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Predictors of Myocardial Ischemia in Patients with Kawasaki Disease: Insights from Patient-Specific Simulations of Coronary Hemodynamics

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Abstract

Current treatments for patients with coronary aneurysms caused by Kawasaki disease (KD) are based primarily on aneurysm size. This ignores hemodynamic factors influencing myocardial ischemic risk. We performed patient-specific computational hemodynamics simulations for 15 KD patients, with parameters tuned to patients’ arterial pressure and cardiac function. Ischemic risk was evaluated in 153 coronary arteries from simulated fractional flow reserve (FFR), wall shear stress, and residence time. FFR correlated weakly with aneurysm \(Z\)-scores (correlation coefficient, \({r}_{P}=-0.47\)) but correlated better with the ratio of maximum-to-minimum aneurysmal lumen diameter (\({r}_{P}=-0.64\)). FFR dropped more rapidly distal to aneurysms, and this correlated more with the lumen diameter ratio (\({r}_{P}=0.73\)) than \(Z\)-score (\({r}_{P}=0.54\)). Wall shear stress correlated better with the diameter ratio (\({r}_{P}=-0.51\)), while residence time correlated more with \(Z\)-score (\({r}_{P}=0.52\)). Overall, the maximum-to-minimum diameter ratio predicted ischemic risk better than \(Z\)-score. Although FFR immediately distal to aneurysms was nonsignificant, its rapid rate of decrease suggests elevated risk.

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Data Availability

All models built for this study have been made publicly available through the Vascular Model Repository (www.vascularmodel.com).

References

  1. Bluestein D, Niu L, Schoephoerster RT, Dewanjee MK. Fluid mechanics of arterial stenosis: relationship to the development of mural thrombus. Ann Biomed Eng. 1997;25:344–56.

    Article  CAS  PubMed  Google Scholar 

  2. Bogren HG, Klipstein RH, Firmin DN, et al. Quantitation of antegrade and retrograde blood flow in the human aorta by magnetic resonance velocity mapping. Am Heart J. 1989;117(6):1214–22.

    Article  CAS  PubMed  Google Scholar 

  3. Burns JC, Glodé MP. Kawasaki syndrome. Lancet. 2004;364:533–44.

    Article  PubMed  Google Scholar 

  4. Chiu JJ, Chien S. Effects of disturbed flow on vascular endothelium: pathophysiological basis and clinical perspectives. Physiol Rev. 2011;91(1):327–87.

    Article  PubMed  Google Scholar 

  5. Coogan JS, Humphrey JD, Figueroa CA. Computational simulations of hemodynamic changes within thoracic, coronary, and cerebral arteries following early wall remodeling in response to distal aortic coarctation. Biomech Model Mechanobiol. 2013;12:79–93.

    Article  PubMed  Google Scholar 

  6. Dallaire F, Dahdah N. New equations and a critical appraisal of coronary artery z scores in healthy children. J Am Soc Echocardiogr. 2011;24(1):60–74.

    Article  PubMed  Google Scholar 

  7. Daniels LB, Tjajadi MS, Walford HH, et al. Prevalence of Kawasaki disease in young adults with suspected myocardial ischemia. Circulation. 2012;125(20):2447–53.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Driessen RS, Danad I, Stuijfzand WJ, et al. Comparison of coronary computed tomography angiography, fractional flow reserve, and perfusion imaging for ischemia diagnosis. J Am Coll Cardiol. 2019;73(2):161–73.

    Article  PubMed  Google Scholar 

  9. Eslami P, Tran J, Jin Z, et al. Effect of wall elasticity on hemodynamics and wall shear stress in patient-specific simulations in the coronary arteries. J Biomech Eng. 2019;142(2):10.

    Google Scholar 

  10. Esmaily-Moghadam M, Hsia TY, Marsden AL. A non-discrete method for computation of residence time in fluid mechanics simulations. Phys Fluids. 2013;25(11):1–21.

    Article  Google Scholar 

  11. Figueroa CA, Vignon-Clementel IE, Jansen KE, et al. A coupled momentum method for modeling blood flow in three-dimensional deformable arteries. Comput Methods Appl Mech Eng. 2006;195(41–43):5685–706.

    Article  Google Scholar 

  12. Gordon JB, Daniels LB, Kahn AM, et al. The spectrum of cardiovascular lesions requiring intervention in adults after Kawasaki disease. JACC: Cardiovasc Interv. 2016;9(7):687–96.

    PubMed  Google Scholar 

  13. Gow BS, Hadfield CD. The elasticity of canine and human coronary arteries with reference to postmortem changes. Circ Res. 1979;45(5):588–94.

