Literature DB >> 23605330

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

Giovanni Donato Aquaro1, Giancarlo Todiere, Gianluca Di Bella, Letizia Guiducci, Alessandro Pingitore, Vincenzo Lionetti.   

Abstract

The quantification of global myocardial blood flow (MBF) by measuring coronary sinus flow by magnetic resonance (MRI) was demonstrated to be very well correlated with positron emission tomography (PET). We proposed a new method for the quantification of regional myocardial perfusion with MRI by the integration of MBF and first pass technique. The aim of this study was to validate this new method for quantification of regional perfusion by comparing it with 13NH13-PET in swine models of myocardial infarction and in humans in resting and hyperemic conditions. MRI and 13NH3-PET was performed in 2 healthy swine, 11 swine models of myocardial infarction (5 reperfused, 6 non reperfused) and in 12 humans at rest and during hyperemia. MBF was estimated by MRI through the quantification of coronary sinus flow and left ventricular (LV) mass. The upslope of signal intensity (SI-upslope) of each myocardial segment was obtained by the first pass gadolinium technique. Regional SI-upslope was indexed by the upslope of the entire left ventricular myocardium (global upslope). Regional myocardial perfusion was estimated as the product of MBF and SI-upslope/global upslope. Regional perfusion was also estimated by 13NH3-PET. A close agreement of the MRI and PET techniques for measurement of regional myocardial perfusion was found in all myocardial segments by Bland-Altman analysis (mean difference 5.1 %; limits of agreement, -37.2-27.5 %). With the integration of the first pass technique and the measurement of global MBF by coronary sinus flow/LV mass, MRI allows direct quantification of regional myocardial perfusion.

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Year:  2013        PMID: 23605330     DOI: 10.1007/s10554-013-0220-z

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


  28 in total

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  2 in total

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