Skip to main content
SpringerLink
Log in

Computational Modeling of Right Ventricular Motion and Intracardiac Flow in Repaired Tetralogy of Fallot

  • Original Article
  • Published:
Cardiovascular Engineering and Technology Aims and scope Submit manuscript

Abstract

Purpose

Patients with repaired Tetralogy of Fallot (rTOF) will develop dilation of the right ventricle (RV) from chronic pulmonary insufficiency and require pulmonary valve replacement (PVR). Cardiac MRI (cMRI) is used to guide therapy but has limitations in studying novel intracardiac flow parameters. This pilot study aimed to demonstrate feasibility of reconstructing RV motion and simulating intracardiac flow in rTOF patients, exclusively using conventional cMRI and an immersed-boundary method computational fluid dynamic (CFD) solver.

Methods

Four rTOF patients and three normal controls underwent cMRI including 4D flow. 3D RV models were segmented from cMRI images. Feature-tracking software captured RV endocardial contours from cMRI long-axis and short-axis cine stacks. RV motion was reconstructed via diffeomorphic mapping (Deformetrica, deformetrica.org), serving as the domain boundary for CFD. Fully-resolved direct numerical simulations were performed over several cardiac cycles. Intracardiac vorticity, kinetic energy (KE) and turbulent kinetic energy (TKE) was measured. For validation, RV motion was compared to manual tracings, results of KE were compared between CFD and 4D flow.

Results

Diastolic vorticity and TKE in rTOF patients were 4.12 ± 2.42 mJ/L and 115 ± 27/s, compared to 2.96 ± 2.16 mJ/L and 78 ± 45/s in controls. There was good agreement between RV motion and manual tracings. The difference in diastolic KE between CFD and 4D flow by Bland-Altman analysis was − 0.89910 to 2 mJ/mL (95% limits of agreement: − 1.351 × 10−2 mJ/mL to 1.171 × 10−2 mJ/mL).

Conclusion

This CFD framework can produce intracardiac flow in rTOF patients. CFD has the potential for predicting the effects of PVR in rTOF patients and improve the clinical indications guided by cMRI.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7

Similar content being viewed by others

References

  1. Ayachit, U. The ParaView guide: updated for ParaView version 4.3. (L. Avila, Ed.) (Full color version.). Los Alamos: Kitware, 2015.

  2. Balasubramanian, S., D. M. Harrild, B. Kerur, E. Marcus, P. del Nido, T. Geva, and A. J. Powell. Impact of surgical pulmonary valve replacement on ventricular strain and synchrony in patients with repaired tetralogy of Fallot: a cardiovascular magnetic resonance feature tracking study. J. Cardiovasc. Magn. Reson. 20(1):37, 2018. https://doi.org/10.1186/s12968-018-0460-0.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Berganza, F. M., C. G. de Alba, N. Özcelik, and D. Adebo. Cardiac magnetic resonance feature tracking biventricular two-dimensional and three-dimensional strains to evaluate ventricular function in children after repaired tetralogy of fallot as compared with healthy children. Pediatr. Cardiol. 38(3):566–574, 2017. https://doi.org/10.1007/s00246-016-1549-6.

    Article  PubMed  Google Scholar 

  4. Berger, S. A., and L.-D. Jou. Flows in stenotic vessels. Annu. Rev. Fluid Mech. 32(1):347–382, 2000. https://doi.org/10.1146/annurev.fluid.32.1.347.

    Article  Google Scholar 

  5. Bhagra, C. J., E. J. Hickey, A. Van De Bruaene, S. L. Roche, E. M. Horlick, and R. M. Wald. Pulmonary valve procedures late after repair of tetralogy of Fallot: current perspectives and contemporary approaches to management. Can. J. Cardiol. 33(9):1138–1149, 2017. https://doi.org/10.1016/j.cjca.2017.06.011.

