Magnetic resonance imaging by synergistic diffusion-diffraction patterns

A simulation-driven supervised learning framework to estimate brain microstructure using diffusion MRI

We propose a framework to train supervised learning models on synthetic data to estimate brain microstructure parameters using diffusion magnetic resonance imaging (dMRI). Although further validation is necessary, the proposed framework aims to seamlessly incorporate realistic simulations into dMRI microstructure estimation. Synthetic data were generated from over 1,000 neuron meshes converted from digital neuronal reconstructions and linked to their neuroanatomical parameters (such as soma volume and neurite length) using an optimized diffusion MRI simulator that produces intracellular dMRI signals from the solution of the Bloch-Torrey partial differential equation. By combining random subsets of simulated neuron signals with a free diffusion compartment signal, we constructed a synthetic dataset containing dMRI signals and 40 tissue microstructure parameters of 1.45 million artificial brain voxels. To implement supervised learning models we chose multilayer perceptrons (MLPs) and trained them on a subset of the synthetic dataset to estimate some microstructure parameters, namely, the volume fractions of soma, neurites, and the free diffusion compartment, as well as the area fractions of soma and neurites. The trained MLPs perform satisfactorily on the synthetic test sets and give promising in-vivo parameter maps on the MGH Connectome Diffusion Microstructure Dataset (CDMD). Most importantly, the estimated volume fractions showed low dependence on the diffusion time, the diffusion time independence of the estimated parameters being a desired property of quantitative microstructure imaging. The synthetic dataset we generated will be valuable for the validation of models that map between the dMRI signals and microstructure parameters. The surface meshes and microstructures parameters of the aforementioned neurons have been made publicly available.

Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure

PURPOSE

Preliminary study to determine whether double pulsed field gradient (PFG) diffusion MRI is sensitive to key features of muscle microstructure related to function.

METHODS

The restricted diffusion profile of molecules in models of muscle microstructure derived from histology were systematically simulated using a numerical simulation approach. Diffusion tensor subspace imaging analysis of the diffusion signal was performed, and spherical anisotropy (SA) was calculated for each model. Linear regression was used to determine the predictive capacity of SA on the fiber area, fiber diameter, and surface area to volume ratio of the models. Additionally, a rat model of muscle hypertrophy was scanned using a single PFG and a double PFG pulse sequence, and the restricted diffusion measurements were compared with histological measurements of microstructure.

RESULTS

Excellent agreement between SA and muscle fiber area (r2  = 0.71; p < 0.0001), fiber diameter (r2  = 0.83; p < 0.0001), and surface area to volume ratio (r2  = 0.97; p < 0.0001) in simulated models was found. In a scanned rat leg, the distribution of these microstructural features measured from histology was broad and demonstrated that there is a wide variance in the microstructural features observed, similar to the SA distributions. However, the distribution of fractional anisotropy measurements in the same tissue was narrow.

CONCLUSIONS

This study demonstrates that SA-a scalar value from diffusion tensor subspace imaging analysis-is highly sensitive to muscle microstructural features predictive of function. Furthermore, these techniques and analysis tools can be translated to real experiments in skeletal muscle. The increased dynamic range of SA compared with fractional anisotropy in the same tissue suggests increased sensitivity to detecting changes in tissue microstructure.

MR cell size imaging with temporal diffusion spectroscopy

Cytological features such as cell size and intracellular morphology provide fundamental information on cell status and hence may provide specific information on changes that arise within biological tissues. Such information is usually obtained by invasive biopsy in current clinical practice, which suffers several well-known disadvantages. Recently, novel MRI methods such as IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) have been developed for direct measurements of mean cell size non-invasively. The IMPULSED protocol is based on using temporal diffusion spectroscopy (TDS) to combine measurements of water diffusion over a wide range of diffusion times to probe cellular microstructure over varying length scales. IMPULSED has been shown to provide rapid, robust, and reliable mapping of mean cell size and is suitable for clinical imaging. More recently, cell size distributions have also been derived by appropriate analyses of data acquired with IMPULSED or similar sequences, which thus provides MRI-cytometry. This review summarizes the basic principles, practical implementations, validations, and example applications of MR cell size imaging based on TDS and demonstrates how cytometric information can be used in various applications. In addition, the limitations and potential future directions of MR cytometry are identified including the diagnosis of nonalcoholic steatohepatitis of the liver and the assessment of treatment response of cancers.

