Complex geometric models of diffusion and relaxation in healthy and damaged white matter

Exploring white matter dynamics and morphology through interactive numerical phantoms: the White Matter Generator

Brain white matter is a dynamic environment that continuously adapts and reorganizes in response to stimuli and pathological changes. Glial cells, especially, play a key role in tissue repair, inflammation modulation, and neural recovery. The movements of glial cells and changes in their concentrations can influence the surrounding axon morphology. We introduce the White Matter Generator (WMG) tool to enable the study of how axon morphology is influenced through such dynamical processes, and how this, in turn, influences the diffusion-weighted MRI signal. This is made possible by allowing interactive changes to the configuration of the phantom generation throughout the optimization process. The phantoms can consist of myelinated axons, unmyelinated axons, and cell clusters, separated by extra-cellular space. Due to morphological flexibility and computational advantages during the optimization, the tool uses ellipsoids as building blocks for all structures; chains of ellipsoids for axons, and individual ellipsoids for cell clusters. After optimization, the ellipsoid representation can be converted to a mesh representation which can be employed in Monte-Carlo diffusion simulations. This offers an effective method for evaluating tissue microstructure models for diffusion-weighted MRI in controlled bio-mimicking white matter environments. Hence, the WMG offers valuable insights into white matter's adaptive nature and implications for diffusion-weighted MRI microstructure models, and thereby holds the potential to advance clinical diagnosis, treatment, and rehabilitation strategies for various neurological disorders and injuries.

Impact of the acquisition protocol on the sensitivity to demyelination and axonal loss of clinically feasible DWI techniques: a simulation study

OBJECTIVE

To evaluate: (a) the specific effect that the demyelination and axonal loss have on the DW signal, and (b) the impact of the sequence parameters on the sensitivity to damage of two clinically feasible DWI techniques, i.e. DKI and NODDI.

METHODS

We performed a Monte Carlo simulation of water diffusion inside a novel synthetic model of white matter in the presence of axonal loss and demyelination, with three compartments with permeable boundaries between them. We compared DKI and NODDI in their ability to detect and assess the damage, using several acquisition protocols. We used the F test statistic as an index of the sensitivity for each DWI parameter to axonal loss and demyelination, respectively.

RESULTS

DKI parameters significantly changed with increasing axonal loss, but, in most cases, not with demyelination; all the NODDI parameters showed sensitivity to both the damage processes (at p < 0.01). However, the acquisition protocol strongly affected the sensitivity to damage of both the DKI and NODDI parameters and, especially for NODDI, the parameter absolute values also.

DISCUSSION

This work is expected to impact future choices for investigating white matter microstructure in focusing on specific stages of the disease, and for selecting the appropriate experimental framework to obtain optimal data quality given the purpose of the experiment.

Five-year longitudinal changes in quantitative spinal cord MRI in multiple sclerosis

BACKGROUND

The spinal cord (SC) is highly relevant to disability in multiple sclerosis (MS), but few studies have evaluated longitudinal changes in quantitative spinal cord magnetic resonance imaging (SC-MRI).

OBJECTIVES

The aim of this study was to characterize the relationships between 5-year changes in SC-MRI with disability in MS.

METHODS

In total, 75 MS patients underwent 3 T SC-MRI and clinical assessment (expanded disability status scale (EDSS) and MS functional composite (MSFC)) at baseline, 2 and 5 years. SC-cross-sectional area (CSA) and diffusion-tensor indices (fractional anisotropy (FA), mean, perpendicular, parallel diffusivity (MD, λ⊥, λ||) and magnetization transfer ratio (MTR)) were extracted at C3-C4. Mixed-effects regression incorporating subject-specific slopes assessed longitudinal change in SC-MRI measures.

RESULTS

SC-CSA and MTR decreased (p = 0.009, p = 0.03) over 5.1 years. There were moderate correlations between 2- and 5-year subject-specific slopes of SC-MRI indices and follow-up EDSS scores (Pearson's r with FA = -0.23 (p < 0.001); MD = 0.31 (p < 0.001); λ⊥ = 0.34 (p < 0.001); λ|| = -0.12 (p = 0.05), MTR = -0.37 (p < 0.001); SC-CSA = -0.47 (p < 0.001) at 5 years); MSFC showed similar trends. The 2- and 5-year subject-specific slopes were robustly correlated (r = 0.93-0.97 for FA, λ⊥, SC-CSA and MTR, all ps < 0.001).

