Literature DB >> 32076671

Improved Evaluation of Lipid-Rich Plaque at Coronary CT Angiography: Head-to-Head Comparison with Intravascular US.

Hidenari Matsumoto1, Satoshi Watanabe1, Eisho Kyo1, Takafumi Tsuji1, Yosuke Ando1, Evann Eisenberg1, Yuka Otaki1, Osamu Manabe1, Sebastien Cadet1, Piotr J Slomka1, Balaji K Tamarappoo1, Daniel S Berman1, Damini Dey1.   

Abstract

PURPOSE: To improve the evaluation of low-attenuation plaque (LAP) by using semiautomated software and to assess whether the use of a proposed automated function (LAP editor) that excludes voxels adjacent to the outer vessel wall improves the relationship between LAP and the presence and size of the lipid-rich component (LRC) verified at intravascular US. At coronary CT angiography, quantification of LAP can improve risk stratification. Plaque, defined as the area between the vessel and the lumen wall, is prone to partial volume effects from the surrounding pericoronary adipose tissue.
MATERIALS AND METHODS: The percentage of LAP (%LAP), defined as the percentage of noncalcified plaque with an attenuation value lower than 30 HU (LAP/total plaque volume) at greater than or equal to 0 mm (%LAP0), greater than or equal to 0.1 mm (%LAP0.1), greater than or equal to 0.3 mm (%LAP0.3), greater than or equal to 0.5 mm (%LAP0.5), and greater than or equal to 0.7 mm (%LAP0.7) inward from the vessel wall boundaries, were quantified in 155 plaques in 90 patients who underwent coronary CT angiography before intravascular US. At intravascular US, the LRC was identified by using echo attenuation, and its size was measured by using the attenuation score (summed score/analysis length) based on the attenuation arc (1 = < 90°, 2 = 90° to < 180°, 3 = 180° to < 270°, 4 = 270°-360°) for every 1 mm.
RESULTS: Use of LAP editing improved the ability for discriminating LRC (areas under receiver operating characteristic curve: 0.667 with %LAP0, 0.713 with %LAP0.1 [P < .001 for comparison with %LAP0]), 0.778 with %LAP0.3 [P < .001], 0.825 with %LAP0.5 [P < .001], 0.802 with %LAP0.7 [P = .002]). %LAP0.5 had the strongest correlation (r = 0.612, P < .001) with LRC size, whereas %LAP0 resulted in the weakest correlation (r = 0.307; P < .001).
CONCLUSION: Evaluation of LAP at coronary CT angiography can be significantly improved by excluding voxels that are adjacent to the vessel wall boundaries by 0.5 mm.Supplemental material is available for this article.© RSNA, 2019. 2019 by the Radiological Society of North America, Inc.

Entities:  

Year:  2019        PMID： 32076671      PMCID： PMC6939749          DOI： 10.1148/ryct.2019190069

Source DB:  PubMed          Journal:  Radiol Cardiothorac Imaging        ISSN： 2638-6135


  37 in total

1.  Consensus standards for acquisition, measurement, and reporting of intravascular optical coherence tomography studies: a report from the International Working Group for Intravascular Optical Coherence Tomography Standardization and Validation.

Authors:  Guillermo J Tearney; Evelyn Regar; Takashi Akasaka; Tom Adriaenssens; Peter Barlis; Hiram G Bezerra; Brett Bouma; Nico Bruining; Jin-man Cho; Saqib Chowdhary; Marco A Costa; Ranil de Silva; Jouke Dijkstra; Carlo Di Mario; Darius Dudek; Darius Dudeck; Erling Falk; Erlin Falk; Marc D Feldman; Peter Fitzgerald; Hector M Garcia-Garcia; Hector Garcia; Nieves Gonzalo; Juan F Granada; Giulio Guagliumi; Niels R Holm; Yasuhiro Honda; Fumiaki Ikeno; Masanori Kawasaki; Janusz Kochman; Lukasz Koltowski; Takashi Kubo; Teruyoshi Kume; Hiroyuki Kyono; Cheung Chi Simon Lam; Guy Lamouche; David P Lee; Martin B Leon; Akiko Maehara; Olivia Manfrini; Gary S Mintz; Kyiouchi Mizuno; Marie-angéle Morel; Seemantini Nadkarni; Hiroyuki Okura; Hiromasa Otake; Arkadiusz Pietrasik; Francesco Prati; Lorenz Räber; Maria D Radu; Johannes Rieber; Maria Riga; Andrew Rollins; Mireille Rosenberg; Vasile Sirbu; Patrick W J C Serruys; Kenei Shimada; Toshiro Shinke; Junya Shite; Eliot Siegel; Shinjo Sonoda; Shinjo Sonada; Melissa Suter; Shigeho Takarada; Atsushi Tanaka; Mitsuyasu Terashima; Troels Thim; Thim Troels; Shiro Uemura; Giovanni J Ughi; Heleen M M van Beusekom; Antonius F W van der Steen; Gerrit-Anne van Es; Gerrit-Ann van Es; Gijs van Soest; Renu Virmani; Sergio Waxman; Neil J Weissman; Giora Weisz
Journal:  J Am Coll Cardiol       Date:  2012-03-20       Impact factor: 24.094

2.  Improvement in LDL is associated with decrease in non-calcified plaque volume on coronary CTA as measured by automated quantitative software.

