A new sequence for single-shot diffusion-weighted NMR spectroscopy by the trace of the diffusion tensor

Single-shot diffusion trace spectroscopic imaging using radial echo planar trajectories

PURPOSE

Demonstrate the feasibility and evaluate the performance of single-shot diffusion trace-weighted radial echo planar spectroscopic imaging (Trace DW-REPSI) for quantifying the trace ADC in phantom and in vivo using a 3T clinical scanner.

THEORY AND METHODS

Trace DW-REPSI datasets were acquired in 10 phantom and 10 healthy volunteers, with a maximum b-value of 1601 s/mm2 and diffusion time of 10.75 ms. The self-navigation properties of radial acquisitions were used for corrections of shot-to-shot phase and frequency shift fluctuations of the raw data. In vivo trace ADCs of total NAA (tNAA), total creatine (tCr), and total choline (tCho) extrapolated to pure gray and white matter fractions were compared, as well as trace ADCs estimated in voxels within white or gray matter-dominant regions.

RESULTS

Trace ADCs in phantom show excellent agreement with reported values, and in vivo ADCs agree well with the expected differences between gray and white matter. For tNAA, tCr, and tCho, the trace ADCs extrapolated to pure gray and white matter ranged from 0.18-0.27 and 0.26-0.38 μm2/ms, respectively. In sets of gray and white matter-dominant voxels, the values ranged from 0.21 to 0.27 and 0.24 to 0.31 μm2/ms, respectively. The overestimated trace ADCs from this sequence can be attributed to the short diffusion time.

CONCLUSION

This study presents the first demonstration of the single-shot diffusion trace-weighted spectroscopic imaging sequence using radial echo planar trajectories. The Trace DW-REPSI sequence could provide an estimate of the trace ADC in a much shorter scan time compared to conventional approaches that require three separate measurements.

Single-shot diffusion trace-weighted MR spectroscopy: Comparison with unipolar and bipolar diffusion-weighted point-resolved spectroscopy

This study demonstrates the feasibility and performance of the point-resolved spectroscopy (PRESS)-based, single-shot diffusion trace-weighted sequence in quantifying the trace apparent diffusion coefficient (ADC) in phantom and in vivo using a 3-T MRI/MRS scanner. The single-shot diffusion trace-weighted PRESS sequence was implemented and compared with conventional diffusion-weighted (DW)-PRESS variants using bipolar and unipolar diffusion-sensitizing gradients. Nine phantom datasets were acquired using each sequence, and seven volunteers were scanned in three different brain regions to determine the range and variability of trace ADC values, and to allow a comparison of trace ADCs among the sequences. This sequence results in a comparatively stable range of trace ADC values that are statistically significantly higher than those produced from unipolar and bipolar DW-PRESS sequences. Only total n-acetylaspartate, total creatine, and total choline were reliably estimated in all sequences with Cramér-Rao lower bounds of, at most, 20%. The larger trace ADCs from the single-shot sequences are probably attributable to the shorter diffusion time relative to the other sequences. Overall, this study presents the first demonstration of the single-shot diffusion trace-weighted sequence in a clinical scanner at 3 T. The results show excellent agreement of phantom trace ADCs computed with all sequences, and in vivo ADCs agree well with the expected differences between gray and white matter. The diffusion trace-weighted sequence could provide an estimate of the trace ADC in a shorter scan time (by nearly a factor of 3) compared with conventional DW-PRESS approaches that require three separate orthogonal directions.

Apparent diffusion coefficients of 31P metabolites in the human calf muscle at 7 T

PURPOSE

In this study, we aimed to measure the apparent diffusion coefficients (ADCs) of major phosphorous metabolites in the human calf muscle at 7 T with a diffusion-weighted (DW)-STEAM sequence.

METHODS

A DW-STEAM sequence with bipolar gradients was implemented at 7 T, and DW MR spectra were acquired in three orthogonal directions in the human calf muscle of six healthy volunteers (TE/TM/TR = 15 ms/750 ms/5 s) at three b-values (0, 800, and 1200 s/mm²). Frequency and phase alignments were applied prior to spectral averaging. Averaged DW MR spectra were analyzed with LCModel, and ADCs of ³¹P metabolites were estimated.

