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Purpose: To develop a reproducible and fast method to reconstruct MR fingerprinting arterial spin labeling (MRF-ASL) perfusion maps using deep learning. Method: A fully connected neural network, denoted as DeepMARS, was trained using simulation data and added Gaussian noise. Two MRF-ASL models were used to generate the simulation data, specifically a single-compartment model with 4 unknowns parameters and a two-compartment model with 7 unknown parameters. The DeepMARS method was evaluated using MRF-ASL data from healthy subjects (N = 7) and patients with Moymoya disease (N = 3). Computation time, coefficient of determination (R 2 ), and intraclass correlation coefficient (ICC) were compared between DeepMARS and conventional dictionary matching (DM). The relationship between DeepMARS and Look-Locker PASL was evaluated by a linear mixed model. Results: Computation time per voxel was <0.5 ms for DeepMARS and >4 seconds for DM in the single-compartment model. Compared with DM, the DeepMARS showed higher R 2 and significantly improved ICC for single-compartment derived bolus arrival time (BAT) and two-compartment derived cerebral blood flow (CBF) and higher or similar R 2 /ICC for other parameters. In addition, the DeepMARS was significantly correlated with Look-Locker PASL for BAT (single-compartment) and CBF (two-compartment). Moreover, for Moyamoya patients, the location of diminished CBF and prolonged BAT shown in DeepMARS was consistent with the position of occluded arteries shown in time-of-flight MR angiography. Conclusion: Reconstruction of MRF-ASL with DeepMARS is faster and more reproducible than DM. K E Y W O R D S deep learning, DeepMARS, MRF-ASL, reconstruction, reproducibility | 1025 ZHANG et Al.

Given its advantages, PR-SENSE is a significant improvement over other methods for navigator-free high-resolution DWI. Magn Reson Med 78:172-181, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Background The pathogenesis of migraine chronification remains unclear. Functional and structural magnetic resonance imaging studies have shown impaired functional and structural alterations in the brains of patients with chronic migraine. The cerebellum and periaqueductal gray (PAG) play pivotal roles in the neural circuits of pain conduction and analgesia in migraine. However, few neurotransmitter metabolism studies of these migraine-associated regions have been performed. To explore the pathogenesis of migraine chronification, we measured gamma-aminobutyric acid (GABA) and glutamate/glutamine (Glx) levels in the dentate nucleus (DN) and PAG of patients with episodic and chronic migraine and healthy subjects. Methods Using the MEGA-PRESS sequence and a 3-Tesla magnetic resonance scanner (Signa Premier; GE Healthcare, Chicago, IL, USA), we obtained DN and PAG metabolite concentrations from patients with episodic migraine (n = 25), those with chronic migraine (n = 24), and age-matched and sex-matched healthy subjects (n = 16). Patients with chronic migraine were further divided into those with (n = 12) and without (n = 12) medication overuse headache. All scans were performed at the Beijing Tiantan Hospital, Capital Medical University. Results We found that patients with chronic migraine had significantly lower levels of GABA/water (p = 0.011) and GABA/creatine (Cr) (p = 0.026) in the DN and higher levels of Glx/water (p = 0.049) in the PAG than healthy controls. In all patients with migraine, higher GABA levels in the PAG were significantly associated with poorer sleep quality (GABA/water: r = 0.515, p = 0.017, n = 21; GABA/Cr: r = 0.522, p = 0.015, n = 21). Additionally, a lower Glx/Cr ratio in the DN may be associated with more severe migraine disability (r = -0.425, p = 0.055, n = 20), and lower GABA/water (r = -0.424, p = 0.062, n = 20) and Glx/Water (r = -0.452, p = 0.045, n = 20) may be associated with poorer sleep quality. Conclusions Neurochemical levels in the DN and PAG may provide evidence of the pathological mechanisms of migraine chronification. Correlations between migraine characteristics and neurochemical levels revealed the pathological mechanisms of the relevant characteristics.

Purpose: Effective removal of chemical-shift artifacts in echo-planar imaging (EPI) is a challenging problem especially with severe field inhomogeneity. This study aims to develop a reliable water/fat separation technique for point spread function (PSF) encoded EPI (PSF-EPI) by using its intrinsic multiple echo-shifted images. Theory and Methods: EPI with PSF encoding can achieve distortion-free imaging and can be highly accelerated using the tilted-CAIPI technique. In this study, the chemical-shift encoding existing in the intermediate images with different time shifts of PSF-EPI is used for water/fat separation, which is conducted with latest water/fat separation algorithms. The method was tested in T1-weighted, T2-weighted, and diffusion weighted imaging in healthy volunteers. Results: The ability of the proposed method to separate water/fat using intrinsic PSF-EPI signals without extra scans was demonstrated through in vivo T1-weighted, T2-weighted, and diffusion weighted imaging experiments. By exploring different imaging contrasts and regions, the results show that this PSF-EPI based method can separate water/fat and remove fat residues robustly. Conclusion: By using the intrinsic signals of PSF-EPI for water/fat separation, fat signals can be effectively suppressed in EPI even with severe field inhomogeneity.This water/fat separation method for EPI can be extended to multiple image contrasts. The distortion-free PSF-EPI technique, thus, has the potential to provide anatomical and functional images with high-fidelity and practical acquisition efficiency. K E Y W O R D Schemical-shift artifacts, distortion-free imaging, echo-planar imaging (EPI), point spread function (PSF), water/fat separation