Abstract
Background
Fractional flow reserve based on coronary CT angiography (CT-FFR) is gaining importance for non-invasive hemodynamic assessment of coronary artery disease (CAD). We evaluated the on-site CT-FFR with a machine learning algorithm (CT-FFRML) for the detection of hemodynamically significant coronary artery stenosis in comparison to the invasive reference standard of instantaneous wave free ratio (iFR®).
Methods
This study evaluated patients with CAD who had a clinically indicated coronary computed tomography angiography (cCTA) and underwent invasive coronary angiography (ICA) with iFR®-measurements. Standard cCTA studies were acquired with third-generation dual-source computed tomography and analyzed with on-site prototype CT-FFRML software.
Results
We enrolled 40 patients (73% males, mean age 67 ± 12 years) who had iFR®-measurement and CT-FFRML calculation. The mean calculation time of CT-FFRML values was 11 ± 2 min. The CT-FFRML algorithm showed, on per-patient and per-lesion level, respectively, a sensitivity of 92% (95% CI 64–99%) and 87% (95% CI 59–98%), a specificity of 96% (95% CI 81–99%) and 95% (95% CI 84–99%), a positive predictive value of 92% (95% CI 64–99%), and 87% (95% CI 59–98%), and a negative predictive value of 96% (95% CI 81–99%) and 95% (95% CI 84–99%). The area under the receiver operating characteristic curve for CT-FFRML on per-lesion level was 0.97 (95% CI 0.91–1.00). Per lesion, the Pearson’s correlation between the CT-FFRML and iFR® showed a strong correlation of r = 0.82 (p < 0.0001; 95% CI 0.715–0.920).
Conclusion
On-site CT-FFRML correlated well with the invasive reference standard of iFR® and allowed for the non-invasive detection of hemodynamically significant coronary stenosis.
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Abbreviations
- CAD:
-
Coronary artery disease
- cCTA:
-
Coronary computed tomography angiography
- CT:
-
Computed tomography
- CT-FFR:
-
Fractional flow reserve derived from coronary computed tomography angiography
- CT-FFRML :
-
Fractional flow reserve derived from coronary computed tomography angiography based on machine learning algorithm
- ESC:
-
European Society of Cardiology
- FFR:
-
Fractional flow reserve
- ICA:
-
Invasive coronary angiography
- iFR® :
-
Instantaneous wave free ratio
References
Erthal F, Premaratne M, Yam Y, Chen L, Lamba J, Keenan M et al (2018) Appropriate use criteria for cardiac computed tomography: does computed tomography have incremental value in all appropriate use criteria categories? J Thorac Imaging 33(2):132–137
Maroules CD, Rajiah P, Bhasin M, Abbara S (2019) Current evidence in cardiothoracic imaging: growing evidence for coronary computed tomography angiography as a first-line test in stable chest pain. J Thorac Imaging 34(1):4–11
Patel MR, Peterson ED, Dai D, Brennan JM, Redberg RF, Anderson HV et al (2010) Low diagnostic yield of elective coronary angiography. N Engl J Med 362(10):886–895
Patel MR, Dai D, Hernandez AF, Douglas PS, Messenger J, Garratt KN et al (2014) Prevalence and predictors of non-obstructive coronary artery disease identified with coronary angiography in contemporary clinical practice. Am Heart J 167(6):846–852 (e2)
Meijboom WB, Meijs MF, Schuijf JD, Cramer MJ, Mollet NR, van Mieghem CA et al (2008) Diagnostic accuracy of 64-slice computed tomography coronary angiography: a prospective, multicenter, multivendor study. J Am Coll Cardiol 52(25):2135–2144
The SC (2015) CT coronary angiography in patients with suspected angina due to coronary heart disease (SCOT-HEART): an open-label, parallel-group, multicentre trial. Lancet (London, England) 385(9985):2383–2391
Bittner DO, Ferencik M, Douglas PS, Hoffmann U (2016) Coronary CT angiography as a diagnostic and prognostic tool: perspective from a multicenter randomized controlled trial: PROMISE. Curr Cardiol Rep 18(5):40
Taylor CA, Fonte TA, Min JK (2013) Computational fluid dynamics applied to cardiac computed tomography for non-invasive quantification of fractional flow reserve: scientific basis. J Am Coll Cardiol 61(22):2233–2241
Renker M, Schoepf UJ, Becher T, Krampulz N, Kim W, Rolf A et al (2017) Computed tomography in patients with chronic stable angina: fractional flow reserve measurement. Herz 42(1):51–57
Wang R, Renker M, Schoepf UJ, Wichmann JL, Fuller SR, Rier JD et al (2015) Diagnostic value of quantitative stenosis predictors with coronary CT angiography compared to invasive fractional flow reserve. Eur J Radiol 84(8):1509–1515
