Literature DB >> 24280729

Quantitative computed tomographic coronary angiography: does it predict functionally significant coronary stenoses?

Alexia Rossi1, Stella-Lida Papadopoulou, Francesca Pugliese, Brunella Russo, Anoeshka S Dharampal, Admir Dedic, Pieter H Kitslaar, Alexander Broersen, W Bob Meijboom, Robert-Jan van Geuns, Andrew Wragg, Jurgen Ligthart, Carl Schultz, Steffen E Petersen, Koen Nieman, Gabriel P Krestin, Pim J de Feyter.   

Abstract

BACKGROUND: Coronary lesions with a diameter narrowing ≥50% on visual computed tomographic coronary angiography (CTCA) are generally considered for referral to invasive coronary angiography. However, similar to invasive coronary angiography, visual CTCA is often inaccurate in detecting functionally significant coronary lesions. We sought to compare the diagnostic performance of quantitative CTCA with visual CTCA for the detection of functionally significant coronary lesions using fractional flow reserve (FFR) as the reference standard. METHODS AND
RESULTS: CTCA and FFR measurements were obtained in 99 symptomatic patients. In total, 144 coronary lesions detected on CTCA were visually graded for stenosis severity. Quantitative CTCA measurements included lesion length, minimal area diameter, % area stenosis, minimal lumen diameter, % diameter stenosis, and plaque burden [(vessel area-lumen area)/vessel area×100]. Optimal cutoff values of CTCA-derived parameters were determined, and their diagnostic accuracy for the detection of flow-limiting coronary lesions (FFR≤0.80) was compared with visual CTCA. FFR was ≤0.80 in 54 of 144 (38%) coronary lesions. Optimal cutoff values to predict flow-limiting coronary lesion were 10 mm for lesion length, 1.8 mm2 for minimal area diameter, 73% for % area stenosis, 1.5 mm for minimal lumen diameter, 48% for % diameter stenosis, and 76% for plaque burden. No significant difference in sensitivity was found between visual CTCA and quantitative CTCA parameters (P>0.05). The specificity of visual CTCA (42%; 95% confidence interval [CI], 31%-54%) was lower than that of minimal area diameter (68%; 95% CI, 57%-77%; P=0.001), % area stenosis (76%; 95% CI, 65%-84%; P<0.001), minimal lumen diameter (67%; 95% CI, 55%-76%; P=0.001), % diameter stenosis (72%; 95% CI, 62%-80%; P<0.001), and plaque burden (63%; 95% CI, 52%-73%; P=0.004). The specificity of lesion length was comparable with that of visual CTCA.
CONCLUSIONS: Quantitative CTCA improves the prediction of functionally significant coronary lesions compared with visual CTCA assessment but remains insufficient. Functional assessment is still required in lesions of moderate stenosis to accurately detect impaired FFR.

Entities:  

Keywords:  CT coronary angiography; coronary stenosis; fractional flow reserve

Mesh:

Year:  2013        PMID: 24280729     DOI: 10.1161/CIRCIMAGING.112.000277

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


  26 in total

1.  Diagnostic performance of transluminal attenuation gradient and fractional flow reserve by coronary computed tomographic angiography (FFR(CT)) compared to invasive FFR: a sub-group analysis from the DISCOVER-FLOW and DeFACTO studies.

Authors:  Rine Nakanishi; Suguru Matsumoto; Anas Alani; Dong Li; Pieter H Kitslaar; Alexander Broersen; Bon-Kwon Koo; James K Min; Matthew J Budoff
Journal:  Int J Cardiovasc Imaging       Date:  2015-04-24       Impact factor: 2.357

2.  Additional diagnostic value of new CT imaging techniques for the functional assessment of coronary artery disease: a meta-analysis.

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Journal:  Eur Radiol       Date:  2019-01-07       Impact factor: 5.315

Review 3.  Static and dynamic assessment of myocardial perfusion by computed tomography.

Authors:  Ibrahim Danad; Jackie Szymonifka; Joshua Schulman-Marcus; James K Min
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2016-03-24       Impact factor: 6.875

Review 4.  Cardiac CT Imaging of Plaque Vulnerability: Hype or Hope?

Authors:  Martin J Willemink; Tim Leiner; Pál Maurovich-Horvat
Journal:  Curr Cardiol Rep       Date:  2016-04       Impact factor: 2.931

Review 5.  Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods.

Authors:  Haipeng Liu; Aleksandra Wingert; Jian'an Wang; Jucheng Zhang; Xinhong Wang; Jianzhong Sun; Fei Chen; Syed Ghufran Khalid; Jun Jiang; Dingchang Zheng
Journal:  Front Cardiovasc Med       Date:  2021-02-10

6.  Automated Quantitative Plaque Burden from Coronary CT Angiography Noninvasively Predicts Hemodynamic Significance by using Fractional Flow Reserve in Intermediate Coronary Lesions.

Authors:  Mariana Diaz-Zamudio; Damini Dey; Annika Schuhbaeck; Ryo Nakazato; Heidi Gransar; Piotr J Slomka; Jagat Narula; Daniel S Berman; Stephan Achenbach; James K Min; Joon-Hyung Doh; Bon-Kwon Koo
Journal:  Radiology       Date:  2015-04-17       Impact factor: 11.105

7.  Diagnostic performance of quantitative coronary computed tomography angiography and quantitative coronary angiography to predict hemodynamic significance of intermediate-grade stenoses.

Authors:  Olivier Ghekiere; Willem Dewilde; Michel Bellekens; Denis Hoa; Thierry Couvreur; Julien Djekic; Tim Coolen; Isabelle Mancini; Piet K Vanhoenacker; Paul Dendale; Alain Nchimi
Journal:  Int J Cardiovasc Imaging       Date:  2015-09-01       Impact factor: 2.357

Review 8.  CT-based myocardial ischemia evaluation: quantitative angiography, transluminal attenuation gradient, myocardial perfusion, and CT-derived fractional flow reserve.

Authors:  Hyun Jung Koo; Dong Hyun Yang; Young-Hak Kim; Joon-Won Kang; Soo-Jin Kang; Jihoon Kweon; Hyun Jung Kim; Tae-Hwan Lim
Journal:  Int J Cardiovasc Imaging       Date:  2015-12-14       Impact factor: 2.357

Review 9.  Cardiac Computed Tomography - More Than Coronary Arteries? A Clinical Update.

Authors:  Jana Taron; Borek Foldyna; Parastou Eslami; Udo Hoffmann; Konstantin Nikolaou; Fabian Bamberg
Journal:  Rofo       Date:  2019-06-27

10.  Quantitative plaque features from coronary computed tomography angiography to identify regional ischemia by myocardial perfusion imaging.

Authors:  Mariana Diaz-Zamudio; Tobias A Fuchs; Piotr Slomka; Yuka Otaki; Reza Arsanjani; Heidi Gransar; Guido Germano; Daniel S Berman; Philipp A Kaufmann; Damini Dey
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2017-05-01       Impact factor: 6.875

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