Novel pore size-controlled, susceptibility matched, 3D-printed MRI phantoms

PURPOSE

We report the design concept and fabrication of MRI phantoms, containing blocks of aligned microcapillaires that can be stacked into larger arrays to construct diameter distribution phantoms or fractured, to create a "powder-averaged" emulsion of randomly oriented blocks for vetting or calibrating advanced MRI methods, that is, diffusion tensor imaging, AxCaliber MRI, MAP-MRI, and multiple pulsed field gradient or double diffusion-encoded microstructure imaging methods. The goal was to create a susceptibility-matched microscopically anisotropic but macroscopically isotropic phantom with a ground truth diameter that could be used to vet advanced diffusion methods for diameter determination in fibrous tissues.

METHODS

Two-photon polymerization, a novel three-dimensional printing method is used to fabricate blocks of capillaries. Double diffusion encoding methods were employed and analyzed to estimate the expected MRI diameter.

RESULTS

Susceptibility-matched microcapillary blocks or modules that can be assembled into large-scale MRI phantoms have been fabricated and measured using advanced diffusion methods, resulting in microscopic anisotropy and random orientation.

CONCLUSION

This phantom can vet and calibrate various advanced MRI methods and multiple pulsed field gradient or diffusion-encoded microstructure imaging methods. We demonstrated that two double diffusion encoding methods underestimated the ground truth diameter.

Water Diffusion in the Live Human Brain is Gaussian at the Mesoscale

Imaging the live human brain at the mesoscopic scale is a desideratum in basic and clinical neurosciences. Despite the promise of diffusion MRI, the lack of an accurate model relating the measured signal and the associated microstructure has hampered its success. The widely used diffusion tensor MRI (DTI) model assumes an anisotropic Gaussian diffusion process in each voxel, but lacks the ability to capture intravoxel heterogeneity. This study explores the extension of the DTI model to mesoscopic length scales by use of the diffusion tensor distribution (DTD) model, which assumes a Gaussian diffusion process in each subvoxel. DTD MRI has shown promise in addressing some limitations of DTI, particularly in distinguishing among different types of brain cancers and elucidating multiple fiber populations within a voxel. However, its validity in live brain tissue has never been established. Here, multiple diffusion-encoded (MDE) data were acquired in the living human brain using a 3 Tesla MRI scanner with large diffusion weighting factors. Two different diffusion times (Δ = 37, 74 ms) were employed, with other scanning parameters fixed to assess signal decay differences. In vivo diffusion-weighted signals in gray and white matter were nearly identical at the two diffusion times. Fitting the signals to the DTD model yielded indistinguishable results, except in the cerebrospinal fluid (CSF)-filled voxels likely due to pulsatile flow. Overall, the study supports the time invariance of water diffusion at the mesoscopic scale in live brain parenchyma, extending the validity of the anisotropic Gaussian diffusion model in clinical brain imaging.

The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology

A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications in anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g. thalamic subregions, etc.) derived from high-resolution Mean Apparent Propagator-MRI, T2W, and magnetization transfer ratio images ex vivo. We then confirmed the location and borders of these segmented regions in the MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within Analysis of Functional NeuroImages software. Tracing and validating these important deep brain structures in 3D will improve neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, functional MRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

"Tumor Treating Fields" delivered via electromagnetic induction have varied effects across glioma cell lines and electric field amplitudes

Previous studies reported that alternating electric fields (EFs) in the intermediate frequency (100-300 kHz) and low intensity (1-3 V/cm) regime - termed "Tumor Treating Fields" (TTFields) - have a specific, anti-proliferative effect on glioblastoma multiforme (GBM) cells. However, the mechanism(s) of action remain(s) incompletely understood, hindering the clinical adoption of treatments based on TTFields. To advance the study of such treatment in vitro, we developed an inductive device to deliver EFs to cell cultures which improves thermal and osmolar regulation compared to prior devices. Using this inductive device, we applied continuous, 200 kHz electromagnetic fields (EMFs) with a radial EF amplitude profile spanning 0-6.5 V/cm to cultures of primary rat astrocytes and several human GBM cell lines - U87, U118, GSC827, and GSC923 - for a duration of 72 hours. Cell density was assessed via segmented pixel densities from GFP expression (U87, U118) or from staining (astrocytes, GSC827, GSC923). Further RNA-Seq analyses were performed on GSC827 and GSC923 cells. Treated cultures of all cell lines exhibited little to no change in proliferation at lower EF amplitudes (0-3 V/cm). At higher amplitudes (> 4 V/cm), different effects were observed. Apparent cell densities increased (U87), decreased (GSC827, GSC923), or showed little change (U118, astrocytes). RNA-Seq analyses on treated and untreated GSC827 and GSC923 cells revealed differentially expressed gene sets of interest, such as those related to cell cycle control. Up- and down-regulation, however, was not consistent across cell lines nor EF amplitudes. Our results indicate no consistent, anti-proliferative effect of 200 kHz EMFs across GBM cell lines and thus contradict previous in vitro findings. Rather, effects varied across different cell lines and EF amplitude regimes, highlighting the need to assess the effect(s) of TTFields and similar treatments on a per cell line basis.

The Subcortical Atlas of the Marmoset ("SAM") monkey based on high-resolution MRI and histology

A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications for anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the "SAM," from 251 delineated subcortical regions (e.g., thalamic subregions, etc.) derived from the high-resolution MAP-MRI, T2W, and MTR images ex vivo. We then confirmed the location and borders of these segmented regions in MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within AFNI. Tracing and validating these important deep brain structures in 3D improves neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, fMRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

Optimizing Brain Health of United States Special Operations Forces

United States Special Operations Forces (SOF) personnel are frequently exposed to explosive blasts in training and combat. However, the effects of repeated blast exposure on the human brain are incompletely understood. Moreover, there is currently no diagnostic test to detect repeated blast brain injury (rBBI). In this "Human Performance Optimization" article, we discuss how the development and implementation of a reliable diagnostic test for rBBI has the potential to promote SOF brain health, combat readiness, and quality of life.