JEDI: Joint Estimation Diffusion Imaging of macroscopic and microscopic tissue properties

PURPOSE

A new method for enhancing the sensitivity of diffusion MRI (dMRI) by combining the data from single (sPFG) and double (dPFG) pulsed field gradient experiments is presented.

METHODS

This method uses our JESTER framework to combine microscopic anisotropy information from dFPG experiments using a new method called diffusion tensor subspace imaging (DiTSI) to augment the macroscopic anisotropy information from sPFG data analyzed using our guided by entropy spectrum pathways method. This new method, called joint estimation diffusion imaging (JEDI), combines the sensitivity to macroscopic diffusion anisotropy of sPFG with the sensitivity to microscopic diffusion anisotropy of dPFG methods.

RESULTS

Its ability to produce significantly more detailed anisotropy maps and more complete fiber tracts than existing methods within both brain white matter (WM) and gray matter (GM) is demonstrated on normal human subjects on data collected using a novel fast, robust, and clinically feasible sPFG/dPFG acquisition.

CONCLUSIONS

The potential utility of this method is suggested by an initial demonstration of its ability to mitigate the problem of gyral bias. The capability of more completely characterizing the tissue structure and connectivity throughout the entire brain has broad implications for the utility and scope of dMRI in a wide range of research and clinical applications.

Stimulated echo double diffusion encoded imaging of closed pores: Influence and removal of unbalanced terms

Nuclear magnetic resonance (NMR) diffusion pore imaging has been proposed to study the shape of arbitrary closed pores filled with an NMR-detectable medium by use of nonclassical diffusion encoding schemes. Potential applications can be found in biomedical imaging and porous media research. When studying non-point-symmetric pores, NMR signals with nonvanishing imaginary parts arise containing the pore shape information, which is lost for classical diffusion encoding schemes. Key limitations are the required high magnetic field gradient amplitudes and T2 relaxation while approaching the diffusion long-time limit. To benefit from the slower T1 decay, we demonstrate the feasibility of diffusion pore imaging with stimulated echoes using Monte Carlo simulations and experiments with hyperpolarized xenon-129 gas in well-defined geometries and show that the necessary complex-valued signals can be acquired. Analytical derivation of the stimulated echo double diffusion encoded signal was performed to investigate the effect of the additionally arising undesired terms on the complex phase information. These terms correspond to signals arising for spin-echo sequences with unbalanced gradients. For most possible applications, the unbalanced terms can be neglected. If non-negligible, selection of the appropriate signal component using a phase cycling scheme was demonstrated experimentally. Using stimulated echoes may be a step towards application of diffusion pore imaging to larger pores with gradient amplitudes available today in preclinical systems.

Experimental determination of pore shapes using phase retrieval from q-space NMR diffraction

This paper presents an approach to solving the phase problem in nuclear magnetic resonance (NMR) diffusion pore imaging, a method that allows imaging the shape of arbitrary closed pores filled with an NMR-detectable medium for investigation of the microstructure of biological tissue and porous materials. Classical q-space imaging composed of two short diffusion-encoding gradient pulses yields, analogously to diffraction experiments, the modulus squared of the Fourier transform of the pore image which entails an inversion problem: An unambiguous reconstruction of the pore image requires both magnitude and phase. Here the phase information is recovered from the Fourier modulus by applying a phase retrieval algorithm. This allows omitting experimentally challenging phase measurements using specialized temporal gradient profiles. A combination of the hybrid input-output algorithm and the error reduction algorithm was used with dynamically adapting support (shrinkwrap extension). No a priori knowledge on the pore shape was fed to the algorithm except for a finite pore extent. The phase retrieval approach proved successful for simulated data with and without noise and was validated in phantom experiments with well-defined pores using hyperpolarized xenon gas.

