Literature DB >> 29964183

Investigating and reducing the effects of confounding factors for robust T1 and T2 mapping with cardiac MR fingerprinting.

Jesse I Hamilton1, Yun Jiang2, Dan Ma3, Wei-Ching Lo4, Vikas Gulani5, Mark Griswold6, Nicole Seiberlich7.   

Abstract

This study aims to improve the accuracy and consistency of T1 and T2 measurements using cardiac MR Fingerprinting (cMRF) by investigating and accounting for the effects of confounding factors including slice profile, inversion and T2 preparation pulse efficiency, and B1+. The goal is to understand how measurements with different pulse sequences are affected by these factors. This can be used to determine which factors must be taken into account for accurate measurements, and which may be mitigated by the selection of an appropriate pulse sequence. Simulations were performed using a numerical cardiac phantom to assess the accuracy of over 600 cMRF sequences with different flip angles, TRs, and preparation pulses. A subset of sequences, including one with the lowest errors in T1 and T2 maps, was used in subsequent analyses. Errors due to non-ideal slice profile, preparation pulse efficiency, and B1+ were quantified in Bloch simulations. Corrections for these effects were included in the dictionary generation and demonstrated in phantom and in vivo cardiac imaging at 3 T. Neglecting to model slice profile and preparation pulse efficiency led to underestimated T1 and overestimated T2 for most cMRF sequences. Sequences with smaller maximum flip angles were less affected by slice profile and B1+. Simulating all corrections in the dictionary improved the accuracy of T1 and T2 phantom measurements, regardless of acquisition pattern. More consistent myocardial T1 and T2 values were measured using different sequences after corrections. Based on these results, a pulse sequence which is minimally affected by confounding factors can be selected, and the appropriate residual corrections included for robust T1 and T2 mapping.
Copyright © 2018 Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 29964183      PMCID: PMC7755105          DOI: 10.1016/j.mri.2018.06.018

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  36 in total

1.  IR TrueFISP with a golden-ratio-based radial readout: fast quantification of T1, T2, and proton density.

Authors:  Philipp Ehses; Nicole Seiberlich; Dan Ma; Felix A Breuer; Peter M Jakob; Mark A Griswold; Vikas Gulani
Journal:  Magn Reson Med       Date:  2012-02-29       Impact factor: 4.668

Review 2.  Adiabatic pulses.

Authors:  A Tannús; M Garwood
Journal:  NMR Biomed       Date:  1997-12       Impact factor: 4.044

3.  RF slice profile effects in magnetic resonance fingerprinting.

Authors:  Taehwa Hong; Dongyeob Han; Min-Oh Kim; Dong-Hyun Kim
Journal:  Magn Reson Imaging       Date:  2017-04-05       Impact factor: 2.546

4.  Algorithm comparison for schedule optimization in MR fingerprinting.

Authors:  Ouri Cohen; Matthew S Rosen
Journal:  Magn Reson Imaging       Date:  2017-02-24       Impact factor: 2.546

5.  The intrinsic signal-to-noise ratio in NMR imaging.

Authors:  W A Edelstein; G H Glover; C J Hardy; R W Redington
Journal:  Magn Reson Med       Date:  1986-08       Impact factor: 4.668

6.  Fast 3D magnetic resonance fingerprinting for a whole-brain coverage.

Authors:  Dan Ma; Yun Jiang; Yong Chen; Debra McGivney; Bhairav Mehta; Vikas Gulani; Mark Griswold
Journal:  Magn Reson Med       Date:  2017-08-22       Impact factor: 4.668

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.  Adiabatic inversion pulses for myocardial T1 mapping.

Authors:  Peter Kellman; Daniel A Herzka; Michael Schacht Hansen
Journal:  Magn Reson Med       Date:  2013-05-30       Impact factor: 4.668

9.  Shortened Modified Look-Locker Inversion recovery (ShMOLLI) for clinical myocardial T1-mapping at 1.5 and 3 T within a 9 heartbeat breathhold.