Multimodal anatomical mapping of subcortical regions in marmoset monkeys using high-resolution MRI and matched histology with multiple stains

Subcortical nuclei and other deep brain structures play essential roles in regulating the central and peripheral nervous systems. However, many of these nuclei and their subregions are challenging to identify and delineate in conventional MRI due to their small size, hidden location, and often subtle contrasts compared to neighboring regions. To address these limitations, we scanned the whole brain of the marmoset monkeys in ex vivo using a clinically feasible diffusion MRI method, called the mean apparent propagator (MAP)-MRI, along with T2W and MTR (T1-like contrast) images acquired at 7 Tesla. Additionally, we registered these multimodal MRI volumes to the high-resolution images of matched whole-brain histology sections with seven different stains obtained from the same brain specimens. At high spatial resolution, the microstructural parameters and fiber orientation distribution functions derived with MAP-MRI can distinguish the subregions of many subcortical and deep brain structures, including fiber tracts of different sizes and orientations. The good correlation with multiple but distinct histological stains from the same brain serves as a thorough validation of the structures identified with MAP-MRI and other MRI parameters. Moreover, the anatomical details of deep brain structures found in the volumes of MAP-MRI parameters are not visible in conventional T1W or T2W images. The high-resolution mapping using novel MRI contrasts, combined and correlated with histology, can elucidate structures that were previously invisible radiologically. Thus, this multimodal approach offers a roadmap toward identifying salient brain areas in vivo in future neuroradiological studies. It also provides a useful anatomical standard reference for the region definition of subcortical targets and the generation of a 3D digital template atlas for the marmoset brain research (Saleem et al., 2023). Additionally, we conducted a cross-species comparison between marmoset and macaque monkeys using results from our previous studies (Saleem et al., 2021). We found that the two species had distinct patterns of iron distribution in subregions of the basal ganglia, red nucleus, and deep cerebellar nuclei, confirmed with T2W MRI and histology.

Mapping the individual human cortex using multidimensional MRI and unsupervised learning

Human evolution has seen the development of higher-order cognitive and social capabilities in conjunction with the unique laminar cytoarchitecture of the human cortex. Moreover, early-life cortical maldevelopment has been associated with various neurodevelopmental diseases. Despite these connections, there is currently no noninvasive technique available for imaging the detailed cortical laminar structure. This study aims to address this scientific and clinical gap by introducing an approach for imaging human cortical lamina. This method combines diffusion-relaxation multidimensional MRI with a tailored unsupervised machine learning approach that introduces enhanced microstructural sensitivity. This new imaging method simultaneously encodes the microstructure, the local chemical composition and importantly their correlation within complex and heterogenous tissue. To validate our approach, we compared the intra-cortical layers obtained using our ex vivo MRI-based method with those derived from Nissl staining of postmortem human brain specimens. The integration of unsupervised learning with diffusion-relaxation correlation MRI generated maps that demonstrate sensitivity to areal differences in cytoarchitectonic features observed in histology. Significantly, our observations revealed layer-specific diffusion-relaxation signatures, showing reductions in both relaxation times and diffusivities at the deeper cortical levels. These findings suggest a radial decrease in myelin content and changes in cell size and anisotropy, reflecting variations in both cytoarchitecture and myeloarchitecture. Additionally, we demonstrated that 1D relaxation and high-order diffusion MRI scalar indices, even when aggregated and used jointly in a multimodal fashion, cannot disentangle the cortical layers. Looking ahead, our technique holds the potential to open new avenues of research in human neurodevelopment and the vast array of disorders caused by disruptions in neurodevelopment.

Correspondence of mean apparent propagator MRI metrics with phosphorylated tau and astrogliosis in chronic traumatic encephalopathy

Chronic traumatic encephalopathy is a neurodegenerative disease that is diagnosed and staged based on the localization and extent of phosphorylated tau pathology. Although its identification remains the primary diagnostic criteria to distinguish chronic traumatic encephalopathy from other tauopathies, the hyperphosphorylated tau that accumulates in neurofibrillary tangles in cortical grey matter and perivascular regions is often accompanied by concomitant pathology such as astrogliosis. Mean apparent propagator MRI is a clinically feasible diffusion MRI method that is suitable to characterize microstructure of complex biological media efficiently and comprehensively. We performed quantitative correlations between propagator metrics and underlying phosphorylated tau and astroglial pathology in a cross-sectional study of 10 ex vivo human tissue specimens with 'high chronic traumatic encephalopathy' at 0.25 mm isotropic voxels. Linear mixed effects analysis of regions of interest showed significant relationships of phosphorylated tau with propagator-estimated non-Gaussianity in cortical grey matter (P = 0.002) and of astrogliosis with propagator anisotropy in superficial cortical white matter (P = 0.0009). The positive correlation between phosphorylated tau and non-Gaussianity was found to be modest but significant (R2 = 0.44, P = 6.0 × 10-5) using linear regression. We developed an unsupervised clustering algorithm with non-Gaussianity and propagator anisotropy as inputs, which was able to identify voxels in superficial cortical white matter that corresponded to astrocytes that were accumulated at the grey-white matter interface. Our results suggest that mean apparent propagator MRI at high spatial resolution provides a means to not only identify phosphorylated tau pathology but also detect regions with astrocytic pathology and may therefore prove diagnostically valuable in the evaluation of concomitant pathology in cortical tissue with complex microstructure.

Ion-induced changes in DNA gels

Small angle neutron scattering (SANS) measurements are reported for DNA gels under near physiological conditions in which the concentration of monovalent and divalent counter-ions and the pH are varied. The scattering intensity I(q) is described by a two-term equation, one due to osmotic concentration fluctuations and the other coming from static inhomogeneities frozen in by the cross-links. SANS in the low q range indicates the presence of large clusters and the size of which exceeds the resolution of the experiment. In the intermediate q-range, the intensity increases with the CaCl2 concentration and the slope approaches -1, corresponding to linear (rod-like) scatterers. In the highest q region, the scattering response is governed by the local chain geometry. Screening of electrostatic interactions by sodium chloride causes a moderate increase in the SANS intensity that is accompanied by an increase in the mesh size L of the network. Addition of calcium chloride, or a decrease in pH, produces similar trends, and ultimately leads to phase separation. The scattering intensity at q = 0, estimated from independent measurements of the osmotic pressure Π, is in excellent agreement with I(0) from the SANS measurements. Anomalous small angle X-ray scattering (ASAXS) measurements on the uncross-linked DNA show that the monovalent ion cloud is only weakly influenced by the addition of divalent ions. Conversely, the divalent counter-ion cloud tightly follows the contour of polymer chains.

