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PurposeMR fingerprinting (MRF) can be used for quantitative estimation of physical parameters in MRI. Here, we extend the method to incorporate B1 estimation.MethodsThe acquisition is based on steady state free precession MR fingerprinting with a Cartesian trajectory. To increase the sensitivity to the B1 profile, abrupt changes in flip angle were introduced in the sequence. Slice profile and B1 effects were included in the dictionary and the results from two‐ and three‐dimensional (3D) acquisitions were compared. Acceleration was demonstrated using retrospective undersampling in the phase encode directions of 3D data exploiting redundancy between MRF frames at the edges of k‐space.ResultsWithout B1 estimation, T2 and B1 were inaccurate by more than 20%. Abrupt changes in flip angle improved B1 maps. T1 and T2 values obtained with the new MRF methods agree with classical spin echo measurements and are independent of the B1 field profile. When using view sharing reconstruction, results remained accurate (error <10%) when sampling under 10% of k‐space from the 3D data.ConclusionThe methods demonstrated here can successfully measure T1, T2, and B1. Errors due to slice profile can be substantially reduced by including its effect in the dictionary or acquiring data in 3D. Magn Reson Med 76:1127–1135, 2016. © 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

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Monoamine oxidase (MAO) inhibitors ameliorate contractile function in diabetic animals, but the mechanisms remain unknown. Equally elusive is the interplay between the cardiomyocyte alterations induced by hyperglycemia and the accompanying inflammation. Here we show that exposure of primary cardiomyocytes to high glucose and pro-inflammatory stimuli leads to MAO-dependent increase in reactive oxygen species that causes permeability transition pore opening and mitochondrial dysfunction. These events occur upstream of endoplasmic reticulum (ER) stress and are abolished by the MAO inhibitor pargyline, highlighting the role of these flavoenzymes in the ER/mitochondria cross-talk. In vivo, streptozotocin administration to mice induced oxidative changes and ER stress in the heart, events that were abolished by pargyline. Moreover, MAO inhibition prevented both mast cell degranulation and altered collagen deposition, thereby normalizing diastolic function. Taken together, these results elucidate the mechanisms underlying MAO-induced damage in diabetic cardiomyopathy and provide novel evidence for the role of MAOs in inflammation and inter-organelle communication. MAO inhibitors may be considered as a therapeutic option for diabetic complications as well as for other disorders in which mast cell degranulation is a dominant phenomenon.

Purpose To investigate a computationally efficient method for optimizing the Cramér‐Rao Lower Bound (CRLB) of quantitative sequences without using approximations or an analytical expression of the signal. Methods Automatic differentiation was applied to Bloch simulations and used to optimize several quantitative sequences without the need for approximations or an analytical expression. The results were validated with in vivo measurements and comparisons to prior art. Multi‐echo spin echo and DESPOT1 were used as benchmarks to verify the CRLB implementation. The CRLB of the Magnetic Resonance Fingerprinting (MRF) sequence, which has a complicated analytical formulation, was also optimized using automatic differentiation. Results The sequence parameters obtained for multi‐echo spin echo and DESPOT1 matched results obtained using conventional methods. In vivo, MRF scans demonstrate that the CRLB optimization obtained with automatic differentiation can improve performance in presence of white noise. For MRF, the CRLB optimization converges in 1.1 CPU hours for NitalicTR = 400 and has O(NTR) asymptotic runtime scaling for the calculation of the CRLB objective and gradient. Conclusions Automatic differentiation can be used to optimize the CRLB of quantitative sequences without using approximations or analytical expressions. For MRF, the runtime is computationally efficient and can be used to investigate confounding factors as well as MRF sequences with a greater number of repetitions.

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Novel methods for quantitative, transient-state multiparametric imaging are increasingly being demonstrated for assessment of disease and treatment efficacy. Here, we build on these by assessing the most common Non-Cartesian readout trajectories (2D/3D radials and spirals), demonstrating efficient anti-aliasing with a k- space view-sharing technique, and proposing novel methods for parameter inference with neural networks that incorporate the estimation of proton density. Our results show good agreement with gold standard and phantom references for all readout trajectories at 1.5 T and 3 T. Parameters inferred with the neural network were within 6.58% difference from the parameters inferred with a high-resolution dictionary. Concordance correlation coefficients were above 0.92 and the normalized root mean squared error ranged between 4.2 and 12.7% with respect to gold-standard phantom references for T1 and T2. In vivo acquisitions demonstrate sub-millimetric isotropic resolution in under five minutes with reconstruction and inference times < 7 min. Our 3D quantitative transient-state imaging approach could enable high-resolution multiparametric tissue quantification within clinically acceptable acquisition and reconstruction times.

Purpose To obtain a fast and robust fat‐water separation with simultaneous estimation of water T 1 , fat T 1 , and fat fraction maps. Methods We modified an MR fingerprinting (MRF) framework to use a single dictionary combination of a water and fat dictionary. A variable TE acquisition pattern with maximum TE = 4.8 ms was used to increase the fat–water separability. Radiofrequency (RF) spoiling was used to reduce the size of the dictionary by reducing T 2 sensitivity. The technique was compared both in vitro and in vivo to an MRF method that incorporated 3‐point Dixon (DIXON MRF), as well as Cartesian IDEAL with different acquisition parameters. Results The proposed dictionary‐based fat–water separation technique (DBFW MRF) successfully provided fat fraction, water, and fat T 1 , B 0 , and B 1+ maps both in vitro and in vivo. The fat fraction and water T 1 values obtained with DBFW MRF show excellent agreement with DIXON MRF as well as with the reference values obtained using a Cartesian IDEAL with a long TR (concordance correlation coefficient: 0.97/0.99 for fat fraction–water T 1 ). Whereas fat fraction values with Cartesian IDEAL were degraded in the presence of T 1 saturation, MRF methods successfully estimated and accounted for T 1 in the fat fraction estimates. Conclusion The DBFW MRF technique can successfully provide T 1 and fat fraction quantification in under 20 s per slice, intrinsically correcting T 1 biases typical of fast Dixon techniques. These features could improve the diagnostic quality and use of images in presence of fat.