RESULTS

Four metabolites (phosphocreatine (PCr), adenosine triphosphate (ATP), inorganic phosphate (Pi) and glycerol phosphorylcholine (GPC)) were quantified at all b-values with mean CRLBs below 10%. The ADC values of PCr, ATP, Pi, and GPC were (0.24 ± 0.02, 0.15 ± 0.04, 0.43 ± 0.14, 0.40 ± 0.09) × 10^-3 mm²/s, respectively.

CONCLUSION

The ADCs of four ³¹P metabolites were successfully measured in the human calf muscle at 7 T, among which those of ATP, Pi and GPC were reported for the first time in humans. This study paves the way to investigate ³¹P metabolite diffusion properties in health and disease on the clinical MR scanner.

Cross-term-compensated gradient waveform design for tensor-valued diffusion MRI

Diffusion MRI uses magnetic field gradients to sensitize the signal to the random motion of spins. In addition to the prescribed gradient waveforms, background field gradients contribute to the diffusion weighting and thereby cause an error in the measured signal and consequent parameterization. The most prominent contribution to the error comes from so-called 'cross-terms.' In this work we present a novel gradient waveform design that enables diffusion encoding that cancels such cross-terms and yields a more accurate measurement. This is achieved by numerical optimization that maximizes encoding efficiency with a simultaneous constraint on the 'cross-term sensitivity' (c = 0). We found that the optimized cross-term-compensated waveforms were superior to previous cross-term-compensated designs for a wide range of waveform types that yield linear, planar, and spherical b-tensor encoding. The efficacy of the proposed design was also demonstrated in practical experiments using a clinical MRI system. The sensitivity to cross-terms was evaluated in a water phantom with a folded surface which provoked strong internal field gradients. In every comparison, the cross-term-compensated waveforms were robust to the effects of background gradients, whereas conventional designs were not. We also propose a method to measure background gradients from diffusion-weighted data, and show that cross-term-compensated waveforms produce parameters that are markedly less dependent on the background compared to non-compensated designs. Finally, we also used simulations to show that the proposed cross-term compensation was robust to background gradients in the interval 0 to 3 mT/m, whereas non-compensated designs were impacted in terms of a severe signal and parameter bias. In conclusion, we have proposed and demonstrated a waveform design that yields efficient cross-term compensation and facilitates accurate diffusion MRI in the presence of static background gradients regardless of their amplitude and direction. The optimization framework is compatible with arbitrary spin-echo sequence timing and RF events, b-tensor shapes, suppression of concomitant gradient effects and motion encoding, and is shared in open source.

Magic DIAMOND: Multi-fascicle diffusion compartment imaging with tensor distribution modeling and tensor-valued diffusion encoding

Diffusion tensor imaging provides increased sensitivity to microstructural tissue changes compared to conventional anatomical imaging but also presents limited specificity. To tackle this problem, the DIAMOND model subdivides the voxel content into diffusion compartments and draws from diffusion-weighted data to estimate compartmental non-central matrix-variate Gamma distributions of diffusion tensors. It models each sub-voxel fascicle separately, resolving crossing white-matter pathways and allowing for a fascicle-element (fixel) based analysis of microstructural features. Alternatively, specific features of the intra-voxel diffusion tensor distribution can be selectively measured using tensor-valued diffusion-weighted acquisition schemes. However, the impact of such schemes on estimating brain microstructural features has only been studied in a handful of parametric single-fascicle models. In this work, we derive a general Laplace transform for the non-central matrix-variate Gamma distribution, which enables the extension of DIAMOND to tensor-valued encoded data. We then evaluate this "Magic DIAMOND" model in silico and in vivo on various combinations of tensor-valued encoded data. Assessing uncertainty on parameter estimation via stratified bootstrap, we investigate both voxel-based and fixel-based metrics by carrying out multi-peak tractography. We demonstrate using in silico evaluations that tensor-valued diffusion encoding significantly improves Magic DIAMOND's accuracy. Most importantly, we show in vivo that our estimated metrics can be robustly mapped along tracks across regions of fiber crossing, which opens new perspectives for tractometry and microstructure mapping along specific white-matter tracts.

