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Virtual Planning and Patient-Specific Graft Design for Aortic Repairs

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Abstract

Purpose

Patients presenting with coarctation of the aorta (CoA) may also suffer from co-existing transverse arch hypoplasia (TAH). Depending on the risks associated with the surgery and the severity of TAH, clinicians may decide to repair only CoA, and monitor the TAH to see if it improves as the patient grows. While acutely successful, eventually hemodynamics may become suboptimal if TAH is left untreated. The objective of this work aims to develop a patient-specific surgical planning framework for predicting and assessing postoperative outcomes of simple CoA repair and comprehensive repair of CoA and TAH.

Methods

The surgical planning framework consisted of virtual clamp placement, stenosis resection, and design and optimization of patient-specific aortic grafts that involved geometrical modeling of the graft and computational fluid dynamics (CFD) simulation for evaluating various surgical plans. Time-dependent CFD simulations were performed using Windkessel boundary conditions at the outlets that were obtained from patient-specific non-invasive pressure and flow data to predict hemodynamics before and after the virtual repairs. We applied the proposed framework to investigate optimal repairs for six patients (n = 6) diagnosed with both CoA and TAH. Design optimization was performed by creating a combination of a tubular graft and a waterslide patch to reconstruct the aortic arch. The surfaces of the designed graft were parameterized to optimize the shape.

Results

Peak systolic pressure drop (PSPD) and time-averaged wall shear stress (TAWSS) were used as performance metrics to evaluate surgical outcomes of various graft designs and implantation. The average PSPD improvements were 28% and 44% after the isolated CoA repair and comprehensive repair, respectively. Maximum values of TAWSS were decreased by 60% after CoA repair and further improved by 22% after the comprehensive repair. The oscillatory shear index was calculated and the values were confirmed to be in the normal range after the repairs.

Conclusion

The results showed that the comprehensive repair outperforms the simple CoA repair and may be more advantageous in the long term in some patients. We demonstrated that the surgical planning and patient-specific flow simulations could potentially affect the selection and outcomes of aorta repairs.

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Abbreviations

CoA:

Coarctation of aorta

TAH:

Transverse arch hypoplasia

AAo:

Ascending aorta

DAo:

Descending aorta

BCA:

Brachiocephalic artery

LCCA:

Left common carotid artery

LSA:

Left subclavian artery

PA:

Pulmonary artery

EEEA:

Extended end-to-end anastomosis

MRI:

Magnetic resonance imaging

BSA:

Body surface area

WK:

Windkessel

PSPD:

Peak systolic pressure drop

TAWSS:

Time-averaged wall shear stress

OSI:

Oscillatory shear index

References

  1. Alkashkari, W., S. Albugami, and Z. M. Hijazi. Management of coarctation of the aorta in adult patients: state of the art. Korean Circ. J. 49:298–313, 2019. https://doi.org/10.4070/kcj.2018.0433.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Meadows, J., M. Minahan, D. B. McElhinney, et al. Intermediate outcomes in the prospective, multicenter coarctation of the aorta stent trial (COAST). Circulation. 131:1656–1664, 2015. https://doi.org/10.1161/CIRCULATIONAHA.114.013937.

    Article  PubMed  Google Scholar 

  3. Yang, L., X. Chua, D. D. Rajgor, et al. A systematic review and meta-analysis of outcomes of transcatheter stent implantation for the primary treatment of native coarctation. Int. J. Cardiol. 223:1025–1034, 2016. https://doi.org/10.1016/j.ijcard.2016.08.295.

    Article  PubMed  Google Scholar 

  4. LaDisa, J. F., R. J. Dholakia, C. A. Figueroa, et al. Computational simulations demonstrate altered wall shear stress in aortic coarctation patients treated by resection with end-to-end anastomosis. Congenit. Heart. Dis. 6:432–443, 2011. https://doi.org/10.1111/j.1747-0803.2011.00553.x.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Wendell, D. C., I. Friehs, M. M. Samyn, et al. Treating a 20 mmHg gradient alleviates myocardial hypertrophy in experimental aortic coarctation. J. Surg. Res. 218:194–201, 2017. https://doi.org/10.1016/j.jss.2017.05.053.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Nguyen, L., and S. C. Cook. Coarctation of the aorta: strategies for improving outcomes. Cardiol. Clin. 33:521–530, 2015. https://doi.org/10.1016/j.ccl.2015.07.011.

