Literature DB >> 32500541

Cardiac cine magnetic resonance fingerprinting for combined ejection fraction, T1 and T2 quantification.

Jesse I Hamilton1,2, Yun Jiang1,3, Brendan Eck2, Mark Griswold2,3, Nicole Seiberlich1,2,3.   

Abstract

This study introduces a technique called cine magnetic resonance fingerprinting (cine-MRF) for simultaneous T1 , T2 and ejection fraction (EF) quantification. Data acquired with a free-running MRF sequence are retrospectively sorted into different cardiac phases using an external electrocardiogram (ECG) signal. A low-rank reconstruction with a finite difference sparsity constraint along the cardiac motion dimension yields images resolved by cardiac phase. To improve SNR and precision in the parameter maps, these images are nonrigidly registered to the same phase and matched to a dictionary to generate T1 and T2 maps. Cine images for computing left ventricular volumes and EF are also derived from the same data. Cine-MRF was tested in simulations using a numerical relaxation phantom. Phantom and in vivo scans of 19 subjects were performed at 3 T during a 10.9 seconds breath-hold with an in-plane resolution of 1.6 x 1.6 mm2 and 24 cardiac phases. Left ventricular EF values obtained with cine-MRF agreed with the conventional cine images (mean bias -1.0%). Average myocardial T1 times in diastole/systole were 1398/1391 ms with cine-MRF, 1394/1378 ms with ECG-triggered cardiac MRF (cMRF) and 1234/1212 ms with MOLLI; and T2 values were 30.7/30.3 ms with cine-MRF, 32.6/32.9 ms with ECG-triggered cMRF and 37.6/41.0 ms with T2 -prepared FLASH. Cine-MRF and ECG-triggered cMRF relaxation times were in good agreement. Cine-MRF T1 values were significantly longer than MOLLI, and cine-MRF T2 values were significantly shorter than T2 -prepared FLASH. In summary, cine-MRF can potentially streamline cardiac MRI exams by combining left ventricle functional assessment and T1 -T2 mapping into one time-efficient acquisition.
© 2020 John Wiley & Sons, Ltd.

Entities:  

Keywords:  cine, ejection fraction, low rank, magnetic resonance fingerprinting, myocardial tissue characterization, T1 mapping, T2 mapping

Year:  2020        PMID: 32500541      PMCID: PMC7772953          DOI: 10.1002/nbm.4323

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  55 in total

1.  Image reconstruction algorithm for motion insensitive MR Fingerprinting (MRF): MORF.

Authors:  Bhairav Bipin Mehta; Dan Ma; Eric Yann Pierre; Yun Jiang; Simone Coppo; Mark Alan Griswold
Journal:  Magn Reson Med       Date:  2018-05-06       Impact factor: 4.668

2.  Sparse MRI: The application of compressed sensing for rapid MR imaging.

Authors:  Michael Lustig; David Donoho; John M Pauly
Journal:  Magn Reson Med       Date:  2007-12       Impact factor: 4.668

3.  Pseudo Steady-State Free Precession for MR-Fingerprinting.

Authors:  Jakob Assländer; Steffen J Glaser; Jürgen Hennig
Journal:  Magn Reson Med       Date:  2016-04-15       Impact factor: 4.668

4.  XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing.

Authors:  Li Feng; Leon Axel; Hersh Chandarana; Kai Tobias Block; Daniel K Sodickson; Ricardo Otazo
Journal:  Magn Reson Med       Date:  2015-03-25       Impact factor: 4.668

5.  Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart.