Authors:  Stefan K Piechnik; Vanessa M Ferreira; Erica Dall'Armellina; Lowri E Cochlin; Andreas Greiser; Stefan Neubauer; Matthew D Robson
Journal:  J Cardiovasc Magn Reson       Date:  2010-11-19       Impact factor: 5.364

10.  Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by the Society for Cardiovascular Magnetic Resonance (SCMR) endorsed by the European Association for Cardiovascular Imaging (EACVI).

Authors:  Daniel R Messroghli; James C Moon; Vanessa M Ferreira; Lars Grosse-Wortmann; Taigang He; Peter Kellman; Julia Mascherbauer; Reza Nezafat; Michael Salerno; Erik B Schelbert; Andrew J Taylor; Richard Thompson; Martin Ugander; Ruud B van Heeswijk; Matthias G Friedrich
Journal:  J Cardiovasc Magn Reson       Date:  2017-10-09       Impact factor: 5.364

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  23 in total

1.  Simultaneous multislice cardiac magnetic resonance fingerprinting using low rank reconstruction.

Authors:  Jesse I Hamilton; Yun Jiang; Dan Ma; Yong Chen; Wei-Ching Lo; Mark Griswold; Nicole Seiberlich
Journal:  NMR Biomed       Date:  2018-12-18       Impact factor: 4.044

Review 2.  Magnetic resonance fingerprinting: an overview.

Authors:  Charit Tippareddy; Walter Zhao; Jeffrey L Sunshine; Mark Griswold; Dan Ma; Chaitra Badve
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-05-26       Impact factor: 9.236

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

Authors:  Jesse I Hamilton; Yun Jiang; Brendan Eck; Mark Griswold; Nicole Seiberlich
Journal:  NMR Biomed       Date:  2020-06-05       Impact factor: 4.044

Review 4.  Magnetic resonance fingerprinting review part 2: Technique and directions.

Authors:  Debra F McGivney; Rasim Boyacıoğlu; Yun Jiang; Megan E Poorman; Nicole Seiberlich; Vikas Gulani; Kathryn E Keenan; Mark A Griswold; Dan Ma
Journal:  J Magn Reson Imaging       Date:  2019-07-25       Impact factor: 4.813

5.  Machine Learning for Rapid Magnetic Resonance Fingerprinting Tissue Property Quantification.

Authors:  Jesse I Hamilton; Nicole Seiberlich
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2019-09-11       Impact factor: 10.961

Review 6.  Cardiac Magnetic Resonance Fingerprinting: Technical Overview and Initial Results.

Authors:  Yuchi Liu; Jesse Hamilton; Sanjay Rajagopalan; Nicole Seiberlich
Journal:  JACC Cardiovasc Imaging       Date:  2018-12

Review 7.  Myocardial T1 and ECV Measurement: Underlying Concepts and Technical Considerations.

Authors:  Austin A Robinson; Kelvin Chow; Michael Salerno
Journal:  JACC Cardiovasc Imaging       Date:  2019-09-18

8.  Summary of Imaging in 2020: Visualizing the Future of Healthcare with MR Imaging.

Authors:  Brooke A Corbin; Alyssa C Pollard; Matthew J Allen; Mark D Pagel
Journal:  Mol Imaging Biol       Date:  2019-04       Impact factor: 3.488

9.  Simultaneous Mapping of T1 and T2 Using Cardiac Magnetic Resonance Fingerprinting in a Cohort of Healthy Subjects at 1.5T.

Authors:  Jesse I Hamilton; Shivani Pahwa; Joseph Adedigba; Samuel Frankel; Gregory O'Connor; Rahul Thomas; Jonathan R Walker; Ozden Killinc; Wei-Ching Lo; Joshua Batesole; Seunghee Margevicius; Mark Griswold; Sanjay Rajagopalan; Vikas Gulani; Nicole Seiberlich
Journal:  J Magn Reson Imaging       Date:  2020-03-28       Impact factor: 4.813

10.  Targeted Biopsy Validation of Peripheral Zone Prostate Cancer Characterization With Magnetic Resonance Fingerprinting and Diffusion Mapping.

Authors:  Ananya Panda; Gregory OʼConnor; Wei Ching Lo; Yun Jiang; Seunghee Margevicius; Mark Schluchter; Lee E Ponsky; Vikas Gulani
Journal:  Invest Radiol       Date:  2019-08       Impact factor: 6.016

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