Literature DB >> 23417447

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

Michiel A de Graaf1, 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.   

Abstract

Plaque constitution on computed tomography coronary angiography (CTA) is associated with prognosis. At present only visual assessment of plaque constitution is possible. An accurate automatic, quantitative approach for CTA plaque constitution assessment would improve reproducibility and allows higher accuracy. The present study assessed the feasibility of a fully automatic and quantitative analysis of atherosclerosis on CTA. Clinically derived CTA and intravascular ultrasound virtual histology (IVUS VH) datasets were used to investigate the correlation between quantitatively automatically derived CTA parameters and IVUS VH. A total of 57 patients underwent CTA prior to IVUS VH. First, quantitative CTA quantitative computed tomography (QCT) was performed. Per lesion stenosis parameters and plaque volumes were assessed. Using predefined HU thresholds, CTA plaque volume was differentiated in 4 different plaque types necrotic core (NC), dense calcium (DC), fibrotic (FI) and fibro-fatty tissue (FF). At the identical level of the coronary, the same parameters were derived from IVUS VH. Bland-Altman analyses were performed to assess the agreement between QCT and IVUS VH. Assessment of plaque volume using QCT in 108 lesions showed excellent correlation with IVUS VH (r = 0.928, p < 0.001) (Fig. 1). The correlation of both FF and FI volume on IVUS VH and QCT was good (r = 0.714, p < 0.001 and r = 0.695, p < 0.001 respectively) with corresponding bias and 95 % limits of agreement of 24 mm(3) (-42; 90) and 7.7 mm(3) (-54; 70). Furthermore, NC and DC were well-correlated in both modalities (r = 0.523, p < 0.001) and (r = 0.736, p < 0.001). Automatic, quantitative CTA tissue characterization is feasible using a dedicated software tool. Fig. 1 Schematic illustration of the characterization of coronary plaque on CTA: cross-correlation with IVUS VH. First, the 3-dimensional centerline was generated from the CTA data set using an automatic tree extraction algorithm (Panel I). Using a unique registration a complete pullback series of IVUS images was mapped on the CTA volume using true anatomical markers (Panel II). Fully automatic lumen and vessel wall contour detection was performed for both imaging modalities (Panel III). Finally, fusion-based quantification of atherosclerotic lesions was based on the lumen and vessel wall contours as well as the corresponding reference lines (estimate of normal tapering of the coronary artery), as shown in panel IV. At the level of the minimal lumen area (MLA) (yellow lines), stenosis parameters, could be calculated for both imaging techniques. Additionally, plaque volumes and plaque types were derived for the whole coronary artery lesion, ranging from the proximal to distal lesion marker (blue markers). Fibrotic tissue was labeled in dark green, Fibro-fatty tissue in light green, dense calcium in white and necrotic core was labeled in red.

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Year:  2013        PMID: 23417447     DOI: 10.1007/s10554-013-0194-x

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


  27 in total

1.  Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography.

Authors:  Guanyu Yang; Pieter Kitslaar; Michel Frenay; Alexander Broersen; Mark J Boogers; Jeroen J Bax; Johan H C Reiber; Jouke Dijkstra
Journal:  Int J Cardiovasc Imaging       Date:  2011-06-03       Impact factor: 2.357

2.  Coronary plaque classification with intravascular ultrasound radiofrequency data analysis.

Authors:  Anuja Nair; Barry D Kuban; E Murat Tuzcu; Paul Schoenhagen; Steven E Nissen; D Geoffrey Vince
Journal:  Circulation       Date:  2002-10-22       Impact factor: 29.690

3.  Characterisation of the "vulnerable" coronary plaque by multi-detector computed tomography: a correlative study with intravascular ultrasound-derived radiofrequency analysis of plaque composition.

Authors:  Giovanna Sarno; Piet Vanhoenacker; Isabel Decramer; Joanne D Schuijf; Johanna Schuijf; Gabjia Pundziute; Pundziute Gabjia; Paulina Margolis; Satya Gupta; Jeroen J Bax; Jeroen Bax; William Wijns
Journal:  EuroIntervention       Date:  2008-11       Impact factor: 6.534

4.  Coronary arterial atherosclerotic plaque imaging by contrast-enhanced computed tomography: fantasy or reality?

Authors:  Kamran Akram; Sarah Rinehart; Szilard Voros
Journal:  J Nucl Cardiol       Date:  2008-09-21       Impact factor: 5.952

5.  Quantification of coronary plaque by 64-slice computed tomography: a comparison with quantitative intracoronary ultrasound.