Baumann S, Becher T, Schoepf UJ, Lossnitzer D, Henzler T, Akin I et al (2017) Fractional flow reserve derived by coronary computed tomography angiography: a sophisticated analysis method for detecting hemodynamically significant coronary stenosis. Herz 42(6):604–606
Schmermund A, Eckert J, Schmidt M, Magedanz A, Voigtlander T (2018) Coronary computed tomography angiography: a method coming of age. Clin Res Cardiol 107(Suppl 2):40–48
Ihdayhid AR, Sakaguchi T, Linde JJ, Sorgaard MH, Kofoed KF, Fujisawa Y et al (2018) Performance of computed tomography-derived fractional flow reserve using reduced-order modelling and static computed tomography stress myocardial perfusion imaging for detection of haemodynamically significant coronary stenosis. Eur Heart J Cardiovasc Imaging 19(11):1234–1243
Schuijf JD, Ko BS, Di Carli MF, Hislop-Jambrich J, Ihdayhid AR, Seneviratne SK et al (2018) Fractional flow reserve and myocardial perfusion by computed tomography: a guide to clinical application. Eur Heart J Cardiovasc Imaging 19(2):127–135
Schwartz FR, Koweek LM, Norgaard BL (2019) Current evidence in cardiothoracic imaging: computed tomography-derived fractional flow reserve in stable chest pain. J Thorac Imaging 34(1):12–17
Benton SM Jr, Tesche C, De Cecco CN, Duguay TM, Schoepf UJ, Bayer RR 2nd (2018) Noninvasive derivation of fractional flow reserve from coronary computed tomographic angiography: a review. J Thorac Imaging 33(2):88–96
Baumann S, Akin I, Borggrefe M, Ball BD Jr, Schoepf UJ, Renker M (2016) Different approaches for coronary computed tomography angiography-derived versus invasive fractional flow reserve assessment. Am J Cardiol 117(3):486
Gonzalez JA, Lipinski MJ, Flors L, Shaw PW, Kramer CM, Salerno M (2015) Meta-analysis of diagnostic performance of coronary computed tomography angiography, computed tomography perfusion, and computed tomography-fractional flow reserve in functional myocardial ischemia assessment versus invasive fractional flow reserve. Am J Cardiol 116(9):1469–1478
Douglas PS, Pontone G, Hlatky MA, Patel MR, Norgaard BL, Byrne RA et al (2015) Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: the prospective longitudinal trial of FFR (CT): outcome and resource impacts study. Eur Heart J 36(47):3359–3367
Koo BK, Erglis A, Doh JH, Daniels DV, Jegere S, Kim HS 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(19):1989–1997
Min JK, Leipsic J, Pencina MJ, Berman DS, Koo BK, van Mieghem C et al (2012) Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. JAMA 308(12):1237–1245
Norgaard BL, Leipsic J, Gaur S, Seneviratne S, Ko BS, Ito H 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(12):1145–1155
Coenen A, Kim YH, Kruk M, Tesche C, De Geer J, Kurata A et al (2018) Diagnostic accuracy of a machine-learning approach to coronary computed tomographic angiography-based fractional flow reserve: result from the MACHINE consortium. Circ Cardiovasc Imaging 11(6):e007217
Tesche C, De Cecco CN, Baumann S, Renker M, McLaurin TW, Duguay TM et al (2018) Coronary CT angiography-derived fractional flow reserve: machine learning algorithm versus computational fluid dynamics modeling. Radiology 288(1):64–72
Windecker S, Kolh P, Alfonso F, Collet JP, Cremer J, Falk V et al (2014) 2014 ESC/EACTS guidelines on myocardial revascularization: the task force on myocardial revascularization of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS)Developed with the special contribution of the European Association of Percutaneous Cardiovascular Interventions (EAPCI). Eur Heart J 35(37):2541–2619
Wolk MJ, Bailey SR, Doherty JU, Douglas PS, Hendel RC, Kramer CM et al (2014) ACCF/AHA/ASE/ASNC/HFSA/HRS/SCAI/SCCT/SCMR/STS 2013 multimodality appropriate use criteria for the detection and risk assessment of stable ischemic heart disease: a report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and Society of Thoracic Surgeons. J Am Coll Cardiol 63(4):380–406
Harle T, Meyer S, Vahldiek F, Elsasser A (2016) Differences between automatically detected and steady-state fractional flow reserve. Clin Res Cardiol 105(2):127–134
Harle T, Zeymer U, Hochadel M, Zahn R, Kerber S, Zrenner B et al (2017) Real-world use of fractional flow reserve in Germany: results of the prospective ALKK coronary angiography and PCI registry. Clin Res Cardiol 106(2):140–150
Kleiman NS (2011) Bringing it all together: integration of physiology with anatomy during cardiac catheterization. J Am Coll Cardiol 58(12):1219–1221
