2000. A waiver of consent was approved by the Stony Brook Committee on Research in Human Subjects (CORIHS-2013–2357-F) and Rabin Medical Center Helsinki Committee (0636–16-RMC) for retrospective collection of de-identified patient images. No animal studies were carried out by the authors for this article.
Conflict of Interest
Author DB has an equity interest in Polynova Cardiovascular Inc. Author BK is a consultant of Polynova Cardiovascular Inc. All the other authors declare no conflict of interest.
IRB Approval
2013–2357-R5, 2/10/2021
Additional information
Associate Editor Adrian Chester oversaw the review of this article
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Anam, S.B., Kovarovic, B.J., Ghosh, R.P. et al. Assessment of Paravalvular Leak Severity and Thrombogenic Potential in Transcatheter Bicuspid Aortic Valve Replacements Using Patient-Specific Computational Modeling. J. of Cardiovasc. Trans. Res. 15, 834–844 (2022). https://doi.org/10.1007/s12265-021-10191-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12265-021-10191-z