Literature DB >> 31728679

Impact of baseline calibration on semiquantitative assessment of myocardial perfusion reserve by adenosine stress MRI.

Andreas Seitz1, Giancarlo Pirozzolo2, Udo Sechtem2, Raffi Bekeredjian2, Peter Ong2, Heiko Mahrholdt2.   

Abstract

In this study, we sought to investigate the impact of baseline calibration, which is used in quantitative cardiac MRI perfusion analysis to correct for surface coil inhomogeneity and noise, on myocardial perfusion reserve index (MPRI) and its contribution to previously reported paradoxical low MPRI < 1.0 in patients with unobstructed coronary arteries. Semiquantitative perfusion analysis was performed in 20 patients with unobstructed coronary arteries undergoing stress/rest perfusion CMR and in ten patients undergoing paired rest perfusion CMR. The following baseline calibration settings were compared: (1) baseline division, (2) baseline subtraction and (3) no baseline calibration. In uncalibrated analysis, we observed ~ 20% segmental dispersion of signal intensity (SI)-over-time curves. Both baseline subtraction and baseline division reduced relative dispersion of t0-SI (p < 0.001), but only baseline division corrected for dispersion of peak-SI and maximum upslope also (p < 0.001). In the assessment of perfusion indices, however, baseline division resulted in paradoxical low MPRI (1.01 ± 0.23 vs. 1.63 ± 0.38, p < 0.001) and rest perfusion index (RPI 0.54 ± 0.07 vs. 0.94 ± 0.12, p < 0.001), respectively. This was due to a reversed ratio of blood-pool and myocardial baseline-SI before the second perfusion study caused by circulating contrast agent from the first injection. In conclusion, baseline division reliably corrects for inhomogeneity of the surface coil sensitivity profile facilitating comparisons of regional myocardial perfusion during hyperemia or at rest. However, in the assessment of MPRI, baseline division can lead to paradoxical low results (even MPRI < 1.0 in patients with unobstructed coronary arteries) potentially mimicking severely impaired perfusion reserve. Thus, in the assessment of MPRI we propose to waive baseline calibration.

Entities:  

Keywords:  Adenosine stress perfusion CMR; Baseline calibration; Baseline correction; MPRI; Myocardial perfusion reserve; Surface coil sensitivity profile

Mesh:

Substances:

Year:  2019        PMID: 31728679     DOI: 10.1007/s10554-019-01729-z

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


  40 in total

1.  Quantitative magnetic resonance perfusion imaging detects anatomic and physiologic coronary artery disease as measured by coronary angiography and fractional flow reserve.

Authors:  Marco A Costa; Steven Shoemaker; Hideki Futamatsu; Chris Klassen; Dominick J Angiolillo; Minh Nguyen; Alan Siuciak; Paul Gilmore; Martin M Zenni; Luis Guzman; Theodore A Bass; Norbert Wilke
Journal:  J Am Coll Cardiol       Date:  2007-07-23       Impact factor: 24.094

2.  Contrast-dose relation in first-pass myocardial MR perfusion imaging.

Authors:  Wolfgang Utz; Thoralf Niendorf; Ralf Wassmuth; Daniel Messroghli; Rainer Dietz; Jeanette Schulz-Menger
Journal:  J Magn Reson Imaging       Date:  2007-06       Impact factor: 4.813

3.  Quantitative myocardial perfusion analysis with a dual-bolus contrast-enhanced first-pass MRI technique in humans.

Authors:  Li-Yueh Hsu; Kenneth L Rhoads; Jessica E Holly; Peter Kellman; Anthony H Aletras; Andrew E Arai
Journal:  J Magn Reson Imaging       Date:  2006-03       Impact factor: 4.813

4.  Intensity correction of phased-array surface coil images.

Authors:  J W Murakami; C E Hayes; E Weinberger
Journal:  Magn Reson Med       Date:  1996-04       Impact factor: 4.668

5.  Reproducibility of first-pass cardiovascular magnetic resonance myocardial perfusion.

Authors:  Abdulghani M Larghat; Neil Maredia; John Biglands; John P Greenwood; Stephen G Ball; Michael Jerosch-Herold; Aleksandra Radjenovic; Sven Plein
Journal:  J Magn Reson Imaging       Date:  2013-01-18       Impact factor: 4.813

6.  Navigator-gated 3D blood oxygen level-dependent CMR at 3.0-T for detection of stress-induced myocardial ischemic reactions.

Authors:  Cosima Jahnke; Rolf Gebker; Robert Manka; Bernhard Schnackenburg; Eckart Fleck; Ingo Paetsch
Journal:  JACC Cardiovasc Imaging       Date:  2010-04

7.  Assessment of coronary flow reserve: comparison between contrast-enhanced magnetic resonance imaging and positron emission tomography.

Authors:  Tareq Ibrahim; Stephan G Nekolla; Karin Schreiber; Kenichi Odaka; Stefan Volz; Julinda Mehilli; Martin Güthlin; Wolfram Delius; Markus Schwaiger
Journal:  J Am Coll Cardiol       Date:  2002-03-06       Impact factor: 24.094

Review 8.  Role of PET to evaluate coronary microvascular dysfunction in non-ischemic cardiomyopathies.

Authors:  Paco E Bravo; Marcelo F Di Carli; Sharmila Dorbala
Journal:  Heart Fail Rev       Date:  2017-07       Impact factor: 4.214

Review 9.  Modeling to link regional myocardial work, metabolism and blood flows.

Authors:  James B Bassingthwaighte; Daniel A Beard; Brian E Carlson; Ranjan K Dash; Kalyan Vinnakota
Journal:  Ann Biomed Eng       Date:  2012-08-23       Impact factor: 3.934

10.  High-resolution magnetic resonance myocardial perfusion imaging at 3.0-Tesla to detect hemodynamically significant coronary stenoses as determined by fractional flow reserve.

Authors:  Timothy Lockie; Masaki Ishida; Divaka Perera; Amedeo Chiribiri; Kalpa De Silva; Sebastian Kozerke; Mike Marber; Eike Nagel; Reza Rezavi; Simon Redwood; Sven Plein
Journal:  J Am Coll Cardiol       Date:  2011-01-04       Impact factor: 24.094

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