    Article  CAS  PubMed  Google Scholar 

  14. Grande Gutierrez N, Mathew M, McCrindle BW, et al. Hemodynamic variables in aneurysms are associated with thrombotic risk in children with Kawasaki disease. Int J Cardiol. 2019;281:15–21.

    Article  PubMed  Google Scholar 

  15. Grande Gutierrez N, Alber M, Kahn AM, et al. Computational modeling of blood component transport related to coronary artery thrombosis in Kawasaki disease. PLOS Comp Bio. 2021;17(9):e1009331.

    Article  CAS  Google Scholar 

  16. Haycock GB, Schwartz GJ, Wisotsky DH. Geometric method for measuring body surface area: a height-weight formula validated in infants, children, and adults. J Pediatr. 1978;93(1):62–6.

    Article  CAS  PubMed  Google Scholar 

  17. Jansen KE, Whiting CH, Hulbert GM. A generalized-a method for integrating the filtered Navier-Stokes equations with a stabilized finite element method. Comput Methods Appl Mech Eng. 1999;190(3–4):305–20.

    Google Scholar 

  18. Karády J, Mayrhofer T, Ivanov A, et al. Cost-effectiveness analysis of anatomic vs functional index testing in patients with low-risk stable chest pain. JAMA Netw Open. 2020;3(12):e2028312–e2028312.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Kim HJ, Vignon-Clementel IE, Coogan JS, et al. Patient-specific modeling of blood flow and pressure in human coronary arteries. Ann Biomed Eng. 2010;38(10):3195–209.

    Article  CAS  PubMed  Google Scholar 

  20. Kim HJ, Vignon-Clementel IE, Figueroa CA, et al. On coupling a lumped parameter heart model and a three-dimensional finite element aorta model. Ann Biomed Eng. 2009;37(11):2153–69.

    Article  CAS  PubMed  Google Scholar 

  21. Lan IS, Liu J, Yang W, et al. Validation of the reduced unified continuum formulation against in vitro 4D-flow MRI. Ann Biomed Eng. 2022;1–17:2022.

    Google Scholar 

  22. McCrindle BW, Rowley AH, Newburger JW, et al. Diagnosis, treatment, and long-term management of Kawasaki disease. Circulation. 2017;135:e927–99.

    Article  PubMed  Google Scholar 

  23. Min JK, Leipsic J, Pencina MJ, et al. Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA. 2012;308(12):1237–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Murakami T, Tanaka N. The physiological significance of coronary aneurysms in Kawasaki disease. EuroIntervention. 2011;7:944–7.

    Article  PubMed  Google Scholar 

  25. Murray CD. The physiological principle of minimum work 1: the vascular system and the cost of blood volume. Proc Natl Acad Sci. 1926;12(3):207–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ogawa S, Ohkubo T, Fukazawa R, et al. Estimation of myocardial hemodynamics before and after intervention in children with Kawasaki disease. J Am Coll Cardiol. 2004;43(4):653–61.

    Article  PubMed  Google Scholar 

  27. Pijls NHJ, de Bruyne B, Peels K, et al. Measurement of fractional flow reserve to assess the functional severity of coronary-artery stenoses. N Engl J Med. 1996;334(26):1703–8.

    Article  CAS  PubMed  Google Scholar 

  28. Pijls NHJ, Fearon WF, Tonino PAL, et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention in patients with multivessel coronary artery disease: 2-year follow-up of the FAME study. J Am Coll Cardiol. 2010;56(3):177–84.

    Article  PubMed  Google Scholar 

  29. Podessor BK, Neumann F, Neumann M, et al. Outer radius-wall thickness ratio, a postmortem quantitative histology in human coronary arteries. Acta Anat. 1998;163:63–8.

    Article  Google Scholar 

  30. Reininger AJ, Reininger CB, Heinzmann U, Wurzinger LJ. Residence time in niches of stagnant flow determines fibrin clot formation in an arterial branching model - detailed flow analysis and experimental results. Thromb Haemost. 1995;74(3):916–22.

    Article  CAS  PubMed  Google Scholar 

  31. Rizk SRY, El Said G, Daniels LB, et al. Acute myocardial ischemia in adults secondary to missed Kawasaki disease in childhood. Am J Cardiol. 2015;115(4):423–7.

    Article  PubMed  Google Scholar 

  32. Roccabianca S, Figueroa CA, Tellides G, Humphrey JD. Quantification of regional differences in aortic stiffness in the aging human. J Mech Behav Biomed Mater. 2014;29:618–34.

    Article  CAS  PubMed  Google Scholar 

  33. Sankaran S, Esmaily-Moghadam M, Kahn AM, et al. Patient-specific multiscale modeling of blood flow for coronary artery bypass graft surgery. Ann Biomed Eng. 2012;40(10):2228–42.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Sengupta D, Kahn AM, Burns JC, et al. Image-based modeling of hemodynamics in coronary artery aneurysms caused by Kawasaki disease. Biomech Model Mechanobiol. 2012;11:915–32.

