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Purpose: To address the systematic bias in whole-brain dual flip angle (DFA) T 1 -mapping at 7T by optimizing the flip angle pair and carefully selecting radiofrequency (RF) pulse shape and duration., Theory and Methods: Spoiled gradient echoes can be used to estimate whole-brain maps of T 1 . This can be accomplished by using only two acquisitions with different flip angles, that is, a DFA-based approach. Although DFA-based T 1 -mapping is seemingly straightforward to implement, it is sensitive to bias caused by incomplete spoiling and incidental magnetization transfer effects. Further bias is introduced by the increased B 0 and B 1 + inhomogeneities at 7T. Experiments were performed to determine the optimal flip angle pair and appropriate RF pulse shape and duration. Obtained T 1 estimates were validated using inversion recovery prepared echo planar imaging and compared to literature values. A multi-echo readout was used to increase signal-to-noise ratio, enabling quantification of R 2 ∗ and susceptibility, χ., Results: Incomplete spoiling was observed above a local flip angle of approximately 20°. An asymmetric gauss-filtered sinc pulse with a constant duration of 700 μs showed a sufficiently flat frequency response profile to avoid incomplete excitation in areas with high B 0 offsets. A pulse duration of 700 μs minimized effects from incidental magnetization transfer., Conclusion: When performing DFA-based T 1 -mapping one should (a) limit the higher flip angle to avoid incomplete spoiling, (b) use a RF pulse shape insensitive to B 0 inhomogeneities and (c) apply a constant RF pulse duration, balanced to minimize incidental magnetization transfer., (© 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

Microstructure imaging techniques based on tensor-valued diffusion encoding have gained popularity within the MRI research community. Unlike conventional diffusion encoding-applied along a single direction in each shot-tensor-valued encoding employs diffusion encoding along multiple directions within a single preparation of the signal. The benefit is that such encoding may probe tissue features that are not accessible by conventional encoding. For example, diffusional variance decomposition (DIVIDE) takes advantage of tensor-valued encoding to probe microscopic diffusion anisotropy independent of orientation coherence. The drawback is that tensor-valued encoding generally requires gradient waveforms that are more demanding on hardware; it has therefore been used primarily in MRI systems with relatively high performance. The purpose of this work was to explore tensor-valued diffusion encoding on clinical MRI systems with varying performance to test its technical feasibility within the context of DIVIDE. We performed whole-brain imaging with linear and spherical b-tensor encoding at field strengths between 1.5 and 7 T, and at maximal gradient amplitudes between 45 and 80 mT/m. Asymmetric gradient waveforms were optimized numerically to yield b-values up to 2 ms/μm2. Technical feasibility was assessed in terms of the repeatability, SNR, and quality of DIVIDE parameter maps. Variable system performance resulted in echo times between 83 to 115 ms and total acquisition times of 6 to 9 minutes when using 80 signal samples and resolution 2×2×4 mm3. As expected, the repeatability, signal-to-noise ratio and parameter map quality depended on hardware performance. We conclude that tensor-valued encoding is feasible for a wide range of MRI systems-even at 1.5 T with maximal gradient waveform amplitudes of 33 mT/m-and baseline experimental design and quality parameters for all included configurations. This demonstrates that tissue features, beyond those accessible by conventional diffusion encoding, can be explored on a wide range of MRI systems., Competing Interests: MN declares research support from, and ownership interests in, Colloidal Resource and it subsidiary Random Walk Imaging AB. FSz is a former employee of Random Walk Imaging AB. Remaining authors declare no conflict of interest.

Purpose: Filter exchange imaging (FEXI) is sensitive to the rate of diffusional water exchange, which depends, eg, on the cell membrane permeability. The aim was to optimize and analyze the ability of FEXI to infer differences in the apparent exchange rate (AXR) in the brain between two populations., Methods: A FEXI protocol was optimized for minimal measurement variance in the AXR. The AXR variance was investigated by test-retest acquisitions in six brain regions in 18 healthy volunteers. Preoperative FEXI data and postoperative microphotos were obtained in six meningiomas and five astrocytomas., Results: Protocol optimization reduced the coefficient of variation of AXR by approximately 40%. Test-retest AXR values were heterogeneous across normal brain regions, from 0.3 ± 0.2 s -1 in the corpus callosum to 1.8 ± 0.3 s -1 in the frontal white matter. According to analysis of statistical power, in all brain regions except one, group differences of 0.3-0.5 s -1 in the AXR can be inferred using 5 to 10 subjects per group. An AXR difference of this magnitude was observed between meningiomas (0.6 ± 0.1 s -1 ) and astrocytomas (1.0 ± 0.3 s -1 )., Conclusions: With the optimized protocol, FEXI has the ability to infer relevant differences in the AXR between two populations for small group sizes. Magn Reson Med 77:1104-1114, 2017. © 2016 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., (© 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

