Literature DB >> 26595913

Development of Real-Time Magnetic Resonance Imaging of Mouse Hearts at 9.4 Tesla--Simulations and First Application.

Tobias Wech, Nicole Seiberlich, Andreas Schindele, Vicente Grau, Leonie Diffley, Michael L Gyngell, Alfio Borzì, Herbert Köstler, Jurgen E Schneider.   

Abstract

A novel method for real-time magnetic resonance imaging for the assessment of cardiac function in mice at 9.4 T is proposed. The technique combines a highly undersampled radial gradient echo acquisition with an image reconstruction utilizing both parallel imaging and compressed sensing. Simulations on an in silico phantom were performed to determine the achievable acceleration factor and to optimize regularization parameters. Several parameters characterizing the quality of the reconstructed images (such as spatial and temporal image sharpness or compartment areas) were calculated for this purpose. Subsequently, double-gated segmented cine data as well as non-gated undersampled real-time data using only six projections per timeframe (temporal resolution  ∼ 10 ms) were acquired in a mid-ventricular slice of four normal mouse hearts in vivo. The highly accelerated data sets were then subjected to the introduced reconstruction technique and results were validated against the fully sampled references. Functional parameters obtained from real-time and fully sampled data agreed well with a comparable accuracy for left-ventricular volumes and a slightly larger scatter for mass. This study introduces and validates a real-time cine-MRI technique, which significantly reduces scan time in preclinical cardiac functional imaging and has the potential to investigate mouse models with abnormal heart rhythm.

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Year:  2015        PMID: 26595913      PMCID: PMC4948122          DOI: 10.1109/TMI.2015.2501832

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  32 in total

1.  Adaptive reconstruction of phased array MR imagery.

Authors:  D O Walsh; A F Gmitro; M W Marcellin
Journal:  Magn Reson Med       Date:  2000-05       Impact factor: 4.668

2.  Generalized autocalibrating partially parallel acquisitions (GRAPPA).

Authors:  Mark A Griswold; Peter M Jakob; Robin M Heidemann; Mathias Nittka; Vladimir Jellus; Jianmin Wang; Berthold Kiefer; Axel Haase
Journal:  Magn Reson Med       Date:  2002-06       Impact factor: 4.668

3.  Comparison between prospective and retrospective triggering for mouse cardiac MRI.

Authors:  Edwin Heijman; Wolter de Graaf; Petra Niessen; Arno Nauerth; Guillaume van Eys; Larry de Graaf; Klaas Nicolay; Gustav J Strijkers
Journal:  NMR Biomed       Date:  2007-06       Impact factor: 4.044

4.  Improved radial GRAPPA calibration for real-time free-breathing cardiac imaging.

Authors:  Nicole Seiberlich; Philipp Ehses; Jeff Duerk; Robert Gilkeson; Mark Griswold
Journal:  Magn Reson Med       Date:  2010-09-24       Impact factor: 4.668

5.  Evaluation of manual and automatic segmentation of the mouse heart from CINE MR images.

Authors:  Edwin Heijman; Jean-Paul Aben; Cindy Penners; Petra Niessen; René Guillaume; Guillaume van Eys; Klaas Nicolay; Gustav J Strijkers
Journal:  J Magn Reson Imaging       Date:  2008-01       Impact factor: 4.813

6.  Ultra-fast and accurate assessment of cardiac function in rats using accelerated MRI at 9.4 Tesla.

Authors:  Jürgen E Schneider; Titus Lanz; Hannah Barnes; Debra Medway; Lee-Anne Stork; Craig A Lygate; Sean Smart; Mark A Griswold; Stefan Neubauer
Journal:  Magn Reson Med       Date:  2008-03       Impact factor: 4.668

7.  iASPP, a previously unidentified regulator of desmosomes, prevents arrhythmogenic right ventricular cardiomyopathy (ARVC)-induced sudden death.

Authors:  Mario Notari; Ying Hu; Gopinath Sutendra; Zinaida Dedeić; Min Lu; Laurent Dupays; Arash Yavari; Carolyn A Carr; Shan Zhong; Aaisha Opel; Andrew Tinker; Kieran Clarke; Hugh Watkins; David J P Ferguson; David P Kelsell; Sofia de Noronha; Mary N Sheppard; Mike Hollinshead; Timothy J Mohun; Xin Lu
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-17       Impact factor: 11.205

8.  Accelerating cine-MR imaging in mouse hearts using compressed sensing.

Authors:  Tobias Wech; Angela Lemke; Debra Medway; Lee-Anne Stork; Craig A Lygate; Stefan Neubauer; Herbert Köstler; Jürgen E Schneider
Journal:  J Magn Reson Imaging       Date:  2011-09-19       Impact factor: 4.813

9.  Fast, high-resolution in vivo cine magnetic resonance imaging in normal and failing mouse hearts on a vertical 11.7 T system.

Authors:  Jürgen E Schneider; Paul J Cassidy; Craig Lygate; Damian J Tyler; Frank Wiesmann; Stuart M Grieve; Karen Hulbert; Kieran Clarke; Stefan Neubauer
Journal:  J Magn Reson Imaging       Date:  2003-12       Impact factor: 4.813

10.  Accelerated cardiac magnetic resonance imaging in the mouse using an eight-channel array at 9.4 Tesla.

Authors:  Jürgen E Schneider; Titus Lanz; Hannah Barnes; Lee-Anne Stork; Steffen Bohl; Craig A Lygate; Roger J Ordidge; Stefan Neubauer
Journal:  Magn Reson Med       Date:  2011-01       Impact factor: 4.668

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  3 in total

1.  Optimization and validation of accelerated golden-angle radial sparse MRI reconstruction with self-calibrating GRAPPA operator gridding.

Authors:  Thomas Benkert; Ye Tian; Chenchan Huang; Edward V R DiBella; Hersh Chandarana; Li Feng
Journal:  Magn Reson Med       Date:  2017-11-28       Impact factor: 4.668

2.  Three-dimensional self-gated cardiac MR imaging for the evaluation of myocardial infarction in mouse model on a 3T clinical MR system.

Authors:  Xiaoyong Zhang; Bensheng Qiu; Zijun Wei; Fei Yan; Caiyun Shi; Shi Su; Xin Liu; Jim X Ji; Guoxi Xie
Journal:  PLoS One       Date:  2017-12-07       Impact factor: 3.240

3.  Feasibility of real-time cine cardiac magnetic resonance imaging to predict the presence of significant retrosternal adhesions prior to redo-sternotomy.

Authors:  Riad Abou Zahr; Vasu Gooty; Animesh Tandon; Gerald Greil; Timothy Pirolli; Ryan Davies; Robert Jaquiss; Claudio Ramaciotti; Tarique Hussain
Journal:  J Cardiovasc Magn Reson       Date:  2019-10-31       Impact factor: 5.364

  3 in total

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