Authors:  Daniel R Messroghli; Aleksandra Radjenovic; Sebastian Kozerke; David M Higgins; Mohan U Sivananthan; John P Ridgway
Journal:  Magn Reson Med       Date:  2004-07       Impact factor: 4.668

6.  Quantitative evaluation of ischemic myocardial scar tissue by unenhanced T1 mapping using 3.0 Tesla MR scanner.

Authors:  Aylin Okur; Mecit Kantarcı; Yeşim Kızrak; Sema Yıldız; Berhan Pirimoğlu; Leyla Karaca; Hayri Oğul; Serdar Sevimli
Journal:  Diagn Interv Radiol       Date:  2014 Sep-Oct       Impact factor: 2.630

7.  MR Fingerprinting for Rapid Quantitative Abdominal Imaging.

Authors:  Yong Chen; Yun Jiang; Shivani Pahwa; Dan Ma; Lan Lu; Michael D Twieg; Katherine L Wright; Nicole Seiberlich; Mark A Griswold; Vikas Gulani
Journal:  Radiology       Date:  2016-01-21       Impact factor: 11.105

8.  Accuracy, precision, and reproducibility of four T1 mapping sequences: a head-to-head comparison of MOLLI, ShMOLLI, SASHA, and SAPPHIRE.

Authors:  Sébastien Roujol; Sebastian Weingärtner; Murilo Foppa; Kelvin Chow; Keigo Kawaji; Long H Ngo; Peter Kellman; Warren J Manning; Richard B Thompson; Reza Nezafat
Journal:  Radiology       Date:  2014-04-04       Impact factor: 11.105

9.  Myocardial T1-mapping at 3T using saturation-recovery: reference values, precision and comparison with MOLLI.

Authors:  Sebastian Weingärtner; Nadja M Meßner; Johannes Budjan; Dirk Loßnitzer; Uwe Mattler; Theano Papavassiliu; Frank G Zöllner; Lothar R Schad
Journal:  J Cardiovasc Magn Reson       Date:  2016-11-18       Impact factor: 5.364

10.  Free-running cardiac magnetic resonance fingerprinting: Joint T1/T2 map and Cine imaging.

Authors:  O Jaubert; G Cruz; A Bustin; T Schneider; P Koken; M Doneva; D Rueckert; R M Botnar; C Prieto
Journal:  Magn Reson Imaging       Date:  2020-02-13       Impact factor: 2.546

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  6 in total

1.  Free-breathing 3D cardiac T1 mapping with transmit B1 correction at 3T.

Authors:  Paul Kyu Han; Thibault Marin; Yanis Djebra; Vanessa Landes; Yue Zhuo; Georges El Fakhri; Chao Ma
Journal:  Magn Reson Med       Date:  2021-11-23       Impact factor: 4.668

Review 2.  Cardiac magnetic resonance fingerprinting: Trends in technical development and potential clinical applications.

Authors:  Brendan L Eck; Scott D Flamm; Deborah H Kwon; W H Wilson Tang; Claudia Prieto Vasquez; Nicole Seiberlich
Journal:  Prog Nucl Magn Reson Spectrosc       Date:  2020-11-06       Impact factor: 9.795

Review 3.  Rapid MR relaxometry using deep learning: An overview of current techniques and emerging trends.

Authors:  Li Feng; Dan Ma; Fang Liu
Journal:  NMR Biomed       Date:  2020-10-15       Impact factor: 4.478

4.  Myocardial T1, T2, T2*, and fat fraction quantification via low-rank motion-corrected cardiac MR fingerprinting.

Authors:  Gastao José Lima da Cruz; Carlos Velasco; Begoña Lavin; Olivier Jaubert; Rene Michael Botnar; Claudia Prieto
Journal:  Magn Reson Med       Date:  2022-01-26       Impact factor: 3.737

5.  A Self-Supervised Deep Learning Reconstruction for Shortening the Breathhold and Acquisition Window in Cardiac Magnetic Resonance Fingerprinting.

Authors:  Jesse I Hamilton
Journal:  Front Cardiovasc Med       Date:  2022-06-23

6.  Cardiac phase-resolved late gadolinium enhancement imaging.

Authors:  Sebastian Weingärtner; Ömer B Demirel; Francisco Gama; Iain Pierce; Thomas A Treibel; Jeanette Schulz-Menger; Mehmet Akçakaya
Journal:  Front Cardiovasc Med       Date:  2022-09-29
  6 in total

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