A novel framework for in-vivo diffusion tensor distribution MRI of the human brain

Neural tissue microstructure plays an important role in developmental, physiological and pathophysiological processes. Diffusion tensor distribution (DTD) MRI helps probe subvoxel heterogeneity by describing water diffusion within a voxel using an ensemble of non-exchanging compartments characterized by a probability density function of diffusion tensors. In this study, we provide a new framework for acquiring multiple diffusion encoding (MDE) images and estimating DTD from them in the human brain in vivo. We interfused pulsed field gradients (iPFG) in a single spin echo to generate arbitrary b-tensors of rank one, two, or three without introducing concomitant gradient artifacts. Employing well-defined diffusion encoding parameters we show that iPFG retains salient features of a traditional multiple-PFG (mPFG/MDE) sequence while reducing the echo time and coherence pathway artifacts thereby extending its applications beyond DTD MRI. Our DTD is a maximum entropy tensor-variate normal distribution whose tensor random variables are constrained to be positive definite to ensure their physicality. In each voxel, the second-order mean and fourth-order covariance tensors of the DTD are estimated using a Monte Carlo method that synthesizes micro-diffusion tensors with corresponding size, shape, and orientation distributions to best fit the measured MDE images. From these tensors we obtain the spectrum of diffusion tensor ellipsoid sizes and shapes, and the microscopic orientation distribution function (μODF) and microscopic fractional anisotropy (μFA) that disentangle the underlying heterogeneity within a voxel. Using the DTD-derived μODF, we introduce a new method to perform fiber tractography capable of resolving complex fiber configurations. The results revealed microscopic anisotropy in various gray and white matter regions and skewed MD distributions in cerebellar gray matter not observed previously. DTD MRI tractography captured complex white matter fiber organization consistent with known anatomy. DTD MRI also resolved some degeneracies associated with diffusion tensor imaging (DTI) and elucidated the source of diffusion heterogeneity which may help improve the diagnosis of various neurological diseases and disorders.

Multimodal anatomical mapping of subcortical regions in Marmoset monkeys using high-resolution MRI and matched histology with multiple stains

Subcortical nuclei and other deep brain structures play essential roles in regulating the central and peripheral nervous systems. However, many of these nuclei and their subregions are challenging to identify and delineate in conventional MRI due to their small size, hidden location, and often subtle contrasts compared to neighboring regions. To address these limitations, we scanned the whole brain of the marmoset monkeys in ex vivo using a clinically feasible diffusion MRI method, called the mean apparent propagator (MAP)-MRI, along with T2W and MTR (T1-like contrast) images acquired at 7 Tesla. Additionally, we registered these multimodal MRI volumes to the high-resolution images of matched whole-brain histology sections with seven different stains obtained from the same brain specimens. At high spatial resolution, the microstructural parameters and fiber orientation distribution functions derived with MAP-MRI can distinguish the subregions of many subcortical and deep brain structures, including fiber tracts of different sizes and orientations. The good correlation with multiple but distinct histological stains from the same brain serves as a thorough validation of the structures identified with MAP-MRI and other MRI parameters. Moreover, the anatomical details of deep brain structures found in the volumes of MAP-MRI parameters are not visible in conventional T1W or T2W images. The high-resolution mapping using novel MRI contrasts, combined and correlated with histology, can elucidate structures that were previously invisible radiologically. Thus, this multimodal approach offers a roadmap toward identifying salient brain areas in vivo in future neuroradiological studies. It also provides a useful anatomical standard reference for the region definition of subcortical targets and the generation of a 3D digital template atlas for the marmoset brain research (Saleem et al., 2023). Additionally, we conducted a cross-species comparison between marmoset and macaque monkeys using results from our previous studies (Saleem et al., 2021). We found that the two species had distinct patterns of iron distribution in subregions of the basal ganglia, red nucleus, and deep cerebellar nuclei, confirmed with T2W MRI and histology.

Oligodendrocyte-mediated myelin plasticity and its role in neural synchronization

Temporal synchrony of signals arriving from different neurons or brain regions is essential for proper neural processing. Nevertheless, it is not well understood how such synchrony is achieved and maintained in a complex network of time-delayed neural interactions. Myelin plasticity, accomplished by oligodendrocytes (OLs), has been suggested as an efficient mechanism for controlling timing in brain communications through adaptive changes of axonal conduction velocity and consequently conduction time delays, or latencies; however, local rules and feedback mechanisms that OLs use to achieve synchronization are not known. We propose a mathematical model of oligodendrocyte-mediated myelin plasticity (OMP) in which OLs play an active role in providing such feedback. This is achieved without using arrival times at the synapse or modulatory signaling from astrocytes; instead, it relies on the presence of global and transient OL responses to local action potentials in the axons they myelinate. While inspired by OL morphology, we provide the theoretical underpinnings that motivated the model and explore its performance for a wide range of its parameters. Our results indicate that when the characteristic time of OL's transient intracellular responses to neural spikes is between 10 and 40 ms and the firing rates in individual axons are relatively low (⪅ 10 Hz), the OMP model efficiently synchronizes correlated and time-locked signals while latencies in axons carrying independent signals are unaffected. This suggests a novel form of selective synchronization in the CNS in which oligodendrocytes play an active role by modulating the conduction delays of correlated spike trains as they traverse to their targets.

Water exchange rates measure active transport and homeostasis in neural tissue

For its size, the brain is the most metabolically active organ in the body. Most of its energy demand is used to maintain stable homeostatic physiological conditions. Altered homeostasis and active states are hallmarks of many diseases and disorders. Yet there is currently no direct and reliable method to assess homeostasis and absolute basal activity of cells in the tissue noninvasively without exogenous tracers or contrast agents. We propose a novel low-field, high-gradient diffusion exchange NMR method capable of directly measuring cellular metabolic activity via the rate constant for water exchange across cell membranes. Exchange rates are 140 ± 16 s−1 under normal conditions in viable ex vivo neonatal mouse spinal cords. High repeatability across samples suggest that values are absolute and intrinsic to the tissue. Using temperature and drug (ouabain) perturbations, we find that the majority of water exchange is metabolically active and coupled to active transport by the sodiumpotassium pump. We show that this water exchange rate is sensitive primarily to tissue homeostasis and provides distinct functional information. In contrast, the Apparent Diffusion Coefficient (ADC) measured with sub-millisecond diffusion times is sensitive primarily to tissue microstructure but not activity. Water exchange appears independently regulated from microstructural and oxygenation changes reported by ADC and T1 relaxation measurements in an oxygen–glucose deprivation model of stroke; exchange rates remain stable for 30–40 minutes before dropping to levels similar to the effect of ouabain and never completely recovering when oxygen and glucose are restored.