    Article  PubMed  Google Scholar 

  7. Ma, Z.-L., J. Yan, S.-J. Li, et al. Coarctation of the aorta with aortic arch hypoplasia: midterm outcomes of aortic arch reconstruction with autologous pulmonary artery patch. Chin. Med. J. (Engl.). 130:2802–2807, 2017. https://doi.org/10.4103/0366-6999.215279.

    Article  PubMed  Google Scholar 

  8. Thomson, J., A. Mulpur, R. Guerrero, et al. Outcome after extended arch repair for aortic coarctation. Heart. 2006. https://doi.org/10.1136/hrt.2004.058685.

    Article  PubMed  Google Scholar 

  9. Soynov, I., Y. Sinelnikov, Y. Gorbatykh, et al. Modified reverse aortoplasty versus extended anastomosis in patients with coarctation of the aorta and distal arch hypoplasia. Eur. J. Cardio-Thorac. Surg. 53:254–261, 2018. https://doi.org/10.1093/ejcts/ezx249.

    Article  Google Scholar 

  10. Wen, S., J. Cen, J. Chen, et al. The application of autologous pulmonary artery in surgical correction of complicated aortic arch anomaly. J. Thorac. Dis. 8:3301–3306, 2016.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Quennelle, S., A. J. Powell, T. Geva, and A. Prakash. Persistent aortic arch hypoplasia after coarctation treatment is associated with late systemic hypertension. J. Am. Heart Assoc. Cardiovasc. Cerebrovasc. Dis.4:e001978, 2015. https://doi.org/10.1161/JAHA.115.001978.

    Article  Google Scholar 

  12. Rakhra, S. S., M. Lee, A. J. Iyengar, et al. Poor outcomes after surgery for coarctation repair with hypoplastic arch warrants more extensive initial surgery and close long-term follow-up. Interact. Cardiovasc. Thorac. Surg. 16:31–36, 2013. https://doi.org/10.1093/icvts/ivs301.

    Article  PubMed  Google Scholar 

  13. Liu, X., N. Hibino, Y.-H. Loke, et al. Surgical planning and optimization of patient-specific Fontan grafts with uncertain post-operative boundary conditions and anastomosis displacement. IEEE Trans. Biomed. Eng. 2022. https://doi.org/10.1109/TBME.2022.3170922.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Loke, Y.-H., B. Kim, P. Mass, et al. Role of surgeon intuition and computer-aided design in Fontan optimization: a computational fluid dynamics simulation study. J. Thorac. Cardiovasc. Surg. 160:203-212.e2, 2020. https://doi.org/10.1016/j.jtcvs.2019.12.068.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Trusty, P. M., Z. A. Wei, T. C. Slesnick, et al. The first cohort of prospective Fontan surgical planning patients with follow up data: how accurate is surgical planning? J. Thorac. Cardiovasc. Surg. 157:1146–1155, 2019. https://doi.org/10.1016/j.jtcvs.2018.11.102.

    Article  PubMed  Google Scholar 

  16. Wu, Q., V. Cleveland, S. Aslan, et al. Hemodynamics of convergent cavopulmonary connection with ventricular assist device for Fontan surgery: a computational and experimental study. In: Bioinformatics, 2023

  17. Liu, X., B. Kim, Y.-H. Loke, et al. Semi-automatic planning and three-dimensional electrospinning of patient-specific grafts for Fontan surgery. IEEE Trans. Biomed. Eng. 69:186–198, 2022. https://doi.org/10.1109/TBME.2021.3091113.

    Article  PubMed  Google Scholar 

  18. Armstrong, A. K., J. D. Zampi, L. M. Itu, and L. N. Benson. Use of 3D rotational angiography to perform computational fluid dynamics and virtual interventions in aortic coarctation. Catheter. Cardiovasc. Interv. 95:294–299, 2020. https://doi.org/10.1002/ccd.28507.

    Article  PubMed  Google Scholar 

  19. Aslan, S., X. Liu, Q. Wu, et al. Virtual planning and simulation of coarctation repair in hypoplastic aortic arches: is fixing the coarctation alone enough? In: Bioinformatics, pp. 138–143, 2022

  20. Backer, C. L., C. Mavroudis, E. A. Zias, et al. Repair of coarctation with resection and extended end-to-end anastomosis. Ann. Thorac. Surg. 66:1365–1370, 1998. https://doi.org/10.1016/S0003-4975(98)00671-7.