CONCLUSION

In MS, certain quantitative SC-MRI indices change over 5 years, reflecting ongoing tissue changes. Subject-specific trajectories of SC-MRI index change at 2 and 5 years are strongly correlated and highly relevant to follow-up disability. These findings suggest that individual dynamics of change should be accounted for when interpreting longitudinal SC-MRI measures and that measuring short-term change is predictive of long-term clinical disability.

ConFiG: Contextual Fibre Growth to generate realistic axonal packing for diffusion MRI simulation

This paper presents Contextual Fibre Growth (ConFiG), an approach to generate white matter numerical phantoms by mimicking natural fibre genesis. ConFiG grows fibres one-by-one, following simple rules motivated by real axonal guidance mechanisms. These simple rules enable ConFiG to generate phantoms with tuneable microstructural features by growing fibres while attempting to meet morphological targets such as user-specified density and orientation distribution. We compare ConFiG to the state-of-the-art approach based on packing fibres together by generating phantoms in a range of fibre configurations including crossing fibre bundles and orientation dispersion. Results demonstrate that ConFiG produces phantoms with up to 20% higher densities than the state-of-the-art, particularly in complex configurations with crossing fibres. We additionally show that the microstructural morphology of ConFiG phantoms is comparable to real tissue, producing diameter and orientation distributions close to electron microscopy estimates from real tissue as well as capturing complex fibre cross sections. Signals simulated from ConFiG phantoms match real diffusion MRI data well, showing that ConFiG phantoms can be used to generate realistic diffusion MRI data. This demonstrates the feasibility of ConFiG to generate realistic synthetic diffusion MRI data for developing and validating microstructure modelling approaches.

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We present ConFiG, a biologically motivated numerical phantom generator for white matter.

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ConFiG produces phantoms with state-of-the-art density and realistic microstructure.

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Diffusion MRI simulations in ConFiG phantoms are comparable to real dMRI signals.

Diffusion MRI microstructural models in the cervical spinal cord - Application, normative values, and correlations with histological analysis

Multi-compartment tissue modeling using diffusion magnetic resonance imaging has proven valuable in the brain, offering novel indices sensitive to the tissue microstructural environment in vivo on clinical MRI scanners. However, application, characterization, and validation of these models in the spinal cord remain relatively under-studied. In this study, we apply a diffusion "signal" model (diffusion tensor imaging, DTI) and two commonly implemented "microstructural" models (neurite orientation dispersion and density imaging, NODDI; spherical mean technique, SMT) in the human cervical spinal cord of twenty-one healthy controls. We first provide normative values of DTI, SMT, and NODDI indices in a number of white matter ascending and descending pathways, as well as various gray matter regions. We then aim to validate the sensitivity and specificity of these diffusion-derived contrasts by relating these measures to indices of the tissue microenvironment provided by a histological template. We find that DTI indices are sensitive to a number of microstructural features, but lack specificity. The microstructural models also show sensitivity to a number of microstructure features; however, they do not capture the specific microstructural features explicitly modelled. Although often regarded as a simple extension of the brain in the central nervous system, it may be necessary to re-envision, or specifically adapt, diffusion microstructural models for application to the human spinal cord with clinically feasible acquisitions - specifically, adjusting, adapting, and re-validating the modeling as it relates to both theory (i.e. relevant biology, assumptions, and signal regimes) and parameter estimation (for example challenges of acquisition, artifacts, and processing).

Challenges in diffusion MRI tractography - Lessons learned from international benchmark competitions

Diffusion MRI (dMRI) fiber tractography has become a pillar of the neuroimaging community due to its ability to noninvasively map the structural connectivity of the brain. Despite widespread use in clinical and research domains, these methods suffer from several potential drawbacks or limitations. Thus, validating the accuracy and reproducibility of techniques is critical for sound scientific conclusions and effective clinical outcomes. Towards this end, a number of international benchmark competitions, or "challenges", has been organized by the diffusion MRI community in order to investigate the reliability of the tractography process by providing a platform to compare algorithms and results in a fair manner, and evaluate common and emerging algorithms in an effort to advance the state of the field. In this paper, we summarize the lessons from a decade of challenges in tractography, and give perspective on the past, present, and future "challenges" that the field of diffusion tractography faces.

Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook

Phantoms, both numerical (software) and physical (hardware), can serve as a gold standard for the validation of MRI methods probing the brain microstructure. This review aims to provide guidelines on how to build, implement, or choose the right phantom for a particular application, along with an overview of the current state-of-the-art of phantoms dedicated to study brain microstructure with MRI. For physical phantoms, we discuss the essential requirements and relevant characteristics of both the (NMR visible) liquid and (NMR invisible) phantom materials that induce relevant microstructural features detectable via MRI, based on diffusion, intra-voxel incoherent motion, magnetization transfer or magnetic susceptibility weighted contrast. In particular, for diffusion MRI, many useful phantoms have been proposed, ranging from simple liquids to advanced biomimetic phantoms consisting of hollow or plain microfibers and capillaries. For numerical phantoms, the focus is on Monte Carlo simulations of random walk, for which the basic principles, along with useful criteria to check and potential pitfalls are reviewed, in addition to a literature overview highlighting recent advances. While many phantoms exist already, the current review aims to stimulate further research in the field and to address remaining needs.

Design and validation of diffusion MRI models of white matter

Diffusion MRI is arguably the method of choice for characterizing white matter microstructure in vivo. Over the typical duration of diffusion encoding, the displacement of water molecules is conveniently on a length scale similar to that of the underlying cellular structures. Moreover, water molecules in white matter are largely compartmentalized which enables biologically-inspired compartmental diffusion models to characterize and quantify the true biological microstructure. A plethora of white matter models have been proposed. However, overparameterization and mathematical fitting complications encourage the introduction of simplifying assumptions that vary between different approaches. These choices impact the quantitative estimation of model parameters with potential detriments to their biological accuracy and promised specificity. First, we review biophysical white matter models in use and recapitulate their underlying assumptions and realms of applicability. Second, we present up-to-date efforts to validate parameters estimated from biophysical models. Simulations and dedicated phantoms are useful in assessing the performance of models when the ground truth is known. However, the biggest challenge remains the validation of the "biological accuracy" of estimated parameters. Complementary techniques such as microscopy of fixed tissue specimens have facilitated direct comparisons of estimates of white matter fiber orientation and densities. However, validation of compartmental diffusivities remains challenging, and complementary MRI-based techniques such as alternative diffusion encodings, compartment-specific contrast agents and metabolites have been used to validate diffusion models. Finally, white matter injury and disease pose additional challenges to modeling, which are also discussed. This review aims to provide an overview of the current state of models and their validation and to stimulate further research in the field to solve the remaining open questions and converge towards consensus.

Longitudinal MR spectroscopy of neurodegeneration in multiple sclerosis with diffusion of the intra-axonal constituent N-acetylaspartate

Multiple sclerosis (MS) is a pathologically complex CNS disease: inflammation, demyelination, and neuroaxonal degeneration occur concurrently and may depend on one another. Current therapies are aimed at the immune-mediated, inflammatory destruction of myelin, whereas axonal degeneration is ongoing and not specifically targeted. Diffusion-weighted magnetic resonance spectroscopy can measure the diffusivity of metabolites in vivo, such as the axonal/neuronal constituent N-acetylaspartate, allowing compartment-specific assessment of disease-related changes. Previously, we found significantly lower N-acetylaspartate diffusivity in people with MS compared to healthy controls (Wood et al., 2012) suggesting that this technique can measure axonal degeneration and could be useful in developing neuroprotective agents. In this longitudinal study, we found that N-acetylaspartate diffusivity decreased by 8.3% (p < 0.05) over 6 months in participants who were experiencing clinical or MRI evidence of inflammatory activity (n = 13), whereas there was no significant change in N-acetylaspartate diffusivity in the context of clinical and radiological stability (n = 6). As N-acetylaspartate diffusivity measurements are thought to more specifically reflect the intra-axonal space, these data suggest that N-acetylaspartate diffusivity can report on axonal health on the background of multiple pathological processes in MS, both cross-sectionally and longitudinally.

Subject-specific regional measures of water diffusion are associated with impairment in chronic spinal cord injury

PURPOSE

We aimed to identify non-invasive imaging parameters that can serve as biomarkers for the integrity of the spinal cord, which is paramount to neurological function. Diffusion tensor imaging (DTI) indices are sensitive to axonal and myelin damage, and have strong potential to serve as such biomarkers. However, averaging DTI indices over large regions of interest (ROIs), a common approach to analyzing the images of injured spinal cord, leads to loss of subject-specific information. We investigated if DTI-tractography-driven, subject-specific demarcation approach can yield measures that are more specific to impairment.