1D and 2D diffusion pore imaging on a preclinical MR system using adaptive rephasing: Feasibility and pulse sequence comparison

Diffusion pore imaging (DPI) has recently been proposed as a means to acquire images of the average pore shape in an image voxel or region of interest. The highly asymmetric gradient scheme of its sequence makes it substantially demanding in terms of the hardware of the NMR system. The aim of this work is to show the feasibility of DPI on a preclinical 9.4T animal scanner. Using water-filled capillaries with an inner radius of 10μm, four different variants of the DPI sequence were compared in 1D and 2D measurements. The pulse sequences applied cover the basic implementation using one long and one temporally narrow gradient pulse, a CPMG-like variant with multiple refocusing RF pulses as well as two variants splitting up the long gradient and distributing it on either side of the refocusing pulse. Substantial differences between the methods were found in terms of signal-to-noise ratio, contrast, blurring, deviations from the expected results and sensitivity to gradient imperfections. Each of the tested sequences was found to produce characteristic gradient mismatches dependent on the absolute value, direction and sign of the applied q-value. Read gradients were applied to compensate these mismatches translating them into time shifts, which enabled 1D DPI yielding capillary radius estimations within the tolerances specified by the manufacturer. For a successful DPI application in 2D, a novel gradient amplitude adaption scheme was implemented to correct for the occurring time shifts. Using this adaption, higher conformity to the expected pore shape, reduced blurring and enhanced contrast were achieved. Images of the phantom's pore shape could be acquired with a nominal resolution of 2.2μm.

Nuclear magnetic resonance diffusion pore imaging: Experimental phase detection by double diffusion encoding

Diffusion pore imaging is an extension of diffusion-weighted nuclear magnetic resonance imaging enabling the direct measurement of the shape of arbitrarily formed, closed pores by probing diffusion restrictions using the motion of spin-bearing particles. Examples of such pores comprise cells in biological tissue or oil containing cavities in porous rocks. All pores contained in the measurement volume contribute to one reconstructed image, which reduces the problem of vanishing signal at increasing resolution present in conventional magnetic resonance imaging. It has been previously experimentally demonstrated that pore imaging using a combination of a long and a narrow magnetic field gradient pulse is feasible. In this work, an experimental verification is presented showing that pores can be imaged using short gradient pulses only. Experiments were carried out using hyperpolarized xenon gas in well-defined pores. The phase required for pore image reconstruction was retrieved from double diffusion encoded (DDE) measurements, while the magnitude could either be obtained from DDE signals or classical diffusion measurements with single encoding. The occurring image artifacts caused by restrictions of the gradient system, insufficient diffusion time, and by the phase reconstruction approach were investigated. Employing short gradient pulses only is advantageous compared to the initial long-narrow approach due to a more flexible sequence design when omitting the long gradient and due to faster convergence to the diffusion long-time limit, which may enable application to larger pores.

Q-space truncation and sampling in diffusion spectrum imaging

PURPOSE

To characterize the q-space truncation and sampling on the spin-displacement probability density function (PDF) in diffusion spectrum imaging (DSI).

METHODS

DSI data were acquired using the MGH-USC connectome scanner (Gmax  = 300 mT/m) with bmax  = 30,000 s/mm2 , 17 × 17 × 17, 15 × 15 × 15 and 11 × 11 × 11 grids in ex vivo human brains and bmax  = 10,000 s/mm2 , 11 × 11 × 11 grid in vivo. An additional in vivo scan using bmax =7,000 s/mm2 , 11 × 11 × 11 grid was performed with a derated gradient strength of 40 mT/m. PDFs and orientation distribution functions (ODFs) were reconstructed with different q-space filtering and PDF integration lengths, and from down-sampled data by factors of two and three.