    Article  CAS  PubMed  Google Scholar 

  21. Lopez, L., S. Colan, M. Stylianou, et al. Relationship of echocardiographic z scores adjusted for body surface area to age, sex, race, and ethnicity: the pediatric heart network normal echocardiogram database. Circ. Cardiovasc. Imaging. 10:e006979, 2017. https://doi.org/10.1161/CIRCIMAGING.117.006979.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Kaiser, T., C. J. Kellenberger, M. Albisetti, et al. Normal values for aortic diameters in children and adolescents—assessment in vivo by contrast-enhanced CMR-angiography. J. Cardiovasc. Magn. Reson. 10:56, 2008. https://doi.org/10.1186/1532-429X-10-56.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Aslan, S., Y.-H. Loke, P. Mass, et al. Design and simulation of patient-specific tissue-engineered bifurcated right ventricle-pulmonary artery grafts using computational fluid dynamics. In: 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE). pp. 1012–1018, 2019

  24. Itu, L., D. Neumann, V. Mihalef, et al. Non-invasive assessment of patient-specific aortic haemodynamics from four-dimensional flow MRI data. Interface Focus. 8:20170006, 2017. https://doi.org/10.1098/rsfs.2017.0006.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Aslan, S., P. Mass, Y.-H. Loke, et al. Non-invasive prediction of peak systolic pressure drop across coarctation of aorta using computational fluid dynamics. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. 2020:2295–2298, 2020. https://doi.org/10.1109/EMBC44109.2020.9176461.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Karmonik, C., A. Brown, K. Debus, et al. CFD challenge: predicting patient-specific hemodynamics at rest and stress through an aortic coarctation. In: Statistical atlases and computational models of the heart. Imaging and modelling challenges, edited by O. Camara, T. Mansi, M. Pop, et al. Berlin: Springer, 2014, pp. 94–101.

    Chapter  Google Scholar 

  27. Dux-Santoy, L., A. Guala, J. Sotelo, et al. Low and oscillatory wall shear stress is not related to aortic dilation in patients with bicuspid aortic valve. Arterioscler. Thromb. Vasc. Biol. 40:e10–e20, 2020. https://doi.org/10.1161/ATVBAHA.119.313636.

    Article  CAS  PubMed  Google Scholar 

  28. Boumpouli, M., E. L. Sauvage, C. Capelli, et al. Characterization of flow dynamics in the pulmonary bifurcation of patients with repaired tetralogy of fallot: a computational approach. Front. Cardiovasc. Med. 8:703717, 2021.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Hathcock, J. J. Flow effects on coagulation and thrombosis. Arterioscler. Thromb. Vasc. Biol. 26:1729–1737, 2006. https://doi.org/10.1161/01.ATV.0000229658.76797.30.

    Article  CAS  PubMed  Google Scholar 

  30. Wang, H., D. Balzani, V. Vedula, et al. On the potential self-amplification of aneurysms due to tissue degradation and blood flow revealed from FSI simulations. Front. Physiol.12:785780, 2021. https://doi.org/10.3389/fphys.2021.785780.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Peters, B., P. Ewert, and F. Berger. The role of stents in the treatment of congenital heart disease: current status and future perspectives. Ann. Pediatr. Cardiol. 2:3–23, 2009. https://doi.org/10.4103/0974-2069.52802.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Bürk, J., P. Blanke, Z. Stankovic, et al. Evaluation of 3D blood flow patterns and wall shear stress in the normal and dilated thoracic aorta using flow-sensitive 4D CMR. J. Cardiovasc. Magn. Reson. 14:84, 2012. https://doi.org/10.1186/1532-429X-14-84.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Rafieianzab, D., M. A. Abazari, M. Soltani, and M. Alimohammadi. The effect of coarctation degrees on wall shear stress indices. Sci. Rep. 11:12757, 2021. https://doi.org/10.1038/s41598-021-92104-3.