METHODS

In 18 individuals with chronic spinal cord injury (SCI), subject-specific demarcation of the injury region was performed using DTI tractography, which yielded three regions relative to injury (RRI; regions superior to, at, and below injury epicenter). DTI indices averaged over each RRI were correlated with measures of residual motor and sensory function, obtained using the International Standard of Neurological Classification for Spinal Cord Injury (ISNCSCI).

RESULTS

Total ISNCSCI score (ISNCSCI-tot; sum of ISNCSCI motor and sensory scores) was significantly (p < 0.05) correlated with fractional anisotropy and axial and radial diffusivities. ISNCSCI-tot showed strongest correlation with indices measured from the region inferior to the injury epicenter (IRRI), the degree of which exceeded that of those measured from the entire cervical cord-suggesting contribution from Wallerian degeneration.

CONCLUSION

DTI tractography-driven, subject-specific injury demarcation approach provided measures that were more specific to impairment. Notably, DTI indices obtained from the IRRI region showed the highest specificity to impairment, demonstrating their strong potential as biomarkers for the SCI severity.

Diffusion microscopist simulator: a general Monte Carlo simulation system for diffusion magnetic resonance imaging

This article describes the development and application of an integrated, generalized, and efficient Monte Carlo simulation system for diffusion magnetic resonance imaging (dMRI), named Diffusion Microscopist Simulator (DMS). DMS comprises a random walk Monte Carlo simulator and an MR image synthesizer. The former has the capacity to perform large-scale simulations of Brownian dynamics in the virtual environments of neural tissues at various levels of complexity, and the latter is flexible enough to synthesize dMRI datasets from a variety of simulated MRI pulse sequences. The aims of DMS are to give insights into the link between the fundamental diffusion process in biological tissues and the features observed in dMRI, as well as to provide appropriate ground-truth information for the development, optimization, and validation of dMRI acquisition schemes for different applications. The validity, efficiency, and potential applications of DMS are evaluated through four benchmark experiments, including the simulated dMRI of white matter fibers, the multiple scattering diffusion imaging, the biophysical modeling of polar cell membranes, and the high angular resolution diffusion imaging and fiber tractography of complex fiber configurations. We expect that this novel software tool would be substantially advantageous to clarify the interrelationship between dMRI and the microscopic characteristics of brain tissues, and to advance the biophysical modeling and the dMRI methodologies.

Extensive neurological recovery from a complete spinal cord injury: a case report and hypothesis on the role of cortical plasticity

Neurological recovery in patients with severe spinal cord injury (SCI) is extremely rare. We have identified a patient with chronic cervical traumatic SCI, who suffered a complete loss of motor and sensory function below the injury for 6 weeks after the injury, but experienced a progressive neurological recovery that continued for 17 years. The extent of the patient's recovery from the severe trauma-induced paralysis is rare and remarkable. A detailed study of this patient using diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), and resting state fMRI (rs-fMRI) revealed structural and functional changes in the central nervous system that may be associated with the neurological recovery. Sixty-two percent cervical cord white matter atrophy was observed. DTI-derived quantities, more sensitive to axons, demonstrated focal changes, while MTI-derived quantity, more sensitive to myelin, showed a diffuse change. No significant cortical structural changes were observed, while rs-fMRI revealed increased brain functional connectivity between sensorimotor and visual networks. The study provides comprehensive description of the structural and functional changes in the patient using advanced MR imaging technique. This multimodal MR imaging study also shows the potential of rs-fMRI to measure the extent of cortical plasticity.

