Literature DB >> 24269264

Myocardial CT perfusion imaging in a large animal model: comparison of dynamic versus single-phase acquisitions.

Florian Schwarz1, Rabea Hinkel2, Elisabeth Baloch1, Roy P Marcus1, Kristof Hildebrandt1, Torleif A Sandner1, Christian Kupatt2, Verena Hoffmann3, Bernd J Wintersperger4, Maximilian F Reiser5, Daniel Theisen5, Konstantin Nikolaou5, Fabian Bamberg6.   

Abstract

OBJECTIVES: This study sought to compare dynamic versus single-phase high-pitch computed tomography (CT) acquisitions for the assessment of myocardial perfusion in a porcine model with adjustable degrees of coronary stenosis.
BACKGROUND: The incremental value of the 2 different approaches to CT-based myocardial perfusion imaging remains unclear.
METHODS: Country pigs received stent implantation in the left anterior descending coronary artery, in which an adjustable narrowing (50% and 75% stenoses) was created using a balloon catheter. All animals underwent CT-based rest and adenosine-stress myocardial perfusion imaging using dynamic and single-phase high-pitch acquisitions at both degrees of stenosis. Fluorescent microspheres served as a reference standard for myocardial blood flow. Segmental CT-based myocardial blood flow (MBFCT) was derived from dynamic acquisitions. Segmental single-phase enhancement (SPE) was recorded from high-pitch, single-phase examinations. MBFCT and SPE were compared between post-stenotic and reference segments, and receiver-operating characteristic curve analysis was performed.
RESULTS: Among 6 animals (28 ± 2 kg), there were significant differences of MBFCT and SPE between post-stenotic and reference segments for all acquisitions at 75% stenosis. By contrast, although for 50% stenosis at rest, MBFCT was lower in post-stenotic than in reference segments (0.65 ± 0.10 ml/g/min vs. 0.75 ± 0.16 ml/g/min, p < 0.05), there was no difference for SPE (128 ± 27 Hounsfield units vs. 137 ± 35 Hounsfield units, p = 0.17), which also did not significantly change under adenosine stress. In receiver-operating characteristic curve analyses, segmental MBFCT showed significantly better performance for ischemia prediction at 75% stenosis and stress (area under the curve: 0.99 vs. 0.89, p < 0.05) as well as for 50% stenosis, regardless of adenosine administration (area under the curve: 0.74 vs. 0.57 and 0.88 vs. 0.61, respectively, both p < 0.05).
CONCLUSIONS: At higher degrees of coronary stenosis, both MBFCT and SPE permit an accurate prediction of segmental myocardial hypoperfusion. However, accuracy of MBFCT is higher than that of SPE at 50% stenosis and can be increased by adenosine stress at both degrees of stenosis.
Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  AUC; CT; CTA; FM; HU; Hounsfield units; MBF(CT); MBF(MIC); ROC; ROI; SPE; area under the curve; cardiac CT; computed tomography; computed tomography angiography; computed tomography–derived myocardial blood flow; fluorescent microsphere(s); infarct; ischemia; microsphere-derived myocardial blood flow; myocardial perfusion; receiver-operating characteristic; region of interest; single-phase enhancement

Mesh:

Substances:

Year:  2013        PMID: 24269264     DOI: 10.1016/j.jcmg.2013.05.018

Source DB:  PubMed          Journal:  JACC Cardiovasc Imaging        ISSN: 1876-7591


  22 in total

Review 1.  Cardiac CT for myocardial ischaemia detection and characterization--comparative analysis.

Authors:  A M Bucher; C N De Cecco; U J Schoepf; R Wang; F G Meinel; S R Binukrishnan; J V Spearman; T J Vogl; B Ruzsics
Journal:  Br J Radiol       Date:  2014-08-19       Impact factor: 3.039

Review 2.  Static and dynamic assessment of myocardial perfusion by computed tomography.

Authors:  Ibrahim Danad; Jackie Szymonifka; Joshua Schulman-Marcus; James K Min
Journal:  Eur Heart J Cardiovasc Imaging       Date:  2016-03-24       Impact factor: 6.875

3.  Image quality and diagnostic accuracy of coronary CT angiography derived from low-dose dynamic CT myocardial perfusion: a feasibility study with comparison to invasive coronary angiography.

Authors:  Xu Dai; Mengmeng Yu; Jingwei Pan; Zhigang Lu; Chengxing Shen; Yining Wang; Bin Lu; Jiayin Zhang
Journal:  Eur Radiol       Date:  2018-11-09       Impact factor: 5.315

4.  Myocardial ischemia detection with single-phase CT perfusion in symptomatic patients using high-pitch helical image acquisition technique.

Authors:  Bernhard Bischoff; Simon Deseive; Martin Rampp; Andrei Todica; Marc Wermke; Stefan Martinoff; Steffen Massberg; Maximilian F Reiser; Hans-Christoph Becker; Jörg Hausleiter
Journal:  Int J Cardiovasc Imaging       Date:  2016-11-15       Impact factor: 2.357

Review 5.  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

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.  Myocardial perfusion of infarcted and normal myocardium in propofol-anesthetized minipigs using (82)Rubidium PET.

Authors:  Thomas Rasmussen; Bjarke Follin; Jens Kastrup; Thomas Emil Christensen; Karsten Pharao Hammelev; Andreas Kjær; Philip Hasbak
Journal:  J Nucl Cardiol       Date:  2016-03-01       Impact factor: 5.952

9.  Low-Radiation-Dose Stress Myocardial Perfusion Measurement Using First-Pass Analysis Dynamic Computed Tomography: A Preliminary Investigation in a Swine Model.

Authors:  Logan Hubbard; Shant Malkasian; Yixiao Zhao; Pablo Abbona; Jungnam Kwon; Sabee Molloi
Journal:  Invest Radiol       Date:  2019-12       Impact factor: 6.016

10.  Comprehensive Assessment of Coronary Artery Disease by Using First-Pass Analysis Dynamic CT Perfusion: Validation in a Swine Model.

Authors:  Logan Hubbard; Jerry Lipinski; Benjamin Ziemer; Shant Malkasian; Bahman Sadeghi; Hanna Javan; Elliott M Groves; Brian Dertli; Sabee Molloi
Journal:  Radiology       Date:  2017-10-23       Impact factor: 11.105

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