).q RSNA, 2016 Purpose:To develop a magnetic resonance (MR) "fingerprinting" technique for quantitative abdominal imaging. Materials and Methods:This HIPAA-compliant study had institutional review board approval, and informed consent was obtained from all subjects. To achieve accurate quantification in the presence of marked B 0 and B 1 field inhomogeneities, the MR fingerprinting framework was extended by using a twodimensional fast imaging with steady-state free precession, or FISP, acquisition and a Bloch-Siegert B 1 mapping method. The accuracy of the proposed technique was validated by using agarose phantoms. Quantitative measurements were performed in eight asymptomatic subjects and in six patients with 20 focal liver lesions. A two-tailed Student t test was used to compare the T1 and T2 results in metastatic adenocarcinoma with those in surrounding liver parenchyma and healthy subjects. Results:Phantom experiments showed good agreement with standard methods in T1 and T2 after B 1 correction. In vivo studies demonstrated that quantitative T1, T2, and B 1 maps can be acquired within a breath hold of approximately 19 seconds. T1 and T2 measurements were compatible with those in the literature. Representative values included the following: liver, 745 msec 6 65 (standard deviation) and 31 msec 6 6; renal medulla, 1702 msec 6 205 and 60 msec 6 21; renal cortex, 1314 msec 6 77 and 47 msec 6 10; spleen, 1232 msec 6 92 and 60 msec 6 19; skeletal muscle, 1100 msec 6 59 and 44 msec 6 9; and fat, 253 msec 6 42 and 77 msec 6 16, respectively. T1 and T2 in metastatic adenocarcinoma were 1673 msec 6 331 and 43 msec 6 13, respectively, significantly different from surrounding liver parenchyma relaxation times of 840 msec 6 113 and 28 msec 6 3 (P , .0001 and P , .01) and those in hepatic parenchyma in healthy volunteers (745 msec 6 65 and 31 msec 6 6, P , .0001 and P = .021, respectively). Conclusion:A rapid technique for quantitative abdominal imaging was developed that allows simultaneous quantification of multiple tissue properties within one 19-second breath hold, with measurements comparable to those in published literature.q RSNA, 2016

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Non-Cartesian parallel imaging has played an important role in reducing data acquisition time in MRI. The use of non-Cartesian trajectories can enable more efficient coverage of k-space, which can be leveraged to reduce scan times. These trajectories can be undersampled to achieve even faster scan times, but the resulting images may contain aliasing artifacts. Just as Cartesian parallel imaging can be employed to reconstruct images from undersampled Cartesian data, non-Cartesian parallel imaging methods can mitigate aliasing artifacts by using additional spatial encoding information in the form of the non-homogeneous sensitivities of multi-coil phased arrays. This review will begin with an overview of non-Cartesian k-space trajectories and their sampling properties, followed by an in-depth discussion of several selected non-Cartesian parallel imaging algorithms. Three representative non-Cartesian parallel imaging methods will be described, including Conjugate Gradient SENSE (CG SENSE), non-Cartesian GRAPPA, and Iterative Self-Consistent Parallel Imaging Reconstruction (SPIRiT). After a discussion of these three techniques, several potential promising clinical applications of non-Cartesian parallel imaging will be covered.

In this study, the acquisition of ASL data and quantification of multiple hemodynamic parameters was explored using a Magnetic Resonance Fingerprinting (MRF) approach. A pseudo-continuous ASL labeling scheme was used with pseudo-randomized timings to acquire the MRF ASL data in a 2.5 min acquisition. A large dictionary of MRF ASL signals was generated by combining a wide range of physical and hemodynamic properties with the pseudo-random MRF ASL sequence and a two-compartment model. The acquired signals were matched to the dictionary to provide simultaneous quantification of cerebral blood flow, tissue time-to-peak, cerebral blood volume, arterial time-to-peak, B, and T A study in seven healthy volunteers resulted in the following values across the population in grey matter (mean ± standard deviation): cerebral blood flow of 69.1 ± 6.1 ml/min/100 g, arterial time-to-peak of 1.5 ± 0.1 s, tissue time-to-peak of 1.5 ± 0.1 s, T of 1634 ms, cerebral blood volume of 0.0048 ± 0.0005. The CBF measurements were compared to standard pCASL CBF estimates using a one-compartment model, and a Bland-Altman analysis showed good agreement with a minor bias. Repeatability was tested in five volunteers in the same exam session, and no statistical difference was seen. In addition to this validation, the MRF ASL acquisition's sensitivity to the physical and physiological parameters of interest was studied numerically.