Complete fourier direct magnetic resonance imaging (CFD-MRI) for diffusion MRI

The foundation for an accurate and unifying Fourier-based theory of diffusion weighted magnetic resonance imaging (DW-MRI) is constructed by carefully re-examining the first principles of DW-MRI signal formation and deriving its mathematical model from scratch. The derivations are specifically obtained for DW-MRI signal by including all of its elements (e.g., imaging gradients) using complex values. Particle methods are utilized in contrast to conventional partial differential equations approach. The signal is shown to be the Fourier transform of the joint distribution of number of the magnetic moments (at a given location at the initial time) and magnetic moment displacement integrals. In effect, the k-space is augmented by three more dimensions, corresponding to the frequency variables dual to displacement integral vectors. The joint distribution function is recovered by applying the Fourier transform to the complete high-dimensional data set. In the process, to obtain a physically meaningful real valued distribution function, phase corrections are applied for the re-establishment of Hermitian symmetry in the signal. Consequently, the method is fully unconstrained and directly presents the distribution of displacement integrals without any assumptions such as symmetry or Markovian property. The joint distribution function is visualized with isosurfaces, which describe the displacement integrals, overlaid on the distribution map of the number of magnetic moments with low mobility. The model provides an accurate description of the molecular motion measurements via DW-MRI. The improvement of the characterization of tissue microstructure leads to a better localization, detection and assessment of biological properties such as white matter integrity. The results are demonstrated on the experimental data obtained from an ex vivo baboon brain.

Langevin dynamics modeling of the water diffusion tensor in partially aligned collagen networks

In this work, a Langevin dynamics model of the diffusion of water in articular cartilage was developed. Numerical simulations of the translational dynamics of water molecules and their interaction with collagen fibers were used to study the quantitative relationship between the organization of the collagen fiber network and the diffusion tensor of water in model cartilage. Langevin dynamics was used to simulate water diffusion in both ordered and partially disordered cartilage models. In addition, an analytical approach was developed to estimate the diffusion tensor for a network comprising a given distribution of fiber orientations. The key findings are that (1) an approximately linear relationship was observed between collagen volume fraction and the fractional anisotropy of the diffusion tensor in fiber networks of a given degree of alignment, (2) for any given fiber volume fraction, fractional anisotropy follows a fiber alignment dependency similar to the square of the second Legendre polynomial of cos(θ), with the minimum anisotropy occurring at approximately the magic angle (θ(MA)), and (3) a decrease in the principal eigenvalue and an increase in the transverse eigenvalues is observed as the fiber orientation angle θ progresses from 0° to 90°. The corresponding diffusion ellipsoids are prolate for θ<θ(MA), spherical for θ≈θ(MA), and oblate for θ>θ(MA). Expansion of the model to include discrimination between the combined effects of alignment disorder and collagen fiber volume fraction on the diffusion tensor is discussed.

Multiparametric MRI correlates of sensorimotor function in the spinal cord in multiple sclerosis

BACKGROUND

Spinal cord (SC) pathology is a major contributor to clinical disability in multiple sclerosis (MS). Conventional magnetic resonance imaging (MRI), specifically SC-MRI lesion load measures that include lesion count and volume, demonstrate only a modest relationship with the clinical status of MS patients. Although SC cross-sectional area (CSA) correlates better with clinical dysfunction than MRI lesion count, SC atrophy likely signifies irreversible tissue loss. Using quantitative MRI indices sensitive to early and late microstructural changes in the spinal cord, we searched for the presence of better correlations between MRI measures and clinical status in MS.

OBJECTIVES

We investigated whether diffusion-tensor imaging indices and the magnetization-transfer ratio (MTR) were better associated with the clinical status of MS patients than conventional SC-MRI measures.

METHODS

A total of 129 MS patients underwent 3-tesla cervical SC-MRI and quantitative sensorimotor function testing, using the Vibratron-II and dynamometer. Regions-of-interest circumscribed the SC on axial slices between C3-C4. We calculated SC-CSA, fractional anisotropy (FA), mean diffusivity (MD), perpendicular diffusivity (λ perpendicular), parallel diffusivity (λ||) and MTR. We used multivariable linear regression to determine if there were any associations between MRI indices and clinical measures of dysfunction.

RESULTS

All MRI indices were significantly different in subjects with MS versus healthy controls, and between the progressive versus relapsing MS subtypes, with the exception of λ||. In multivariable regression models that were adjusted for age, sex, brain parenchymal fraction, and SC-CSA, the MRI indices independently explained variability in hip flexion strength (p-values: MD, λ perpendicular, λ|| < 0.001; FA = 0.07), vibration sensation threshold (p-values: FA = 0.04; MTR = 0.05; λ perpendicular = 0.06), and Expanded Disability Status Scale scores (p-values: FA = 0.003; MD = 0.03; λ perpendicular = 0.005; MTR = 0.02).