    Article  PubMed  Google Scholar 

  6. Bhatt, A. B., E. Foster, K. Kuehl, J. Alpert, S. Brabeck, S. Crumb, et al. Congenital heart disease in the older adult: a scientific statement from the American Heart Association. Circulation 131(21):1884–1931, 2015. https://doi.org/10.1161/CIR.0000000000000204.

    Article  PubMed  Google Scholar 

  7. Biffi, B., J. L. Bruse, M. A. Zuluaga, H. N. Ntsinjana, A. M. Taylor, and S. Schievano. Investigating cardiac motion patterns using synthetic high-resolution 3D cardiovascular magnetic resonance images and statistical shape analysis. Front. Pediatr. 2017. https://doi.org/10.3389/fped.2017.00034.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Biglino, G., C. Capelli, J. Bruse, G. M. Bosi, A. M. Taylor, and S. Schievano. Computational modelling for congenital heart disease: how far are we from clinical translation? Heart 103(2):98–103, 2017. https://doi.org/10.1136/heartjnl-2016-310423.

    Article  PubMed  Google Scholar 

  9. Capuano, F., Y.-H. Loke, and E. Balaras. Blood flow dynamics at the pulmonary artery bifurcation. Fluids 4(4):190, 2019. https://doi.org/10.3390/fluids4040190.

    Article  CAS  Google Scholar 

  10. Dumont, K., J. M. A. Stijnen, J. Vierendeels, F. N. van de Vosse, and P. R. Verdonck. Validation of a fluid-structure interaction model of a heart valve using the dynamic mesh method in fluent. Comput. Methods Biomech. Biomed. Eng. 7(3):139–146, 2004. https://doi.org/10.1080/10255840410001715222.

    Article  CAS  Google Scholar 

  11. Durrleman, S., M. Prastawa, N. Charon, J. R. Korenberg, S. Joshi, G. Gerig, and A. Trouvé. Morphometry of anatomical shape complexes with dense deformations and sparse parameters. NeuroImage 101:35–49, 2014. https://doi.org/10.1016/j.neuroimage.2014.06.043.

    Article  PubMed  Google Scholar 

  12. Dutta, T., and W. S. Aronow. Echocardiographic evaluation of the right ventricle: Clinical implications. Clin. Cardiol. 40(8):542–548, 2017. https://doi.org/10.1002/clc.22694.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Egbe, A. C., S. Vallabhajosyula, and H. M. Connolly. Trends and outcomes of pulmonary valve replacement in tetralogy of Fallot. Int. J. Cardiol. 2019. https://doi.org/10.1016/j.ijcard.2019.07.063.

    Article  PubMed  Google Scholar 

  14. Fogel, M. A., K. S. Sundareswaran, D. de Zelicourt, L. P. Dasi, T. Pawlowski, J. Rome, and A. P. Yoganathan. Power loss and right ventricular efficiency in patients after tetralogy of Fallot repair with pulmonary insufficiency: clinical implications. J. Thorac. Cardiovasc. Surg. 143(6):1279–1285, 2012. https://doi.org/10.1016/j.jtcvs.2011.10.066.

    Article  PubMed  Google Scholar 

  15. Francois, C. J., S. Srinivasan, M. L. Schiebler, S. B. Reeder, E. Niespodzany, B. R. Landgraf, et al. 4D cardiovascular magnetic resonance velocity mapping of alterations of right heart flow patterns and main pulmonary artery hemodynamics in tetralogy of Fallot. J. Cardiovasc. Magn. Reson. 14(1):16, 2012. https://doi.org/10.1186/1532-429X-14-16.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Fredriksson, A., A. Trzebiatowska-Krzynska, P. Dyverfeldt, J. Engvall, T. Ebbers, and C.-J. Carlhäll. Turbulent kinetic energy in the right ventricle: potential MR marker for risk stratification of adults with repaired Tetralogy of Fallot. J. Magn. Reson. Imaging 47(4):1043–1053, 2018. https://doi.org/10.1002/jmri.25830.