RESULTS

Both ex vivo and in vivo data showed Gibbs ringing in PDFs, which becomes the main source of artifact in the subsequently reconstructed ODFs. For down-sampled data, PDFs interfere with the first replicas or their ringing, leading to obscured orientations in ODFs.

CONCLUSION

The minimum required q-space sampling density corresponds to a field-of-view approximately equal to twice the mean displacement distance (MDD) of the tissue. The 11 × 11 × 11 grid is suitable for both ex vivo and in vivo DSI experiments. To minimize the effects of Gibbs ringing, ODFs should be reconstructed from unfiltered q-space data with the integration length over the PDF constrained to around the MDD. Magn Reson Med 76:1750-1763, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Model-based estimation of microscopic anisotropy using diffusion MRI: a simulation study

Non-invasive estimation of cell size and shape is a key challenge in diffusion MRI. This article presents a model-based approach that provides independent estimates of pore size and eccentricity from diffusion MRI data. The technique uses a geometric model of finite cylinders with gamma-distributed radii to represent pores of various sizes and elongations. We consider both macroscopically isotropic substrates and substrates of semi-coherently oriented anisotropic pores and we use Monte Carlo simulations to generate synthetic data. We compare the sensitivity of single and double diffusion encoding (SDE and DDE) sequences to the size distribution and eccentricity, and further analyse different protocols of DDE sequences with parallel and/or perpendicular pairs of gradients. We show that explicitly accounting for size distribution is necessary for accurate microstructural parameter estimates, and a model that assumes a single size yields biased eccentricity values. We also find that SDE sequences support estimates, although DDE sequences with mixed parallel and perpendicular gradients enhance accuracy. In the case of macroscopically anisotropic substrates, this model-based approach can be extended to a rotationally invariant framework to provide features of pore shape (specifically eccentricity) in the presence of size distribution and orientation dispersion.

NMR-based diffusion lattice imaging

Nuclear magnetic resonance (NMR) diffusion experiments are widely employed as they yield information about structures hindering the diffusion process, e.g., about cell membranes. While it has been shown in recent articles that these experiments can be used to determine the shape of closed pores averaged over a volume of interest, it is still an open question how much information can be gained in open well-connected systems. In this theoretical work, it is shown that the full structure information of connected periodic systems is accessible. To this end, the so-called "SEquential Rephasing by Pulsed field-gradient Encoding N Time intervals" (SERPENT) sequence is used, which employs several diffusion encoding gradient pulses with different amplitudes. Two two-dimensional solid matrices that are surrounded by an NMR-visible medium are considered: a hexagonal lattice of cylinders and a rectangular lattice of isosceles triangles.

Effects of pore-size and shape distributions on diffusion pore imaging by nuclear magnetic resonance

In medical imaging and porous media research, NMR diffusion measurements are extensively used to investigate the structure of diffusion restrictions such as cell membranes. Recently, several methods have been proposed to unambiguously determine the shape of arbitrary closed pores or cells filled with an NMR-visible medium by diffusion experiments. The first approach uses a combination of a long and a short diffusion-weighting gradient pulse, while the other techniques employ short gradient pulses only. While the eventual aim of these methods is to determine pore-size and shape distributions, the focus has been so far on identical pores. Thus, the aim of this work is to investigate the ability of these different methods to resolve pore-size and orientation distributions. Simulations were performed comparing the various pore imaging techniques employing different distributions of pore size and orientation and varying timing parameters. The long-narrow gradient profile is most advantageous to investigate pore distributions, because average pore images can be directly obtained. The short-gradient methods suppress larger pores or induce a considerable blurring. Moreover, pore-shape-specific artifacts occur; for example, the central part of a distribution of cylinders may be largely underestimated. Depending on the actual pore distribution, short-gradient methods may nonetheless yield good approximations of the average pore shape. Furthermore, the application of short-gradient methods can be advantageous to differentiate whether pore-size distributions or intensity distributions, e.g., due to surface relaxation, are predominant.

