Diagnostic accuracy of two-dimensional coronary angiographic-derived fractional flow reserve-Preliminary results.
coronary angiography
fractional flow reserve
quantitative coronary analysis
quantitative flow ratio
Journal
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
ISSN: 1522-726X
Titre abrégé: Catheter Cardiovasc Interv
Pays: United States
ID NLM: 100884139
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
revised:
01
04
2020
received:
26
01
2020
accepted:
03
07
2020
pubmed:
28
7
2020
medline:
25
9
2021
entrez:
28
7
2020
Statut:
ppublish
Résumé
Noninvasive fractional flow reserve (NiFFR) is an emerging method for evaluating the functional significance of a coronary lesion during diagnostic coronary angiography (CAG). The method relies on the computational flow dynamics and the three-dimensional (3D) reconstruction of the vessel extracted from CAG. In the present study, we sought to evaluate the diagnostic performance and applicability of 2D-based NiFFR. In this prospective observational study, we evaluated 2D-based NiFFR in 279 candidates for invasive CAG and invasive fractional flow reserve (FFR). NiFFR was calculated via two methods: variable NiFFR, in which the contrast transport time was extracted from the angiographic view, and fixed NiFFR, in which a prespecified frame count was applied. The final analysis was performed on 245 patients (250 lesions). Variable NiFFR had an area under the receiver operating characteristic curve of 81.5%, an accuracy of 80.0%, a sensitivity of 82.2%, a specificity of 82.2%, a negative predictive value of 91.4%, and a positive predictive value of 63.6%. The mean difference between FFR and NiFFR was -0.0244 ±.0616 (p ≤.0001). A pressure wire-free hybrid strategy was possible in 68.8% of our population with variable NiFFR. Our 2D-based NiFFR yielded results comparable to those derived from 3D-based software. Our findings should; however, be confirmed in larger trials.
Types de publication
Journal Article
Observational Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
E484-E494Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2020 Wiley Periodicals LLC.
Références
Green NE, Chen SY, Messenger JC, Groves BM, Carroll JD. Three-dimensional vascular angiography. Curr Probl Cardiol. 2004;29(3):104-142.
Pijls NH, Van Gelder B, Van der Voort P, et al. Fractional flow reserve. A useful index to evaluate the influence of an epicardial coronary stenosis on myocardial blood flow. Circulation. 1995;92(11):3183-3193.
Pijls NH, van Schaardenburgh P, Manoharan G, et al. Percutaneous coronary intervention of functionally nonsignificant stenosis: 5-year follow-up of the DEFER study. J Am Coll Cardiol. 2007;49(21):2105-2111.
Tonino PA, De Bruyne B, Pijls NH, et al. Fractional flow reserve versus angiography for guiding percutaneous coronary intervention. N Engl J Med. 2009;360(3):213-224.
Toth GG, Toth B, Johnson NP, et al. Revascularization decisions in patients with stable angina and intermediate lesions: results of the international survey on interventional strategy. Circ Cardiovasc Interv. 2014;7(6):751-759.
Knuuti J, Wijns W, Saraste A, et al. 2019 ESC guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2019;41(3):407-477.
Dattilo PB, Prasad A, Honeycutt E, Wang TY, Messenger JC. Contemporary patterns of fractional flow reserve and intravascular ultrasound use among patients undergoing percutaneous coronary intervention in the United States: insights from the National Cardiovascular Data Registry. J Am Coll Cardiol. 2012;60(22):2337-2339.
Dehmer GJ, Weaver D, Roe MT, et al. A contemporary view of diagnostic cardiac catheterization and percutaneous coronary intervention in the United States: a report from the CathPCI registry of the National Cardiovascular Data Registry, 2010 through June 2011. J Am Coll Cardiol. 2012;60(20):2017-2031.
Morris PD, Ryan D, Morton AC, et al. Virtual fractional flow reserve from coronary angiography: modeling the significance of coronary lesions: results from the VIRTU-1 (VIRTUal fractional flow reserve from coronary angiography) study. JACC Cardiovasc Interv. 2013;6(2):149-157.
Fearon WF, Achenbach S, Engstrom T, et al. Accuracy of fractional flow reserve derived from coronary angiography. Circulation. 2019;139(4):477-484.
Masdjedi K, van Zandvoort LJC, Balbi MM, et al. Validation of 3-dimensional quantitative coronary angiography based software to calculate fractional flow reserve: fast assessment of STenosis severity (FAST)-study. EuroIntervention. 2019. https://doi.org/10.4244/EIJ-D-19-00466. [Epub ahead of print].
Papafaklis MI, Muramatsu T, Ishibashi Y, et al. Fast virtual functional assessment of intermediate coronary lesions using routine angiographic data and blood flow simulation in humans: comparison with pressure wire-fractional flow reserve. EuroIntervention. 2014;10(5):574-583.
Tu S, Holm NR, Koning G, Maeng M, Reiber JH. The impact of acquisition angle differences on three-dimensional quantitative coronary angiography. Catheter Cardiovasc Interv. 2011;78(2):214-222.