    Article  CAS  Google Scholar 

  34. Kwon, S., J. Feinstein, R. Dholakia, and J. LaDisa. Quantification of local hemodynamic alterations caused by virtual implantation of three commercially available stents for the treatment of aortic coarctation. Pediatr. Cardiol. 2013. https://doi.org/10.1007/s00246-013-0845-7.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Callaghan, F. M., and S. M. Grieve. Normal patterns of thoracic aortic wall shear stress measured using four-dimensional flow MRI in a large population. Am. J. Physiol. Heart Circ. Physiol. 315:H1174–H1181, 2018. https://doi.org/10.1152/ajpheart.00017.2018.

    Article  CAS  PubMed  Google Scholar 

  36. Miyazaki, S., K. Itatani, T. Furusawa, et al. Validation of numerical simulation methods in aortic arch using 4D Flow MRI. Heart Vessels. 32:1032–1044, 2017. https://doi.org/10.1007/s00380-017-0979-2.

    Article  PubMed  Google Scholar 

  37. Arzani, A., and S. C. Shadden. Characterizations and correlations of wall shear stress in aneurysmal flow. J. Biomech. Eng. 2016. https://doi.org/10.1115/1.4032056.

    Article  PubMed  Google Scholar 

  38. Dolan, J. M., J. Kolega, and H. Meng. High wall shear stress and spatial gradients in vascular pathology: a review. Ann. Biomed. Eng. 41:1411–1427, 2013. https://doi.org/10.1007/s10439-012-0695-0.

    Article  PubMed  Google Scholar 

  39. Lopes, D., H. Puga, J. C. Teixeira, and S. F. Teixeira. Influence of arterial mechanical properties on carotid blood flow: comparison of CFD and FSI studies. Int. J. Mech. Sci. 160:209–218, 2019. https://doi.org/10.1016/j.ijmecsci.2019.06.029.

    Article  Google Scholar 

  40. Beckmann, E., and A. S. Jassar. Coarctation repair—redo challenges in the adults: what to do? J. Vis. Surg. 4:76, 2018. https://doi.org/10.21037/jovs.2018.04.07.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Hong, J. C., J. S. Coselli, and O. Preventza. The dos and don’ts of open and endovascular thoracoabdominal aortic aneurysm repair. Innovations. 15:513–520, 2020. https://doi.org/10.1177/1556984520967304.

    Article  PubMed  Google Scholar 

  42. Uzzaman, M. M., N. E. Khan, B. Davies, et al. Long-term outcome of interrupted arch repair with direct anastomosis and homograft augmentation patch. Ann. Thorac. Surg. 105:1819–1826, 2018. https://doi.org/10.1016/j.athoracsur.2018.01.035.

    Article  PubMed  Google Scholar 

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Acknowledgments

This research was supported by the National Institutes of Health (award #R01HL143468 and #R21HD090671), and the Maryland Technology Development Corporation (Maryland Innovation Initiative Award # 1120-004). This research project was conducted using computational resources at the Advanced Research Computing at Hopkins (ARCH) (https://www.arch.jhu.edu).

Funding

Funding was provided by NIH (R01HL143468, R33HD090671, R21HD090671).

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Authors and Affiliations

  1. Department of Mechanical Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD, 21218, USA

    Seda Aslan, Xiaolong Liu, Qiyuan Wu & Axel Krieger

  2. Division of Cardiology, Children’s National Hospital, Washington, DC, USA

    Paige Mass, Yue-Hin Loke & Laura Olivieri

  3. Nanofiber Solutions, Dublin, OH, USA

    Jed Johnson & Joey Huddle

  4. Section of Cardiac Surgery, Department of Surgery, The University of Chicago Medicine, Chicago, IL, USA

    Narutoshi Hibino

  5. Department of Mechanical Engineering, Texas Tech University, Lubbock, TX, USA

    Xiaolong Liu

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  1. Seda Aslan
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Correspondence to Seda Aslan.

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Conflict of interest

Axel Krieger and Xiaolong Liu are founders of and hold shares of stock options in CorFix Medical, Inc. The results of the study discussed in this publication could affect the value of CorFix Medical Inc. This arrangement has been reviewed and approved by the Johns Hopkins University in accordance with its conflict-of-interest policies. Jed Johnson is a co-founder and stockholder of Nanofiber Solutions.

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Aslan, S., Liu, X., Wu, Q. et al. Virtual Planning and Patient-Specific Graft Design for Aortic Repairs. Cardiovasc Eng Tech 15, 123–136 (2024). https://doi.org/10.1007/s13239-023-00701-2

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