Literature DB >> 24570085

Feasibility of dynamic CT-based adenosine stress myocardial perfusion imaging to detect and differentiate ischemic and infarcted myocardium in an large experimental porcine animal model.

Fabian Bamberg1, Rabea Hinkel, Roy P Marcus, Elisabeth Baloch, Kristof Hildebrandt, Florian Schwarz, Holger Hetterich, Torleif A Sandner, Christopher L Schlett, Ullrich Ebersberger, Christian Kupatt, Udo Hoffmann, Maximilian F Reiser, Daniel Theisen, Konstantin Nikolaou.   

Abstract

The purpose of the study is feasibility of dynamic CT perfusion imaging to detect and differentiate ischemic and infarcted myocardium in a large porcine model. 12 Country pigs completed either implantation of a 75 % luminal coronary stenosis in the left anterior descending coronary artery simulating ischemia or balloon-occlusion inducing infarction. Dynamic CT-perfusion imaging (100 kV, 300 mAs), fluorescent microspheres, and histopathology were performed in all models. CT based myocardial blood flow (MBFCT), blood volume (MBVCT) and transit constant (Ktrans), as well as microsphere's based myocardial blood flow (MBFMic) were derived for each myocardial segment. According to histopathology or microsphere measurements, 20 myocardial segments were classified as infarcted and 23 were ischemic (12 and 14 %, respectively). Across all perfusion states, MBFCT strongly predicted MBFMic (β 0.88 ± 0.12, p < 0.0001). MBFCT, MBVCT, and Ktrans were significantly lower in ischemic/infarcted when compared to reference myocardium (all p < 0.01). Relative differences of all CT parameters between affected and non-affected myocardium were higher for infarcted when compared to ischemic segments under rest (48.4 vs. 22.6 % and 46.1 vs. 22.9 % for MBFCT, MBVCT, respectively). Under stress, MBFCT was significantly lower in infarcted than in ischemic myocardium (67.8 ± 26 vs. 88.2 ± 22 ml/100 ml/min, p = 0.002). In a large animal model, CT-derived parameters of myocardial perfusion may enable detection and differentiation of ischemic and infarcted myocardium.

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Year:  2014        PMID: 24570085     DOI: 10.1007/s10554-014-0390-3

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


  28 in total

1.  Automation of the use of fluorescent microspheres for the determination of blood flow.

Authors:  E Thein; S Raab; A G Harris; K Messmer
Journal:  Comput Methods Programs Biomed       Date:  2000-01       Impact factor: 5.428

Review 2.  Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association.

Authors:  Manuel D Cerqueira; Neil J Weissman; Vasken Dilsizian; Alice K Jacobs; Sanjiv Kaul; Warren K Laskey; Dudley J Pennell; John A Rumberger; Thomas Ryan; Mario S Verani
Journal:  Circulation       Date:  2002-01-29       Impact factor: 29.690

Review 3.  Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association.

Authors:  Manuel D Cerqueira; Neil J Weissman; Vasken Dilsizian; Alice K Jacobs; Sanjiv Kaul; Waren K Laskey; Dudley J Pennell; John A Rumberger; Thomas Ryan; Mario S Verani
Journal:  Int J Cardiovasc Imaging       Date:  2002-02       Impact factor: 2.357

4.  Quantitative whole heart stress perfusion CT imaging as noninvasive assessment of hemodynamics in coronary artery stenosis: preliminary animal experience.

Authors:  Andreas H Mahnken; Ernst Klotz; Hubertus Pietsch; Bernhard Schmidt; Thomas Allmendinger; Ulrike Haberland; Willi A Kalender; Thomas Flohr
Journal:  Invest Radiol       Date:  2010-06       Impact factor: 6.016

5.  Multidetector computed tomography myocardial perfusion imaging during adenosine stress.

Authors:  Richard T George; Caterina Silva; Marco A S Cordeiro; Anthony DiPaula; Douglas R Thompson; William F McCarthy; Takashi Ichihara; Joao A C Lima; Albert C Lardo
Journal:  J Am Coll Cardiol       Date:  2006-06-21       Impact factor: 24.094

6.  Stress and rest dynamic myocardial perfusion imaging by evaluation of complete time-attenuation curves with dual-source CT.

Authors:  Kheng-Thye Ho; Kia-Chong Chua; Ernst Klotz; Christoph Panknin
Journal:  JACC Cardiovasc Imaging       Date:  2010-08

7.  Detection of hemodynamically significant coronary artery stenosis: incremental diagnostic value of dynamic CT-based myocardial perfusion imaging.

Authors:  Fabian Bamberg; Alexander Becker; Florian Schwarz; Roy P Marcus; Martin Greif; Franz von Ziegler; Ron Blankstein; Udo Hoffmann; Wieland H Sommer; Verena S Hoffmann; Thorsten R C Johnson; Hans-Christoph R Becker; Bernd J Wintersperger; Maximilian F Reiser; Konstantin Nikolaou
Journal:  Radiology       Date:  2011-09       Impact factor: 11.105

8.  Quantification of myocardial blood flow by adenosine-stress CT perfusion imaging in pigs during various degrees of stenosis correlates well with coronary artery blood flow and fractional flow reserve.