    Article  PubMed  Google Scholar 

  35. Sengupta D, Kahn AM, Kung E, et al. Thrombotic risk stratification using computational modeling in patients with coronary artery aneurysms following Kawasaki disease. Biomech Model Mechanobiol. 2014;13:1261–76.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Si H (2015) TetGen, a Delaunay-based quality tetrahedral mesh generator. ACM Trans Math Softw 41(11)

  37. Tran JS, Schiavazzi DE, Ramachandra AB, et al. Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations. Comput Fluids. 2017;142:128–38.

    Article  PubMed  Google Scholar 

  38. Tsuda E, Abe T, Tamaki W. Acute coronary syndrome in adult patients with coronary artery lesions caused by Kawasaki disease: review of case reports. Cardiol Young. 2011;21(1):74–82.

    Article  PubMed  Google Scholar 

  39. Updegrove A, Wilson NM, Merkow J, et al. SimVascular: an open source pipeline for cardiovascular simulation. Ann Biomed Eng. 2016;45(3):525–41.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Wilson RF, Wyche K, Christensen BV, Zimmer S, Laxson DD. Effects of adenosine on human coronary arterial circulation. Circulation. 1990;82(5):1595–606.

    Article  CAS  PubMed  Google Scholar 

  41. Zhou Y, Kassab GS, Molloi S. On the design of the coronary arterial tree: a generalization of Murray’s law. Phys Med Biol. 1999;44(12):2929–45.

    Article  CAS  PubMed  Google Scholar 

  42. Ziegler T, Bouzourène K, Harrison VJ, Brunner HR, Hayoz D. Influence of oscillatory and unidirectional flow environments on the expression of endothelin and nitric oxide synthase in cultured endothelial cells. Arterioscler Thromb Vasc Bio. 1998;18(5):686–92.

    Article  CAS  Google Scholar 

  43. Secomb TW. Blood flow in the microcirculation. Annu Rev Fluid Mech. 2017;49:443–61.

    Article  Google Scholar 

  44. Eslami P, Tran J, Jin Z, et al. Effect of wall elasticity on hemodynamics and wall shear stress in patient-specific simulations in the coronary arteries. J Biomech Eng. 2020;142(2):1–10.

    Article  Google Scholar 

Download references

Acknowledgements

Computing resources were provided by XSEDE and the Stanford Research Computing Center.

Funding

We are grateful to the Hooper Family Trust for funding this study. This work was also supported by a grant from Kyung Hee University (KHU-20220908) and NIH grant 5R01HL141712-03.

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Authors and Affiliations

  1. Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA, USA

    Karthik Menon & Alison L. Marsden

  2. Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA

    Karthik Menon & Alison L. Marsden

  3. Department of Mechanical Engineering, Kyung Hee University, Yongin-Si, Gyeonggi-Do, South Korea

    Jongmin Seo

  4. Department of Pediatrics, Nippon Medical School Hospital, Tokyo, Japan

    Ryuji Fukazawa & Shunichi Ogawa

  5. Division of Cardiovascular Medicine, University of California San Diego School of Medicine, La Jolla, CA, USA

    Andrew M. Kahn

  6. Department of Pediatrics, University of California San Diego School of Medicine, La Jolla, CA, USA

    Jane C. Burns

  7. Department of Bioengineering, Stanford University, Stanford, CA, USA

    Alison L. Marsden

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  1. Karthik Menon
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  2. Jongmin Seo
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  3. Ryuji Fukazawa
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  4. Shunichi Ogawa
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  5. Andrew M. Kahn
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  7. Alison L. Marsden
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Corresponding author

Correspondence to Alison L. Marsden.

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Ethics Approval and Consent to Participate

This study was approved by the Institutional Review Board at Lucile Packard Children’s Hospital, Stanford, CA, USA, University of California San Diego School of Medicine, La Jolla, CA, USA, and Nippon Medical School Hospital, Tokyo, Japan. Written informed consent was received prior to patient participation.

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The authors declare no competing interests.

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Associate Editor Marat Fudim oversaw the review of this article.

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Karthik Menon and Jongmin Seo are designated as co-first authors.

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Menon, K., Seo, J., Fukazawa, R. et al. Predictors of Myocardial Ischemia in Patients with Kawasaki Disease: Insights from Patient-Specific Simulations of Coronary Hemodynamics. J. of Cardiovasc. Trans. Res. 16, 1099–1109 (2023). https://doi.org/10.1007/s12265-023-10374-w

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