Literature DB >> 20223537

Free breathing cardiac real-time cine MR without ECG triggering.

Meinrad Beer1, Heimo Stamm2, Wolfram Machann3, Andreas Weng2, Jan P Goltz3, Frank Breunig3, Frank Weidemann3, Dietbert Hahn2, Herbert Köstler2.   

Abstract

The increasing frequency of LV functional MRI studies demands for faster methods and for more comfort for the patient. We tested, whether real-time (RT) non ECG triggered MRI allows a considerable shortening of examination time in high reproducibility. RT and standard ECG-triggered breathhold cine MRI was acquired in 9 volunteers and 21 patients. Differences between both methods were assessed by Bland-Altman analyses including variability studies. Compared to standard cine MRI, RT decreased data acquisition time by more than the factor of ten. RT produced comparable results (e.g. EF in %: +0.67 [-5.63, 6.97]) except for a slight overestimation of LV mass. Interstudy and intraobserver variability of RT cine showed a low variability. Consequently, free-breathing RT cine proved to be a reliable and suitable tool for clinical routine and may be particularly relevant in patients with sub-optimal breath-holding ability and arrhythmia.
Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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Year:  2010        PMID: 20223537     DOI: 10.1016/j.ijcard.2010.02.052

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  3 in total

1.  Highly accelerated real-time cardiac cine MRI using k-t SPARSE-SENSE.

Authors:  Li Feng; Monvadi B Srichai; Ruth P Lim; Alexis Harrison; Wilson King; Ganesh Adluru; Edward V R Dibella; Daniel K Sodickson; Ricardo Otazo; Daniel Kim
Journal:  Magn Reson Med       Date:  2012-08-06       Impact factor: 4.668

2.  Evaluation of left ventricular ejection fraction using through-time radial GRAPPA.

Authors:  Gunhild Aandal; Vidya Nadig; Victoria Yeh; Prabhakar Rajiah; Trevor Jenkins; Abdus Sattar; Mark Griswold; Vikas Gulani; Robert C Gilkeson; Nicole Seiberlich
Journal:  J Cardiovasc Magn Reson       Date:  2014-10-01       Impact factor: 5.364

3.  Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging.

Authors:  Fan Yang; Yan He; Mubashir Hussain; Hong Xie; Pinggui Lei
Journal:  Comput Math Methods Med       Date:  2017-07-26       Impact factor: 2.238

  3 in total

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