Literature DB >> 24839136

Accuracy and reproducibility of automated, standardized coronary transluminal attenuation gradient measurements.

Yiannis S Chatzizisis1, Elizabeth George, Tianrun Cai, Urvi P Fulwadhva, Kanako K Kumamaru, Kurt Schultz, Yasuko Fujisawa, Carlos Rassi, Michael Steigner, Richard T Mather, Ron Blankstein, Frank J Rybicki, Dimitrios Mitsouras.   

Abstract

Coronary computed tomography angiography (CCTA) contrast opacification gradients, or transluminal attenuation gradients (TAG) offer incremental value to predict functionally significant lesions. This study introduces and evaluates an automated gradients software package that can potentially supplant current, labor-intensive manual TAG calculation methods. All 60 major coronary arteries in 20 patients who underwent a clinically indicated single heart beat 320 × 0.5 mm detector row CCTA were retrospectively evaluated by two readers using a previously validated manual measurement approach and two additional readers who used the new automated gradient software. Accuracy of the automated method against the manual measurements, considered the reference standard, was assessed via linear regression and Bland-Altman analyses. Inter- and intra-observer reproducibility and factors that can affect accuracy or reproducibility of both manual and automated TAG measurements, including CAD severity and iterative reconstruction, were also assessed. Analysis time was reduced by 68% when compared to manual TAG measurement. There was excellent correlation between automated TAG and the reference standard manual TAG. Bland-Altman analyses indicated low mean differences (1 HU/cm) and narrower inter- and intra-observer limits of agreement for automated compared to manual measurements (25 and 36% reduction with automated software, respectively). Among patient and technical factors assessed, none affected agreement of manual and automated TAG measurement. Automated 320 × 0.5 mm detector row gradient software reduces computation time by 68% with high accuracy and reproducibility.

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Year:  2014        PMID: 24839136      PMCID: PMC4104747          DOI: 10.1007/s10554-014-0446-4

Source DB:  PubMed          Journal:  Int J Cardiovasc Imaging        ISSN: 1569-5794            Impact factor:   2.357


  19 in total

1.  Noninvasive diagnosis of ischemia-causing coronary stenosis using CT angiography: diagnostic value of transluminal attenuation gradient and fractional flow reserve computed from coronary CT angiography compared to invasively measured fractional flow reserve.

Authors:  Yeonyee E Yoon; Jin-Ho Choi; Ji-Hyun Kim; Kyung-Woo Park; Joon-Hyung Doh; Yong-Jin Kim; Bon-Kwon Koo; James K Min; Andrejs Erglis; Hyeon-Cheol Gwon; Yeon Hyeon Choe; Dong-Ju Choi; Hyo-Soo Kim; Byung-Hee Oh; Young-Bae Park
Journal:  JACC Cardiovasc Imaging       Date:  2012-11

2.  Diagnostic performance of intracoronary gradient-based methods by coronary computed tomography angiography for the evaluation of physiologically significant coronary artery stenoses: a validation study with fractional flow reserve.

Authors:  Jin-Ho Choi; Bon-Kwon Koo; Yeonyee E Yoon; James K Min; Young-Bin Song; Joo-Yong Hahn; Seung-Hyuk Choi; Hyeon-Cheol Gwon; Yeon Hyeon Choe
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2012-07-15       Impact factor: 6.875

3.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

4.  Automatic quantification and characterization of coronary atherosclerosis with computed tomography coronary angiography: cross-correlation with intravascular ultrasound virtual histology.

Authors:  Michiel A de Graaf; Alexander Broersen; Pieter H Kitslaar; Cornelis J Roos; Jouke Dijkstra; Boudewijn P F Lelieveldt; J Wouter Jukema; Martin J Schalij; Victoria Delgado; Jeroen J Bax; Johan H C Reiber; Arthur J Scholte
Journal:  Int J Cardiovasc Imaging       Date:  2013-02-16       Impact factor: 2.357

5.  Transluminal attenuation gradient in coronary computed tomography angiography is a novel noninvasive approach to the identification of functionally significant coronary artery stenosis: a comparison with fractional flow reserve.

Authors:  Dennis T L Wong; Brian S Ko; James D Cameron; Nitesh Nerlekar; Michael C H Leung; Yuvaraj Malaiapan; Marcus Crossett; Darryl P Leong; Stephen G Worthley; John Troupis; Ian T Meredith; Sujith K Seneviratne
Journal:  J Am Coll Cardiol       Date:  2013-02-13       Impact factor: 24.094

6.  Computed tomography angiography and perfusion to assess coronary artery stenosis causing perfusion defects by single photon emission computed tomography: the CORE320 study.

Authors:  Carlos E Rochitte; Richard T George; Marcus Y Chen; Armin Arbab-Zadeh; Marc Dewey; Julie M Miller; Hiroyuki Niinuma; Kunihiro Yoshioka; Kakuya Kitagawa; Shiro Nakamori; Roger Laham; Andrea L Vavere; Rodrigo J Cerci; Vishal C Mehra; Cesar Nomura; Klaus F Kofoed; Masahiro Jinzaki; Sachio Kuribayashi; Albert de Roos; Michael Laule; Swee Yaw Tan; John Hoe; Narinder Paul; Frank J Rybicki; Jeffery A Brinker; Andrew E Arai; Christopher Cox; Melvin E Clouse; Marcelo F Di Carli; Joao A C Lima
Journal:  Eur Heart J       Date:  2013-11-19       Impact factor: 29.983

7.  Narrowing the phase window width in prospectively ECG-gated single heart beat 320-detector row coronary CT angiography.

