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1.5 and 3 Tesla quantification of myocardial perfusion reserve in comparison to fractional flow reserve

  • Peter Bernhardt
  • Thomas Walcher
  • Wolfgang Rottbauer
  • Jochen Wöhrle
Open Access
Poster presentation
  • 345 Downloads

Keywords

Coronary Artery Disease Cardiac Magnetic Resonance Fractional Flow Reserve Cardiac Magnetic Resonance Imaging Receiver Operator Curve 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Background

Quantitative myocardial perfusion reserve (MPR) analysis is capable of noninvasive detection of significant coronary artery disease. However, little is known about MPR evaluation in comparison to fractional flow reserve (FFR), especially at 3 Tesla. Aim of our study was to compare quantitative MPR at 1.5 and 3 Tesla against FFR.

Methods

Thirty-four patients referred for coronary x-ray angiography with suspected or known coronary artery disease underwent cardiac magnetic resonance imaging (CMR) at 1.5 and 3 Tesla, and additionally FFR measurement in LAD, CX and RCA. MPR was calculated in 544 myocardial segments at both field strenghts. FFR was measured in 109 coronary arteries with a cut-off value of ≤0.8 for relevant stenosis.

Results

In 38 coronary arteries (N=19 LAD, N=8 CX, N=11 RCA) a reduced FFR ≤0.8 was found. Receiver operator curve analysis yielded a higher area under the curve for 3 Tesla in comparison to 1.5 Tesla MPR (0.96 vs 0.65, p<0.001) resulting in higher values for sensitivity (90.5% vs. 61.9%) and specificity (100% vs. 76.9%), respectively.

Conclusions

Both field strengths, 1.5 and 3 Tesla, are capable to detect hemodynamic significant coronary artery stenoses using quantitative MPR analysis. The diagnostic accuracy at 3 Tesla is however superior to 1.5 Tesla for MPR quantification.

Funding

The study was partially funded by a research grant of Guerbet (France).

Copyright information

© Bernhardt et al; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • Peter Bernhardt
    • 1
  • Thomas Walcher
    • 1
  • Wolfgang Rottbauer
    • 1
  • Jochen Wöhrle
    • 1
  1. 1.University of UlmUlmGermany

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