    Article  PubMed  Google Scholar 

  17. Fredriksson, A. G., J. Zajac, J. Eriksson, P. Dyverfeldt, A. F. Bolger, T. Ebbers, and C.-J. Carlhäll. 4-D blood flow in the human right ventricle. Am. J. Physiol. Heart Circ. Physiol. 301(6):H2344–H2350, 2011. https://doi.org/10.1152/ajpheart.00622.2011.

    Article  CAS  PubMed  Google Scholar 

  18. Geva, T. Indications for pulmonary valve replacement in repaired tetralogy of Fallot: The Quest Continues. Circulation 128(17):1855–1857, 2013. https://doi.org/10.1161/CIRCULATIONAHA.113.005878.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Haggerty, C. M., M. Restrepo, E. Tang, D. A. de Zélicourt, K. S. Sundareswaran, L. Mirabella, et al. Fontan hemodynamics from 100 patient-specific cardiac magnetic resonance studies: A computational fluid dynamics analysis. J. Thorac. Cardiovasc. Surg. 148(4):1481–1489, 2014. https://doi.org/10.1016/j.jtcvs.2013.11.060.

    Article  PubMed  Google Scholar 

  20. Harrild, D. M., E. Marcus, B. Hasan, M. E. Alexander, A. J. Powell, T. Geva, and D. B. McElhinney. Impact of transcatheter pulmonary valve replacement on biventricular strain and synchrony assessed by cardiac magnetic resonance feature tracking. Circ. Cardiovasc. Interv. 6(6):680–687, 2013. https://doi.org/10.1161/CIRCINTERVENTIONS.113.000690.

    Article  PubMed  Google Scholar 

  21. Hasan, A., E. M. Kolahdouz, A. Enquobahrie, T. G. Caranasos, J. P. Vavalle, and B. E. Griffith. Image-based immersed boundary model of the aortic root. Med. Eng. Phys. 47:72–84, 2017. https://doi.org/10.1016/j.medengphy.2017.05.007.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Heng, E. L., M. A. Gatzoulis, A. Uebing, B. Sethia, H. Uemura, G. C. Smith, et al. Immediate and midterm cardiac remodeling after surgical pulmonary valve replacement in adults with repaired tetralogy of fallot: a prospective cardiovascular magnetic resonance and clinical study. Circulation 136(18):1703–1713, 2017. https://doi.org/10.1161/CIRCULATIONAHA.117.027402.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Hirtler, D., J. Garcia, A. J. Barker, and J. Geiger. Assessment of intracardiac flow and vorticity in the right heart of patients after repair of tetralogy of Fallot by flow-sensitive 4D MRI. Eur. Radiol. 26(10):3598–3607, 2016. https://doi.org/10.1007/s00330-015-4186-1.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Hunt, J. C., A. A. Wray, and P. Moin. Eddies, Streams, and Convergence Zones in Turbulent Flows. Center for Turbulence Research, 1988.

  25. Itatani, K., S. Miyazaki, T. Furusawa, S. Numata, S. Yamazaki, K. Morimoto, et al. New imaging tools in cardiovascular medicine: computational fluid dynamics and 4D flow MRI. Gen. Thorac. Cardiovasc. Surg. 65(11):611–621, 2017. https://doi.org/10.1007/s11748-017-0834-5.

    Article  PubMed  Google Scholar 

  26. Jacobs, K., J. Rigdon, F. Chan, J. Y. Cheng, M. T. Alley, S. Vasanawala, and S. A. Maskatia. Direct measurement of atrioventricular valve regurgitant jets using 4D flow cardiovascular magnetic resonance is accurate and reliable for children with congenital heart disease: a retrospective cohort study. J. Cardiovasc. Magn. Reson. 22(1):33, 2020. https://doi.org/10.1186/s12968-020-00612-4.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Kalaitzidis, P., S. Orwat, A. Kempny, R. Robert, B. Peters, S. Sarikouch, et al. Biventricular dyssynchrony on cardiac magnetic resonance imaging and its correlation with myocardial deformation, ventricular function and objective exercise capacity in patients with repaired tetralogy of Fallot. Int. J. Cardiol. 264:53–57, 2018. https://doi.org/10.1016/j.ijcard.2018.04.005.

