Literature DB >> 20928890

Estimates of systolic and diastolic myocardial blood flow by dynamic contrast-enhanced MRI.

Aleksandra Radjenovic1, John D Biglands, Abdulghani Larghat, John P Ridgway, Stephen G Ball, John P Greenwood, Michael Jerosch-Herold, Sven Plein.   

Abstract

Myocardial blood flow varies during the cardiac cycle in response to pulsatile changes in epicardial circulation and cyclical variation in myocardial tension. First-pass assessment of myocardial perfusion by dynamic contrast-enhanced MRI is one of the most challenging applications of MRI because of the spatial and temporal constraints imposed by the cardiac physiology and the nature of dynamic contrast-enhanced MRI signal collection. Here, we describe a dynamic contrast-enhanced MRI method for simultaneous assessment of systolic and diastolic myocardial blood flow. The feasibility of this method was demonstrated in a study of 17 healthy volunteers at rest and under adenosine-induced vasodilatory stress. We found that myocardial blood flow was independent of the cardiac phase at rest. However, under adenosine-induced hyperemia, myocardial blood flow and myocardial perfusion reserve were significantly higher in diastole than in systole. Furthermore, the transmural distribution of myocardial blood flow and myocardial perfusion reserve was cardiac phase dependent, with a reversal of the typical subendocardial to subepicardial myocardial blood flow gradient in systole, but not diastole, under stress. The observed difference between systolic and diastolic myocardial blood flow must be taken into account when assessing myocardial blood flow using dynamic contrast-enhanced MRI. Furthermore, targeted assessment of systolic or diastolic perfusion using dynamic contrast-enhanced MRI may provide novel insights into the pathophysiology of ischemic and microvascular heart disease.
Copyright © 2010 Wiley-Liss, Inc.

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Year:  2010        PMID: 20928890     DOI: 10.1002/mrm.22538

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


  23 in total

1.  Endocardial and epicardial myocardial perfusion determined by semi-quantitative and quantitative myocardial perfusion magnetic resonance.

Authors:  Abdulghani Larghat; John Biglands; Neil Maredia; John P Greenwood; Stephen G Ball; Michael Jerosch-Herold; Aleksandra Radjenovic; Sven Plein
Journal:  Int J Cardiovasc Imaging       Date:  2011-11-29       Impact factor: 2.357

2.  Patterns of myocardial perfusion in humans evaluated with contrast-enhanced 320 multidetector computed tomography.

Authors:  J Tobias Kühl; Jesper J Linde; Andreas Fuchs; Thomas S Kristensen; Henning Kelbæk; Richard T George; Jens D Hove; Klaus Fuglsang Kofoed
Journal:  Int J Cardiovasc Imaging       Date:  2011-12-06       Impact factor: 2.357

3.  Improved quantification of myocardial blood flow using highly constrained back projection reconstruction.

Authors:  David Chen; Behzad Sharif; Rohan Dharmakumar; Louise E J Thomson; C Noel Bairey Merz; Daniel S Berman; Debiao Li
Journal:  Magn Reson Med       Date:  2013-10-01       Impact factor: 4.668

4.  Whole-heart, ungated, free-breathing, cardiac-phase-resolved myocardial perfusion MRI by using Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state (CRIMP).

Authors:  Ye Tian; Jason Mendes; Brent Wilson; Alexander Ross; Ravi Ranjan; Edward DiBella; Ganesh Adluru
Journal:  Magn Reson Med       Date:  2020-06-03       Impact factor: 4.668

5.  Influence of the cardiac cycle on time-intensity curves using multislice dynamic magnetic resonance perfusion.

Authors:  Alain Nchimi; Isabelle Mancini; Thomas K Y Broussaud
Journal:  Int J Cardiovasc Imaging       Date:  2014-06-14       Impact factor: 2.357

6.  Accelerating free breathing myocardial perfusion MRI using multi coil radial k-t SLR.

Authors:  Sajan Goud Lingala; Edward DiBella; Ganesh Adluru; Christopher McGann; Mathews Jacob
Journal:  Phys Med Biol       Date:  2013-09-27       Impact factor: 3.609

7.  Quantification of myocardial blood flow using non-electrocardiogram-triggered MRI with three-slice coverage.

Authors:  David Chen; Behzad Sharif; Xiaoming Bi; Janet Wei; Louise E J Thomson; C Noel Bairey Merz; Daniel S Berman; Debiao Li
Journal:  Magn Reson Med       Date:  2015-06-08       Impact factor: 4.668

8.  Assessment of coronary artery stenosis severity and location: quantitative analysis of transmural perfusion gradients by high-resolution MRI versus FFR.

Authors:  Amedeo Chiribiri; Gilion L T F Hautvast; Timothy Lockie; Andreas Schuster; Boris Bigalke; Luca Olivotti; Simon R Redwood; Marcel Breeuwer; Sven Plein; Eike Nagel
Journal:  JACC Cardiovasc Imaging       Date:  2013-04-10

9.  Interstudy repeatability of self-gated quantitative myocardial perfusion MRI.

Authors:  Devavrat Likhite; Promporn Suksaranjit; Ganesh Adluru; Nan Hu; Cindy Weng; Eugene Kholmovski; Chris McGann; Brent Wilson; Edward DiBella
Journal:  J Magn Reson Imaging       Date:  2015-12-13       Impact factor: 4.813

10.  Quantification of myocardial blood flow using non-ECG-triggered MR imaging.

Authors:  David Chen; Behzad Sharif; Rohan Dharmakumar; Louise E J Thomson; C Noel Bairey Merz; Daniel S Berman; Debiao Li
Journal:  Magn Reson Med       Date:  2014-09-16       Impact factor: 4.668

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