Gradient waveform design for tensor-valued encoding in diffusion MRI

Diffusion encoding along multiple spatial directions per signal acquisition can be described in terms of a b-tensor. The benefit of tensor-valued diffusion encoding is that it unlocks the 'shape of the b-tensor' as a new encoding dimension. By modulating the b-tensor shape, we can control the sensitivity to microscopic diffusion anisotropy which can be used as a contrast mechanism; a feature that is inaccessible by conventional diffusion encoding. Since imaging methods based on tensor-valued diffusion encoding are finding an increasing number of applications we are prompted to highlight the challenge of designing the optimal gradient waveforms for any given application. In this review, we first establish the basic design objectives in creating field gradient waveforms for tensor-valued diffusion MRI. We also survey additional design considerations related to limitations imposed by hardware and physiology, potential confounding effects that cannot be captured by the b-tensor, and artifacts related to the diffusion encoding waveform. Throughout, we discuss the expected compromises and tradeoffs with an aim to establish a more complete understanding of gradient waveform design and its impact on accurate measurements and interpretations of data.

Motion-compensated b-tensor encoding for in vivo cardiac diffusion-weighted imaging

Motion is a major confound in diffusion-weighted imaging (DWI) in the body, and it is a common cause of image artefacts. The effects are particularly severe in cardiac applications, due to the nonrigid cyclical deformation of the myocardium. Spin echo-based DWI commonly employs gradient moment-nulling techniques to desensitise the acquisition to velocity and acceleration, ie, nulling gradient moments up to the 2nd order (M2-nulled). However, current M2-nulled DWI scans are limited to encode diffusion along a single direction at a time. We propose a method for designing b-tensors of arbitrary shapes, including planar, spherical, prolate and oblate tensors, while nulling gradient moments up to the 2nd order and beyond. The design strategy comprises initialising the diffusion encoding gradients in two encoding blocks about the refocusing pulse, followed by appropriate scaling and rotation, which further enables nulling undesired effects of concomitant gradients. Proof-of-concept assessment of in vivo mean diffusivity (MD) was performed using linear and spherical tensor encoding (LTE and STE, respectively) in the hearts of five healthy volunteers. The results of the M2-nulled STE showed that (a) the sequence was robust to cardiac motion, and (b) MD was higher than that acquired using standard M2-nulled LTE, where diffusion-weighting was applied in three orthogonal directions, which may be attributed to the presence of restricted diffusion and microscopic diffusion anisotropy. Provided adequate signal-to-noise ratio, STE could significantly shorten estimation of MD compared with the conventional LTE approach. Importantly, our theoretical analysis and the proposed gradient waveform design may be useful in microstructure imaging beyond diffusion tensor imaging where the effects of motion must be suppressed.

Probing Surface-to-Volume Ratio of an Anisotropic Medium by Diffusion NMR with General Gradient Encoding

Since the seminal paper by Mitra et al., diffusion MR has been widely used in order to estimate surface-to-volume ratios. In this paper, we generalize Mitra's formula for arbitrary diffusion encoding waveforms, including recently developed q-space trajectory encoding sequences. We show that the surface-to-volume ratio can be significantly misestimated using the original Mitra's formula without taking into account the applied gradient profile. In order to obtain more accurate estimation in anisotropic samples, we propose an efficient and robust optimization algorithm to design diffusion gradient waveforms with prescribed features. Our results are supported by Monte Carlo simulations.

Apparent diffusion coefficients of the five major metabolites measured in the human brain in vivo at 3T

PURPOSE

To measure the apparent diffusion coefficients (ADC) of five main metabolites in the human brain at 3T with PRESS and STEAM, avoiding measurement biases because of cross-terms. Cross-terms arise from interactions between slice-selection and spoiler gradients in the localized spectroscopy sequence and the diffusion gradients.

METHODS

Diffusion-weighted spectra were acquired from the prefrontal cortex in five healthy subjects using STEAM (echo time [TE]/mixing time [TM]/pulse repetition time [TR] = 21.22/105/3000 ms, b-values = 0 and 3172 s/mm2 ) and PRESS (TE/TR = 54.2/3000 ms, b-values = 0 and 2204 s/mm2 ). Diffusion weighting was applied using bipolar gradients in three orthogonal directions. Post-processed spectra were analyzed with LCModel, and the trace/3 ADC values were calculated.

RESULTS

Comparable trace/3 ADC values (0.14-0.18 µm2 /ms) were obtained for five main metabolites with both methods. These metabolites were quantified with Cramér-Rao lower bounds below 15%.