"Tumor Treating Fields" delivered via electromagnetic induction have varied effects across glioma cell lines and electric field amplitudes

Previous studies reported that alternating electric fields (EFs) in the intermediate frequency (100 - 300 kHz) and low intensity (1 - 3 V/cm) regime - termed "Tumor Treating Fields" (TTFields) - have a specific, anti-proliferative effect on glioblastoma multiforme (GBM) cells. However, the mechanism(s) of action remain(s) incompletely understood, hindering the clinical adoption of treatments based on TTFields. To advance the study of such treatment in vitro , we developed an inductive device to deliver EFs to cell cultures which improves thermal and osmolar regulation compared to prior devices. Using this inductive device, we applied continuous, 200 kHz electromagnetic fields (EMFs) with a radial EF amplitude profile spanning 0 - 6.5 V/cm to cultures of primary rat astrocytes and several human GBM cell lines - U87, U118, GSC827, and GSC923 - for a duration of 72 hours. Cell density was assessed via segmented pixel densities from GFP expression (U87, U118) or from staining (astrocytes, GSC827, GSC923). Further RNA-Seq analyses were performed on GSC827 and GSC923 cells. Treated cultures of all cell lines exhibited little to no change in proliferation at lower EF amplitudes (0 - 3 V/cm). At higher amplitudes (> 4 V/cm), different effects were observed. Apparent cell densities increased (U87), decreased (GSC827, GSC923), or showed little change (U118, astrocytes). RNA-Seq analyses on treated and untreated GSC827 and GSC923 cells revealed differentially expressed gene sets of interest, such as those related to cell cycle control. Up- and down-regulation, however, was not consistent across cell lines nor EF amplitudes. Our results indicate no consistent, anti-proliferative effect of 200 kHz EMFs across GBM cell lines and thus contradict previous in vitro findings. Rather, effects varied across different cell lines and EF amplitude regimes, highlighting the need to assess the effect(s) of TTFields and similar treatments on a per cell line basis.

COnstrained Reference frame diffusion TEnsor Correlation Spectroscopic (CORTECS) MRI: A practical framework for high-resolution diffusion tensor distribution imaging

High-resolution imaging studies have consistently shown that in cortical tissue water diffuses preferentially along radial and tangential orientations with respect to the cortical surface, in agreement with histology. These dominant orientations do not change significantly even if the relative contributions from microscopic water pools to the net voxel signal vary across experiments that use different diffusion times, b-values, TEs, and TRs. With this in mind, we propose a practical new framework for imaging non-parametric diffusion tensor distributions (DTDs) by constraining the microscopic diffusion tensors of the DTD to be diagonalized using the same orthonormal reference frame of the mesoscopic voxel. In each voxel, the constrained DTD (cDTD) is completely determined by the correlation spectrum of the microscopic principal diffusivities associated with the axes of the voxel reference frame. Consequently, all cDTDs are inherently limited to the domain of positive definite tensors and can be reconstructed efficiently using Inverse Laplace Transform methods. Moreover, the cDTD reconstruction can be performed using only data acquired efficiently with single diffusion encoding, although it also supports datasets with multiple diffusion encoding. In tissues with a well-defined architecture, such as the cortex, we can further constrain the cDTD to contain only cylindrically symmetric diffusion tensors and measure the 2D correlation spectra of principal diffusivities along the radial and tangential orientation with respect to the cortical surface. To demonstrate this framework, we perform numerical simulations and analyze high-resolution dMRI data from a fixed macaque monkey brain. We estimate 2D cDTDs in the cortex and derive, in each voxel, the marginal distributions of the microscopic principal diffusivities, the corresponding distributions of the microscopic fractional anisotropies and mean diffusivities along with their 2D correlation spectra to quantify the cDTD shape-size characteristics. Signal components corresponding to specific bands in these cDTD-derived spectra show high specificity to cortical laminar structures observed with histology. Our framework drastically simplifies the measurement of non-parametric DTDs in high-resolution datasets with mesoscopic voxel sizes much smaller than the radius of curvature of the underlying anatomy, e.g., cortical surface, and can be applied retrospectively to analyze existing diffusion MRI data from fixed cortical tissues.

High-resolution cortical MAP-MRI reveals areal borders and laminar substructures observed with histological staining

The variations in cellular composition and tissue architecture measured with histology provide the biological basis for partitioning the brain into distinct cytoarchitectonic areas and for characterizing neuropathological tissue alterations. Clearly, there is an urgent need to develop whole-brain neuroradiological methods that can assess cortical cyto- and myeloarchitectonic features non-invasively. Mean apparent propagator (MAP) MRI is a clinically feasible diffusion MRI method that quantifies efficiently and comprehensively the net microscopic displacements of water molecules diffusing in tissues. We investigate the sensitivity of high-resolution MAP-MRI to detecting areal and laminar variations in cortical cytoarchitecture and compare our results with observations from corresponding histological sections in the entire brain of a rhesus macaque monkey. High-resolution images of MAP-derived parameters, in particular the propagator anisotropy (PA), non-gaussianity (NG), and the return-to-axis probability (RTAP) reveal cortical area-specific lamination patterns in good agreement with the corresponding histological stained sections. In a few regions, the MAP parameters provide superior contrast to the five histological stains used in this study, delineating more clearly boundaries and transition regions between cortical areas and laminar substructures. Throughout the cortex, various MAP parameters can be used to delineate transition regions between specific cortical areas observed with histology and to refine areal boundaries estimated using atlas registration-based cortical parcellation. Using surface-based analysis of MAP parameters we quantify the cortical depth dependence of diffusion propagators in multiple regions-of-interest in a consistent and rigorous manner that is largely independent of the cortical folding geometry. The ability to assess cortical cytoarchitectonic features efficiently and non-invasively, its clinical feasibility, and translatability make high-resolution MAP-MRI a promising 3D imaging tool for studying whole-brain cortical organization, characterizing abnormal cortical development, improving early diagnosis of neurodegenerative diseases, identifying targets for biopsies, and complementing neuropathological investigations.

Prestressed Composite Polymer Gels as a Model of the Extracellular-Matrix of Cartilage

Articular cartilage is a composite hydrogel found in animal and human joints, which exhibits unique load-bearing properties that have been challenging to reproduce in synthetic materials and model in molecular dynamics (MD) simulations. We computationally investigate a composite hydrogel that mimics key functional properties of articular cartilage as a potential biomimetic model to investigate its unique load-bearing properties. Specifically, we find that the emergence of prestress in composite gels derives primarily from the stiffness of the polymer matrix and the asymmetry in the enthalpic interactions of the embedded particles and polymer matrix. Our MD simulations of the development of prestress agree qualitatively with osmotic pressure measurements observed in our model composite hydrogel material.

