Skip to main content
SpringerLink
Log in

On-site evaluation of CT-based fractional flow reserve using simple boundary conditions for computational fluid dynamics

  • Original Paper
  • Published:
The International Journal of Cardiovascular Imaging Aims and scope Submit manuscript

Abstract

Fractional flow reserve (FFR) is an established method for diagnosing physiological coronary artery stenosis. A method for computing FFR using coronary computed tomography (CT) images was recently developed. However, its calculation requires off-site supercomputer analysis. Here, we report the preliminary result of a method using simple estimation of boundary conditions. The lumen boundaries of the coronary arteries were semi-automatically delineated using full width at half maximum of CT number profiles. The computational fluid dynamics (CFD) of the blood flow was performed using the boundary conditions of a fixed pressure at the coronary ostium and flow rates at each outlet. The total inflow at the coronary ostium was estimated based on the uniform wall shear stress hypothesis and corrected using a hyperemic multiplier to gain a hyperemic flow rate. The flow distribution from a parent vessel to the downstream daughter vessels was determined according to Murray’s law. FFR estimated by CFD was calculated as FFRCFD = Pd/Pa. We collected patients who underwent coronary CT and coronary angiography followed by invasively measured FFR and compared FFRCFD with FFR. Sensitivity, specificity, and correlations were assessed. A total of 48 patients and 72 arteries were assessed. The correlation coefficient of FFRCFD with FFR was 0.56. The cut-off value was ≤ 0.80, sensitivity was 59.1%, and specificity was 94.0%. CFD-based FFR using simple boundary conditions for on-site clinical computation provided FFRCFD values that were moderately correlated with invasively measured FFR.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Pijls NHJ, de Bruyne B, Peels K et al (1996) Measurement of fractional flow reserve to assess the functional severity of coronary-artery stenoses. N Engl J Med 334:1703–1708. https://doi.org/10.1056/NEJM199606273342604

    Article  CAS  PubMed  Google Scholar 

  2. Pijls NHJ, van Schaardenburgh P, Manoharan G et al (2007) Percutaneous coronary intervention of functionally nonsignificant stenosis. 5-Year follow-up of the DEFER study. J Am Coll Cardiol 49:2105–2111. https://doi.org/10.1016/j.jacc.2007.01.087

    Article  PubMed  Google Scholar 

  3. Tonino PAL, De Bruyne B, Pijls NHJ et al (2009) Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med 360:213–224. https://doi.org/10.1056/NEJMoa0807611

    Article  CAS  PubMed  Google Scholar 

  4. De Bruyne B, Pijls NHJ, Kalesan B et al (2012) Fractional flow reserve-guided PCI versus medical therapy in stable coronary disease. N Engl J Med 367:991–1001. https://doi.org/10.1056/NEJMoa1205361

    Article  CAS  PubMed  Google Scholar 

  5. De Bruyne B, Fearon WF, Pijls NHJ et al (2014) Fractional flow reserve-guided PCI for stable coronary artery disease. N Engl J Med 371:1208–1217. https://doi.org/10.1056/NEJMoa1408758

    Article  CAS  PubMed  Google Scholar 

  6. Xaplanteris P, Fournier S, Pijls NHJ et al (2018) Five-year outcomes with PCI guided by fractional flow reserve. N Engl J Med 379:250–259. https://doi.org/10.1056/NEJMoa1803538

    Article  PubMed  Google Scholar 

  7. Tanaka N, Kohsaka S, Murata T et al (2019) Treatment strategy modification and its implication on the medical cost of fractional flow reserve-guided percutaneous coronary intervention in Japan. J Cardiol 73:38–44. https://doi.org/10.1016/j.jjcc.2018.05.018

    Article  PubMed  Google Scholar 

  8. Hirose K, Chikamori T, Hida S et al (2018) Application of pressure-derived myocardial fractional flow reserve in chronic hemodialysis patients. J Cardiol 71:52–58. https://doi.org/10.1016/j.jjcc.2017.05.007

    Article  PubMed  Google Scholar 

  9. Davies JE, Sen S, Dehbi H-M et al (2017) Use of the instantaneous wave-free ratio or fractional flow reserve in PCI. N Engl J Med. https://doi.org/10.1056/NEJMoa1700445

    Article  PubMed  PubMed Central  Google Scholar 

  10. Liu X, Gao Z, Xiong H et al (2016) Three-dimensional hemodynamics analysis of the circle of Willis in the patient-specific nonintegral arterial structures. Biomech Model Mechanobiol 15:1439–1456. https://doi.org/10.1007/s10237-016-0773-6

    Article  PubMed  Google Scholar 

  11. Koo BK, Erglis A, Doh JH et al (2011) Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms: results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noni. J Am Coll Cardiol 58:1989–1997. https://doi.org/10.1016/j.jacc.2011.06.066

    Article  PubMed  Google Scholar 

  12. Nakazato R, Park HB, Berman DS et al (2013) Noninvasive fractional flow reserve derived from computed tomography angiography for coronary lesions of intermediate stenosis severity results from the DeFACTO study. Circ Cardiovasc Imaging 6:881–889. https://doi.org/10.1161/CIRCIMAGING.113.000297

    Article  PubMed  Google Scholar 

  13. Nørgaard BL, Leipsic J, Gaur S et al (2014) Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). J Am Coll Cardiol 63:1145–1155. https://doi.org/10.1016/j.jacc.2013.11.043

    Article  PubMed  Google Scholar 

  14. Nozue T, Fukui K, Takamura T et al (2017) Effects of alogliptin on fractional flow reserve evaluated by coronary computed tomography angiography in patients with type 2 diabetes: rationale and design of the TRACT study. J Cardiol 69:518–522. https://doi.org/10.1016/j.jjcc.2016.04.014