CONCLUSION

The ADC values of the five main metabolites were successfully measured in the human brain at 3T with eliminated directional dependence. Both STEAM and PRESS can be used to probe the diffusivity of metabolites in normal brain and various pathologies on the clinical scanner with slightly higher precision achieved with STEAM for glutamate and myo-inositol. Magn Reson Med 79:2896-2901, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Liquid crystal phantom for validation of microscopic diffusion anisotropy measurements on clinical MRI systems

PURPOSE

To develop a phantom for validating MRI pulse sequences and data processing methods to quantify microscopic diffusion anisotropy in the human brain.

METHODS

Using a liquid crystal consisting of water, detergent, and hydrocarbon, we designed a 0.5-L spherical phantom showing the theoretically highest possible degree of microscopic anisotropy. Data were acquired on the Connectome scanner using echo-planar imaging signal readout and diffusion encoding with axisymmetric b-tensors of varying magnitude, anisotropy, and orientation. The mean diffusivity, fractional anisotropy (FA), and microscopic FA (µFA) parameters were estimated.

RESULTS

The phantom was observed to have values of mean diffusivity similar to brain tissue, and relaxation times compatible with echo-planar imaging echo times on the order of 100 ms. The estimated values of µFA were at the theoretical maximum of 1.0, whereas the values of FA spanned the interval from 0.0 to 0.8 as a result of varying orientational order of the anisotropic domains within each voxel.

CONCLUSIONS

The proposed phantom can be manufactured by mixing three widely available chemicals in volumes comparable to a human head. The acquired data are in excellent agreement with theoretical predictions, showing that the phantom is ideal for validating methods for measuring microscopic diffusion anisotropy on clinical MRI systems. Magn Reson Med 79:1817-1828, 2018. © 2017 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 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Distinguishing neuronal from astrocytic subcellular microstructures using in vivo Double Diffusion Encoded 1H MRS at 21.1 T

Measuring cellular microstructures non-invasively and achieving specificity towards a cell-type population within an interrogated in vivo tissue, remains an outstanding challenge in brain research. Magnetic Resonance Spectroscopy (MRS) provides an opportunity to achieve cellular specificity via the spectral resolution of metabolites such as N-Acetylaspartate (NAA) and myo-Inositol (mI), which are considered neuronal and astrocytic markers, respectively. Yet the information typically obtained with MRS describes metabolic concentrations, diffusion coefficients or relaxation rates rather than microstructures. Understanding how these metabolites are compartmentalized is a challenging but important goal, which so far has been mainly addressed using diffusion models. Here, we present direct in vivo evidence for the confinement of NAA and mI within sub-cellular components, namely, the randomly oriented process of neurons and astrocytes, respectively. Our approach applied Relaxation Enhanced MRS at ultrahigh (21.1 T) field, and used its high ¹H sensitivity to measure restricted diffusion correlations for NAA and mI using a Double Diffusion Encoding (DDE) filter. While very low macroscopic anisotropy was revealed by spatially localized Diffusion Tensor Spectroscopy, DDE displayed characteristic amplitude modulations reporting on confinements in otherwise randomly oriented anisotropic microstructures for both metabolites. This implies that for the chosen set of parameters, the DDE measurements had a biased sensitivity towards NAA and mI sited in the more confined environments of neurites and astrocytic branches, than in the cell somata. These measurements thus provide intrinsic diffusivities and compartment diameters, and revealed subcellular neuronal and astrocytic morphologies in normal in vivo rat brains. The relevance of these measurements towards human applications—which could in turn help understand CNS plasticity as well as diagnose brain diseases—is discussed.

In vivo diffusion MRS investigation of non-water molecules in biological tissues

Diffusion MRS of non-water molecules offers great potential in directly revealing various tissue microstructures and physiology at both cellular and subcellular levels. In brain, ¹ H diffusion MRS has been demonstrated as a new tool for probing normal tissue microstructures and their pathological changes. In skeletal muscle, ¹ H diffusion MRS could characterize slow and restricted intramyocellular lipid diffusion, providing a sensitive marker for metabolic alterations, while ³¹ P diffusion MRS can measure ATP and PCr diffusion, which may reflect the capacity of cellular energy transport, complementing the information from frequently used ³¹ P MRS in muscle. In intervertebral disk, ¹ H diffusion MRS can directly monitor extracellular matrix integrity by quantifying the mobility of macromolecules such as proteoglycans and collagens. In tumor tissue, ¹³ C diffusion MRS could probe intracellular glycolytic metabolism, while ¹ H diffusion MRS may separate the spectrally overlapped lactate and lipid resonances. In this review, recent diffusion MRS studies of these biologically relevant non-water molecules under normal and diseased conditions will be presented. Technical considerations for diffusion MRS experiments will be discussed. With advances in MRI hardware and diffusion methodology, diffusion MRS of non-water molecules is expected to provide increasingly valuable and biologically specific information on tissue microstructures and physiology, complementing the traditional diffusion MRI of small and ubiquitous water molecules. Copyright © 2016 John Wiley & Sons, Ltd.

