Skip to main content

A Computational Framework for Personalized Blood Flow Analysis in the Human Left Atrium

Abstract

Atrial fibrillation (AF), the most common human arrhythmia, is a marker of an increased risk of embolic stroke. However, recent studies suggest that AF may not be mechanistically responsible for the stroke events. An alternative explanation for the mechanism of intracardiac thrombosis and stroke in patients with AF is structural remodeling of the left atrium (LA). Nevertheless, a mechanistic link between LA structural remodeling and intracardiac thrombosis is unclear, because there is no clinically feasible methodology to evaluate the complex relationship between these two phenomena in individual patients. Computational fluid dynamics (CFD) is a powerful tool that could potentially link LA structural remodeling and intracardiac thrombosis in individual patients by evaluating the patient-specific LA blood flow characteristics. However, the lack of knowledge of the material and mechanical properties of the heart wall in specific patients makes it challenging to solve the complexity of fluid–structure interaction. In this study, our aim was to develop a clinically feasible methodology to perform personalized blood flow analysis within the heart. We propose an alternative computational approach to perform personalized blood flow analysis by providing the three-dimensional LA endocardial surface motion estimated from patient-specific cardiac CT images. In two patients (case 1 and 2), a four-dimensional displacement vector field was estimated using nonrigid registration. The LA blood outflow across the mitral valve (MV) was calculated from the LV volume, and the flow field within the LA was derived from the incompressible Navier–Stokes equation. The CFD results successfully captured characteristic features of LA blood flow observed clinically by transesophageal echocardiogram. The LA global flow characteristics and vortex structures also agreed well with previous reports. The time course of LAA emptying was similar in both cases, despite the substantial difference in the LA structure and function. We conclude that our CT-based, personalized LA blood flow analysis is a clinically feasible methodology that can be used to improve our understanding of the mechanism of intracardiac thrombosis and stroke in individual patients with LA structural remodeling.

This is a preview of subscription content, access via your institution.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Abbreviations

AF:

Atrial fibrillation

CFD:

Computational fluid dynamics

CT:

Computed tomography

LA:

Left atrium

LAA:

Left atrial appendage

LV:

Left ventricle

MV:

Mitral valve

PV:

Pulmonary vein

TEE:

Transesophageal echocardiogram

3D:

Three-dimensional

4D:

Four-dimensional

References

  1. 1.

    Agmon, Y., B. K. Khandheria, F. Gentile, and J. B. Seward. Echocardiographic assessment of the left atrial appendage. J. Am. Coll. Cardiol. 34:1867–1877, 1999. doi:10.1016/S0735-1097(99)00472-6.

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Al-Issa, A., Y. Inoue, J. Cammin, Q. Tang, S. Nazarian, H. Calkins, E. K. Fishman, K. Taguchi, and H. Ashikaga. Regional function analysis of left atrial appendage using motion estimation CT and risk of stroke in patients with atrial fibrillation. Eur. Hear. J. Cardiovasc. Imaging jev207, 2015. doi:10.1093/ehjci/jev207.

  3. 3.

    Benjamin, E. J., R. B. D’Agostino, A. J. Belanger, P. A. Wolf, and D. Levy. Left atrial size and the risk of stroke and death: the Framingham heart study. Circulation 92:835–841, 1995. doi:10.1161/01.CIR.92.4.835.

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Blackshear, J. L., and J. A. Odell. Appendage obliteration to reduce stroke in cardiac surgical patients with atrial fibrillation. Ann. Thorac. Surg. 61:755–759, 1996. doi:10.1016/0003-4975(95)00887-X.

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Brambatti, M., S. J. Connolly, M. R. Gold, C. A. Morillo, A. Capucci, C. Muto, C. P. Lau, I. C. Van Gelder, S. H. Hohnloser, M. Carlson, E. Fain, J. Nakamya, G. H. Mairesse, M. Halytska, W. Q. Deng, C. W. Israel, and J. S. Healey. Temporal relationship between subclinical atrial fibrillation and embolic events. Circulation 129:2094–2099, 2014. doi:10.1161/CIRCULATIONAHA.113.007825.

    Article  PubMed  Google Scholar 

  6. 6.