Identifying transcranial magnetic stimulation induced EEG signatures of different neuronal elements in primary motor cortex

OBJECTIVE

To investigate the neuronal elements involved in the activation of corticospinal neurons in the primary motor cortex (M1).

METHODS

We studied 10 healthy subjects. Cortical evoked potentials with different components induced by monophasic transcranial magnetic stimulation (TMS) in anterior-posterior and posterior-anterior currents recorded with electroencephalography (EEG) were analyzed.

RESULTS

EEG signatures with P25 and N45 components recorded at the C3 electrode with posterior-anterior current were larger than those with anterior-posterior current, while the signatures with P180 and N280 components recorded at the FC1 electrode with anterior-posterior current were larger than those with posterior-anterior current. The source localization analysis revealed that the cortical evoked potential with anterior-posterior current distributed both in the M1 and premotor cortex while that with posterior-anterior current only located in the M1.

CONCLUSIONS

We conclude that the activation of corticospinal pyramidal neurons in the M1 is affected by various neuronal elements including the local intracortical circuits in the M1 and inputs from premotor cortex with different sensitivities to TMS in opposite current directions.

SIGNIFICANCE

Our finding helped answer a longstanding question about how the corticospinal pathway from the M1 is functionally organized and activated.

Molecular dynamics study of the swelling and osmotic properties of compact nanogel particles

Owing to their great importance in materials science and other fields, we investigate the solution and osmotic properties of uncharged compact nanogel particles over a wide range of solvent quality and particle concentration by molecular dynamics (MD) simulations. We characterize the osmotic pressure by estimating the second and third virial coefficients, and by extension, we identify the θ-point where the second virial coefficient vanishes. Calculations of the structure factor indicate that these particles are similar to macrogels in that the particle-like scattering profile disappears at moderate concentrations. We also find that improving the solvent quality enhances the spatial segmental uniformity, while significant heterogeneous structure arises near the θ-point. Well below the θ-point where the second osmotic virial coefficient vanishes, these heterogeneous structures become less prevalent as the particles tend to collapse. We also investigate the degree of swelling and structure of compact nanogel particles with a variable excluded volume interaction and gel particle concentration. The osmotic modulus and the scaling exponents in good and θ-point conditions of these gels are characteristic of interacting randomly branched polymers, i.e., "lattice animals".

Mapping astrogliosis in the individual human brain using multidimensional MRI

There are currently no non-invasive imaging methods available for astrogliosis assessment or mapping in the central nervous system despite its essential role in the response to many disease states, such as infarcts, neurodegenerative conditions, traumatic brain injury and infection. Multidimensional MRI is an increasingly employed imaging modality that maximizes the amount of encoded chemical and microstructural information by probing relaxation (T1 and T2) and diffusion mechanisms simultaneously. Here, we harness the exquisite sensitivity of this imagining modality to derive a signature of astrogliosis and disentangle it from normative brain at the individual level using machine learning. We investigated ex vivo cerebral cortical tissue specimens derived from seven subjects who sustained blast-induced injuries, which resulted in scar-border forming astrogliosis without being accompanied by other types of neuropathological abnormality, and from seven control brain donors. By performing a combined post-mortem radiology and histopathology correlation study we found that astrogliosis induces microstructural and chemical changes that are robustly detected with multidimensional MRI, and which can be attributed to astrogliosis because no axonal damage, demyelination or tauopathy were histologically observed in any of the cases in the study. Importantly, we showed that no one-dimensional T1, T2 or diffusion MRI measurement can disentangle the microscopic alterations caused by this neuropathology. Based on these findings, we developed a within-subject anomaly detection procedure that generates MRI-based astrogliosis biomarker maps ex vivo, which were significantly and strongly correlated with co-registered histological images of increased glial fibrillary acidic protein deposition (r = 0.856, P < 0.0001; r = 0.789, P < 0.0001; r = 0.793, P < 0.0001, for diffusion-T2, diffusion-T1 and T1-T2 multidimensional data sets, respectively). Our findings elucidate the underpinning of MRI signal response from astrogliosis, and the demonstrated high spatial sensitivity and specificity in detecting reactive astrocytes at the individual level, and if reproduced in vivo, will significantly impact neuroimaging studies of injury, disease, repair and aging, in which astrogliosis has so far been an invisible process radiologically.

Hydrogel composite mimics biological tissues

A novel composite hydrogel was developed that shows remarkable similarities to load bearing biological tissues. The composite gel consisting of a poly(vinyl alcohol (PVA) matrix filled with poly(acrylic acid) (PAA) microgel particles exhibits osmotic and mechanical properties that are qualitatively different from regular gels. In the PVA/PAA system the swollen PAA particles "inflate" the PVA network. The swelling of the PAA is limited by the tensile stress P_el developing in the PVA matrix. P_el increases with increasing swelling degree, which is opposite to the decrease of the elastic pressure observed in regular gels. The maximum tensile stress Pmaxel can be identified as a quantity that defines the load bearing ability of the composite gel. Systematic osmotic swelling pressure measurements have been made on PVA/PAA gels to determine the effects of PVA stiffness, PAA crosslink density, and Ca²⁺ ion concentration on Pmaxel. It is found that Pmaxel increases with the stiffness of the PVA matrix, and decreases with (i) increasing crosslink density of the PAA and (ii) increasing Ca²⁺ ion concentration. Small angle neutron scattering (SANS) measurements indicate only a weak interaction between the PVA and PAA gels. It is demonstrated that the osmotic swelling pressure of PVA/PAA composite gels reproduces the osmotic behavior of healthy and osteoarthritic cartilage.

Disentangling the effects of restriction and exchange with diffusion exchange spectroscopy

Diffusion exchange spectroscopy (DEXSY) is a multidimensional NMR technique that can reveal how water molecules exchange between compartments within heterogeneous media, such as biological tissue. Data from DEXSY experiments is typically processed using numerical inverse Laplace transforms (ILTs) to produce a diffusion-diffusion spectrum. A tacit assumption of this ILT approach is that the signal behavior is Gaussian - i.e., the spin echo intensity decays exponentially with the degree of diffusion weighting. The assumptions that underlie Gaussian signal behavior may be violated, however, depending on the gradient strength applied and the sample under study. We argue that non-Gaussian signal behavior due to restrictions is to be expected in the study of biological tissue using diffusion NMR. Further, we argue that this signal behavior can produce confounding features in the diffusion-diffusion spectra obtained from numerical ILTs of DEXSY data - entangling the effects of restriction and exchange. Specifically, restricted signal behavior can result in broadening of peaks and in the appearance of illusory exchanging compartments with distributed diffusivities, which pearl into multiple peaks if not highly regularized. We demonstrate these effects on simulated data. That said, we suggest the use of features in the signal acquisition domain that can be used to rapidly probe exchange without employing an ILT. We also propose a means to characterize the non-Gaussian signal behavior due to restrictions within a sample using DEXSY measurements with a near zero mixing time or storage interval. We propose a combined acquisition scheme to independently characterize restriction and exchange with various DEXSY measurements, which we term Restriction and Exchange from Equally-weighted Double and Single Diffusion Encodings (REEDS-DE). We test this method on ex vivo neonatal mouse spinal cord - a sample consisting primarily of gray matter - using a low-field, static gradient NMR system. In sum, we highlight critical shortcomings of prevailing DEXSY analysis methods that conflate the effects of restriction and exchange, and suggest a viable experimental approach to disentangle them.

Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome

The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain - from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.

Orientational changes of white matter fibers in Alzheimer's disease and amnestic mild cognitive impairment

White matter abnormalities represent early neuropathological events in neurodegenerative diseases such as Alzheimer's disease (AD), investigating these white matter alterations would likely provide valuable insights into pathological changes over the course of AD. Using a novel mathematical framework called "Director Field Analysis" (DFA), we investigated the geometric microstructural properties (i.e., splay, bend, twist, and total distortion) in the orientation of white matter fibers in AD, amnestic mild cognitive impairment (aMCI), and cognitively normal (CN) individuals from the Alzheimer's Disease Neuroimaging Initiative 2 database. Results revealed that AD patients had extensive orientational changes in the bilateral anterior thalamic radiation, corticospinal tract, inferior and superior longitudinal fasciculus, inferior fronto-occipital fasciculus, and uncinate fasciculus in comparison with CN. We postulate that these orientational changes of white matter fibers may be partially caused by the expansion of lateral ventricle, white matter atrophy, and gray matter atrophy in AD. In contrast, aMCI individuals showed subtle orientational changes in the left inferior longitudinal fasciculus and right uncinate fasciculus, which showed a significant association with the cognitive performance, suggesting that these regions may be preferential vulnerable to breakdown by neurodegenerative brain disorders, thereby resulting in the patients' cognitive impairment. To our knowledge, this article is the first to examine geometric microstructural changes in the orientation of white matter fibers in AD and aMCI. Our findings demonstrate that the orientational information of white matter fibers could provide novel insight into the underlying biological and pathological changes in AD and aMCI.

Multidimensional MRI for Characterization of Subtle Axonal Injury Accelerated Using an Adaptive Nonlocal Multispectral Filter

Multidimensional MRI is an emerging approach that simultaneously encodes water relaxation (T₁ and T₂) and mobility (diffusion) and replaces voxel-averaged values with subvoxel distributions of those MR properties. While conventional (i.e., voxel-averaged) MRI methods cannot adequately quantify the microscopic heterogeneity of biological tissue, using subvoxel information allows to selectively map a specific T₁-T₂-diffusion spectral range that corresponds to a group of tissue elements. The major obstacle to the adoption of rich, multidimensional MRI protocols for diagnostic or monitoring purposes is the prolonged scan time. Our main goal in the present study is to evaluate the performance of a nonlocal estimation of multispectral magnitudes (NESMA) filter on reduced datasets to limit the total acquisition time required for reliable multidimensional MRI characterization of the brain. Here we focused and reprocessed results from a recent study that identified potential imaging biomarkers of axonal injury pathology from the joint analysis of multidimensional MRI, in particular voxelwise T₁-T₂ and diffusion-T₂ spectra in human Corpus Callosum, and histopathological data. We tested the performance of NESMA and its effect on the accuracy of the injury biomarker maps, relative to the co-registered histological reference. Noise reduction improved the accuracy of the resulting injury biomarker maps, while permitting data reduction of 35.7 and 59.6% from the full dataset for T₁-T₂ and diffusion-T₂ cases, respectively. As successful clinical proof-of-concept applications of multidimensional MRI are continuously being introduced, reliable and robust noise removal and consequent acquisition acceleration would advance the field towards clinically-feasible diagnostic multidimensional MRI protocols.

Diffuse axonal injury has a characteristic multidimensional MRI signature in the human brain

Axonal injury is a major contributor to the clinical symptomatology in patients with traumatic brain injury. Conventional neuroradiological tools, such as CT and MRI, are insensitive to diffuse axonal injury (DAI) caused by trauma. Diffusion tensor MRI parameters may change in DAI lesions; however, the nature of these changes is inconsistent. Multidimensional MRI is an emerging approach that combines T1, T2, and diffusion, and replaces voxel-averaged values with distributions, which allows selective isolation of specific potential abnormal components. By performing a combined post-mortem multidimensional MRI and histopathology study, we aimed to investigate T1-T2-diffusion changes linked to DAI and to define their histopathological correlates. Corpora callosa derived from eight subjects who had sustained traumatic brain injury, and three control brain donors underwent post-mortem ex vivo MRI at 7 T. Multidimensional, diffusion tensor, and quantitative T1 and T2 MRI data were acquired and processed. Following MRI acquisition, slices from the same tissue were tested for amyloid precursor protein (APP) immunoreactivity to define DAI severity. A robust image co-registration method was applied to accurately match MRI-derived parameters and histopathology, after which 12 regions of interest per tissue block were selected based on APP density, but blind to MRI. We identified abnormal multidimensional T1-T2, diffusion-T2, and diffusion-T1 components that are strongly associated with DAI and used them to generate axonal injury images. We found that compared to control white matter, mild and severe DAI lesions contained significantly larger abnormal T1-T2 component (P = 0.005 and P < 0.001, respectively), and significantly larger abnormal diffusion-T2 component (P = 0.005 and P < 0.001, respectively). Furthermore, within patients with traumatic brain injury the multidimensional MRI biomarkers differentiated normal-appearing white matter from mild and severe DAI lesions, with significantly larger abnormal T1-T2 and diffusion-T2 components (P = 0.003 and P < 0.001, respectively, for T1-T2; P = 0.022 and P < 0.001, respectively, for diffusion-T2). Conversely, none of the conventional quantitative MRI parameters were able to differentiate lesions and normal-appearing white matter. Lastly, we found that the abnormal T1-T2, diffusion-T1, and diffusion-T2 components and their axonal damage images were strongly correlated with quantitative APP staining (r = 0.876, P < 0.001; r = 0.727, P < 0.001; and r = 0.743, P < 0.001, respectively), while producing negligible intensities in grey matter and in normal-appearing white matter. These results suggest that multidimensional MRI may provide non-invasive biomarkers for detection of DAI, which is the pathological substrate for neurological disorders ranging from concussion to severe traumatic brain injury.

