Literature DB >> 16458154

Accuracy of 64-slice computed tomography to classify and quantify plaque volumes in the proximal coronary system: a comparative study using intravascular ultrasound.

Alexander W Leber1, Alexander Becker, Andreas Knez, Franz von Ziegler, Marc Sirol, Konstantin Nikolaou, Bernd Ohnesorge, Zahi A Fayad, Christoph R Becker, Maximilian Reiser, Gerhard Steinbeck, Peter Boekstegers.   

Abstract

OBJECTIVES: We evaluated the accuracy of a new 64-slice computed tomography (CT) scanner, compared with intravascular ultrasound, to visualize atherosclerosis in the proximal coronary system.
BACKGROUND: Noninvasive determination of plaque composition and plaque burden may be important to improve risk stratification.
METHODS: In 20 patients, a 64-slice CT scan (Sensation 64, Siemens Medical Solutions, Forchheim, Germany) and an intravascular ultrasound investigation of vessels without stenosis >50% was performed. Diagnostic image quality with 64-slice CT was obtained in 36 vessels in 19 patients.
RESULTS: In these vessels, which were divided in 3-mm sections, 64-slice CT enabled a correct detection of plaque in 54 of 65 (83%) sections containing noncalcified plaques, 50 of 53 (94%) sections containing mixed plaques, and 41 of 43 (95%) sections containing calcified plaques. In 192 of 204 (94%) sections, atherosclerotic lesions were excluded correctly. In addition, 64-slice CT enabled the visualization of 7 of 10 (70%) sections revealing a lipid pool and could identify a spotty calcification pattern in 27 of 30 (90%) sections. The correlation coefficient to determine plaque volumes per vessel was r2 = 0.69 (p < 0.001) with an underestimation of mixed and noncalcified plaque volumes (p < 0.03) and a trend to overestimate calcified plaque volumes by 64-slice CT. The interobserver variability to determine plaque volumes was 37%. Interobserver agreement to identify atherosclerotic sections was good (Cohen's kappa coefficient = 0.75).
CONCLUSIONS: We conclude that 64-slice CT reveals encouraging results to noninvasively detect different types of coronary plaques located in the proximal coronary system. The ability to determine plaque burden currently is hampered by mainly an insufficient reproducibility.

Entities:  

Mesh:

Year:  2006        PMID: 16458154     DOI: 10.1016/j.jacc.2005.10.058

Source DB:  PubMed          Journal:  J Am Coll Cardiol        ISSN: 0735-1097            Impact factor:   24.094


  181 in total

1.  Assessment of atherosclerotic plaques in a rabbit model by delayed-phase contrast-enhanced CT angiography: comparison with histopathology.

Authors:  Jin Hur; Young Jin Kim; Hyo Sup Shim; Hye-Jeong Lee; Ji Eun Nam; Kyu Ok Choe; Byoung Wook Choi
Journal:  Int J Cardiovasc Imaging       Date:  2011-01-30       Impact factor: 2.357

2.  Variability and accuracy of coronary CT angiography including use of iterative reconstruction algorithms for plaque burden assessment as compared with intravascular ultrasound-an ex vivo study.

Authors:  Paul Stolzmann; Christopher L Schlett; Pal Maurovich-Horvat; Akiko Maehara; Shixin Ma; Hans Scheffel; Leif-Christopher Engel; Mihály Károlyi; Gary S Mintz; Udo Hoffmann
Journal:  Eur Radiol       Date:  2012-05-24       Impact factor: 5.315

3.  Influence of statin treatment on coronary atherosclerosis visualised using multidetector computed tomography.

Authors:  Hans Hoffmann; Katja Frieler; Peter Schlattmann; Bernd Hamm; Marc Dewey
Journal:  Eur Radiol       Date:  2010-07-18       Impact factor: 5.315

4.  Effect of reader experience on variability, evaluation time and accuracy of coronary plaque detection with computed tomography coronary angiography.

Authors:  Stefan C Saur; Hatem Alkadhi; Paul Stolzmann; Stephan Baumüller; Sebastian Leschka; Hans Scheffel; Lotus Desbiolles; Thomas J Fuchs; Gábor Székely; Philippe C Cattin
Journal:  Eur Radiol       Date:  2010-01-30       Impact factor: 5.315

5.  Reproducibility in the assessment of noncalcified coronary plaque with 256-slice multi-detector CT and automated plaque analysis software.

Authors:  Min Su Lee; Eun Ju Chun; Kil Joong Kim; Jeong A Kim; Mani Vembar; Sang Il Choi
Journal:  Int J Cardiovasc Imaging       Date:  2010-10-06       Impact factor: 2.357

6.  Rapid changes in plaque composition and morphology after intensive lipid lowering therapy: study with serial coronary CT angiography.

Authors:  Masaya Shimojima; Masa-Aki Kawashiri; Yutaka Nitta; Taiji Yoshida; Shouji Katsuda; Bunji Kaku; Tomio Taguchi; Akira Hasegawa; Tetsuo Konno; Kenshi Hayashi; Masakazu Yamagishi
Journal:  Am J Cardiovasc Dis       Date:  2012-05-15

7.  Sex-related differences in serum matrix metalloproteinase-9 screening non-calcified and mixed coronary atherosclerotic plaques in outpatients with chest pain.

Authors:  Chun Gu; Fang Wang; Zhihui Hou; Bin Lv; Yang Wang; Xiangfeng Cong; Xi Chen
Journal:  Heart Vessels       Date:  2017-07-19       Impact factor: 2.037

8.  Presence and extent of coronary artery disease by cardiac computed tomography and risk for acute coronary syndrome in cocaine users among patients with chest pain.

Authors:  Fabian Bamberg; Christopher L Schlett; Quynh A Truong; Ian S Rogers; Wolfgang Koenig; John T Nagurney; Sujith Seneviratne; Sam J Lehman; Ricardo C Cury; Suhny Abbara; Javed Butler; Hang Lee; Thomas J Brady; Udo Hoffmann
Journal:  Am J Cardiol       Date:  2008-12-26       Impact factor: 2.778

9.  Coronary plaque quantification by voxel analysis: dual-source MDCT angiography versus intravascular sonography.

Authors:  Harald Brodoefel; Christof Burgstahler; Adeel Sabir; Chun-Shan Yam; Faisal Khosa; Claus D Claussen; Melvin E Clouse
Journal:  AJR Am J Roentgenol       Date:  2009-03       Impact factor: 3.959

10.  Increased coronary atherosclerotic plaque vulnerability by coronary computed tomography angiography in HIV-infected men.

Authors:  Markella V Zanni; Suhny Abbara; Janet Lo; Bryan Wai; David Hark; Eleni Marmarelis; Steven K Grinspoon
Journal:  AIDS       Date:  2013-05-15       Impact factor: 4.177

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.