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Cardiac MR Fingerprinting: Overview, Technical Developments, and Applications

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Date 2023 Dec 28
PMID 38153855
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Abstract

Cardiovascular magnetic resonance (CMR) is an established imaging modality with proven utility in assessing cardiovascular diseases. The ability of CMR to characterize myocardial tissue using T- and T-weighted imaging, parametric mapping, and late gadolinium enhancement has allowed for the non-invasive identification of specific pathologies not previously possible with modalities like echocardiography. However, CMR examinations are lengthy and technically complex, requiring multiple pulse sequences and different anatomical planes to comprehensively assess myocardial structure, function, and tissue composition. To increase the overall impact of this modality, there is a need to simplify and shorten CMR exams to improve access and efficiency, while also providing reproducible quantitative measurements. Multiparametric MRI techniques that measure multiple tissue properties offer one potential solution to this problem. This review provides an in-depth look at one such multiparametric approach, cardiac magnetic resonance fingerprinting (MRF). The article is structured as follows. First, a brief review of single-parametric and (non-Fingerprinting) multiparametric CMR mapping techniques is presented. Second, a general overview of cardiac MRF is provided covering pulse sequence implementation, dictionary generation, fast k-space sampling methods, and pattern recognition. Third, recent technical advances in cardiac MRF are covered spanning a variety of topics, including simultaneous multislice and 3D sampling, motion correction algorithms, cine MRF, synthetic multicontrast imaging, extensions to measure additional clinically important tissue properties (proton density fat fraction, T*, and T), and deep learning methods for image reconstruction and parameter estimation. The last section will discuss potential clinical applications, concluding with a perspective on how multiparametric techniques like MRF may enable streamlined CMR protocols. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.

References
1.
McCrohon J, Moon J, Prasad S, McKenna W, Lorenz C, Coats A . Differentiation of heart failure related to dilated cardiomyopathy and coronary artery disease using gadolinium-enhanced cardiovascular magnetic resonance. Circulation. 2003; 108(1):54-9. DOI: 10.1161/01.CIR.0000078641.19365.4C. View

2.
He T, Gatehouse P, Kirk P, Tanner M, Smith G, Keegan J . Black-blood T2* technique for myocardial iron measurement in thalassemia. J Magn Reson Imaging. 2007; 25(6):1205-9. DOI: 10.1002/jmri.20929. View

3.
Hamilton J . A Self-Supervised Deep Learning Reconstruction for Shortening the Breathhold and Acquisition Window in Cardiac Magnetic Resonance Fingerprinting. Front Cardiovasc Med. 2022; 9:928546. PMC: 9260051. DOI: 10.3389/fcvm.2022.928546. View

4.
Kellman P, Hansen M . T1-mapping in the heart: accuracy and precision. J Cardiovasc Magn Reson. 2014; 16:2. PMC: 3927683. DOI: 10.1186/1532-429X-16-2. View

5.
Santini F, Kawel-Boehm N, Greiser A, Bremerich J, Bieri O . Simultaneous T1 and T2 quantification of the myocardium using cardiac balanced-SSFP inversion recovery with interleaved sampling acquisition (CABIRIA). Magn Reson Med. 2014; 74(2):365-71. DOI: 10.1002/mrm.25402. View