Fractional motion model for characterization of anomalous diffusion from NMR signals

Measuring molecular diffusion has been used to characterize the properties of living organisms and porous materials. NMR is able to detect the diffusion process in vivo and noninvasively. The fractional motion (FM) model is appropriate to describe anomalous diffusion phenomenon in crowded environments, such as living cells. However, no FM-based NMR theory has yet been established. Here, we present a general formulation of the FM-based NMR signal under the influence of arbitrary magnetic field gradient waveforms. An explicit analytic solution of the stretched exponential decay format for NMR signals with finite-width Stejskal-Tanner bipolar pulse magnetic field gradients is presented. Signals from a numerical simulation matched well with the theoretical prediction. In vivo diffusion-weighted brain images were acquired and analyzed using the proposed theory, and the resulting parametric maps exhibit remarkable contrasts between different brain tissues.

Magnetic-resonance pore imaging of nonsymmetric microscopic pore shapes

Imaging of the microstructure of porous media such as biological tissue or porous solids is of high interest in health science and technology, engineering and material science. Magnetic resonance pore imaging (MRPI) is a recent technique based on nuclear magnetic resonance (NMR) which allows us to acquire images of the average pore shape in a given sample. Here we provide details on the experimental design, challenges, and requirements of MRPI, including its calibration procedures. Utilizing a laser-machined phantom sample, we present images of microscopic pores with a hemiequilateral triangular shape even in the presence of NMR relaxation effects at the pore walls. We therefore show that MRPI is applicable to porous samples without a priori knowledge about their pore shape and symmetry. Furthermore, we introduce "MRPI mapping," which combines MRPI with conventional magnetic resonance imaging (MRI). This enables one to resolve microscopic pore sizes and shapes spatially, thus expanding the application of MRPI to samples with heterogeneous distributions of pores.

PGSE, OGSE, and sensitivity to axon diameter in diffusion MRI: Insight from a simulation study

Purpose

To identify optimal pulsed gradient spin‐echo (PGSE) and oscillating gradient spin‐echo (OGSE) sequence settings for maximizing sensitivity to axon diameter in idealized and practical conditions.

Methods

Simulations on a simple two‐compartment white matter model (with nonpermeable cylinders) are used to investigate a wide space of clinically plausible PGSE and OGSE sequence parameters with trapezoidal diffusion gradient waveforms. Signal sensitivity is measured as a derivative of the signal with respect to axon diameter. Models of parallel and dispersed fibers are investigated separately to represent idealized and practical conditions.

Results

Simulations show that, for the simple case of gradients perfectly perpendicular to straight parallel fibers, PGSE always gives maximum sensitivity. However, in real‐world scenarios where fibers have unknown and dispersed orientation, low‐frequency OGSE provides higher sensitivity. Maximum sensitivity results show that on current clinical scanners (G_max = 60 mT/m, signal to noise ratio (SNR) = 20) axon diameters below 6 µm are indistinguishable from zero. Scanners with stronger gradient systems such as the Massachusetts General Hospital (MGH) Connectom scanner (G_max = 300 mT/m) can extend this sensitivity limit down to 2–3 µm, probing a much greater proportion of the underlying axon diameter distribution.