    Article  PubMed  Google Scholar 

  28. Kim, J., D. Kim, and H. Choi. An immersed-boundary finite-volume method for simulations of flow in complex geometries. J. Comput. Phys. 171(1):132–150, 2001. https://doi.org/10.1006/jcph.2001.6778.

    Article  CAS  Google Scholar 

  29. Leonardi, B., A. M. Taylor, T. Mansi, I. Voigt, M. Sermesant, X. Pennec, et al. Computational modelling of the right ventricle in repaired tetralogy of Fallot: can it provide insight into patient treatment? Eur. Heart J. 14(4):381–386, 2013. https://doi.org/10.1093/ehjci/jes239.

    Article  Google Scholar 

  30. Liu, B., A. M. Dardeer, W. E. Moody, N. C. Edwards, L. E. Hudsmith, and R. P. Steeds. Normal values for myocardial deformation within the right heart measured by feature-tracking cardiovascular magnetic resonance imaging. Int. J. Cardiol. 252:220–223, 2018. https://doi.org/10.1016/j.ijcard.2017.10.106.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Loke, Y.-H., A. S. Harahsheh, A. Krieger, and L. J. Olivieri. Usage of 3D models of tetralogy of Fallot for medical education: impact on learning congenital heart disease. BMC Med. Educ. 2017. https://doi.org/10.1186/s12909-017-0889-0.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Loke, Y.-H., A. Krieger, C. Sable, and L. Olivieri. Novel uses for three-dimensional printing in congenital heart disease. Curr. Pediatr. Rep. 4(2):28–34, 2016. https://doi.org/10.1007/s40124-016-0099-y.

    Article  Google Scholar 

  33. Mangual, J. O., F. Domenichini, and G. Pedrizzetti. Describing the highly three dimensional right ventricle flow. Ann. Biomed. Eng. 40(8):1790–1801, 2012. https://doi.org/10.1007/s10439-012-0540-5.

    Article  CAS  PubMed  Google Scholar 

  34. Mangual, J. O., F. Domenichini, and G. Pedrizzetti. Three dimensional numerical assessment of the right ventricular flow using 4D echocardiography boundary data. Eur. J. Mech. B 35:25–30, 2012. https://doi.org/10.1016/j.euromechflu.2012.01.022.

    Article  Google Scholar 

  35. Mansi, T., I. Voigt, B. Leonardi, X. Pennec, S. Durrleman, M. Sermesant, et al. A statistical model for quantification and prediction of cardiac remodelling: application to tetralogy of Fallot. IEEE Trans. Med. Imaging 30(9):1605–1616, 2011. https://doi.org/10.1109/TMI.2011.2135375.

    Article  CAS  PubMed  Google Scholar 

  36. Mikhail, A., G. D. Labbio, A. Darwish, and L. Kadem. How pulmonary valve regurgitation after tetralogy of fallot repair changes the flow dynamics in the right ventricle: an in vitro study. Med. Eng. Phys. 83:48–55, 2020. https://doi.org/10.1016/j.medengphy.2020.07.014.

    Article  PubMed  Google Scholar 

  37. Mittal, R., J. H. Seo, V. Vedula, Y. J. Choi, H. Liu, H. H. Huang, et al. Computational modeling of cardiac hemodynamics: Current status and future outlook. J. Comput. Phys. 305:1065–1082, 2016. https://doi.org/10.1016/j.jcp.2015.11.022.

    Article  Google Scholar 

  38. Mooij, C. F., C. J. de Wit, D. A. Graham, A. J. Powell, and T. Geva. Reproducibility of MRI measurements of right ventricular size and function in patients with normal and dilated ventricles. J. Magn. Reson. Imaging 28(1):67–73, 2008. https://doi.org/10.1002/jmri.21407.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Nguyen, K.-L., F. Han, Z. Zhou, D. Z. Brunengraber, I. Ayad, D. S. Levi, et al. 4D MUSIC CMR: value-based imaging of neonates and infants with congenital heart disease. J. Cardiovasc. Magn. Reson. 19(1):40, 2017. https://doi.org/10.1186/s12968-017-0352-8.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Nies, M., and J. I. Brenner. Tetralogy of Fallot: epidemiology meets real-world management: lessons from the Baltimore-Washington Infant Study. Cardiol. Young 23(6):867–870, 2013. https://doi.org/10.1017/S1047951113001698.