    Chnafa, C., S. Mendez, and F. Nicoud. Image-based large-eddy simulation in a realistic left heart. Comput. Fluids 94:173–187, 2014. doi:10.1016/j.compfluid.2014.01.030.

    Article  Google Scholar 

  7. 7.

    Daccarett, M., T. J. Badger, N. Akoum, N. S. Burgon, C. Mahnkopf, G. Vergara, E. Kholmovski, C. J. McGann, D. Parker, J. Brachmann, R. S. MacLeod, and N. F. Marrouche. Association of left atrial fibrosis detected by delayed-enhancement magnetic resonance imaging and the risk of stroke in patients with atrial fibrillation. J. Am. Coll. Cardiol. 57:831, 2011. doi:10.1016/j.jacc.2010.09.049.

    Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Daoud, E. G., T. V. Glotzer, D. G. Wyse, M. D. Ezekowitz, C. Hilker, J. Koehler, P. D. Ziegler, and T. Investigators. Temporal relationship of atrial tachyarrhythmias, cerebrovascular events, and systemic emboli based on stored device data: a subgroup analysis of TRENDS. Heart Rhythm 8:1416–1423, 2011. doi:10.1016/j.hrthm.2011.04.022.

    Article  PubMed  Google Scholar 

  9. 9.

    Di Biase, L., P. Santangeli, M. Anselmino, P. Mohanty, I. Salvetti, S. Gili, R. Horton, J. E. Sanchez, R. Bai, S. Mohanty, A. Pump, M. Cereceda Brantes, G. J. Gallinghouse, J. D. Burkhardt, M. Cereceda Brantes, F. Cesarani, M. Scaglione, A. Natale, and F. Gaita. Does the left atrial appendage morphology correlate with the risk of stroke in patients with atrial fibrillation? Results from a multicenter study. J. Am. Coll. Cardiol. 60:531–538, 2012. doi:10.1016/j.jacc.2012.04.032.

    Article  PubMed  Google Scholar 

  10. 10.

    Fatema, K., K. R. Bailey, G. W. Petty, I. Meissner, M. Osranek, A. A. Alsaileek, B. K. Khandheria, T. S. Tsang, and J. B. Seward. Increased left atrial volume index: potent biomarker for first-ever ischemic stroke. Mayo Clin. Proc. 83:1107–1115, 2008. doi:10.4065/83.10.1107.

    Article  PubMed  Google Scholar 

  11. 11.

    Fyrenius, A., L. Wigström, T. Ebbers, M. Karlsson, J. Engvall, and A. F. Bolger. Three dimensional flow in the human left atrium. Heart 86:448–455, 2001. doi:10.1136/heart.86.4.448.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Goubergrits, L., U. Kertzscher, K. Affeld, C. Petz, D. Stalling, and H. C. Hege. Numerical dye washout method as a tool for characterizing the heart valve flow: study of three standard mechanical heart valves. ASAIO J. 54:50–57, 2008. doi:10.1097/MAT.0b013e31815c5e38.

    Article  PubMed  Google Scholar 

  13. 13.

    Healey, J. S., S. J. Connolly, M. R. Gold, C. W. Israel, I. C. Van Gelder, A. Capucci, C. P. Lau, E. Fain, S. Yang, C. Bailleul, C. A. Morillo, M. Carlson, E. Themeles, E. S. Kaufman, and S. H. Hohnloser. Subclinical atrial fibrillation and the risk of stroke. N. Engl. J. Med. 366:120–129, 2012. doi:10.1056/NEJMoa1105575.

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Inoue, Y. Y., A. Alissa, I. M. Khurram, K. Fukumoto, M. Habibi, B. A. Venkatesh, S. L. Zimmerman, S. Nazarian, R. D. Berger, H. Calkins, J. A. Lima, and H. Ashikaga. Quantitative tissue-tracking cardiac magnetic resonance (CMR) of left atrial deformation and the risk of stroke in patients with atrial fibrillation. J. Am. Heart Assoc. 4:e001844–e001844, 2015. doi:10.1161/JAHA.115.001844.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Khurram, I. M., J. Dewire, M. Mager, F. Maqbool, S. L. Zimmerman, V. Zipunnikov, R. Beinart, J. E. Marine, D. D. Spragg, R. D. Berger, H. Ashikaga, S. Nazarian, and H. Calkins. Relationship between left atrial appendage morphology and stroke in patients with atrial fibrillation. Heart Rhythm 10:1843–1849, 2013. doi:10.1016/j.hrthm.2013.09.065.