Conclusion

Low‐frequency OGSE provides additional sensitivity to PGSE in practical situations. OGSE is particularly advantageous for systems with high performance gradients. Magn Reson Med 75:688–700, 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 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Magnetic resonance signal moment determination using the Earth's magnetic field

We demonstrate a method to manipulate magnetic resonance data such that the moments of the signal spatial distribution are readily accessible. Usually, magnetic resonance imaging relies on data acquired in so-called k-space which is subsequently Fourier transformed to render an image. Here, via analysis of the complex signal in the vicinity of the centre of k-space we are able to access the first three moments of the signal spatial distribution, ultimately in multiple directions. This is demonstrated for biofouling of a reverse osmosis (RO) membrane module, rendering unique information and an early warning of the onset of fouling. The analysis is particularly applicable for the use of mobile magnetic resonance spectrometers; here we demonstrate it using an Earth's magnetic field system.

Noninvasive quantification of solid tumor microstructure using VERDICT MRI

There is a need for biomarkers that are useful for noninvasive imaging of tumor pathophysiology and drug efficacy. Through its use of endogenous water, diffusion-weighted MRI (DW-MRI) can be used to probe local tissue architecture and structure. However, most DW-MRI studies of cancer tissues have relied on simplistic mathematical models, such as apparent diffusion coefficient (ADC) or intravoxel incoherent motion (IVIM) models, which produce equivocal results on the relation of the model parameter estimate with the underlying tissue microstructure. Here, we present a novel technique called VERDICT (Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors) to quantify and map histologic features of tumors in vivo. VERDICT couples DW-MRI to a mathematical model of tumor tissue to access features such as cell size, vascular volume fraction, intra- and extracellular volume fractions, and pseudo-diffusivity associated with blood flow. To illustrate VERDICT, we used two tumor xenograft models of colorectal cancer with different cellular and vascular phenotypes. Our experiments visualized known differences in the tissue microstructure of each model and the significant decrease in cell volume resulting from administration of the cytotoxic drug gemcitabine, reflecting the apoptotic volume decrease. In contrast, the standard ADC and IVIM models failed to detect either of these differences. Our results illustrate the superior features of VERDICT for cancer imaging, establishing it as a noninvasive method to monitor and stratify treatment responses.

Measuring small compartment dimensions by probing diffusion dynamics via Non-uniform Oscillating-Gradient Spin-Echo (NOGSE) NMR

Noninvasive measurements of microstructure in materials, cells, and in biological tissues, constitute a unique capability of gradient-assisted NMR. Diffusion-diffraction MR approaches pioneered by Callaghan demonstrated this ability; Oscillating-Gradient Spin-Echo (OGSE) methodologies tackle the demanding gradient amplitudes required for observing diffraction patterns by utilizing constant-frequency oscillating gradient pairs that probe the diffusion spectrum, D(ω). Here we present a new class of diffusion MR experiments, termed Non-uniform Oscillating-Gradient Spin-Echo (NOGSE), which dynamically probe multiple frequencies of the diffusion spectral density at once, thus affording direct microstructural information on the compartment's dimension. The NOGSE methodology applies N constant-amplitude gradient oscillations; N-1 of these oscillations are spaced by a characteristic time x, followed by a single gradient oscillation characterized by a time y, such that the diffusion dynamics is probed while keeping (N-1)x+y≡TNOGSE constant. These constant-time, fixed-gradient-amplitude, multi-frequency attributes render NOGSE particularly useful for probing small compartment dimensions with relatively weak gradients - alleviating difficulties associated with probing D(ω) frequency-by-frequency or with varying relaxation weightings, as in other diffusion-monitoring experiments. Analytical descriptions of the NOGSE signal are given, and the sequence's ability to extract small compartment sizes with a sensitivity towards length to the sixth power, is demonstrated using a microstructural phantom. Excellent agreement between theory and experiments was evidenced even upon applying weak gradient amplitudes. An MR imaging version of NOGSE was also implemented in ex vivo pig spinal cords and mouse brains, affording maps based on compartment sizes. The effects of size distributions on NOGSE are also briefly analyzed.