CONCLUSIONS

In a large, heterogeneous MS sample, quantitative SC-MRI indices demonstrated independent associations with system-specific and global clinical dysfunction. Our findings suggest that the indices studied may provide important information about microstructural SC changes and the substrates of limb disability in MS. The identified structure-function relationships underpin the potential utility of these measures in assessments of therapeutic efficacy.

Investigating axonal damage in multiple sclerosis by diffusion tensor spectroscopy

Sensitive and specific in vivo measures of axonal damage, an important determinant of clinical status in multiple sclerosis (MS), might greatly benefit prognostication and therapy assessment. Diffusion tensor spectroscopy (DTS) combines features of diffusion tensor imaging and magnetic resonance spectroscopy, allowing measurement of the diffusion properties of intracellular, cell-type-specific metabolites. As such, it may be sensitive to disruption of tissue microstructure within neurons. In this cross-sectional pilot study, diffusion of the neuronal metabolite N-acetylaspartate (NAA) was measured in the human normal-appearing corpus callosum on a 7 tesla MRI scanner, comparing 15 MS patients and 14 healthy controls. We found that NAA parallel diffusivity is lower in MS (p = 0.030) and inversely correlated with both water parallel diffusivity (p = 0.020) and clinical severity (p = 0.015). Interpreted in the context of previous experiments, our findings provide preliminary evidence that DTS can distinguish axonopathy from other processes such as inflammation, edema, demyelination, and gliosis. By detecting reduced diffusion of NAA parallel to axons in white matter, DTS may thus be capable of distinguishing axonal disruption in MS in the setting of increased parallel diffusion of water, which is commonly observed in MS but pathologically nonspecific.

q-space and conventional diffusion imaging of axon and myelin damage in the rat spinal cord after axotomy

Parallel and perpendicular diffusion properties of water in the rat spinal cord were investigated 3 and 30 days after dorsal root axotomy, a specific insult resulting in early axonal degeneration followed by later myelin damage in the dorsal column white matter. Results from q-space analysis (i.e., the diffusion probability density function) obtained with strong diffusion weighting were compared to conventional anisotropy and diffusivity measurements at low b-values, as well as to histology for axon and myelin damage. q-Space contrasts included the height (return to zero displacement probability), full width at half maximum, root mean square displacement, and kurtosis excess of the probability density function, which quantifies the deviation from gaussian diffusion. Following axotomy, a significant increase in perpendicular diffusion (with decreased kurtosis excess) and decrease in parallel diffusion (with increased kurtosis excess) were found in lesions relative to uninjured white matter. Notably, a significant change in abnormal parallel diffusion was detected from 3 to 30 days with full width at half maximum, but not with conventional diffusivity. Also, directional full width at half maximum and root mean square displacement measurements exhibited different sensitivities to white matter damage. When compared to histology, the increase in perpendicular diffusion was not specific to demyelination, whereas combined reduced parallel diffusion and increased perpendicular diffusion was associated with axon damage.

Neurite beading is sufficient to decrease the apparent diffusion coefficient after ischemic stroke

Diffusion-weighted MRI (DWI) is a sensitive and reliable marker of cerebral ischemia. Within minutes of an ischemic event in the brain, the microscopic motion of water molecules measured with DWI, termed the apparent diffusion coefficient (ADC), decreases within the infarcted region. However, although the change is related to cell swelling, the precise pathological mechanism remains elusive. We show that focal enlargement and constriction, or beading, in axons and dendrites are sufficient to substantially decrease ADC. We first derived a biophysical model of neurite beading, and we show that the beaded morphology allows a larger volume to be encompassed within an equivalent surface area and is, therefore, a consequence of osmotic imbalance after ischemia. The DWI experiment simulated within the model revealed that intracellular ADC decreased by 79% in beaded neurites compared with the unbeaded form. To validate the model experimentally, excised rat sciatic nerves were subjected to stretching, which induced beading but did not cause a bulk shift of water into the axon (i.e., swelling). Beading-induced changes in cell-membrane morphology were sufficient to significantly hinder water mobility and thereby decrease ADC, and the experimental measurements were in excellent agreement with the simulated values. This is a demonstration that neurite beading accurately captures the diffusion changes measured in vivo. The results significantly advance the specificity of DWI in ischemia and other acute neurological injuries and will greatly aid the development of treatment strategies to monitor and repair damaged brain in both clinical and experimental settings.