Literature DB >> 21469192

Quantification of myocardial blood flow using model based analysis of first-pass perfusion MRI: extraction fraction of Gd-DTPA varies with myocardial blood flow in human myocardium.

Masaki Ishida1, Takashi Ichihara, Motonori Nagata, Nanaka Ishida, Shinichi Takase, Tairo Kurita, Masaaki Ito, Kan Takeda, Hajime Sakuma.   

Abstract

For the absolute quantification of myocardial blood flow (MBF), Patlak plot-derived K1 need to be converted to MBF by using the relation between the extraction fraction of gadolinium contrast agent and MBF. This study was conducted to determine the relation between extraction fraction of Gd-DTPA and MBF in human heart at rest and during stress. Thirty-four patients (19 men, mean age of 66.5 ± 11.0 years) with normal coronary arteries and no myocardial infarction were retrospectively evaluated. First-pass myocardial perfusion MRI during adenosine triphosphate stress and at rest was performed using a dual bolus approach to correct for saturation of the blood signal. Myocardial K1 was quantified by Patlak plot method. Mean MBF was determined from coronary sinus flow measured by phase contrast cine MRI and left ventricle mass measured by cine MRI. The extraction fraction of Gd-DTPA was calculated as the K1 divided by the mean MBF. The extraction fraction of Gd-DTPA was 0.46 ± 0.22 at rest and 0.32 ± 0.13 during stress (P < 0.001). The relationship between extraction fraction (E) and MBF in human myocardium can be approximated as E = 1 - exp(-(0.14 × MBF + 0.56)/MBF). The current results indicate that MBF can be accurately quantified by Patlak plot method of first-pass myocardial perfusion MRI by performing a correction of extraction fraction.
Copyright © 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 21469192     DOI: 10.1002/mrm.22936

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  13 in total

1.  Free-breathing cardiac MR stress perfusion with real-time slice tracking.

Authors:  Tamer A Basha; Sébastien Roujol; Kraig V Kissinger; Beth Goddu; Sophie Berg; Warren J Manning; Reza Nezafat
Journal:  Magn Reson Med       Date:  2013-10-07       Impact factor: 4.668

2.  Leakage and water exchange characterization of gadofosveset in the myocardium.

Authors:  Octavia Bane; Daniel C Lee; Brandon C Benefield; Kathleen R Harris; Neil R Chatterjee; James C Carr; Timothy J Carroll
Journal:  Magn Reson Imaging       Date:  2013-12-07       Impact factor: 2.546

3.  An empirical method for reducing variability and complexity of myocardial perfusion quantification by dual bolus cardiac MRI.

Authors:  Neil Chatterjee; Brandon C Benefield; Kathleen R Harris; Jacob U Fluckiger; Timothy Carroll; Daniel C Lee
Journal:  Magn Reson Med       Date:  2016-09-08       Impact factor: 4.668

Review 4.  Quantitative Assessment of Coronary Microvascular Function: Dynamic Single-Photon Emission Computed Tomography, Positron Emission Tomography, Ultrasound, Computed Tomography, and Magnetic Resonance Imaging.

Authors:  Attila Feher; Albert J Sinusas
Journal:  Circ Cardiovasc Imaging       Date:  2017-08       Impact factor: 7.792

5.  Clinical Validation of the Accuracy of Absolute Myocardial Blood Flow Quantification with Dual-Source CT Using 15O-Water PET.

Authors:  Masafumi Takafuji; Kakuya Kitagawa; Masaki Ishida; Yasutaka Ichikawa; Satoshi Nakamura; Shiro Nakamori; Tairo Kurita; Kaoru Dohi; Hajime Sakuma
Journal:  Radiol Cardiothorac Imaging       Date:  2021-10-28

Review 6.  Quantitative myocardial perfusion imaging by cardiovascular magnetic resonance and positron emission tomography.

Authors:  K Bratis; I Mahmoud; A Chiribiri; E Nagel
Journal:  J Nucl Cardiol       Date:  2013-07-19       Impact factor: 5.952

7.  A fast and effective method of quantifying myocardial perfusion by magnetic resonance imaging.

Authors:  Giovanni Donato Aquaro; Giancarlo Todiere; Gianluca Di Bella; Letizia Guiducci; Alessandro Pingitore; Vincenzo Lionetti
Journal:  Int J Cardiovasc Imaging       Date:  2013-04-21       Impact factor: 2.357

8.  Estimating extraction fraction and blood flow by combining first-pass myocardial perfusion and T1 mapping results.

Authors:  Devavrat Likhite; Promporn Suksaranjit; Ganesh Adluru; Brent Wilson; Edward DiBella
Journal:  Quant Imaging Med Surg       Date:  2017-10

9.  Comparison of the Diagnostic Performance of Four Quantitative Myocardial Perfusion Estimation Methods Used in Cardiac MR Imaging: CE-MARC Substudy.

Authors:  John D Biglands; Derek R Magee; Steven P Sourbron; Sven Plein; John P Greenwood; Aleksandra Radjenovic
Journal:  Radiology       Date:  2014-12-18       Impact factor: 11.105

10.  Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation.

Authors:  Hui Xue; Louise A E Brown; Sonia Nielles-Vallespin; Sven Plein; Peter Kellman
Journal:  Magn Reson Med       Date:  2019-08-23       Impact factor: 4.668

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