Literature DB >> 30309764

Coronary CTA enhanced with CTA based FFR analysis provides higher diagnostic value than invasive coronary angiography in patients with intermediate coronary stenosis.

Łukasz Wardziak1, Mariusz Kruk2, Weronika Pleban3, Marcin Demkow4, Witold Rużyłło5, Zofia Dzielińska6, Cezary Kępka7.   

Abstract

BACKGROUND: CTA based FFR, a software based application, enhances diagnostic value of coronary computed tomography angiography (CTA) examination. However it remains unknown whether it improves accuracy over the gold standard of invasive coronary angiography (ICA) in predicting functionally significant coronary stenosis. The aim of our study was to compare diagnostic accuracies of coronary CTA, CTA based FFR, and ICA, with invasive FFR as the reference standard in patients with intermediate stenosis on CTA.
METHODS: 96 intermediate stenoses (50-90%) from 90 subjects, with intermediate pre-test probability of CAD, who underwent coronary CTA were analyzed. Each patient had subsequent ICA with FFR. CTA based FFR (cFFR v2.1, Siemens) analysis was performed on-site. The stenoses with invasive FFR≤0.8 were considered hemodynamically significant.
RESULTS: 41/96 stenoses were hemodynamically significant (FFR≤0.8). While the area under ROC curves (AUC) for identification of significant stenosis evaluated on QCA (0.653), visual ICA (0.652), qCTA (0.690) and visual CTA (0.660) did not significantly differ, the AUC for CTA based FFR (0.835) was significantly higher (p = 0.004, p = 0.004, p = 0.010, p = 0.007, respectively). The accuracies of CTA based FFR, qCTA and QCA were 76%, 63% and 58% respectively.
CONCLUSION: Our results suggest that diagnostic potential of routine coronary CTA, augmented with CTA based FFR analysis, is superior to ICA in patients with intermediate stenosis.
Copyright © 2018. Published by Elsevier Inc.

Entities:  

Keywords:  Computed tomography angiography; Coronary artery disease; Fractional flow reserve; Invasive coronary angiography; Machine learning

Mesh:

Year:  2018        PMID: 30309764     DOI: 10.1016/j.jcct.2018.10.004

Source DB:  PubMed          Journal:  J Cardiovasc Comput Tomogr        ISSN: 1876-861X


  8 in total

1.  Computed tomography angiography-derived fractional flow reserve (CT-FFR) for the detection of myocardial ischemia with invasive fractional flow reserve as reference: systematic review and meta-analysis.

Authors:  Baiyan Zhuang; Shuli Wang; Shihua Zhao; Minjie Lu
Journal:  Eur Radiol       Date:  2019-11-06       Impact factor: 5.315

2.  Synergistic prognostic value of coronary distensibility index and fractional flow reserve based cCTA for major adverse cardiac events in patients with Coronary artery disease.

Authors:  Xiao-Long Zhu; Zhi-Ying Pang; Wei Jiang; Ting-Yu Dong
Journal:  BMC Cardiovasc Disord       Date:  2022-05-14       Impact factor: 2.174

Review 3.  Computed tomographic evaluation of myocardial ischemia.

Authors:  Yuki Tanabe; Akira Kurata; Takuya Matsuda; Kazuki Yoshida; Dhiraj Baruah; Teruhito Kido; Teruhito Mochizuki; Prabhakar Rajiah
Journal:  Jpn J Radiol       Date:  2020-02-05       Impact factor: 2.374

Review 4.  Machine Learning for Assessment of Coronary Artery Disease in Cardiac CT: A Survey.

Authors:  Nils Hampe; Jelmer M Wolterink; Sanne G M van Velzen; Tim Leiner; Ivana Išgum
Journal:  Front Cardiovasc Med       Date:  2019-11-26

Review 5.  Current and Future Applications of Artificial Intelligence in Coronary Artery Disease.

Authors:  Nitesh Gautam; Prachi Saluja; Abdallah Malkawi; Mark G Rabbat; Mouaz H Al-Mallah; Gianluca Pontone; Yiye Zhang; Benjamin C Lee; Subhi J Al'Aref
Journal:  Healthcare (Basel)       Date:  2022-01-26

6.  Coronary CT Value in Quantitative Assessment of Intermediate Stenosis.

Authors:  Laura Zajančkauskienė; Laura Radionovaitė; Antanas Jankauskas; Audra Banišauskaitė; Gintarė Šakalytė
Journal:  Medicina (Kaunas)       Date:  2022-07-20       Impact factor: 2.948

Review 7.  Revascularization strategies for patients with established chronic coronary syndrome.

Authors:  Casper F Coerkamp; Marieke Hoogewerf; Bart P van Putte; Yolande Appelman; Pieter A Doevendans
Journal:  Eur J Clin Invest       Date:  2022-04-29       Impact factor: 5.722

Review 8.  Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications.

Authors:  Chris Boyd; Greg Brown; Timothy Kleinig; Joseph Dawson; Mark D McDonnell; Mark Jenkinson; Eva Bezak
Journal:  Diagnostics (Basel)       Date:  2021-03-19
  8 in total

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