Tu S, Huang Z, Koning G, Cui K, Reiber JH. A novel three-dimensional quantitative coronary angiography system: in-vivo comparison with intravascular ultrasound for assessing arterial segment length. Catheter Cardiovasc Interv. 2010;76(2):291-298.
Tu S, Westra J, Yang J, et al. Diagnostic accuracy of fast computational approaches to derive fractional flow reserve from diagnostic coronary angiography. JACC Cardiovasc Interv. 2016;9(19):2024-2035.
Westra J, Andersen BK, Campo G, et al. Diagnostic performance of in-procedure angiography-derived quantitative flow reserve compared to pressure-derived fractional flow reserve: the FAVOR II Europe-Japan study. J Am Heart Assoc. 2018;7(14):e009603.
Westra J, Tu S, Winther S, et al. Evaluation of coronary artery stenosis by quantitative flow ratio during invasive coronary angiography: the WIFI II study (wire-free functional imaging II). Circ Cardiovasc Imaging. 2018;11(3):e007107.
Xu B, Tu S, Qiao S, et al. Diagnostic accuracy of angiography-based quantitative flow ratio measurements for online assessment of coronary stenosis. J Am Coll Cardiol. 2017;70(25):3077-3087.
Collet C, Onuma Y, Sonck J, et al. Diagnostic performance of angiography-derived fractional flow reserve: a systematic review and Bayesian meta-analysis. Eur Heart J. 2018;39(35):3314-3321.
Abo-Aly M, Lolay G, Adams C, Ahmed AE, Abdel-Latif A, Ziada KM. Comparison of intracoronary versus intravenous adenosine-induced maximal hyperemia for fractional flow reserve measurement: a systematic review and meta-analysis. Catheter Cardiovasc Interv. 2019;94(5):714-721.
Schlundt C, Bietau C, Klinghammer L, et al. Comparison of intracoronary versus intravenous administration of adenosine for measurement of coronary fractional flow reserve. Circ Cardiovasc Interv. 2015;8(5):e001781.
Toth GG, Johnson NP, Jeremias A, et al. Standardization of fractional flow reserve measurements. J Am Coll Cardiol. 2016;68(7):742-753.
Wilson RF, Wyche K, Christensen BV, Zimmer S, Laxson DD. Effects of adenosine on human coronary arterial circulation. Circulation. 1990;82(5):1595-1606.
Womersley JR. Method for the calculation of velocity, rate of flow and viscous drag in arteries when the pressure gradient is known. J Physiol. 1955;127(3):553-563.
Vasava P, Jalali P, Dabagh M, Kolari PJ. Finite element modelling of pulsatile blood flow in idealized model of human aortic arch: study of hypotension and hypertension. Comput Math Methods Med. 2012;2012:861837.
Tanedo JS, Kelly RF, Marquez M, et al. Assessing coronary blood flow dynamics with the TIMI frame count method: comparison with simultaneous intracoronary Doppler and ultrasound. Catheter Cardiovasc Interv. 2001;53(4):459-463.
Gibson CM, Cannon CP, Daley WL, et al. TIMI frame count: a quantitative method of assessing coronary artery flow. Circulation. 1996;93(5):879-888.
Iguchi T, Hasegawa T, Nishimura S, et al. Impact of lesion length on functional significance in intermediate coronary lesions. Clin Cardiol. 2013;36(3):172-177.
Park SJ, Kang SJ, Ahn JM, et al. Visual-functional mismatch between coronary angiography and fractional flow reserve. JACC Cardiovasc Interv. 2012;5(10):1029-1036.
Ciccarelli G, Barbato E, Toth GG, et al. Angiography versus hemodynamics to predict the natural history of coronary stenoses: fractional flow reserve versus angiography in multivessel evaluation 2 substudy. Circulation. 2018;137(14):1475-1485.
Johnson NP, Toth GG, Lai D, et al. Prognostic value of fractional flow reserve: linking physiologic severity to clinical outcomes. J Am Coll Cardiol. 2014;64(16):1641-1654.
Henglin M, Stein G, Hushcha PV, Snoek J, Wiltschko AB, Cheng S. Machine learning approaches in cardiovascular imaging. Circ Cardiovasc Imaging. 2017;10(10):e005614.
Cho H, Lee JG, Kang SJ, et al. Angiography-based machine learning for predicting fractional flow reserve in intermediate coronary artery lesions. J Am Heart Assoc. 2019;8(4):e011685.
Gashi K, Bosboom EMH, van de Vosse FN. The influence of model order reduction on the computed fractional flow reserve using parameterized coronary geometries. J Biomech. 2019;82:313-323.
Trobs M, Achenbach S, Rother J, et al. Comparison of fractional flow reserve based on computational fluid dynamics modeling using coronary angiographic vessel morphology versus invasively measured fractional flow reserve. Am J Cardiol. 2016;117(1):29-35.