Whole-Brain Imaging of Subvoxel T1-Diffusion Correlation Spectra in Human Subjects

T1 relaxation and water mobility generate eloquent MRI tissue contrasts with great diagnostic value in many neuroradiological applications. However, conventional methods do not adequately quantify the microscopic heterogeneity of these important biophysical properties within a voxel, and therefore have limited biological specificity. We describe a new correlation spectroscopic (CS) MRI method for measuring how T1 and mean diffusivity (MD) co-vary in microscopic tissue environments. We develop a clinical pulse sequence that combines inversion recovery (IR) with single-shot isotropic diffusion encoding (IDE) to efficiently acquire whole-brain MRIs with a wide range of joint T1-MD weightings. Unlike conventional diffusion encoding, the IDE preparation ensures that all subvoxel water pools are weighted by their MDs regardless of the sizes, shapes, and orientations of their corresponding microscopic diffusion tensors. Accordingly, IR-IDE measurements are well-suited for model-free, quantitative spectroscopic analysis of microscopic water pools. Using numerical simulations, phantom experiments, and data from healthy volunteers we demonstrate how IR-IDE MRIs can be processed to reconstruct maps of two-dimensional joint probability density functions, i.e., correlation spectra, of subvoxel T1-MD values. In vivo T1-MD spectra show distinct cerebrospinal fluid and parenchymal tissue components specific to white matter, cortical gray matter, basal ganglia, and myelinated fiber pathways, suggesting the potential for improved biological specificity. The one-dimensional marginal distributions derived from the T1-MD correlation spectra agree well with results from other relaxation spectroscopic and quantitative MRI studies, validating the T1-MD contrast encoding and the spectral reconstruction. Mapping subvoxel T1-diffusion correlations in patient populations may provide a more nuanced, comprehensive, sensitive, and specific neuroradiological assessment of the non-specific changes seen on fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted MRIs (DWIs) in cancer, ischemic stroke, or brain injury.

A single-shot measurement of time-dependent diffusion over sub-millisecond timescales using static field gradient NMR

Time-dependent diffusion behavior is probed over sub-millisecond timescales in a single shot using a nuclear magnetic resonance static gradient time-incremented echo train acquisition (SG-TIETA) framework. The method extends the Carr-Purcell-Meiboom-Gill cycle under a static field gradient by discretely incrementing the π-pulse spacings to simultaneously avoid off-resonance effects and probe a range of timescales (50-500 µs). Pulse spacings are optimized based on a derived ruleset. The remaining effects of pulse inaccuracy are examined and found to be consistent across pure liquids of different diffusivities: water, decane, and octanol-1. A pulse accuracy correction is developed. Instantaneous diffusivity, Dinst(t), curves (i.e., half of the time derivative of the mean-squared displacement in the gradient direction) are recovered from pulse accuracy-corrected SG-TIETA decays using a model-free log-linear least squares inversion method validated by Monte Carlo simulations. A signal-averaged 1-min experiment is described. A flat Dinst(t) is measured on pure dodecamethylcyclohexasiloxane, whereas decreasing Dinst(t) is measured on yeast suspensions, consistent with the expected short-time Dinst(t) behavior for confining microstructural barriers on the order of micrometers.

Ion-Induced Volume Transition in Gels and Its Role in Biology

Incremental changes in ionic composition, solvent quality, and temperature can lead to reversible and abrupt structural changes in many synthetic and biopolymer systems. In the biological milieu, this nonlinear response is believed to play an important functional role in various biological systems, including DNA condensation, cell secretion, water flow in xylem of plants, cell resting potential, and formation of membraneless organelles. While these systems are markedly different from one another, a physicochemical framework that treats them as polyelectrolytes, provides a means to interpret experimental results and make in silico predictions. This article summarizes experimental results made on ion-induced volume phase transition in a polyelectrolyte model gel (sodium polyacrylate) and observations on the above-mentioned biological systems indicating the existence of a steep response.

A new framework for MR diffusion tensor distribution

The ability to characterize heterogeneous and anisotropic water diffusion processes within macroscopic MRI voxels non-invasively and in vivo is a desideratum in biology, neuroscience, and medicine. While an MRI voxel may contain approximately a microliter of tissue, our goal is to examine intravoxel diffusion processes on the order of picoliters. Here we propose a new theoretical framework and efficient experimental design to describe and measure such intravoxel structural heterogeneity and anisotropy. We assume that a constrained normal tensor-variate distribution (CNTVD) describes the variability of positive definite diffusion tensors within a voxel which extends its applicability to a wide range of b-values while preserving the richness of diffusion tensor distribution (DTD) paradigm unlike existing models. We introduce a new Monte Carlo (MC) scheme to synthesize realistic 6D DTD numerical phantoms and invert the MR signal. We show that the signal inversion is well-posed and estimate the CNTVD parameters parsimoniously by exploiting the different symmetries of the mean and covariance tensors of CNTVD. The robustness of the estimation pipeline is assessed by adding noise to calculated MR signals and compared with the ground truth. A family of invariant parameters and glyphs which characterize microscopic shape, size and orientation heterogeneity within a voxel are also presented.

Multidimensional correlation MRI

Multidimensional correlation spectroscopy is emerging as a novel MRI modality that is well suited for microstructure and microdynamic imaging studies, especially of biological specimens. Conventional MRI methods only provide voxel-averaged and mostly macroscopically averaged information; these methods cannot disentangle intra-voxel heterogeneity on the basis of both water mobility and local chemical interactions. By correlating multiple MR contrast mechanisms and processing the data in an integrated manner, correlation spectroscopy is able to resolve the distribution of water populations according to their chemical and physical interactions with the environment. The use of a non-parametric, phenomenological representation of the multidimensional MR signal makes no assumptions about tissue structure, thereby allowing the study of microscopic structure and composition of complex heterogeneous biological systems. However, until recently, vast data requirements have confined these types of measurement to non-localized NMR applications and prevented them from being widely and successfully used in conjunction with imaging. Recent groundbreaking advancements have allowed this powerful NMR methodology to be migrated to MRI, initiating its emergence as a promising imaging approach. This review is not intended to cover the entire field of multidimensional MR; instead, it focuses on pioneering imaging applications and the challenges involved. In addition, the background and motivation that have led to multidimensional correlation MR development are discussed, along with the basic underlying mathematical concepts. The goal of the present work is to provide the reader with a fundamental understanding of the techniques developed and their potential benefits, and to provide guidance to help refine future applications of this technology.

