Cardiac Magnetic Resonance Fingerprinting: Technical Developments and Initial Clinical Validation

Abstract

Purpose of Review Magnetic resonance imaging (MRI) has enabled non-invasive myocardial tissue characterization in a wide range of cardiovascular diseases by quantifying several tissue specific parameters such as T 1 , T 2 , and T2* relaxation times. Simultaneous assessment of these parameters has recently gained interest to potentially improve diagnostic accuracy and enable further understanding of the underlying disease. However, these quantitative maps are usually acquired sequentially and are not necessarily co-registered, making multi-parametric analysis challenging. Magnetic resonance fingerprinting (MRF) has been recently introduced to unify and streamline parametric mapping into a single simultaneous, multi-parametric, fully co-registered, and efficient scan. Feasibility of cardiac MRF has been demonstrated and initial clinical validation studies are ongoing. Provide an overview of the cardiac MRF framework, recent technical developments and initial undergoing clinical validation. Recent Findings Cardiac MRF has enabled the acquisition of co-registered T 1 and T 2 maps in a single, efficient scan. Initial results demonstrate feasibility of cardiac MRF in healthy subjects and small patient cohorts. Current in vivo results show a small bias and comparable precision in T 1 and T 2 with respect to conventional clinical parametric mapping approaches. This bias may be explained by several confounding factors such as magnetization transfer and field inhomogeneities, which are currently not included in the cardiac MRF model. Initial clinical validation for cardiac MRF has demonstrated good reproducibility in healthy subjects and heart transplant patients, reduced artifacts in inflammatory cardiomyopathy patients and good differentiation between hypertrophic cardiomyopathy and healthy controls. Summary Cardiac MRF has emerged as a novel technique for simultaneous, multi-parametric, and co-registered mapping of different tissue parameters. Initial efforts have focused on enabling T 1 , T 2 , and fat quantification; however this approach has the potential of enabling quantification of several other parameters (such as T 2 * , diffusion, perfusion, and flow) from a single scan. Initial results in healthy subjects and patients are promising, thus further clinical validation is now warranted.

3D free‐breathing cardiac magnetic resonance fingerprinting

“…Underestimation was observed for high T 2 values (not relevant for myocardial characterization), likely due to the absence of long T2prep modules (to encode high T 2 values) in the proposed sequence. T 2 underestimation has been previously reported in brain, 58 abdominal 59 and cardiac 60 MRF, and confounding factors that may account for these differences should be further investigated in the future.…”

“…Extended phase graphs (EPGs) 48,49 were employed to simulate the response of the magnetization to a sequence of 18 heartbeats, corresponding to a slice encoding (as depicted in Figure 1A). Four RR intervals were considered for the simulations: RR = [1500, 1000, 750, 600]ms (corresponding to [40,60,80, 100] beats per minute (bpm)). In each case, the RR intervals were further perturbed by random RR variations drawn for a Gaussian distribution of zero mean and standard deviation of [50,300] and 3fixed flip angle of 10 .…”

Magnetic resonance fingerprinting: from evolution to clinical applications

“…Nonetheless, initial clinical validation results are promising, with reliable differentiation between normal and diseased tissue, reduced artefacts and good reproducibility. 60 A comprehensive overview of recent developments in cMRF can be found in Cruz et al's paper. 60 Potential Implementation and Future of MRF Repeatability and reproducibility in MRF MRF parameter estimates must be repeatable and accurate, so that variations from the norm in that tissue can be confidently attributed to pathology.…”

“…60 A comprehensive overview of recent developments in cMRF can be found in Cruz et al's paper. 60 Potential Implementation and Future of MRF Repeatability and reproducibility in MRF MRF parameter estimates must be repeatable and accurate, so that variations from the norm in that tissue can be confidently attributed to pathology. The ISMRM/NIST system phantom was imaged over 34 days using FISP-MRF in one study.…”

Fast and accurate calculation of myocardial T1 and T2 values using deep learning Bloch equation simulations (DeepBLESS)

“…To address the issue, Bloch equation simulation–based algorithms have been proposed to model the signal evolution of a sequence to ensure accurate parameters estimation, such as the Bloch equation simulation with the slice‐profile correction (BLESSPC) algorithm for the MOLLI 11 and simultaneous radial T 1 ‐T 2 mapping 12 sequences, and the SQAUREMR algorithm for MOLLI 13 . Bloch equation simulation is also the key for accurate T 1 and T 2 map calculation in the cardiac MR fingerprinting (MRF) technique 14‐16 …”