Authors:  Balaji Tamarappoo; Yuka Otaki; Mhairi Doris; Yoav Arnson; Heidi Gransar; Sean Hayes; John Friedman; Louise Thomson; Frances Wang; Alan Rozanski; Piotr Slomka; Damini Dey; Daniel Berman
Journal:  J Cardiovasc Comput Tomogr       Date:  2018-05-07

3.  Automated 3-dimensional quantification of noncalcified and calcified coronary plaque from coronary CT angiography.

Authors:  Damini Dey; Victor Y Cheng; Piotr J Slomka; Ryo Nakazato; Amit Ramesh; Swaminatha Gurudevan; Guido Germano; Daniel S Berman
Journal:  J Cardiovasc Comput Tomogr       Date:  2009-10-01

4.  Reproducibility of coronary artery plaque volume and composition quantification by 64-detector row coronary computed tomographic angiography: an intraobserver, interobserver, and interscan variability study.

Authors:  Victor Y Cheng; Ryo Nakazato; Damini Dey; Swaminatha Gurudevan; Joshua Tabak; Matthew J Budoff; Ronald P Karlsberg; James Min; Daniel S Berman
Journal:  J Cardiovasc Comput Tomogr       Date:  2009-07-30

5.  Computed Tomographic Coronary Angiography-Derived Plaque Characteristics Predict Major Adverse Cardiovascular Events: A Systematic Review and Meta-Analysis.

Authors:  Nitesh Nerlekar; Francis J Ha; Caitlin Cheshire; Hashrul Rashid; James D Cameron; Dennis T Wong; Sujith Seneviratne; Adam J Brown
Journal:  Circ Cardiovasc Imaging       Date:  2018-01       Impact factor: 7.792

6.  Effect of tube potential and luminal contrast attenuation on atherosclerotic plaque attenuation by coronary CT angiography: In vivo comparison with intravascular ultrasound.

Authors:  Hidenari Matsumoto; Satoshi Watanabe; Eisho Kyo; Takafumi Tsuji; Yosuke Ando; Yuka Otaki; Sebastien Cadet; Piotr J Slomka; Daniel S Berman; Damini Dey; Balaji K Tamarappoo
Journal:  J Cardiovasc Comput Tomogr       Date:  2019-02-12

7.  Clinical Feasibility of 3D Automated Coronary Atherosclerotic Plaque Quantification Algorithm on Coronary Computed Tomography Angiography: Comparison with Intravascular Ultrasound.

Authors:  Hyung-Bok Park; Byoung Kwon Lee; Sanghoon Shin; Ran Heo; Reza Arsanjani; Pieter H Kitslaar; Alexander Broersen; Jouke Dijkstra; Sung Gyun Ahn; James K Min; Hyuk-Jae Chang; Myeong-Ki Hong; Yangsoo Jang; Namsik Chung
Journal:  Eur Radiol       Date:  2015-05-21       Impact factor: 5.315

8.  Automated three-dimensional quantification of noncalcified coronary plaque from coronary CT angiography: comparison with intravascular US.

Authors:  Damini Dey; Tiziano Schepis; Mohamed Marwan; Piotr J Slomka; Daniel S Berman; Stephan Achenbach
Journal:  Radiology       Date:  2010-09-09       Impact factor: 11.105

9.  Quantitative global plaque characteristics from coronary computed tomography angiography for the prediction of future cardiac mortality during long-term follow-up.

Authors:  Michaela M Hell; Manish Motwani; Yuka Otaki; Sebastien Cadet; Heidi Gransar; Romalisa Miranda-Peats; Jacob Valk; Piotr J Slomka; Victor Y Cheng; Alan Rozanski; Balaji K Tamarappoo; Sean Hayes; Stephan Achenbach; Daniel S Berman; Damini Dey
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2017-12-01       Impact factor: 6.875

10.  Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions.

Authors:  Sara Gaur; Kristian Altern Øvrehus; Damini Dey; Jonathon Leipsic; Hans Erik Bøtker; Jesper Møller Jensen; Jagat Narula; Amir Ahmadi; Stephan Achenbach; Brian S Ko; Evald Høj Christiansen; Anne Kjer Kaltoft; Daniel S Berman; Hiram Bezerra; Jens Flensted Lassen; Bjarne Linde Nørgaard
Journal:  Eur Heart J       Date:  2016-01-12       Impact factor: 29.983
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  3 in total

1.  Reproducibility of quantitative plaque measurement in advanced coronary artery disease.

Authors:  Mohammed N Meah; Trisha Singh; Michelle C Williams; Marc R Dweck; David E Newby; Piotr Slomka; Philip D Adamson; Alastair J Moss; Damini Dey
Journal:  J Cardiovasc Comput Tomogr       Date:  2020-12-28

2.  Noncalcified plaque burden quantified from coronary computed tomography angiography improves prediction of side branch occlusion after main vessel stenting in bifurcation lesions: results from the CT-PRECISION registry.

Authors:  Kajetan Grodecki; Sebastien Cadet; Adam D Staruch; Anna M Michalowska; Cezary Kepka; Rafal Wolny; Jerzy Pregowski; Mariusz Kruk; Mariusz Debski; Artur Debski; Ilona Michalowska; Piotr J Slomka; Adam Witkowski; Damini Dey; Maksymilian P Opolski
Journal:  Clin Res Cardiol       Date:  2020-05-08       Impact factor: 5.460

3.  Coronary flow impairment in asymptomatic patients with early stage type-2 diabetes: Detection by FFRCT.

Authors:  Monija Mrgan; Bjarne Linde Nørgaard; Damini Dey; Jørgen Gram; Michael Hecht Olsen; Jeppe Gram; Niels Peter Rønnow Sand
Journal:  Diab Vasc Dis Res       Date:  2020 Sep-Oct       Impact factor: 3.291
  3 in total

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