Multidimensional diffusion MRI

Principles from multidimensional NMR spectroscopy, and in particular solid-state NMR, have recently been transferred to the field of diffusion MRI, offering non-invasive characterization of heterogeneous anisotropic materials, such as the human brain, at an unprecedented level of detail. Here we revisit the basic physics of solid-state NMR and diffusion MRI to pinpoint the origin of the somewhat unexpected analogy between the two fields, and provide an overview of current diffusion MRI acquisition protocols and data analysis methods to quantify the composition of heterogeneous materials in terms of diffusion tensor distributions with size, shape, and orientation dimensions. While the most advanced methods allow estimation of the complete multidimensional distributions, simpler methods focus on various projections onto lower-dimensional spaces as well as determination of means and variances rather than actual distributions. Even the less advanced methods provide simple and intuitive scalar parameters that are directly related to microstructural features that can be observed in optical microscopy images, e.g. average cell eccentricity, variance of cell density, and orientational order - properties that are inextricably entangled in conventional diffusion MRI. Key to disentangling all these microstructural features is MRI signal acquisition combining isotropic and directional dimensions, just as in the field of multidimensional solid-state NMR from which most of the ideas for the new methods are derived.

Comparative analysis of isotropic diffusion weighted imaging sequences

Visualisation of living tissue structure and function is a challenging problem of modern imaging techniques. Diffusion MRI allows one to probe in vivo structures on a micrometer scale. However, conventional diffusion measurements are time-consuming procedures, because they require several measurements with different gradient directions. Considerable time savings are therefore possible by measurement schemes that generate an isotropic diffusion weighting in a single shot. Multiple approaches for generating isotropic diffusion weighting are known and have become very popular as useful tools in clinical research. Thus, there is a strong need for a comprehensive comparison of different isotropic weighting approaches. In the present work we introduce two new sequences based on simple (co)sine modulations and compare their performance to established q-space magic-angle spinning sequences and conventional DTI, using a diffusion phantom assembled from microcapillaries and in vivo experiments at 7T. The advantages and disadvantages of all compared schemes are demonstrated and discussed.

Modeling diffusion of intracellular metabolites in the mouse brain up to very high diffusion-weighting: Diffusion in long fibers (almost) accounts for non-monoexponential attenuation

PURPOSE

To investigate how intracellular metabolites diffusion measured in vivo up to very high q/b in the mouse brain can be explained in terms of simple geometries.

METHODS

10 mice were scanned using our new STE-LASER sequence, at 11.7 Tesla (T), up to qmax = 1 μm-1 at diffusion time td = 63.2 ms, corresponding to bmax = 60 ms/µm². We model cell fibers as randomly oriented cylinders, with radius a and intracellular diffusivity Dintracyl, and fit experimental data as a function of q to estimate Dintracyl and a.

RESULTS

Randomly oriented cylinders account well for measured attenuation, giving fiber radii and Dintracyl in the expected ranges (0.5-1.5 µm and 0.30-0.45 µm2/ms, respectively). The only exception is N-acetyl-aspartate (NAA) (extracted a∼0), which we show to be compatible with a small fraction of the NAA pool being confined in highly restricted compartments (with short T2).

CONCLUSION

The non-monoexponential signal attenuation of intracellular metabolites in the mouse brain can be described by diffusion in long and thin cylinders, yielding realistic Dintra and fiber diameters. However, this simple model may require small "corrections" for NAA, in the form of a small fraction of the NAA signal originating from a highly restricted compartment. Magn Reson Med, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Q-space trajectory imaging for multidimensional diffusion MRI of the human brain

This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture.

Metabolite diffusion up to very high b in the mouse brain in vivo: Revisiting the potential correlation between relaxation and diffusion properties

PURPOSE

To assess the potential correlation between metabolites diffusion and relaxation in the mouse brain, which is of importance for interpreting and modeling metabolite diffusion based on pure geometry, irrespective of relaxation properties (multicompartmental relaxation or surface relaxivity).