    Article  PubMed  Google Scholar 

  15. Zarins CK, Zatina MA, Giddens DP et al (1987) Shear stress regulation of artery lumen diameter in experimental atherogenesis. J Vasc Surg 5:413–420. https://doi.org/10.1016/0741-5214(87)90048-6

    Article  CAS  PubMed  Google Scholar 

  16. Wieneke H (2004) Determinants of coronary blood flow in humans: quantification by intracoronary Doppler and ultrasound. J Appl Physiol 98:1076–1082. https://doi.org/10.1152/japplphysiol.00724.2004

    Article  PubMed  Google Scholar 

  17. Murray CD (1931) The physiological principle of minimum work: a reply. J Gen Physiol 14:445. https://doi.org/10.1085/jgp.9.6.835

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Wu FZ, Wu MT (2015) 2014 SCCT guidelines for the interpretation and reporting of coronary CT angiography: a report of the society of cardiovascular computed tomography guidelines committee. J Cardiovasc Comput Tomogr 9:E3. https://doi.org/10.1016/j.jcct.2015.01.003

    Article  PubMed  Google Scholar 

  19. Abbara S, Arbab-Zadeh A, Callister TQ et al (2009) SCCT guidelines for performance of coronary computed tomographic angiography: a report of the society of cardiovascular computed tomography guidelines committee. J Cardiovasc Comput Tomogr 3:190–204. https://doi.org/10.1016/j.jcct.2009.03.004

    Article  PubMed  Google Scholar 

  20. Agatston AS, Janowitz WR, Hildner FJ et al (1990) Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 15:827–832. https://doi.org/10.1016/0735-1097(90)90282-T

    Article  CAS  PubMed  Google Scholar 

  21. Austen WG, Edwards JE, Frye RL et al (1975) A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular Surgery, American Heart Association. Circulation 51:5–40

    Article  CAS  PubMed  Google Scholar 

  22. Lee JM, Choi G, Koo BK et al (2019) Identification of high-risk plaques destined to cause acute coronary syndrome using coronary computed tomographic angiography and computational fluid dynamics. JACC Cardiovasc Imaging 12:1032–1043. https://doi.org/10.1016/j.jcmg.2018.01.023

    Article  PubMed  Google Scholar 

  23. Park JB, Choi G, Chun EJ et al (2016) Computational fluid dynamic measures of wall shear stress are related to coronary lesion characteristics. Heart 102:1655–1661. https://doi.org/10.1136/heartjnl-2016-309299

    Article  PubMed  Google Scholar 

  24. Shi C, Zhang D, Cao K et al (2017) A study of noninvasive fractional flow reserve derived from a simplified method based on coronary computed tomography angiography in suspected coronary artery disease. Biomed Eng Online 16:43. https://doi.org/10.1186/s12938-017-0330-2

    Article  PubMed  PubMed Central  Google Scholar 

  25. Zhang JM, Zhong L, Luo T et al (2016) Simplified models of Non-Invasive fractional flow reserve based on CT images. PLoS ONE 11:1–20. https://doi.org/10.1371/journal.pone.0153070

    Article  CAS  Google Scholar 

  26. Tu S, Barbato E, Köszegi Z et al (2014) Fractional flow reserve calculation from 3-dimensional quantitative coronary angiography and TIMI frame count: a fast computer model to quantify the functional significance of moderately obstructed coronary arteries. JACC Cardiovasc Interv 7:768–777. https://doi.org/10.1016/j.jcin.2014.03.004

    Article  PubMed  Google Scholar 

  27. Leuprecht A, Perktold K, Kozerke S, Boesiger P (2002) Combined CFD and MRI study of blood flow in a human ascending aorta model. Biorheology 39:425–429

    PubMed  Google Scholar 

  28. Torii R, Wood NB, Hadjiloizou N et al (2009) Fluid-structure interaction analysis of a patient-specific right coronary artery with physiological velocity and pressure waveforms. Commun Numer Methods Eng 25:565–580. https://doi.org/10.1002/cnm.1231

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Cardiovascular Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin-Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan

    Yusuke Yoshikawa, Erika Yamamoto, Hiroki Shiomi, Takeshi Kimura & Naritatsu Saito

  2. EBM Corporation, Tokyo, Japan

    Masahiko Nakamoto & Takeharu Hoshi

  3. Biomechanics Laboratory, Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya, Japan

    Masanori Nakamura

  4. Department of Cardiovascular Medicine, Gifu Heart Center, Gifu, Japan

    Shunsuke Imai, Yoshiaki Kawase, Munenori Okubo, Takeshi Kondo & Hitoshi Matsuo

Authors
  1. Yusuke Yoshikawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Masahiko Nakamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Masanori Nakamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Takeharu Hoshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Erika Yamamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shunsuke Imai
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yoshiaki Kawase
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Munenori Okubo
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Hiroki Shiomi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Takeshi Kondo
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Hitoshi Matsuo
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Takeshi Kimura
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Naritatsu Saito
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Naritatsu Saito.

Ethics declarations

Conflicts of interest

None of the authors have anything to declare regarding this article. This study was conducted as a part of the project focused on creation of medical arts by Japan Agency for Medical Research and Development (Grant Number JP17hk0102035).

Research involving human participants and/or animals

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

The need for written informed consent was waived because of the study’s retrospective design.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yoshikawa, Y., Nakamoto, M., Nakamura, M. et al. On-site evaluation of CT-based fractional flow reserve using simple boundary conditions for computational fluid dynamics. Int J Cardiovasc Imaging 36, 337–346 (2020). https://doi.org/10.1007/s10554-019-01709-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10554-019-01709-3

Keywords

Search

Navigation