Authors:  Michael L Steigner; Hansel J Otero; Tianxi Cai; Dimitrios Mitsouras; Leelakrishna Nallamshetty; Amanda G Whitmore; Hale Ersoy; Noah A Levit; Marcelo F Di Carli; Frank J Rybicki
Journal:  Int J Cardiovasc Imaging       Date:  2008-07-29       Impact factor: 2.357

8.  Diagnostic accuracy of fractional flow reserve from anatomic CT angiography.

Authors:  James K Min; Jonathon Leipsic; Michael J Pencina; Daniel S Berman; Bon-Kwon Koo; Carlos van Mieghem; Andrejs Erglis; Fay Y Lin; Allison M Dunning; Patricia Apruzzese; Matthew J Budoff; Jason H Cole; Farouc A Jaffer; Martin B Leon; Jennifer Malpeso; G B John Mancini; Seung-Jung Park; Robert S Schwartz; Leslee J Shaw; Laura Mauri
Journal:  JAMA       Date:  2012-09-26       Impact factor: 56.272

Review 9.  Coronary pressure-derived fractional flow reserve in the assessment of coronary artery stenoses.

Authors:  Nikolaos Kakouros; Frank J Rybicki; Dimitrios Mitsouras; Julie M Miller
Journal:  Eur Radiol       Date:  2012-11-24       Impact factor: 5.315

10.  Simulated 50 % radiation dose reduction in coronary CT angiography using adaptive iterative dose reduction in three-dimensions (AIDR3D).

Authors:  Marcus Y Chen; Michael L Steigner; Steve W Leung; Kanako K Kumamaru; Kurt Schultz; Richard T Mather; Andrew E Arai; Frank J Rybicki
Journal:  Int J Cardiovasc Imaging       Date:  2013-02-13       Impact factor: 2.357

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  7 in total

Review 1.  Cardiovascular imaging 2014 in the International Journal of Cardiovascular Imaging.

Authors: 
Journal:  Int J Cardiovasc Imaging       Date:  2015-03       Impact factor: 2.357

2.  Coronary CT Angiography: Variability of CT Scanners and Readers in Measurement of Plaque Volume.

Authors:  Rolf Symons; Justin Z Morris; Colin O Wu; Amir Pourmorteza; Mark A Ahlman; João A C Lima; Marcus Y Chen; Marissa Mallek; Veit Sandfort; David A Bluemke
Journal:  Radiology       Date:  2016-09-16       Impact factor: 11.105

3.  Clinical significance of transluminal attenuation gradient in 320-row area detector coronary CT angiography.

Authors:  Etsuro Kato; Shinichiro Fujimoto; Kazuhisa Takamura; Yuko Kawaguchi; Chihiro Aoshima; Makoto Hiki; Kanako K Kumamaru; Hiroyuki Daida
Journal:  Heart Vessels       Date:  2017-11-13       Impact factor: 2.037

4.  Contrast opacification difference of mural artery and the transluminal attenuation gradient on coronary computed tomography angiography for detection of systolic compression of myocardial bridge.

Authors:  Yuanliang Xie; Xiang Wang; Wei Xie; Faxiang Chen; Shubo Gao; Yikai Xu
Journal:  Surg Radiol Anat       Date:  2018-04-17       Impact factor: 1.246

5.  The transluminal attenuation gradient in coronary CT angiography for the detection of hemodynamically significant disease: can all arteries be treated equally?

Authors:  Shinichiro Fujimoto; Andreas A Giannopoulos; Kanako K Kumamaru; Rie Matsumori; Anji Tang; Etsuro Kato; Yuko Kawaguchi; Kazuhisa Takamura; Katsumi Miyauchi; Hiroyuki Daida; Frank J Rybicki; Dimitris Mitsouras
Journal:  Br J Radiol       Date:  2018-04-12       Impact factor: 3.039

Review 6.  Noninvasive physiologic assessment of coronary stenoses using cardiac CT.

Authors:  Lei Xu; Zhonghua Sun; Zhanming Fan
Journal:  Biomed Res Int       Date:  2015-01-20       Impact factor: 3.411

7.  Fractional Flow Reserve Estimated at Coronary CT Angiography in Intermediate Lesions: Comparison of Diagnostic Accuracy of Different Methods to Determine Coronary Flow Distribution.

Authors:  Satoru Kishi; Andreas A Giannopoulos; Anji Tang; Nahoko Kato; Yiannis S Chatzizisis; Carole Dennie; Yu Horiuchi; Kengo Tanabe; João A C Lima; Frank J Rybicki; Dimitris Mitsouras
Journal:  Radiology       Date:  2017-11-20       Impact factor: 29.146

  7 in total

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