METHODS

A new diffusion-weighted magnetic resonance spectroscopy sequence is introduced, dubbed "STE-LASER," which presents several nice properties, in particular the absence of cross-terms with selection gradients and a very clean localization. Metabolite diffusion is then measured in a large voxel in the mouse brain at 11.7 Tesla using a cryoprobe, resulting in excellent signal-to-noise ratio, up to very high b-values under different echo time, mixing time, and diffusion time combinations.

RESULTS

Our results suggest that the correlation between relaxation and diffusion properties is extremely small or even nonexistent for metabolites in the mouse brain.

CONCLUSION

The present work strongly supports the interpretation and modeling of metabolite diffusion primarily based on geometry, irrespective of relaxation properties, at least under current experimental conditions. Magn Reson Med 77:1390-1398, 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.

Reproducibility and optimization of in vivo human diffusion-weighted MRS of the corpus callosum at 3 T and 7 T

Diffusion-weighted MRS (DWS) of brain metabolites enables the study of cell-specific alterations in tissue microstructure by probing the diffusion of intracellular metabolites. In particular, the diffusion properties of neuronal N-acetylaspartate (NAA), typically co-measured with N-acetylaspartyl glutamate (NAAG) (NAA + NAAG = tNAA), have been shown to be sensitive to intraneuronal/axonal damage in pathologies such as stroke and multiple sclerosis. Lacking, so far, are empirical assessments of the reproducibility of DWS measures across time and subjects, as well as a systematic investigation of the optimal acquisition parameters for DWS experiments, both of which are sorely needed for clinical applications of the method. In this study, we acquired comprehensive single-volume DWS datasets of the human corpus callosum at 3 T and 7 T. We investigated the inter- and intra-subject variability of empirical and modeled diffusion properties of tNAA [D(avg) (tNAA) and D(model) (tNAA), respectively]. Subsequently, we used a jackknife-like resampling approach to explore the variance of these properties in partial data subsets reflecting different total scan durations. The coefficients of variation (C(V)) and repeatability coefficients (C(R)) for D(avg) (tNAA) and D(model) (tNAA) were calculated for both 3 T and 7 T, with overall lower variability in the 7 T results. Although this work is limited to the estimation of the diffusion properties in the corpus callosum, we show that a careful choice of diffusion-weighting conditions at both field strengths allows the accurate measurement of tNAA diffusion properties in clinically relevant experimental time. Based on the resampling results, we suggest optimized acquisition schemes of 13-min duration at 3T and 10-min duration at 7 T, whilst retaining low variability (C(V) ≈ 8%) for the tNAA diffusion measures. Power calculations for the estimation of D(model )(tNAA) and D(avg) (tNAA) based on the suggested schemes show that less than 21 subjects per group are sufficient for the detection of a 10% effect between two groups in case-control studies.

Measurement of distinctive features of cortical spreading depolarizations with different MRI contrasts

Growing clinical evidence suggests critical involvement of spreading depolarizations (SDs) in the pathophysiology of neurological disorders such as migraine and stroke. MRI provides powerful tools to detect and assess co-occurring cerebral hemodynamic and cellular changes during SDs. This study reports the feasibility and advantages of two MRI scans, based on balanced steady-state free precession (b-SSFP) and diffusion-weighted multi-spin-echo (DT2), heretofore unexplored for monitoring SDs. These were compared with gradient-echo MRI. SDs were induced by KCl application in rat brain. Known for high SNR, the T2- and T1-based b-SSFP contrast was hypothesized to provide higher spatiotemporal specificity than T2*-based gradient-echo scanning. DT2 scanning was designed to provide simultaneous T2 and apparent diffusion coefficient (ADC) measurements, thus enabling combined quantitative assessment of hemodynamic and cellular changes during SDs. Procedures were developed to automate identification of SD-induced responses in all the scans. These responses were analyzed to determine detection sensitivity and temporal characteristics of signals from each scanning method. Cluster analysis was performed to elucidate unique temporal patterns for each contrast. All scans allowed detection of SD-induced responses. b-SSFP scans showed significantly larger relative intensity changes, narrower peak widths and greater spatial specificity compared with gradient-echo MRI. SD-induced effects on ADC, calculated from DT2 scans, showed the most pronounced signal changes, displaying about 20% decrease, as against 10-15% signal increases observed with b-SSFP and gradient-echo scanning. Cluster analysis revealed additional temporal sub-patterns, such as an initial dip on gradient-echo scans and temporally shifted T2 and proton density changes in DT2 data. To summarize, b-SSFP and DT2 scanning provide distinct information on SDs compared with gradient-echo MRI. DT2 scanning, with its potential to simultaneously provide cellular and hemodynamic information, can offer unique information on the inter-relationship between these processes in pathologic brain, which may improve monitoring of spreading depolarizations in (pre)clinical settings.

