Literature DB >> 22843541

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.

Alexia Rossi1, 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.   

Abstract

AIMS: Only few preliminary experimental studies demonstrated the feasibility of adenosine stress CT myocardial perfusion imaging to calculate the absolute myocardial blood flow (MBF), thereby providing information whether a coronary stenosis is flow limiting. Therefore, the aim of our study was to determine whether adenosine stress myocardial perfusion imaging by Dual Source CT (DSCT) enables non-invasive quantification of regional MBF in an animal model with various degrees of coronary flow reduction. METHODS AND
RESULTS: In seven pigs, a coronary flow probe and an adjustable hydraulic occluder were placed around the left anterior descending coronary artery to monitor the distal coronary artery blood flow (CBF) while several degrees of coronary flow reduction were induced. CT perfusion (CT-MBF) was acquired during adenosine stress with no CBF reduction, an intermediate (15-39%) and a severe (40-95%) CBF reduction. Reference standards were CBF and fractional flow reserve measurements (FFR). FFR was simultaneously derived from distal coronary artery pressure and aortic pressure measurements. CT-MBF decreased progressively with increasing CBF reduction severity from 2.68 (2.31-2.81)mL/g/min (normal CBF) to 1.96 (1.83-2.33) mL/g/min (intermediate CBF-reduction) and to 1.55 (1.14-2.06)mL/g/min (severe CBF-reduction) (both P < 0.001). We observed very good correlations between CT-MBF and CBF (r = 0.85, P < 0.001) and CT-MBF and FFR (r = 0.85, P < 0.001).
CONCLUSION: Adenosine stress DSCT myocardial perfusion imaging allows quantification of regional MBF under various degrees of CBF reduction.

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Year:  2012        PMID: 22843541     DOI: 10.1093/ehjci/jes150

Source DB:  PubMed          Journal:  Eur Heart J Cardiovasc Imaging        ISSN: 2047-2404            Impact factor:   6.875


  21 in total

1.  Imaging of coronary flow capacity: is there a role for dynamic CT perfusion imaging?

Authors:  Alexia Rossi; Giuseppe Ferrante
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-05-31       Impact factor: 9.236

2.  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

3.  Novel Imaging Techniques for Heart Failure.

Authors:  Josep L Melero-Ferrer; Raquel López-Vilella; Herminio Morillas-Climent; Jorge Sanz-Sánchez; Ignacio J Sánchez-Lázaro; Luis Almenar-Bonet; Luis Martínez-Dolz
Journal:  Card Fail Rev       Date:  2016-05

Review 4.  Myocardial blood flow quantification for evaluation of coronary artery disease by positron emission tomography, cardiac magnetic resonance imaging, and computed tomography.

Authors:  Alfonso H Waller; Ron Blankstein; Raymond Y Kwong; Marcelo F Di Carli
Journal:  Curr Cardiol Rep       Date:  2014-05       Impact factor: 2.931

5.  Evaluation of static and dynamic perfusion cardiac computed tomography for quantitation and classification tasks.

Authors:  Michael Bindschadler; Dimple Modgil; Kelley R Branch; Patrick J La Riviere; Adam M Alessio
Journal:  J Med Imaging (Bellingham)       Date:  2016-05-02

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

7.  Myocardial blood flow is the dominant factor influencing cardiac magnetic resonance adenosine stress T2.

Authors:  Jill J Weyers; Venkat Ramanan; Ahsan Javed; Jennifer Barry; Melissa Larsen; Krishna Nayak; Graham A Wright; Nilesh R Ghugre
Journal:  NMR Biomed       Date:  2021-11-17       Impact factor: 4.044

8.  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.

Authors:  Fabian Bamberg; 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
Journal:  Int J Cardiovasc Imaging       Date:  2014-02-26       Impact factor: 2.357

9.  Computed tomography segmental calcium score (SCS) to predict stenosis severity of calcified coronary lesions.

Authors:  Francesca Pugliese; M G M Hunink; Willem B Meijboom; Katarzyna Gruszczynsnka; Marco Rengo; Lu Zou; Ian Baron; Marcel L Dijkshoorn; Gabriel P Krestin; Pim J de Feyter
Journal:  Int J Cardiovasc Imaging       Date:  2015-09-14       Impact factor: 2.357

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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