Literature DB >> 28687539

Visual and Quantitative Assessment of Coronary Stenoses at Angiography Versus Fractional Flow Reserve: The Impact of Risk Factors.

Julien Adjedj1, Panagiotis Xaplanteris1, Gabor Toth1, Angela Ferrara1, Mariano Pellicano1, Giovanni Ciccarelli1, Vincent Floré1, Emanuele Barbato1, Bernard De Bruyne2.   

Abstract

BACKGROUND: The correlation between angiographic assessment of coronary stenoses and fractional flow reserve (FFR) is weak. Whether and how risk factors impact the diagnostic accuracy of angiography is unknown. We sought to evaluate the diagnostic accuracy of angiography by visual estimate and by quantitative coronary angiography when compared with FFR and evaluate the influence of risk factors (RF) on this accuracy. METHODS AND
RESULTS: In 1382 coronary stenoses (1104 patients), percent diameter stenosis by visual estimation (DSVE) and by quantitative coronary angiography (DSQCA) was compared with FFR. Patients were divided into 4 subgroups, according to the presence of RFs, and the relationship between DSVE, DSQCA, and FFR was analyzed. Overall, DSVE was significantly higher than DSQCA (P<0.0001); nonetheless, when examined by strata of DS, DSVE was significantly smaller than DSQCA in mild stenoses, although the reverse held true for severe stenoses. Compared with FFR, a large scatter was observed for both DSVE and DSQCA. When using a dichotomous FFR value of 0.80, C statistic was significantly higher for DSVE than for DSQCA (0.712 versus 0.640, respectively; P<0.001). C statistics for DSVE decreased progressively as RFs accumulated (0.776 for ≤1 RF, 0.750 for 2 RFs, 0.713 for 3 RFs and 0.627 for ≥4 RFs; P=0.0053). In addition, in diabetics, the relationship between FFR and angiographic indices was particularly weak (C statistics: 0.524 for DSVE and 0.511 for DSQCA).
CONCLUSIONS: Overall, DSVE has a better diagnostic accuracy than DSQCA to predict the functional significance of coronary stenosis. The predictive accuracy of angiography is moderate in patients with ≤1 RFs, but weakens as RFs accumulate, especially in diabetics.
© 2017 American Heart Association, Inc.

Entities:  

Keywords:  coronary angiography; coronary stenosis; diabetes mellitus; hyperemia; risk factors

Mesh:

Year:  2017        PMID: 28687539     DOI: 10.1161/CIRCIMAGING.117.006243

Source DB:  PubMed          Journal:  Circ Cardiovasc Imaging        ISSN: 1941-9651            Impact factor:   7.792


  13 in total

1.  Influence of diabetes mellitus on the diagnostic performance of machine learning-based coronary CT angiography-derived fractional flow reserve: a multicenter study.

Authors:  Yi Xue; Min Wen Zheng; Yang Hou; Fan Zhou; Jian Hua Li; Yi Ning Wang; Chun Yu Liu; Chang Sheng Zhou; Jia Yin Zhang; Meng Meng Yu; Bo Zhang; Dai Min Zhang; Yan Yi; Lei Xu; Xiu Hua Hu; Guang Ming Lu; Chun Xiang Tang; Long Jiang Zhang
Journal:  Eur Radiol       Date:  2022-01-12       Impact factor: 5.315

2.  Coronary artery to aortic luminal attenuation ratio in coronary CT angiography for the diagnosis of haemodynamically significant coronary artery stenosis.

Authors:  Tomofumi Misaka; Yuki Sugitani; Nobuyuki Asato; Yuko Matsukubo; Masanobu Uemura; Ryuichiro Ashikaga; Takayuki Ishida
Journal:  Br J Radiol       Date:  2019-11-21       Impact factor: 3.039

3.  Accuracy of 3-dimensional and 2-dimensional quantitative coronary angiography for predicting physiological significance of coronary stenosis: a FAVOR II substudy.

Authors:  Daixin Ding; Junqing Yang; Jelmer Westra; Yundai Chen; Yunxiao Chang; Martin Sejr-Hansen; Su Zhang; Evald H Christiansen; Niels R Holm; Bo Xu; Shengxian Tu
Journal:  Cardiovasc Diagn Ther       Date:  2019-10

4.  Application of the DILEMMA score to improve lesion selection for invasive physiological assessment.

Authors:  Michael Michail; Hakim-Moulay Dehbi; Nitesh Nerlekar; Justin E Davies; Andrew S P Sharp; Suneel Talwar; James D Cameron; Adam J Brown; Dennis T Wong; Anthony Mathur; Alun D Hughes; Om Narayan
Journal:  Catheter Cardiovasc Interv       Date:  2019-01-02       Impact factor: 2.692

Review 5.  Comparison of coronary angiography and intracoronary imaging with fractional flow reserve for coronary artery disease evaluation: An anatomical-functional mismatch.

Authors:  Julien Adjedj; Nikolay Stoyanov; Olivier Muller
Journal:  Anatol J Cardiol       Date:  2018-09       Impact factor: 1.596

6.  Coronary computed tomography angiography equals invasive angiography for the prediction of coronary revascularization.

Authors:  Mariusz Dębski; Mariusz Kruk; Sebastian Bujak; Zofia Dzielińska; Marcin Demkow; Cezary Kępka
Journal:  Postepy Kardiol Interwencyjnej       Date:  2019-05-05       Impact factor: 1.426

7.  Mean Platelet Volume is Associated with Pancreatic β-Cell Dysfunction in Nondiabetic Patients with Coronary Artery Disease.

Authors:  Xiliang Zhao; Xiaoli Li; Quan Li; Yicong Ye; Yong Zeng
Journal:  Int J Gen Med       Date:  2021-10-05

8.  Coronary computed tomography angiography using model-based iterative reconstruction algorithms in the detection of significant coronary stenosis: how the plaque type influences the diagnostic performance.

Authors:  Antonio Vizzuso; Riccardo Righi; Aldo Carnevale; Michela Zerbini; Giorgio Benea; Melchiore Giganti
Journal:  Pol J Radiol       Date:  2019-12-09

9.  QFR Predicts the Incidence of Long-Term Adverse Events in Patients with Suspected CAD: Feasibility and Reproducibility of the Method.

Authors:  Andrea Buono; Annika Mühlenhaus; Tabitha Schäfer; Ann-Kristin Trieb; Julian Schmeißer; Franziska Koppe; Thomas Münzel; Remzi Anadol; Tommaso Gori
Journal:  J Clin Med       Date:  2020-01-14       Impact factor: 4.241

10.  Importance of Visual Estimation of Coronary Artery Stenoses and Use of Functional Evaluation for Appropriate Guidance of Coronary Revascularization-Multiple Operator Evaluation.

Authors:  Lucian Calmac; Nicoleta-Monica Popa-Fotea; Vlad Bataila; Vlad Ploscaru; Adrian Turea; Irina Andra Tache; Diana Stoian; Lucian Itu; Elisabeta Badila; Alexandru Scafa-Udriste; Maria Dorobantu
Journal:  Diagnostics (Basel)       Date:  2021-11-30
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