Authors:  Masato Otsuka; Nico Bruining; Niels C Van Pelt; Nico R Mollet; Jurgen M R Ligthart; Eleni Vourvouri; Ronald Hamers; Peter De Jaegere; William Wijns; Ron T Van Domburg; Gregg W Stone; Susan Veldhof; Stefan Verheye; Dariusz Dudek; Patrick W Serruys; Gabriel P Krestin; Pim J De Feyter
Journal:  Invest Radiol       Date:  2008-05       Impact factor: 6.016

6.  The prognostic value of multidetector coronary CT angiography for the prediction of major adverse cardiovascular events: a multicenter observational cohort study.

Authors:  James K Min; J Feignoux; J Treutenaere; T Laperche; J Sablayrolles
Journal:  Int J Cardiovasc Imaging       Date:  2010-03-27       Impact factor: 2.357

7.  Incremental prognostic value of cardiac computed tomography in coronary artery disease using CONFIRM: COroNary computed tomography angiography evaluation for clinical outcomes: an InteRnational Multicenter registry.

Authors:  Benjamin J W Chow; Gary Small; Yeung Yam; Li Chen; Stephan Achenbach; Mouaz Al-Mallah; Daniel S Berman; Matthew J Budoff; Filippo Cademartiri; Tracy Q Callister; Hyuk-Jae Chang; Victor Cheng; Kavitha M Chinnaiyan; Augustin Delago; Allison Dunning; Martin Hadamitzky; Jörg Hausleiter; Philipp Kaufmann; Fay Lin; Erica Maffei; Gilbert L Raff; Leslee J Shaw; Todd C Villines; James K Min
Journal:  Circ Cardiovasc Imaging       Date:  2011-07-05       Impact factor: 7.792

8.  The composition and extent of coronary artery plaque detected by multislice computed tomographic angiography provides incremental prognostic value in patients with suspected coronary artery disease.

Authors:  Tomasz Miszalski-Jamka; Piotr Klimeczek; Robert Banyś; Maciej Krupiński; Krzysztof Nycz; Krzysztof Bury; Michał Lada; Robert Pelberg; Dean Kereiakes; Wojciech Mazur
Journal:  Int J Cardiovasc Imaging       Date:  2011-03-03       Impact factor: 2.357

9.  Impact of luminal density on plaque classification by CT coronary angiography.

Authors:  Maiken Glud Dalager; Morten Bøttcher; Gratien Andersen; Jesper Thygesen; Erik Morre Pedersen; Lone Dejbjerg; Ole Gøtzsche; Hans Erik Bøtker
Journal:  Int J Cardiovasc Imaging       Date:  2010-09-05       Impact factor: 2.357

10.  Prognostic value of multidetector coronary computed tomographic angiography for prediction of all-cause mortality.

Authors:  James K Min; Leslee J Shaw; Richard B Devereux; Peter M Okin; Jonathan W Weinsaft; Donald J Russo; Nicholas J Lippolis; Daniel S Berman; Tracy Q Callister
Journal:  J Am Coll Cardiol       Date:  2007-09-04       Impact factor: 24.094

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  48 in total

1.  Multicenter AIDS Cohort Study Quantitative Coronary Plaque Progression Study: rationale and design.

Authors:  Rine Nakanishi; Wendy S Post; Kazuhiro Osawa; Eranthi Jayawardena; Michael Kim; Nasim Sheidaee; Negin Nezarat; Sina Rahmani; Nicholas Kim; Nicolai Hathiramani; Shriraj Susarla; Frank Palella; Mallory Witt; Michael J Blaha; Todd T Brown; Lawrence Kingsley; Sabina A Haberlen; Christopher Dailing; Matthew J Budoff
Journal:  Coron Artery Dis       Date:  2018-01       Impact factor: 1.439

2.  Relationship of left ventricular mass to coronary atherosclerosis and myocardial ischaemia: the CORE320 multicenter study.