Authors:  Alexia Rossi; André Uitterdijk; Marcel Dijkshoorn; Ernst Klotz; Anoeshka Dharampal; Marcel van Straten; Wim J van der Giessen; Nico Mollet; Robert-Jan van Geuns; Gabriel P Krestin; Dirk J Duncker; Pim J de Feyter; Daphne Merkus
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2012-07-26       Impact factor: 6.875

9.  Incremental value of adenosine-induced stress myocardial perfusion imaging with dual-source CT at cardiac CT angiography.

Authors:  Jose A Rocha-Filho; Ron Blankstein; Leonid D Shturman; Hiram G Bezerra; David R Okada; Ian S Rogers; Brian Ghoshhajra; Udo Hoffmann; Gudrun Feuchtner; Wilfred S Mamuya; Thomas J Brady; Ricardo C Cury
Journal:  Radiology       Date:  2010-02       Impact factor: 11.105

10.  Optimal medical therapy with or without percutaneous coronary intervention to reduce ischemic burden: results from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) trial nuclear substudy.

Authors:  Leslee J Shaw; Daniel S Berman; David J Maron; G B John Mancini; Sean W Hayes; Pamela M Hartigan; William S Weintraub; Robert A O'Rourke; Marcin Dada; John A Spertus; Bernard R Chaitman; John Friedman; Piotr Slomka; Gary V Heller; Guido Germano; Gilbert Gosselin; Peter Berger; William J Kostuk; Ronald G Schwartz; Merill Knudtson; Emir Veledar; Eric R Bates; Benjamin McCallister; Koon K Teo; William E Boden
Journal:  Circulation       Date:  2008-02-11       Impact factor: 29.690

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  11 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.  Structure or entropy in reporting cardiac CT findings.

Authors:  Marc Dewey
Journal:  Int J Cardiovasc Imaging       Date:  2016-07-28       Impact factor: 2.357

3.  Comparison of coronary flow reserve estimated by dynamic radionuclide SPECT and multi-detector x-ray CT.

Authors:  Cecilia Marini; Sara Seitun; Camilla Zawaideh; Matteo Bauckneht; Margherita Castiglione Morelli; Pietro Ameri; Giulia Ferrarazzo; Irilda Budaj; Manrico Balbi; Francesco Fiz; Sara Boccalini; Athena Galletto Pregliasco; Ambra Buschiazzo; Alice Saracco; Maria Claudia Bagnara; Paolo Bruzzi; Claudio Brunelli; Carlo Ferro; Gian Paolo Bezante; Gianmario Sambuceti
Journal:  J Nucl Cardiol       Date:  2016-05-05       Impact factor: 5.952

4.  Accuracy of Myocardial Blood Flow Estimation From Dynamic Contrast-Enhanced Cardiac CT Compared With PET.

Authors:  Adam M Alessio; Michael Bindschadler; Janet M Busey; William P Shuman; James H Caldwell; Kelley R Branch
Journal:  Circ Cardiovasc Imaging       Date:  2019-06-14       Impact factor: 7.792

5.  Differentiation of myocardial ischemia and infarction assessed by dynamic computed tomography perfusion imaging and comparison with cardiac magnetic resonance and single-photon emission computed tomography.

Authors:  Yuki Tanabe; Teruhito Kido; Teruyoshi Uetani; Akira Kurata; Tamami Kono; Akiyoshi Ogimoto; Masao Miyagawa; Tsutomu Soma; Kenya Murase; Hirotaka Iwaki; Teruhito Mochizuki
Journal:  Eur Radiol       Date:  2016-02-06       Impact factor: 5.315

Review 6.  Myocardial blood flow quantification for evaluation of coronary artery disease by computed tomography.

Authors:  Filippo Cademartiri; Sara Seitun; Alberto Clemente; Ludovico La Grutta; Patrizia Toia; Giuseppe Runza; Massimo Midiri; Erica Maffei
Journal:  Cardiovasc Diagn Ther       Date:  2017-04

Review 7.  Quantitative Myocardial Perfusion with Dynamic Contrast-Enhanced Imaging in MRI and CT: Theoretical Models and Current Implementation.

Authors:  G J Pelgrim; A Handayani; H Dijkstra; N H J Prakken; R H J A Slart; M Oudkerk; P M A Van Ooijen; R Vliegenthart; P E Sijens
Journal:  Biomed Res Int       Date:  2016-03-10       Impact factor: 3.411

Review 8.  CT Myocardial Perfusion Imaging: A New Frontier in Cardiac Imaging.

Authors:  Sara Seitun; Cecilia De Lorenzi; Filippo Cademartiri; Angelo Buscaglia; Nicole Travaglio; Manrico Balbi; Gian Paolo Bezante
Journal:  Biomed Res Int       Date:  2018-10-14       Impact factor: 3.411

Review 9.  Coronary Microvascular Dysfunction: PET, CMR and CT Assessment.

Authors:  Elisabetta Tonet; Graziella Pompei; Evelina Faragasso; Alberto Cossu; Rita Pavasini; Giulia Passarini; Matteo Tebaldi; Gianluca Campo
Journal:  J Clin Med       Date:  2021-04-23       Impact factor: 4.241

10.  Dynamic CT perfusion measurement in a cardiac phantom.

Authors:  Benjamin P Ziemer; Logan Hubbard; Jerry Lipinski; Sabee Molloi
Journal:  Int J Cardiovasc Imaging       Date:  2015-07-09       Impact factor: 2.357

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