Gotberg M, Christiansen EH, Gudmundsdottir IJ, Sandhall L, Danielewicz M, Jakobsen L et al (2017) Instantaneous wave-free ratio versus fractional flow reserve to guide PCI. N Engl J Med 376(19):1813–1823
Davies JE, Sen S, Dehbi HM, Al-Lamee R, Petraco R, Nijjer SS et al (2017) Use of the instantaneous wave-free ratio or fractional flow reserve in PCI. N Engl J Med 376(19):1824–1834
Sen S, Escaned J, Malik IS, Mikhail GW, Foale RA, Mila R et al (2012) Development and validation of a new adenosine-independent index of stenosis severity from coronary wave-intensity analysis: results of the ADVISE (ADenosine Vasodilator Independent Stenosis Evaluation) study. J Am Coll Cardiol 59(15):1392–1402
Harle T, Bojara W, Meyer S, Elsasser A (2015) Comparison of instantaneous wave-free ratio (iFR) and fractional flow reserve (FFR)—first real world experience. Int J Cardiol 199:1–7
Neumann FJ, Sousa-Uva M, Ahlsson A, Alfonso F, Banning AP, Benedetto U et al (2018) 2018 ESC/EACTS guidelines on myocardial revascularization. Eur Heart J 40:87–165
Bittencourt MS, Hulten E, Polonsky TS, Hoffman U, Nasir K, Abbara S et al (2016) European Society of Cardiology-recommended coronary artery disease consortium pretest probability scores more accurately predict obstructive coronary disease and cardiovascular events than the diamond and forrester score: the partners registry. Circulation 134(3):201–211
Caselli C, De Graaf MA, Lorenzoni V, Rovai D, Marinelli M, Del Ry S et al (2015) HDL cholesterol, leptin and interleukin-6 predict high risk coronary anatomy assessed by CT angiography in patients with stable chest pain. Atherosclerosis 241(1):55–61
Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R (1990) Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 15(4):827–832
Leipsic J, Abbara S, Achenbach S, Cury R, Earls JP, Mancini GJ et al (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 8(5):342–358
Escaned J, Echavarria-Pinto M, Garcia-Garcia HM, van de Hoef TP, de Vries T, Kaul P et al (2015) Prospective assessment of the diagnostic accuracy of instantaneous wave-free ratio to assess coronary stenosis relevance: results of ADVISE II International, Multicenter Study (ADenosine Vasodilator Independent Stenosis Evaluation II). JACC Cardiovasc Interv 8(6):824–833
DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44(3):837–845
Renker M, Schoepf UJ, Wang R, Meinel FG, Rier JD, Bayer RR 2nd et al (2014) Comparison of diagnostic value of a novel noninvasive coronary computed tomography angiography method versus standard coronary angiography for assessing fractional flow reserve. Am J Cardiol 114(9):1303–1308
Gotberg M, Cook CM, Sen S, Nijjer S, Escaned J, Davies JE (2017) The evolving future of instantaneous wave-free ratio and fractional flow reserve. J Am Coll Cardiol 70(11):1379–1402
Fujimoto S, Kawasaki T, Kumamaru KK, Kawaguchi Y, Dohi T, Okonogi T et al (2018) Diagnostic performance of on-site computed CT-fractional flow reserve based on fluid structure interactions: comparison with invasive fractional flow reserve and instantaneous wave-free ratio. Eur Heart J Cardiovasc Imaging 20:343–352
Hlatky MA, De Bruyne B, Pontone G, Patel MR, Norgaard BL, Byrne RA et al (2015) Quality-of-life and economic outcomes of assessing fractional flow reserve with computed tomography angiography: PLATFORM. J Am Coll Cardiol 66(21):2315–2323
Acknowledgement
Supported by Siemens Healthineers for providing CT-FFRML software for research purposes, which is currently not commercially available. Furthermore, the authors would like to thank Philips Volcano Corporation (Koninklijke Philips N.V. Amsterdam, The Netherland) for their support.
Funding
UJS receives institutional research support and/or honoraria for consulting and speaking from Astellas, Bayer, Bracco, Elucid BioImaging, GE, Guerbet, HeartFlow, and Siemens. SB receives research support from Philips Volcano. All other authors declare that they have no financial disclosures. The presented CT-FFRML software is provided by Siemens and is currently not commercially available.
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Baumann, S., Hirt, M., Schoepf, U.J. et al. Correlation of machine learning computed tomography-based fractional flow reserve with instantaneous wave free ratio to detect hemodynamically significant coronary stenosis. Clin Res Cardiol 109, 735–745 (2020). https://doi.org/10.1007/s00392-019-01562-3
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DOI: https://doi.org/10.1007/s00392-019-01562-3