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Coronary CT angiography-derived fractional flow reserve correlated with invasive fractional flow reserve measurements – initial experience with a novel physician-driven algorithm

  • Cardiac
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Abstract

Objectives

The present study aimed to determine the feasibility of a novel fractional flow reserve (FFR) algorithm based on coronary CT angiography (cCTA) that permits point-of-care assessment, without data transfer to core laboratories, for the evaluation of potentially ischemia-causing stenoses.

Methods

To obtain CT-based FFR, anatomical coronary information and ventricular mass extracted from cCTA datasets were integrated with haemodynamic parameters. CT-based FFR was assessed for 36 coronary artery stenoses in 28 patients in a blinded fashion and compared to catheter-based FFR. Haemodynamically relevant stenoses were defined by an invasive FFR ≤0.80. Time was measured for the processing of each cCTA dataset and CT-based FFR computation. Assessment of cCTA image quality was performed using a 5-point scale.

Results

Mean total time for CT-based FFR determination was 51.9 ± 9.0 min. Per-vessel analysis for the identification of lesion-specific myocardial ischemia demonstrated good correlation (Pearson’s product-moment r = 0.74, p < 0.0001) between the prototype CT-based FFR algorithm and invasive FFR. Subjective image quality analysis resulted in a median score of 4 (interquartile ranges, 3-4).

Conclusions

Our initial data suggest that the CT-based FFR method for the detection of haemodynamically significant stenoses evaluated in the selected population correlates well with invasive FFR and renders time-efficient point-of-care assessment possible.

Key Points

• CT-based FFR computation is a promising novel non-invasive application.

• A novel prototype algorithm permits time-efficient point-of-care CT-based FFR assessment.

• Initial results of the CT-based FFR prototype algorithm compare favourably with FFR.

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Abbreviations

CAD:

Coronary artery disease

cCTA:

Coronary computed tomographic angiography

FFR:

Fractional flow reserve

CT-based FFR:

Fractional flow reserve from coronary computed tomographic angiography

CCA:

Invasive coronary catheter angiography

References

  1. Pijls NH, 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

    Article  CAS  PubMed  Google Scholar 

  2. Toth G, De Bruyne B, Casselman F et al (2013) Fractional flow reserve-guided versus angiography-guided coronary artery bypass graft surgery. Circulation 128:1405–1411

    Article  PubMed  Google Scholar 

  3. Tonino PA, De Bruyne B, Pijls NH et al (2009) Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med 360:213–224

    Article  CAS  PubMed  Google Scholar 

  4. Frauenfelder T, Boutsianis E, Schertler T et al (2007) In-vivo flow simulation in coronary arteries based on computed tomography datasets: feasibility and initial results. Eur Radiol 17:1291–1300

    Article  PubMed  Google Scholar 

  5. Grunau GL, Min JK, Leipsic J (2013) Modeling of fractional flow reserve based on coronary CT angiography. Curr Cardiol Rep 15:336

    Article  PubMed  Google Scholar 

  6. Min JK, Leipsic J, Pencina MJ et al (2012) Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA 308:1237–1245

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  7. 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 noninvasive fractional flow reserve) study. J Am Coll Cardiol 58:1989–1997

    Article  PubMed  Google Scholar 

  8. Norgaard 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

    Article  PubMed  Google Scholar 

  9. Sianos G, Morel MA, Kappetein AP et al (2005) The SYNTAX Score: an angiographic tool grading the complexity of coronary artery disease. EuroInterv 1:219–227

    Google Scholar 

  10. Husmann L, Alkadhi H, Boehm T et al (2006) Influence of cardiac hemodynamic parameters on coronary artery opacification with 64-slice computed tomography. Eur Radiol 16:1111–1116

    Article  PubMed  Google Scholar 

  11. Itu L, Sharma P, Mihalef V, Kamen A, Suciu C, Lomaniciu D (2012) A patient-specific reduced-order model for coronary circulationBiomedical Imaging (ISBI), 2012 9th IEEE International Symposium on, pp 832-835

  12. Sharma P, Itu L, Zheng X et al (2012) A framework for personalization of coronary flow computations during rest and hyperemia. Conf Proc IEEE Eng Med Biol Soc 2012:6665–6668