    Article  PubMed  Google Scholar 

  16. 16.

    Kim, T., A. Y. Cheer, and H. A. Dwyer. A simulated dye method for flow visualization with a computational model for blood flow. J. Biomech. 37:1125–1136, 2004. doi:10.1016/j.jbiomech.2003.12.028.

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Kimura, T., S. Takatsuki, K. Inagawa, Y. Katsumata, T. Nishiyama, N. Nishiyama, K. Fukumoto, Y. Aizawa, Y. Tanimoto, K. Tanimoto, M. Jinzaki, and K. Fukuda. Anatomical characteristics of the left atrial appendage in cardiogenic stroke with low CHADS2 scores. Heart Rhythm 10:921–925, 2013. doi:10.1016/j.hrthm.2013.01.036.

    Article  PubMed  Google Scholar 

  18. 18.

    Kizer, J. R., J. N. Bella, V. Palmieri, J. E. Liu, L. G. Best, E. T. Lee, M. J. Roman, and R. B. Devereux. Left atrial diameter as an independent predictor of first clinical cardiovascular events in middle-aged and elderly adults: the Strong Heart Study (SHS). Am. Heart J. 151:412–418, 2006. doi:10.1016/j.ahj.2005.04.031.

    Article  PubMed  Google Scholar 

  19. 19.

    Koizumi, R., K. Funamoto, T. Hayase, Y. Kanke, M. Shibata, Y. Shiraishi, and T. Yambe. Numerical analysis of hemodynamic changes in the left atrium due to atrial fibrillation. J. Biomech. 48:472–478, 2015. doi:10.1016/j.jbiomech.2014.12.025.

    Article  PubMed  Google Scholar 

  20. 20.

    Ku, D. N. Blood flow in arteries. Annu. Rev. Fluid Mech. 29:399–434, 1997. doi:10.1146/annurev.fluid.29.1.399.

    Article  Google Scholar 

  21. 21.

    Miller, J. M., C. E. Rochitte, M. Dewey, A. Arbab-Zadeh, H. Niinuma, I. Gottlieb, N. Paul, M. E. Clouse, E. P. Shapiro, J. Hoe, A. C. Lardo, D. E. Bush, A. de Roos, C. Cox, J. Brinker, and J. A. C. Lima. Diagnostic performance of coronary angiography by 64-row CT. N. Engl. J. Med. 359:2324–2336, 2008. doi:10.1056/NEJMoa0806576.

    CAS  Article  PubMed  Google Scholar 

  22. 22.

    Morales, H., I. Larrabide, A. Geers, L. San Roman, J. Blasco, J. Macho, and A. Frangi. A virtual coiling technique for image-based aneurysm models by dynamic path planning. IEEE Trans. Med. Imaging 1–11, 2012. doi:10.1109/TMI.2012.2219626.

  23. 23.

    Ozer, N., L. Tokgozoglu, K. Ovunc, G. Kabakci, S. Aksoyek, K. Aytemir, and S. Kes. Left atrial appendage function in patients with cardioembolic stroke in sinus rhythm and atrial fibrillation. J. Am. Soc. Echocardiogr. 13:661–665, 2000. doi:10.1067/mje.2000.105629.

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Piccini, J. P., and J. P. Daubert. Atrial fibrillation and stroke: it’s not necessarily all about the rhythm. Heart Rhythm 8:1424–1425, 2011. doi:10.1016/j.hrthm.2011.05.005.

    Article  PubMed  Google Scholar 

  25. 25.

    Pourmorteza, A., K. H. Schuleri, D. A. Herzka, A. C. Lardo, and E. R. McVeigh. A new method for cardiac computed tomography regional function assessment: Stretch quantifier for endocardial engraved zones (SQUEEZ). Circ. cardiovasc. Imaging 5:243–250, 2012. doi:10.1161/CIRCIMAGING.111.970061.

    Article  PubMed  Google Scholar 

  26. 26.