Authors:  Satoru Kishi; Tiago A Magalhaes; Richard T George; Marc Dewey; Roger J Laham; Hiroyuki Niinuma; Lisa Aronson Friedman; Christopher Cox; Yutaka Tanami; Joanne D Schuijf; Andrea L Vavere; Kakuya Kitagawa; Marcus Y Chen; Cesar H Nomura; Jeffrey A Brinker; Frank J Rybicki; Marcelo F Di Carli; Armin Arbab-Zadeh; Joao A C Lima
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2014-11-02       Impact factor: 6.875

3.  Optimal boundary detection method and window settings for coronary atherosclerotic plaque volume analysis in coronary computed tomography angiography: comparison with intravascular ultrasound.

Authors:  Ran Heo; Hyung-Bok Park; Byoung Kwon Lee; Sanghoon Shin; Reza Arsanjani; James K Min; Hyuk-Jae Chang
Journal:  Eur Radiol       Date:  2015-12-02       Impact factor: 5.315

4.  Reply: High-risk plaque detected on coronary CT angiography predicts acute coronary syndrome.

Authors:  Maros Ferencik; Stefan B Puchner; Udo Hoffmann
Journal:  J Am Coll Cardiol       Date:  2015-03-03       Impact factor: 24.094

5.  Coronary Atherosclerotic Precursors of Acute Coronary Syndromes.

Authors:  Hyuk-Jae Chang; Fay Y Lin; Sang-Eun Lee; Daniele Andreini; Jeroen Bax; Filippo Cademartiri; Kavitha Chinnaiyan; Benjamin J W Chow; Edoardo Conte; Ricardo C Cury; Gudrun Feuchtner; Martin Hadamitzky; Yong-Jin Kim; Jonathon Leipsic; Erica Maffei; Hugo Marques; Fabian Plank; Gianluca Pontone; Gilbert L Raff; Alexander R van Rosendael; Todd C Villines; Harald G Weirich; Subhi J Al'Aref; Lohendran Baskaran; Iksung Cho; Ibrahim Danad; Donghee Han; Ran Heo; Ji Hyun Lee; Asim Rivzi; Wijnand J Stuijfzand; Heidi Gransar; Yao Lu; Ji Min Sung; Hyung-Bok Park; Daniel S Berman; Matthew J Budoff; Habib Samady; Leslee J Shaw; Peter H Stone; Renu Virmani; Jagat Narula; James K Min
Journal:  J Am Coll Cardiol       Date:  2018-06-05       Impact factor: 24.094

Review 6.  Noninvasive Imaging of Atherosclerotic Plaque Progression: Status of Coronary Computed Tomography Angiography.

Authors:  Veit Sandfort; Joao A C Lima; David A Bluemke
Journal:  Circ Cardiovasc Imaging       Date:  2015-07       Impact factor: 7.792

Review 7.  Emerging risk biomarkers in cardiovascular diseases and disorders.

Authors:  Ravi Kant Upadhyay
Journal:  J Lipids       Date:  2015-04-08

8.  Structured learning algorithm for detection of nonobstructive and obstructive coronary plaque lesions from computed tomography angiography.

Authors:  Dongwoo Kang; Damini Dey; Piotr J Slomka; Reza Arsanjani; Ryo Nakazato; Hyunsuk Ko; Daniel S Berman; Debiao Li; C-C Jay Kuo
Journal:  J Med Imaging (Bellingham)       Date:  2015-03-06

9.  Quantitative coronary plaque analysis predicts high-risk plaque morphology on coronary computed tomography angiography: results from the ROMICAT II trial.

Authors:  Ting Liu; Pál Maurovich-Horvat; Thomas Mayrhofer; Stefan B Puchner; Michael T Lu; Khristine Ghemigian; Pieter H Kitslaar; Alexander Broersen; Amit Pursnani; Udo Hoffmann; Maros Ferencik
Journal:  Int J Cardiovasc Imaging       Date:  2017-08-12       Impact factor: 2.357

Review 10.  Plaque assessment by coronary CT.

Authors:  Bálint Szilveszter; Csilla Celeng; Pál Maurovich-Horvat
Journal:  Int J Cardiovasc Imaging       Date:  2015-08-18       Impact factor: 2.357

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