Literature DB >> 25060020

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.

Shengxian Tu1, Emanuele Barbato2, Zsolt Köszegi3, Junqing Yang4, Zhonghua Sun5, Niels R Holm6, Balázs Tar3, Yingguang Li7, Dan Rusinaru2, William Wijns2, Johan H C Reiber7.   

Abstract

OBJECTIVES: This study sought to present a novel computer model for fast computation of myocardial fractional flow reserve (FFR) and to evaluate it in patients with intermediate coronary stenoses.
BACKGROUND: FFR is an indispensable tool to identify individual coronary stenoses causing ischemia. Calculation of FFR from x-ray angiographic data may increase the utility of FFR assessment.
METHODS: Consecutive patients with intermediate coronary stenoses undergoing pressure wire-based FFR measurements were analyzed by a core laboratory. Three-dimensional quantitative coronary angiography (QCA) was performed and the mean volumetric flow rate at hyperemia was calculated using TIMI (Thrombolysis In Myocardial Infarction) frame count combined with 3-dimensional QCA. Computational fluid dynamics was applied subsequently with a novel strategy for the computation of FFR. Diagnostic performance of the computed FFR (FFRQCA) was assessed using wire-based FFR as reference standard.
RESULTS: Computation of FFRQCA was performed on 77 vessels in 68 patients. Average diameter stenosis was 46.6 ± 7.3%. FFRQCA correlated well with FFR (r = 0.81, p < 0.001), with a mean difference of 0.00 ± 0.06 (p = 0.541). Applying the FFR cutoff value of ≤0.8 to FFRQCA resulted in 18 true positives, 50 true negatives, 4 false positives, and 5 false negatives. The area under the receiver-operating characteristic curve was 0.93 for FFRQCA, 0.73 for minimum lumen area, and 0.65 for percent diameter stenosis.
CONCLUSIONS: Computation of FFRQCA is a novel method that allows the assessment of the functional significance of intermediate stenosis. It may emerge as a safe, efficient, and cost-reducing tool for evaluation of coronary stenosis severity during diagnostic angiography.
Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  cardiovascular physiology; computational fluid dynamics; fractional flow reserve; quantitative coronary angiography

Mesh:

Year:  2014        PMID: 25060020     DOI: 10.1016/j.jcin.2014.03.004

Source DB:  PubMed          Journal:  JACC Cardiovasc Interv        ISSN: 1936-8798            Impact factor:   11.195


  88 in total

Review 1.  Missense mutations resulting in type 1 lissencephaly.

Authors:  O Reiner; F M Coquelle
Journal:  Cell Mol Life Sci       Date:  2005-02       Impact factor: 9.261

2.  A simplified formula to calculate fractional flow reserve in sequential lesions circumventing the measurement of coronary wedge pressure: The APIS-S pilot study.

Authors:  Juan Luis Gutiérrez-Chico; Carlos Cortés; Miłosz Jaguszewski; Michele Schincariol; Ignacio J Amat-Santos; Juan A Franco-Peláez; Grzegorz Żuk; Dariusz Ciećwierz; Wojciech Wojakowski; Felipe Navarro; Shengxian Tu; Borja Ibáñez
Journal:  Cardiol J       Date:  2019-07-01       Impact factor: 2.737

3.  Combining anatomy and physiology: New angiography-based and computed tomography coronary angiography-derived fractional flow reserve indices.

Authors:  Mariusz Tomaniak; Patrick W Serruys
Journal:  Cardiol J       Date:  2020       Impact factor: 2.737

Review 4.  A systematic review of imaging anatomy in predicting functional significance of coronary stenoses determined by fractional flow reserve.

Authors:  Miao Chu; Neng Dai; Junqing Yang; Jelmer Westra; Shengxian Tu
Journal:  Int J Cardiovasc Imaging       Date:  2017-03-06       Impact factor: 2.357

Review 5.  Physiome approach for the analysis of vascular flow reserve in the heart and brain.

Authors:  Kyung Eun Lee; Ah-Jin Ryu; Eun-Seok Shin; Eun Bo Shim
Journal:  Pflugers Arch       Date:  2017-03-28       Impact factor: 3.657

6.  Whence we came, whither we go?

Authors:  Shengxian Tu; Tim P van de Hoef; Young-Hak Kim; Javier Escaned; William Wijns
Journal:  Int J Cardiovasc Imaging       Date:  2017-07       Impact factor: 2.357

7.  Superficial wall stress: the long awaited comprehensive biomechanical parameter to objectify and quantify our intuition.

Authors:  Juan Luis Gutiérrez-Chico
Journal:  Int J Cardiovasc Imaging       Date:  2018-06-06       Impact factor: 2.357

8.  Reproducibility of quantitative flow ratio: An inter-core laboratory variability study.

Authors:  Yunxiao Chang; Liwei Chen; Jelmer Westra; Zhongwei Sun; Changdong Guan; Yimin Zhang; Daixin Ding; Bo Xu; Shengxian Tu
Journal:  Cardiol J       Date:  2018-09-20       Impact factor: 2.737

9.  Assessment of superficial coronary vessel wall deformation and stress: validation of in silico models and human coronary arteries in vivo.

Authors:  Xinlei Wu; Clemens von Birgelen; Zehang Li; Su Zhang; Jiayue Huang; Fuyou Liang; Yingguang Li; William Wijns; Shengxian Tu
Journal:  Int J Cardiovasc Imaging       Date:  2018-02-03       Impact factor: 2.357

10.  Simultaneous evaluation of plaque stability and ischemic potential of coronary lesions in a fluid-structure interaction analysis.

Authors:  Xinlei Wu; Clemens von Birgelen; Su Zhang; Daixin Ding; Jiayue Huang; Shengxian Tu
Journal:  Int J Cardiovasc Imaging       Date:  2019-05-03       Impact factor: 2.357

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