    Russo, C., Z. Jin, R. Liu, S. Iwata, A. Tugcu, M. Yoshita, S. Homma, M. S. V. Elkind, T. Rundek, C. Decarli, B. Wright, R. L. Sacco, and M. R. Di Tullio. LA volumes and reservoir function are associated with subclinical cerebrovascular disease: The CABL (Cardiovascular Abnormalities and Brain Lesions) study. JACC. Cardiovasc. Imaging 6:313–324, 2013. doi:10.1016/j.jcmg.2012.10.019.

    Google Scholar 

  27. 27.

    Seo, J. H., and R. Mittal. Effect of diastolic flow patterns on the function of the left ventricle. Phys. Fluids 25:110801, 2013. doi:10.1063/1.4819067.

    Article  Google Scholar 

  28. 28.

    Seo, J. H., V. Vedula, T. Abraham, A. C. Lardo, F. Dawoud, H. Luo, and R. Mittal. Effect of the mitral valve on diastolic flow patterns. Phys. Fluids 26:121901, 2014. doi:10.1063/1.4904094.

    Article  Google Scholar 

  29. 29.

    Smiseth, O. A., C. R. Thompson, K. Lohavanichbutr, H. Ling, J. G. Abel, R. T. Miyagishima, S. V. Lichtenstein, and J. Bowering. The pulmonary venous systolic flow pulse–its origin and relationship to left atrial pressure. J. Am. Coll. Cardiol. 34:802–809, 1999. doi:10.1016/S0735-1097(99)00300-9.

    CAS  Article  PubMed  Google Scholar 

  30. 30.

    Tsang, T. S. M., W. P. Abhayaratna, M. E. Barnes, Y. Miyasaka, B. J. Gersh, K. R. Bailey, S. S. Cha, and J. B. Seward. Prediction of cardiovascular outcomes with left atrial size: Is volume superior to area or diameter? J. Am. Coll. Cardiol. 47:1018–1023, 2006. doi:10.1016/j.jacc.2005.08.077.

    Article  PubMed  Google Scholar 

  31. 31.

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

    PubMed  Google Scholar 

  32. 32.

    Wolf, P. A., R. D. Abbott, and W. B. Kannel. Atrial fibrillation as an independent risk factor for stroke: the Framingham study. Stroke 22:983–988, 1991. doi:10.1161/01.STR.22.8.983.

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Wong, J. M., C. C. Welles, F. Azarbal, M. A. Whooley, N. B. Schiller, and M. P. Turakhia. Relation of left atrial dysfunction to ischemic stroke in patients with coronary heart disease (from the Heart and Soul Study). Am. J. Cardiol. 113:1679–1684, 2014. doi:10.1016/j.amjcard.2014.02.021.

    Article  PubMed  Google Scholar 

  34. 34.

    Zhang, L., and M. Gay. Characterizing left atrial appendage functions in sinus rhythm and atrial fibrillation using computational models. J. Biomech. 41:2515–2523, 2008. doi:10.1016/j.jbiomech.2008.05.012.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors thank Satoshi Ii for valuable input as to the CFD methodology. The authors also thank Yuko Inoue and Susumu Tao for clinical input. This work was supported by research grants from the Japan Society for the Promotion of Science (JSPS) (Research Fellowship for Young Scientist A2616220, to Otani), Magic That Matters Fund for Cardiovascular Research (to Ashikaga) and Zegar Family Foundation (to Ashikaga).

Conflict of interest

None.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Hiroshi Ashikaga.

Additional information

Associate Editor Peter E. McHugh oversaw the review of this article.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 2 (MP4 2514 kb)

Supplementary material 3 (MP4 2486 kb)

Supplementary material 4 (MP4 1868 kb)

Supplementary material 5 (MP4 1686 kb)

Supplementary material 1 (PDF 185 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Otani, T., Al-Issa, A., Pourmorteza, A. et al. A Computational Framework for Personalized Blood Flow Analysis in the Human Left Atrium. Ann Biomed Eng 44, 3284–3294 (2016). https://doi.org/10.1007/s10439-016-1590-x

Download citation

Keywords

  • Image-based simulation
  • Computed tomography
  • Computational fluid dynamics
  • Cardiac mechanics
  • Left atrium