We present the first in vivo application of the filter-exchange imaging protocol for diffusion MRI. The protocol allows noninvasive mapping of the rate of water exchange between microenvironments with different self-diffusivities, such as the intracellular and extracellular spaces in tissue. Since diffusional water exchange across the cell membrane is a fundamental process in human physiology and pathophysiology, clinically feasible and noninvasive imaging of the water exchange rate would offer new means to diagnose disease and monitor treatment response in conditions such as cancer and edema. The in vivo use of filter-exchange imaging was demonstrated by studying the brain of five healthy volunteers and one intracranial tumor (meningioma). Apparent exchange rates in white matter range from 0.8±0.08 s(-1) in the internal capsule, to 1.6±0.11 s(-1) for frontal white matter, indicating that low values are associated with high myelination. Solid tumor displayed values of up to 2.9±0.8 s(-1). In white matter, the apparent exchange rate values suggest intra-axonal exchange times in the order of seconds, confirming the slow exchange assumption in the analysis of diffusion MRI data. We propose that filter-exchange imaging could be used clinically to map the water exchange rate in pathologies. Filter-exchange imaging may also be valuable for evaluating novel therapies targeting the function of aquaporins., (Copyright © 2012 Wiley Periodicals, Inc.)

Water exchange through the cell membranes is an important feature of cells and tissues. The rate of exchange is determined by factors such as membrane lipid composition and organization, as well as the type and activity of aquaporins. A method for noninvasively estimating the rate of water exchange would be useful for characterizing pathological conditions, e.g., tumors, multiple sclerosis, and ischemic stroke, expected to be associated with a change of the membrane barrier properties. This study describes the filter exchange imaging method for determining the rate of water exchange between sites having different apparent diffusion coefficients. The method is based on the filter-exchange pulsed gradient spin-echo NMR spectroscopy experiment, which is here modified to be compatible with the constraints of clinical MR scanners. The data is analyzed using a model-free approach yielding maps of the apparent exchange rate, here being introduced in analogy with the concept of the apparent diffusion coefficient. Proof-of-principle experiments are performed on microimaging and whole-body clinical scanners using yeast suspension phantoms. The limitations and appropriate experimental conditions are examined. The results demonstrate that filter exchange imaging is a fast and reliable method for characterizing exchange, and that it has the potential to become a powerful diagnostic tool., (Copyright © 2011 Wiley-Liss, Inc.)

The accuracy of q-space measurements was evaluated at a 3.0-T clinical magnetic resonance imaging (MRI) scanner, as compared with a 4.7-T nuclear magnetic resonance (NMR) spectrometer. Measurements were performed using a stimulated-echo pulse-sequence on n-decane as well as on polyethylene glycol (PEG) mixed with different concentrations of water, in order to obtain bi-exponential signal decay curves. The diffusion coefficients as well as the modelled diffusional kurtosis K(fit) were obtained from the signal decay curve, while the full-width at half-maximum (FWHM) and the diffusional kurtosis K were obtained from the displacement distribution. Simulations of restricted diffusion, under conditions similar to those obtainable with a clinical MRI scanner, were carried out assuming various degrees of violation of the short gradient pulse (SGP) condition and of the long diffusion time limit. The results indicated that an MRI system can not be used for quantification of structural sizes less than about 10 microm by means of FWHM since the parameter underestimates the confinements due to violation of the SGP condition. However, FWHM can still be used as an important contrast parameter. The obtained kurtosis values were lower than expected from theory and the results showed that care must be taken when interpreting a kurtosis estimate deviating from zero.

The Rician distribution of noise in magnitude magnetic resonance (MR) images is particularly problematic in low signal-to-noise ratio (SNR) regions. The Rician noise distribution causes a nonzero minimum signal in the image, which is often referred to as the rectified noise floor. True low signal is likely to be concealed in the noise, and quantification is severely hampered in low-SNR regions. To address this problem we performed noise reduction (or denoising) by Wiener-like filtering in the wavelet domain. The filtering was applied to complex MRI data before construction of the magnitude image. The noise-reduction algorithm was applied to simulated and experimental diffusion-weighted (DW) images. Denoising considerably reduced the signal standard deviation (SD, by up to 87% in simulated images) and decreased the background noise floor (by approximately a factor of 6 in simulated and experimental images)., ((c) 2006 Wiley-Liss, Inc.)