    PubMed  Google Scholar 

  13. Wilson RF, Wyche K, Christensen BV, Zimmer S, Laxson DD (1990) Effects of adenosine on human coronary arterial circulation. Circulation 82:1595–1606

    Article  CAS  PubMed  Google Scholar 

  14. Raff GL, Abidov A, Achenbach S et al (2009) SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography. J Cardiovasc Comput Tomogr 3:122–136

    Article  PubMed  Google Scholar 

  15. De Cecco CN, Meinel FG, Chiaramida SA, Costello P, Bamberg F, Schoepf UJ (2014) Coronary artery computed tomography scanning. Circulation 129:1341–1345

    Article  PubMed  Google Scholar 

  16. Ebersberger U, Marcus RP, Schoepf UJ et al (2014) Dynamic CT myocardial perfusion imaging: performance of 3D semi-automated evaluation software. Eur Radiol 24:191–199

    Article  PubMed  Google Scholar 

  17. Thilo C, Schoepf UJ, Gordon L, Chiaramida S, Serguson J, Costello P (2009) Integrated assessment of coronary anatomy and myocardial perfusion using a retractable SPECT camera combined with 64-slice CT: initial experience. Eur Radiol 19:845–856

    Article  PubMed  Google Scholar 

  18. Enrico B, Suranyi P, Thilo C, Bonomo L, Costello P, Schoepf UJ (2009) Coronary artery plaque formation at coronary CT angiography: morphological analysis and relationship to hemodynamics. Eur Radiol 19:837–844

    Article  PubMed  Google Scholar 

  19. Nasis A, Ko BS, Leung MC et al (2013) Diagnostic accuracy of combined coronary angiography and adenosine stress myocardial perfusion imaging using 320-detector computed tomography: pilot study. Eur Radiol 23:1812–1821

    Article  PubMed  Google Scholar 

  20. Moscariello A, Vliegenthart R, Schoepf UJ et al (2012) Coronary CT angiography versus conventional cardiac angiography for therapeutic decision making in patients with high likelihood of coronary artery disease. Radiology 265:385–392

    Article  PubMed  Google Scholar 

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Acknowledgments

The scientific guarantor of this publication is U. Joseph Schoepf. The authors of this manuscript declare relationships with the following companies: GE, Bracco, Siemens, Bayer and St. Jude. The authors state that this work has not received any funding. One of the authors has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. No animals were used in this study. No study subjects or cohorts have been previously reported. Methodology: retrospective, diagnostic or prognostic study, performed at one institution. Fast flow computations of coronary blood flow were not carried out in the United States.

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Authors and Affiliations

  1. Heart & Vascular Center, Medical University of South Carolina, Ashley River Tower, 25 Courtenay Drive, Charleston, SC, 29425-2260, USA

    Stefan Baumann, Rui Wang, U. Joseph Schoepf, Daniel H. Steinberg, James V. Spearman, Richard R. Bayer II & Matthias Renker

  2. First Department of Medicine, Faculty of Medicine Mannheim, University Medical Centre Mannheim (UMM), University of Heidelberg, Mannheim, Germany

    Stefan Baumann

  3. Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China

    Rui Wang

  4. Department of Internal Medicine I, Cardiology/Angiology, Giessen University, Giessen, Germany

    Christian W. Hamm & Matthias Renker

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  1. Stefan Baumann
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  2. Rui Wang
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  3. U. Joseph Schoepf
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  4. Daniel H. Steinberg
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  5. James V. Spearman
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  6. Richard R. Bayer II
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  7. Christian W. Hamm
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  8. Matthias Renker
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Correspondence to U. Joseph Schoepf.

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Baumann, S., Wang, R., Schoepf, U.J. et al. Coronary CT angiography-derived fractional flow reserve correlated with invasive fractional flow reserve measurements – initial experience with a novel physician-driven algorithm. Eur Radiol 25, 1201–1207 (2015). https://doi.org/10.1007/s00330-014-3482-5

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  • DOI: https://doi.org/10.1007/s00330-014-3482-5

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