Literature DB >> 26596195

Comparison of Fractional Flow Reserve Based on Computational Fluid Dynamics Modeling Using Coronary Angiographic Vessel Morphology Versus Invasively Measured Fractional Flow Reserve.

Monique Tröbs1, Stephan Achenbach2, Jens Röther1, Thomas Redel3, Michael Scheuering3, David Winneberger3, Klaus Klingenbeck3, Lucian Itu4, Tiziano Passerini5, Ali Kamen5, Puneet Sharma5, Dorin Comaniciu5, Christian Schlundt1.   

Abstract

Invasive fractional flow reserve (FFRinvasive), although gold standard to identify hemodynamically relevant coronary stenoses, is time consuming and potentially associated with complications. We developed and evaluated a new approach to determine lesion-specific FFR on the basis of coronary anatomy as visualized by invasive coronary angiography (FFRangio): 100 coronary lesions (50% to 90% diameter stenosis) in 73 patients (48 men, 25 women; mean age 67 ± 9 years) were studied. On the basis of coronary angiograms acquired at rest from 2 views at angulations at least 30° apart, a PC-based computational fluid dynamics modeling software used personalized boundary conditions determined from 3-dimensional reconstructed angiography, heart rate, and blood pressure to derive FFRangio. The results were compared with FFRinvasive. Interobserver variability was determined in a subset of 25 narrowings. Twenty-nine of 100 coronary lesions were hemodynamically significant (FFRinvasive ≤ 0.80). FFRangio identified these with an accuracy of 90%, sensitivity of 79%, specificity of 94%, positive predictive value of 85%, and negative predictive value of 92%. The area under the receiver operating characteristic curve was 0.93. Correlation between FFRinvasive (mean: 0.84 ± 0.11) and FFRangio (mean: 0.85 ± 0.12) was r = 0.85. Interobserver variability of FFRangio was low, with a correlation of r = 0.88. In conclusion, estimation of coronary FFR with PC-based computational fluid dynamics modeling on the basis of lesion morphology as determined by invasive angiography is possible with high diagnostic accuracy compared to invasive measurements.
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 26596195     DOI: 10.1016/j.amjcard.2015.10.008

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  20 in total

1.  Performing and Interpreting Fractional Flow Reserve Measurements in Clinical Practice: An Expert Consensus Document.

Authors:  Stephan Achenbach; Tanja Rudolph; Johannes Rieber; Holger Eggebrecht; Gert Richardt; Thomas Schmitz; Nikos Werner; Florian Boenner; Helge Möllmann
Journal:  Interv Cardiol       Date:  2017-09

2.  Diagnostic accuracy of quantitative flow ratio (QFR) and vessel fractional flow reserve (vFFR) estimated retrospectively by conventional radiation saving X-ray angiography.

Authors:  Chongying Jin; Anantharaman Ramasamy; Hannah Safi; Yakup Kilic; Vincenzo Tufaro; Retesh Bajaj; Guosheng Fu; Anthony Mathur; Christos V Bourantas; Andreas Baumbach
Journal:  Int J Cardiovasc Imaging       Date:  2021-01-16       Impact factor: 2.357

3.  Diagnostic performance of AccuFFRangio in the functional assessment of coronary stenosis compared with pressure wire-derived fractional flow reserve.

Authors:  Jun Jiang; Lijiang Tang; Changqing Du; Xiaochang Leng; Jingsong He; Yumeng Hu; Liang Dong; Yong Sun; Changling Li; Jianping Xiang; Jian'an Wang
Journal:  Quant Imaging Med Surg       Date:  2022-02

4.  Case Report of First Angiography-Based On-Line FFR Assessment during Coronary Catheterization.

Authors:  Ran Kornowski; Hana Vaknin-Assa
Journal:  Case Rep Cardiol       Date:  2017-08-01

Review 5.  Coronary Physiology Derived from Invasive Angiography: Will it be a Game Changer?

Authors:  Lavinia Gabara; Jonathan Hinton; Julian Gunn; Paul D Morris; Nick Curzen
Journal:  Interv Cardiol       Date:  2020-06-04

6.  Blood residence time to assess significance of coronary artery stenosis.

Authors:  Javad Hashemi; Shesh Rai; Shahab Ghafghazi; R Eric Berson
Journal:  Sci Rep       Date:  2020-07-15       Impact factor: 4.379

7.  Comparison of 1D and 3D Models for the Estimation of Fractional Flow Reserve.

Authors:  P J Blanco; C A Bulant; L O Müller; G D Maso Talou; C Guedes Bezerra; P A Lemos; R A Feijóo
Journal:  Sci Rep       Date:  2018-11-22       Impact factor: 4.379

8.  The importance of side branches in modeling 3D hemodynamics from angiograms for patients with coronary artery disease.

Authors:  Madhurima Vardhan; John Gounley; S James Chen; Andrew M Kahn; Jane A Leopold; Amanda Randles
Journal:  Sci Rep       Date:  2019-06-20       Impact factor: 4.379

9.  Operator-dependent variability of angiography-derived fractional flow reserve and the implications for treatment.

Authors:  Katherine Lal; Rebecca Gosling; Mina Ghobrial; Gareth J Williams; Vignesh Rammohan; D Rod Hose; Patricia V Lawford; Andrew Narracott; John Fenner; Julian P Gunn; Paul D Morris
Journal:  Eur Heart J Digit Health       Date:  2021-02-05

10.  Angiography-Derived Fractional Flow Reserve: More or Less Physiology?

Authors:  Paul D Morris; Nick Curzen; Julian P Gunn
Journal:  J Am Heart Assoc       Date:  2020-03-11       Impact factor: 5.501

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