Literature DB >> 34963645

Characterization of cardiac amyloidosis using cardiac magnetic resonance fingerprinting.

Brendan L Eck1, Nicole Seiberlich2, Scott D Flamm3, Jesse I Hamilton2, Abhilash Suresh4, Yash Kumar4, Mazen Hanna4, Angel Houston5, Derrek Tew5, W H Wilson Tang4, Deborah H Kwon3.   

Abstract

BACKGROUND: Cardiac amyloidosis (CA) is an infiltrative cardiomyopathy with poor prognosis absent appropriate treatment. Elevated native myocardial T1 and T2 have been reported for CA, and tissue characterization by cardiac MRI may expedite diagnosis and treatment. Cardiac Magnetic Resonance Fingerprinting (cMRF) has the potential to enable tissue characterization for CA through rapid, simultaneous T1 and T2 mapping. Furthermore, cMRF signal timecourses may provide additional information beyond myocardial T1 and T2.
METHODS: Nine CA patients and five controls were scanned at 3 T using a prospectively gated cMRF acquisition. Two cMRF-based analysis approaches were examined: (1) relaxometric-based linear discriminant analysis (LDA) using native T1 and T2, and (2) signal timecourse-based LDA. The Fisher coefficient was used to compare the separability of patient and control groups from both approaches. Leave-two-out cross-validation was employed to evaluate the classification error rates of both approaches.
RESULTS: Elevated myocardial T1 and T2 was observed in patients vs controls (T1: 1395 ± 121 vs 1240 ± 36.4 ms, p < 0.05; T2: 36.8 ± 3.3 vs 31.8 ± 2.6 ms, p < 0.05). LDA scores were elevated in patients for relaxometric-based LDA (0.56 ± 0.28 vs 0.18 ± 0.13, p < 0.05) and timecourse-based LDA (0.97 ± 0.02 vs 0.02 ± 0.02, p < 0.05). The Fisher coefficient was greater for timecourse-based LDA (60.8) vs relaxometric-based LDA (1.6). Classification error rates were lower for timecourse-based LDA vs relaxometric-based LDA (12.6 ± 24.3 vs 22.5 ± 30.1%, p < 0.05).
CONCLUSIONS: These findings suggest that cMRF may be a valuable technique for the detection and characterization of CA. Analysis of cMRF signal timecourse data may improve tissue characterization as compared to analysis of native T1 and T2 alone.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cardiac amyloidosis; Magnetic resonance fingerprinting; Magnetic resonance imaging; T(1) mapping; T(2) mapping; Tissue characterization

Mesh:

Year:  2021        PMID: 34963645      PMCID: PMC8857016          DOI: 10.1016/j.ijcard.2021.12.038

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


  10 in total

1.  Magnetization transfer in magnetic resonance fingerprinting.

Authors:  Tom Hilbert; Ding Xia; Kai Tobias Block; Zidan Yu; Riccardo Lattanzi; Daniel K Sodickson; Tobias Kober; Martijn A Cloos
Journal:  Magn Reson Med       Date:  2019-11-25       Impact factor: 4.668

2.  Texture analysis of multiple sclerosis: a comparative study.

Authors:  Jing Zhang; Longzheng Tong; Lei Wang; Ning Li
Journal:  Magn Reson Imaging       Date:  2008-05-29       Impact factor: 2.546

3.  Diffusion Tensor Cardiovascular Magnetic Resonance in Cardiac Amyloidosis.

Authors:  David N Firmin; Dudley J Pennell; Zohya Khalique; Pedro F Ferreira; Andrew D Scott; Sonia Nielles-Vallespin; Ana Martinez-Naharro; Marianna Fontana; Phillip Hawkins
Journal:  Circ Cardiovasc Imaging       Date:  2020-05-15       Impact factor: 7.792

4.  Contrast-free high-resolution 3D magnetization transfer imaging for simultaneous myocardial scar and cardiac vein visualization.

Authors:  Karina López; Radhouene Neji; Rahul K Mukherjee; John Whitaker; Alkystis Phinikaridou; Reza Razavi; Claudia Prieto; Sébastien Roujol; René Botnar
Journal:  MAGMA       Date:  2020-02-20       Impact factor: 2.310

5.  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

Review 6.  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

7.  Magnetic resonance fingerprinting residual signals can disassociate human grey matter regions.

Authors:  Shahrzad Moinian; Viktor Vegh; Kieran O'Brien; David Reutens
Journal:  Brain Struct Funct       Date:  2021-10-25       Impact factor: 3.270

8.  Myocardial native T2 measurement to differentiate light-chain and transthyretin cardiac amyloidosis and assess prognosis.

Authors:  Fourat Ridouani; Thibaud Damy; Vania Tacher; Haytham Derbel; François Legou; Islem Sifaoui; Etienne Audureau; Diane Bodez; Alain Rahmouni; Jean-François Deux
Journal:  J Cardiovasc Magn Reson       Date:  2018-08-16       Impact factor: 5.364

9.  Diffusion-weighting Caused by Spoiler Gradients in the Fast Imaging with Steady-state Precession Sequence May Lead to Inaccurate T2 Measurements in MR Fingerprinting.

Authors:  Yuta Kobayashi; Yasuhiko Terada
Journal:  Magn Reson Med Sci       Date:  2018-05-24       Impact factor: 2.471

10.  Noncontrast T1 mapping for the diagnosis of cardiac amyloidosis.

Authors:  Theodoros D Karamitsos; Stefan K Piechnik; Sanjay M Banypersad; Marianna Fontana; Ntobeko B Ntusi; Vanessa M Ferreira; Carol J Whelan; Saul G Myerson; Matthew D Robson; Philip N Hawkins; Stefan Neubauer; James C Moon
Journal:  JACC Cardiovasc Imaging       Date:  2013-03-14
  10 in total

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