Purpose To introduce a 2D MR Fingerprinting technique for quantification of T1, T2, and M0 in myocardium. Methods An ECG-triggered MR Fingerprinting (MRF) method is introduced for mapping myocardial T1, T2, and M0 during a single breathhold in as short as four heartbeats. The pulse sequence employs variable flip angles, repetition times, inversion recovery times, and T2 preparation dephasing times. A dictionary of possible signal evolutions is simulated for each scan that incorporates the subject’s unique variations in heart rate. Aspects of the sequence design were explored in simulations, and the accuracy and precision of cardiac MRF were assessed in a phantom study. In vivo imaging was performed at 3T in eleven volunteers to generate native parametric maps. Results T1 and T2 measurements from the proposed cardiac MRF sequence correlated well with standard spin echo measurements in the phantom study (R2>0.99). A Bland-Altman analysis revealed good agreement for myocardial T1 measurements between MRF and MOLLI (bias 1ms, 95% limits of agreement −72 to 72ms) and T2 measurements between MRF and T2-prepared bSSFP (bias −2.6ms, 95% limits of agreement −8.5 to 3.3ms). Conclusions MRF can provide quantitative single slice T1, T2, and M0 maps in the heart within a single breathhold.

Purpose-To introduce a 2D MR Fingerprinting technique for quantification of T 1 , T 2 , and M 0 in myocardium.Methods-An ECG-triggered MR Fingerprinting (MRF) method is introduced for mapping myocardial T 1 , T 2 , and M 0 during a single breathhold in as short as four heartbeats. The pulse sequence employs variable flip angles, repetition times, inversion recovery times, and T 2 preparation dephasing times. A dictionary of possible signal evolutions is simulated for each scan that incorporates the subject's unique variations in heart rate. Aspects of the sequence design were explored in simulations, and the accuracy and precision of cardiac MRF were assessed in a phantom study. In vivo imaging was performed at 3T in eleven volunteers to generate native parametric maps.Results-T 1 and T 2 measurements from the proposed cardiac MRF sequence correlated well with standard spin echo measurements in the phantom study (R 2 >0.99). A Bland-Altman analysis revealed good agreement for myocardial T 1 measurements between MRF and MOLLI (bias 1ms, 95% limits of agreement −72 to 72ms) and T 2 measurements between MRF and T 2 -prepared bSSFP (bias −2.6ms, 95% limits of agreement −8.5 to 3.3ms). Conclusions-MRFcan provide quantitative single slice T 1 , T 2 , and M 0 maps in the heart within a single breathhold.

This study aims to improve the accuracy and consistency of T and T measurements using cardiac MR Fingerprinting (cMRF) by investigating and accounting for the effects of confounding factors including slice profile, inversion and T preparation pulse efficiency, and B. 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 T and T maps, was used in subsequent analyses. Errors due to non-ideal slice profile, preparation pulse efficiency, and B 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 T and overestimated T for most cMRF sequences. Sequences with smaller maximum flip angles were less affected by slice profile and B. Simulating all corrections in the dictionary improved the accuracy of T and T phantom measurements, regardless of acquisition pattern. More consistent myocardial T and T 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 T and T mapping.

Magnetic Resonance Imaging (MRI) is an essential technology in modern medicine. However, one of its main drawbacks is the long scan time needed to localize the MR signal in space to generate an image. This review article summarizes some basic principles and recent developments in parallel imaging, a class of image reconstruction techniques for shortening scan time. First, the fundamentals of MRI data acquisition are covered, including the concepts of k-space, undersampling, and aliasing. It is demonstrated that scan time can be reduced by sampling a smaller number of phase encoding lines in k-space; however, without further processing, the resulting images will be degraded by aliasing artifacts. Nearly all modern clinical scanners acquire data from multiple independent receiver coil arrays. Parallel imaging methods exploit properties of these coil arrays to separate aliased pixels in the image domain or to estimate missing k-space data using knowledge of nearby acquired k-space points. Three parallel imaging methods—SENSE, GRAPPA, and SPIRiT—are described in detail, since they are employed clinically and form the foundation for more advanced methods. These techniques can be extended to non-Cartesian sampling patterns, where the collected k-space points do not fall on a rectangular grid. Non-Cartesian acquisitions have several beneficial properties, the most important being the appearance of incoherent aliasing artifacts. Recent advances in simultaneous multi-slice imaging are presented next, which use parallel imaging to disentangle images of several slices that have been acquired at once. Parallel imaging can also be employed to accelerate 3D MRI, in which a contiguous volume is scanned rather than sequential slices. Another class of phase-constrained parallel imaging methods takes advantage of both image magnitude and phase to achieve better reconstruction performance. Finally, some applications are presented of parallel imaging being used to accelerate MR Spectroscopic Imaging.

To develop a fast three-dimensional method for simultaneous T1 and T2 quantification for breast imaging by using MR fingerprinting. Materials and Methods: In this prospective study, variable flip angles and magnetization preparation modules were applied to acquire MR fingerprinting data for each partition of a three-dimensional data set. A fast postprocessing method was implemented by using singular value decomposition. The proposed technique was first validated in phantoms and then applied to 15 healthy female participants (mean age, 24.2 years 6 5.1 [standard deviation]; range, 18-35 years) and 14 female participants with breast cancer (mean age, 55.4 years 6 8.8; range, 39-66 years) between March 2016 and April 2018. The sensitivity of the method to B 1 field inhomogeneity was also evaluated by using the Bloch-Siegert method. Results: Phantom results showed that accurate and volumetric T1 and T2 quantification was achieved by using the proposed technique. The acquisition time for three-dimensional quantitative maps with a spatial resolution of 1.6 3 1.6 3 3 mm 3 was approximately 6 minutes. For healthy participants, averaged T1 and T2 relaxation times for fibroglandular tissues at 3.0 T were 1256 msec 6 171 and 46 msec 6 7, respectively. Compared with normal breast tissues, higher T2 relaxation time (68 msec 6 13) was observed in invasive ductal carcinoma (P , .001), whereas no statistical difference was found in T1 relaxation time (1183 msec 6 256; P = .37). Conclusion: A method was developed for breast imaging by using the MR fingerprinting technique, which allows simultaneous and volumetric quantification of T1 and T2 relaxation times for breast tissues.