    Article  PubMed  Google Scholar 

  41. O’Byrne, M. L., A. C. Glatz, L. Mercer-Rosa, M. J. Gillespie, Y. Dori, E. Goldmuntz, et al. Trends in pulmonary valve replacement in children and adults with tetralogy of fallot. Am. J. Cardiol. 115(1):118–124, 2015. https://doi.org/10.1016/j.amjcard.2014.09.054.

    Article  PubMed  Google Scholar 

  42. Okafor, I., V. Raghav, J. F. Condado, P. A. Midha, G. Kumar, and A. P. Yoganathan. Aortic regurgitation generates a kinematic obstruction which hinders left ventricular filling. Ann. Biomed. Eng. 45(5):1305–1314, 2017. https://doi.org/10.1007/s10439-017-1790-z.

    Article  PubMed  Google Scholar 

  43. Ou-Yang, W.-B., S. Qureshi, J.-B. Ge, S.-S. Hu, S.-J. Li, K.-M. Yang, et al. Multicenter comparison of percutaneous and surgical pulmonary valve replacement in large RVOT. Ann. Thorac. Surg. 110(3):980–987, 2020. https://doi.org/10.1016/j.athoracsur.2020.01.009.

    Article  PubMed  Google Scholar 

  44. Pasipoularides, A. Evaluation of right and left ventricular diastolic filling. J. Cardiovasc. Transl. Res. 6(4):623–639, 2013. https://doi.org/10.1007/s12265-013-9461-4.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Pasipoularides, A. Mechanotransduction mechanisms for intraventricular diastolic vortex forces and myocardial deformations: Part 1. J. Cardiovasc. Translat. Res. 8(1):76–87, 2015. https://doi.org/10.1007/s12265-015-9611-y.

    Article  Google Scholar 

  46. Pasipoularides, A. Mechanotransduction mechanisms for intraventricular diastolic vortex forces and myocardial deformations: Part 2. Journal of Cardiovascular Translational Research 8(5):293–318, 2015. https://doi.org/10.1007/s12265-015-9630-8.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Pasipoularides, A., M. Shu, A. Shah, M. S. Womack, and D. D. Glower. Diastolic right ventricular filling vortex in normal and volume overload states. Am. J. Physiol. Heart Circ. Physiol. 284(4):H1064–H1072, 2003. https://doi.org/10.1152/ajpheart.00804.2002.

    Article  CAS  PubMed  Google Scholar 

  48. Peskin, C. S. Numerical analysis of blood flow in the heart. J. Comput. Phys. 25(3):220–252, 1977. https://doi.org/10.1016/0021-9991(77)90100-0.

    Article  Google Scholar 

  49. Phillips, A. B. M., P. Nevin, A. Shah, V. Olshove, R. Garg, and E. M. Zahn. Development of a novel hybrid strategy for transcatheter pulmonary valve placement in patients following transannular patch repair of tetralogy of fallot: hybrid pulmonary valve implantation. Catheter. Cardiovasc. Interv. 87(3):403–410, 2016. https://doi.org/10.1002/ccd.26315.

    Article  PubMed  Google Scholar 

  50. Posa, A., M. Vanella, and E. Balaras. An adaptive reconstruction for Lagrangian, direct-forcing, immersed-boundary methods. J. Comput. Phys. 351:422–436, 2017. https://doi.org/10.1016/j.jcp.2017.09.047.

    Article  Google Scholar 

  51. Ringenberg, J., M. Deo, V. Devabhaktuni, O. Berenfeld, P. Boyers, and J. Gold. Fast, accurate, and fully automatic segmentation of the right ventricle in short-axis cardiac MRI. Comput. Med. Imaging Graph. 38(3):190–201, 2014. https://doi.org/10.1016/j.compmedimag.2013.12.011.