Coherent dynamical recoupling of diffusion-driven decoherence in magnetic resonance

During recent years, dynamical decoupling (DD) has gained relevance as a tool for manipulating and interrogating quantum systems. This is particularly relevant for spins involved in nuclear magnetic resonance (NMR), where DD sequences can be used to prolong quantum coherences, or to selectively couple or decouple the effects imposed by random environmental fluctuations. In this Letter, we show that these concepts can be exploited to selectively recouple diffusion processes in restricted spaces. The ensuing method provides a novel tool to measure restriction lengths in confined systems such as capillaries, pores or cells. The principles of this method for selectively recoupling diffusion-driven decoherence, its standing within the context of diffusion NMR, extensions to the characterization of other kinds of quantum fluctuations, and corroborating experiments, are presented.

Diffusion pore imaging by hyperpolarized xenon-129 nuclear magnetic resonance

While NMR diffusion measurements are widely used to derive parameters indirectly related to the microstructure of biological tissues and porous media, direct imaging of pore shapes would be of high interest. Here we demonstrate experimentally that complexly shaped closed pores can be imaged by diffusion acquisitions. Collecting the signal from the whole sample eliminates the problem of vanishing signal at increasing resolution of conventional NMR imaging. This approach may be used to noninvasively obtain structural information inaccessible so far such as pore or cell shapes, cell density, or axon integrity.

Shemesh, Westin, and Cohen reply

A Reply to the comment by Valerij G. Kiselev and Dmitry S. Novikov.

Comment on "Magnetic resonance imaging by synergistic diffusion-diffraction patterns"

A Comment on the Letter by N. Shemesh, C.-F. Westin, and Y. Cohen, Phys. Rev. Lett. 108, 058103 (2012).. The authors of the Letter offer a Reply.

Diffusive diffraction phenomenon observed by PGSE NMR technique in a sugar-based low-molecular-mass gel

The paper presents the diffusive diffraction phenomenon observed by the single-pulse-gradient spin-echo (s-PGSE) NMR technique in a real porous material: a gel composed of low-molecular-mass gelator methyl-4,6-O-(p-nitrobenzylidene)-α-D-glucopyranoside and toluene. Thanks to this phenomenon, we can probe the true microstructure (not xerogel) in which the toluene diffuses. To analyze the measured diffusion-diffraction pattern, we employed a composite bicompartmental model that superimposes restricted diffusion in small cavities of the gel matrix within the bundles of crossing fibers, with free diffusion in large and unconfined compartments between the bundles of crossing fibers. For restricted diffusion a pore-hopping formalism was applied. The observation of the diffraction pattern and its analysis leads to the conclusion that the pores, in the slow diffusing compartment of studied gel are ordered, at least locally, and relatively monodisperse with a size of 64 μm. Moreover, the restricting walls formed by the crossing fibers are perpendicular to the direction of the diffusion gradient.

NMR-based diffusion pore imaging

Nuclear magnetic resonance (NMR) diffusion experiments offer a unique opportunity to study boundaries restricting the diffusion process. In a recent Letter [Phys. Rev. Lett. 107, 048102 (2011)], we introduced the idea and concept that such diffusion experiments can be interpreted as NMR imaging experiments. Consequently, images of closed pores, in which the spins diffuse, can be acquired. In the work presented here, an in-depth description of the diffusion pore imaging technique is provided. Image artifacts due to gradient profiles of finite duration, field inhomogeneities, and surface relaxation are considered. Gradients of finite duration lead to image blurring and edge enhancement artifacts. Field inhomogeneities have benign effects on diffusion pore images, and surface relaxation can lead to a shrinkage and shift of the pore image. The relation between boundary structure and the imaginary part of the diffusion weighted signal is analyzed, and it is shown that information on pore coherence can be obtained without the need to measure the phase of the diffusion weighted signal. Moreover, it is shown that quite arbitrary gradient profiles can be used for diffusion pore imaging. The matrices required for numerical calculations are stated and provided as supplemental material.