Influence of polymer end-chemistry on the morphology of perfluorohexane polymeric microcapsules intended as ultrasound contrast agents

Ultrasound contrast agents (UCAs) composed of a liquid perfluorocarbon (PFC) core surrounded by a polymer shell have shown promising echogenicity as well as stability. In a strategy to optimize the ultrasound properties of these systems, encapsulating a liquid PFC with a low boiling point such as perfluorohexane (PFH) was suggested. The ultimate aim of these systems would be to induce phase-transition of the liquid PFH into gas by acoustic droplet vaporization (ADV) to further increase the UCA acoustic response. Microcapsules with a perfluorohexane core have been developed by an emulsion-evaporation process, using three biodegradable polymers: PLGA and PLA with acid (PLA-COOH) and ester (PLA-COOR) terminations. Despite their similar properties, these polymers were found to strongly influence the final microcapsule morphology. While PLGA was able to form nice core-shell microcapsules, the use of PLA-COOH led to decentered microcapsules and big "eye" morphologies, and PLA-COOR induced the formation of "acorn" morphologies. To shed light on morphologies disparities, polymer interfacial behavior was studied at the dichloromethane-water and the PFH-dichloromethane interfaces. One can conclude that the core-shell structure is the result of a significant adsorption of the polymer at the dichloromethane-water interface together with a good stability of the PFH droplet within the emulsion globule. Previous work has shown that the capsule's thickness-to-radius (T/R) ratio can be controlled easily by varying the polymer to perfluorocarbon proportions. This versatility was confirmed for PFH capsules with PLA-COOH and PLGA shells. Finally, the encapsulation efficiency of PFH was assessed by relating the T/R ratio to the volume fraction of PFH and by (19)F NMR spectroscopy.

Measurement tensors in diffusion MRI: generalizing the concept of diffusion encoding

In traditional diffusion MRI, short pulsed field gradients (PFG) are used for the diffusion encoding. The standard Stejskal-Tanner sequence uses one single pair of such gradients, known as single-PFG (sPFG). In this work we describe how trajectories in q-space can be used for diffusion encoding. We discuss how such encoding enables the extension of the well-known scalar b-value to a tensor-valued entity we call the diffusion measurement tensor. The new measurements contain information about higher order diffusion propagator covariances not present in sPFG. As an example analysis, we use this new information to estimate a Gaussian distribution over diffusion tensors in each voxel, described by its mean (a diffusion tensor) and its covariance (a 4th order tensor).

Isotropic diffusion weighting in PGSE NMR by magic-angle spinning of the q-vector

When PGSE NMR is applied to water in microheterogeneous materials such as liquid crystals, foodstuffs, porous rocks, and biological tissues, the signal attenuation is often multi-exponential, indicating the presence of pores having a range of sizes or anisotropic domains having a spread of orientations. Here we modify the standard PGSE experiment by introducing low-amplitude harmonically modulated gradients, which effectively make the q-vector perform magic-angle spinning (MAS) about an axis fixed in the laboratory frame. With this new technique, denoted q-MAS PGSE, the signal attenuation depends on the isotropic average of the local diffusion tensor. The capability of q-MAS PGSE to distinguish between pore size and domain orientation dispersion is demonstrated by experiments on a yeast cell suspension and a polydomain anisotropic liquid crystal. In the latter case, the broad distribution of apparent diffusivities observed with PGSE is narrowed to its isotropic average with q-MAS PGSE in a manner that is analogous to the narrowing of chemical shift anisotropy powder patterns using magic-angle sample spinning in solid-state NMR. The new q-MAS PGSE technique could be useful for resolving size/orientation ambiguities in the interpretation of PGSE data from, e.g., water confined within the axons of human brain tissue.