    Article  PubMed  Google Scholar 

  52. Sacco, F., B. Paun, O. Lehmkuhl, T. L. Iles, P. A. Iaizzo, G. Houzeaux, et al. Evaluating the roles of detailed endocardial structures on right ventricular haemodynamics by means of CFD simulations. Int. J. Num. Methods Biomed. Eng. 34(9):2018. https://doi.org/10.1002/cnm.3115.

    Article  Google Scholar 

  53. Schievano, S., L. Coats, F. Migliavacca, W. Norman, A. Frigiola, J. Deanfield, et al. Variations in right ventricular outflow tract morphology following repair of congenital heart disease: implications for percutaneous pulmonary valve implantation. J. Cardiovasc. Magn. Reson. 9(4):687–695, 2007. https://doi.org/10.1080/10976640601187596.

    Article  PubMed  Google Scholar 

  54. Shibata, M., K. Itatani, T. Hayashi, T. Honda, A. Kitagawa, K. Miyaji, and M. Ono. Flow Energy loss as a predictive parameter for right ventricular deterioration caused by pulmonary regurgitation after tetralogy of fallot repair. Pediatr. Cardiol. 2018. https://doi.org/10.1007/s00246-018-1813-z.

    Article  PubMed  Google Scholar 

  55. Stout, K. K., C. J. Daniels, J. A. Aboulhosn, B. Bozkurt, C. S. Broberg, J. M. Colman, et al. 2018 AHA/ACC Guideline for the Management of Adults With Congenital Heart Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019. https://doi.org/10.1161/CIR.0000000000000603.

    Article  PubMed  Google Scholar 

  56. Tang, D., P. J. del Nido, C. Yang, H. Zuo, X. Huang, R. H. Rathod, et al. Patient-specific MRI-based right ventricle models using different zero-load diastole and systole geometries for better cardiac stress and strain calculations and pulmonary valve replacement surgical outcome predictions. PLoS ONE 11(9):2016. https://doi.org/10.1371/journal.pone.0162986.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Therrien, J., S. C. Siu, P. R. McLaughlin, P. P. Liu, W. G. Williams, and G. D. Webb. Pulmonary valve replacement in adults late after repair of tetralogy of fallot: are we operating too late? J. Am. Coll. Cardiol. 36(5):1670–1675, 2000.

    Article  CAS  Google Scholar 

  58. Van den Eynde, J., M. P. B. O. Sá, D. Vervoort, L. Roever, B. Meyns, W. Budts, et al. Pulmonary valve replacement in tetralogy of Fallot: an updated meta-analysis. Ann. Thorac. Surg. 2020. https://doi.org/10.1016/j.athoracsur.2020.11.040.

    Article  PubMed  Google Scholar 

  59. Vanella, M., and E. Balaras. A moving-least-squares reconstruction for embedded-boundary formulations. J. Comput. Phys. 228(18):6617–6628, 2009. https://doi.org/10.1016/j.jcp.2009.06.003.

    Article  Google Scholar 

  60. Vedula, V., R. George, L. Younes, and R. Mittal. Hemodynamics in the left atrium and its effect on ventricular flow patterns. J. Biomech. Eng. 137(11):2015. https://doi.org/10.1115/1.4031487.

    Article  PubMed  Google Scholar 

  61. Viola, F., V. Meschini, and R. Verzicco. Fluid–structure-electrophysiology interaction (FSEI) in the left-heart: a multi-way coupled computational model. Eur. J. Mech. B 79:212–232, 2020. https://doi.org/10.1016/j.euromechflu.2019.09.006.

