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This study introduces a technique called cine magnetic resonance fingerprinting (cine‐MRF) for simultaneous T₁, T₂and 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 T₁and T₂maps. 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 mm²and 24 cardiac phases. Left ventricular EF values obtained with cine‐MRF agreed with the conventional cine images (mean bias −1.0%). Average myocardial T₁times 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 T₂values 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 T₁values were significantly longer than MOLLI, and cine‐MRF T₂values 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‐T₂mapping into one time‐efficient acquisition.

This study introduces a technique for simultaneous multislice (SMS) cardiac magnetic resonance fingerprinting (cMRF), which improves the slice coverage when quantifying myocardialT_1,T₂, andM₀. The single‐slice cMRF pulse sequence was modified to use multiband (MB) RF pulses for SMS imaging. Different RF phase schedules were used to excite each slice, similar to POMP or CAIPIRINHA, which imparts tissues with a distinguishable and slice‐specific magnetization evolution over time. Because of the high net acceleration factor (R = 48 in plane combined with the slice acceleration), images were first reconstructed with a low rank technique before matching data to a dictionary of signal timecourses generated by a Bloch equation simulation. The proposed method was tested in simulations with a numerical relaxation phantom. Phantom and in vivo cardiac scans of 10 healthy volunteers were also performed at 3 T. With single‐slice acquisitions, the mean relaxation times obtained using the low rank cMRF reconstruction agree with reference values. The low rank method improves the precision inT₁andT₂for both single‐slice and SMS cMRF, and it enables the acquisition of maps with fewer artifacts when using SMS cMRF at higher MB factors. With this technique, in vivo cardiac maps were acquired from three slices simultaneously during a breathhold lasting 16 heartbeats. SMS cMRF improves the efficiency and slice coverage of myocardialT₁andT₂mapping compared with both single‐slice cMRF and conventional cardiac mapping sequences. Thus, this technique is a first step toward whole‐heart simultaneousT₁andT₂quantification with cMRF.

Multiparametric quantitative imaging is gaining increasing interest due to its widespread advantages in clinical applications. Magnetic resonance fingerprinting is a recently introduced approach of fast multiparametric quantitative imaging. In this article, magnetic resonance fingerprinting acquisition, dictionary generation, reconstruction, and validation are reviewed.