    Article  Google Scholar 

  62. Yang, F., Y. Zhang, P. Lei, L. Wang, Y. Miao, H. Xie, and Z. Zeng. A deep learning segmentation approach in free-breathing real-time cardiac magnetic resonance imaging. Biomed. Res. Int. 2019:5636423, 2019. https://doi.org/10.1155/2019/5636423.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Yilmaz, P., K. Wallecan, W. Kristanto, J.-P. Aben, and A. Moelker. Evaluation of a semi-automatic right ventricle segmentation method on short-axis MR images. J. Digit. Imaging 31(5):670–679, 2018. https://doi.org/10.1007/s10278-018-0061-3.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Yu, H., P. J. del Nido, T. Geva, C. Yang, A. Tang, Z. Wu, et al. Patient-specific in vivo right ventricle material parameter estimation for patients with tetralogy of Fallot using MRI-based models with different zero-load diastole and systole morphologies. Int. J. Cardiol. 276:93–99, 2019. https://doi.org/10.1016/j.ijcard.2018.09.030.

    Article  PubMed  Google Scholar 

  65. Zaidi, S. J., W. Cossor, A. Singh, F. Maffesanti, K. Kawaji, J. Woo, et al. Three-dimensional analysis of regional right ventricular shape and function in repaired tetralogy of Fallot using cardiovascular magnetic resonance. Clin. Imaging 52:106–112, 2018. https://doi.org/10.1016/j.clinimag.2018.07.007.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Zijdenbos, A. P., B. M. Dawant, R. A. Margolin, and A. C. Palmer. Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans. Med. Imaging 13(4):716–724, 1994. https://doi.org/10.1109/42.363096.

    Article  CAS  PubMed  Google Scholar 

  67. Zou, K. H., S. K. Warfield, A. Bharatha, C. M. C. Tempany, M. R. Kaus, S. J. Haker, et al. Statistical validation of image segmentation quality based on a spatial overlap index. Acad. Radiol. 11(2):178–189, 2004. https://doi.org/10.1016/s1076-6332(03)00671-8.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This publication was supported by Award Number UL1TR001876 from the NIH National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. This work was also supported by institutional funding through Children’s National Hospital (Board of Visitors grant) to pay for licensing of segmentation software (Mimics, Materialise). Dr. Francesco Capuano was supported by Università degli Studi di Napoli “Federico II”.

Author information

Author notes

  1. Yue-Hin Loke

    Present address: Division of Cardiology, Children’s National Hospital, 111 Michigan Ave NW W3-200, Washington, DC, 20010, USA

Authors and Affiliations

  1. Division of Cardiology, Children’s National Hospital, 111 Michigan Ave NW W3-200, Washington, DC, 20010, USA

    Laura J. Olivieri

  2. Department of Industrial Engineering, Università degli Studi di Napoli “Federico II”, 80125, Naples, Italy

    Francesco Capuano

  3. Department of Mechanics, Mathematics and Management, Politecnico di Bari, 70126, Bari, Italy

    Francesco Capuano

  4. Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA

    Laura J. Olivieri

  5. Department of Mechanical and Aerospace Engineering, George Washington University, Washington, DC, 20052, USA

    Elias Balaras

Authors
  1. Yue-Hin Loke
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Francesco Capuano
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elias Balaras
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Laura J. Olivieri
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yue-Hin Loke.

Ethics declarations

Disclosures

Dr. Yue-Hin Loke receives partial salary support from NIH R01 HL143468-01 and R21 HL156045. Dr. Francesco Capuano also received support from NIH UL1TR001876.

Research involving human rights

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000.

Informed consent

Informed consent was obtained from all patients for being included in the study was obtained from all patients for being included in the study.

Additional information

Associate Editor Ajit P. Yoganathan oversaw the review of this article.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary material 1 (MP4 3987 kb)

Supplementary material 2 (MP4 36734 kb)

Supplementary material 3 (MP4 15372 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Loke, YH., Capuano, F., Balaras, E. et al. Computational Modeling of Right Ventricular Motion and Intracardiac Flow in Repaired Tetralogy of Fallot. Cardiovasc Eng Tech 13, 41–54 (2022). https://doi.org/10.1007/s13239-021-00558-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13239-021-00558-3

Keywords

Search

Navigation