A Novel In Vitro Device to Deliver Induced Electromagnetic Fields to Cell and Tissue Cultures

We have developed a novel, to our knowledge, in vitro instrument that can deliver intermediate-frequency (100-400 kHz), moderate-intensity (up to and exceeding 6.5 V/cm pk-pk) electric fields (EFs) to cell and tissue cultures generated using induced electromagnetic fields (EMFs) in an air-core solenoid coil. A major application of these EFs is as an emerging cancer treatment modality. In vitro studies by Novocure reported that intermediate-frequency (100-300 kHz), low-amplitude (1-3 V/cm) EFs, which they called "tumor-treating fields (TTFields)," had an antimitotic effect on glioblastoma multiforme (GBM) cells. The effect was found to increase with increasing EF amplitude. Despite continued theoretical, preclinical, and clinical study, the mechanism of action remains incompletely understood. All previous in vitro studies of "TTFields" have used attached, capacitively coupled electrodes to deliver alternating EFs to cell and tissue cultures. This contacting delivery method suffers from a poorly characterized EF profile and conductive heating that limits the duration and amplitude of the applied EFs. In contrast, our device delivers EFs with a well-characterized radial profile in a noncontacting manner, eliminating conductive heating and enabling thermally regulated EF delivery. To test and demonstrate our system, we generated continuous, 200-kHz EMF with an EF amplitude profile spanning 0-6.5 V/cm pk-pk and applied them to exemplar human thyroid cell cultures for 72 h. We observed moderate reduction in cell density (<10%) at low EF amplitudes (<4 V/cm) and a greater reduction in cell density of up to 25% at higher amplitudes (4-6.5 V/cm). Our device can be readily extended to other EF frequency and amplitude regimes. Future studies with this device should contribute to the ongoing debate about the efficacy and mechanism(s) of action of "TTFields" by better isolating the effects of EFs and providing access to previously inaccessible EF regimes.

Real-time measurement of diffusion exchange rate in biological tissue

Diffusion exchange spectroscopy (DEXSY) provides a means to isolate the signal attenuation associated with exchange from other sources of signal loss. With the total diffusion weighting b₁+b₂=b_s held constant, DEXSY signals acquired with b₁=0 or b₂=0 have no exchange weighting, while a DEXSY signal acquired with b₁=b₂ has maximal exchange weighting. The exchange rate can be estimated by fitting a diffusion exchange model to signals acquired with variable mixing times. Conventionally, acquired signals are normalized by a signal with b₁=0 and b₂=0 to remove the decay due to spin-lattice relaxation. Instead, division by a signal with equal b_s but b₁=0 or b₂=0 reduces spin-lattice relaxation weighting of the apparent exchange rate (AXR). Furthermore, apparent diffusion-weighted R₁ relaxation rates can be estimated from non-exchange-weighted DEXSY signals. Estimated R₁ values are utilized to remove signal decay due to spin-lattice relaxation from exchange-weighted signals, permitting a more precise estimate of AXR with less data. Data reduction methods are proposed and tested with regards to statistical accuracy and precision of AXR estimates on simulated and experimental data. Simulations show that the methods are capable of accurately measuring the ground-truth exchange rate. The methods remain accurate even when the assumption that DEXSY signals attenuate with b is violated, as occurs for restricted diffusion. Experimental data was collected from fixed neonatal mouse spinal cord samples at 25 and 7°C using the strong static magnetic field gradient produced by a single-sided permanent magnet (i.e., an NMR MOUSE). The most rapid method for exchange measurements requires only five data points (an 80 s experiment as implemented) and achieves a similar level of accuracy and precision to the baseline method using 44 data points. This represents a significant improvement in acquisition speed, overcoming a barrier which has limited the use of DEXSY on living specimen.

Limits to flow detection in phase contrast MRI

Pulsed gradient spin echo (PGSE) complex signal behavior becomes dominated by attenuation rather than oscillation when displacements due to flow are similar or less than diffusive displacements. In this "slow-flow" regime, the optimal displacement encoding parameter q for phase contrast velocimetry depends on the diffusive length scale q s l o w = 1 / l D = 1 / 2 D Δ rather than the velocity encoding parameter v _enc = π/(qΔ). The minimum detectable mean velocity using the difference between the phase at +q _slow and -q _slow is 〈 v m i n 〉 = 1 / SNR D / Δ . These theories are then validated and applied to MRI by performing PGSE echo planar imaging experiments on water flowing through a column with a bulk region and a beadpack region at controlled flow rates. Velocities as slow as 6 μm/s are detected with velocimetry. Theories, MRI experimental protocols, and validation on a controlled phantom help to bridge the gap between porous media NMR and pre-clinical phase contrast and diffusion MRI.

Composite Hydrogel Model of Cartilage Predicts Its Load-Bearing Ability

Articular cartilage is a load-bearing tissue found in animal and human joints. It is a composite gel-like material in which a fibrous collagen network encapsulates large proteoglycan assemblies that imbibe fluid and “inflate” the network. Here we describe a composite hydrogel consisting of a cross-linked polyvinyl alcohol matrix filled with poly(acrylic acid) microparticles that mimics functional properties and biomechanical behavior of cartilage. The swelling and mechanical behaviors of this biomimetic model system are strikingly similar to that of human cartilage. The development of synthetic composite gel-based articular cartilage analog suggests new avenues to explore material properties, and their change in disease and degeneration, as well as novel strategies for developing composite tissue-engineered cartilage constructs for regenerative medicine applications.

Measuring conduction velocity distributions in peripheral nerves using neurophysiological techniques

OBJECTIVE

To determine how long it takes for neural impulses to travel along peripheral nerve fibers in living humans.

METHODS

A collision test was performed to measure the conduction velocity distribution of the ulnar nerve. Two stimuli at the distal and proximal sites were used to produce the collision. Compound muscle or nerve action potentials were recorded to perform the measurements on the motor or mixed nerve, respectively. Interstimulus interval was set at 1-5 ms. A quadri-pulse technique was used to measure the refractory period and calibrate the conduction time.

RESULTS

Compound muscle action potential produced by the proximal stimulation started to emerge at the interstimulus interval of about 1.5 ms and increased with the increment in interstimulus interval. Two groups of motor nerve fibers with different conduction velocities were identified. The mixed nerve showed a wider conduction velocity distribution with identification of more subgroups of nerve fibers than the motor nerve.

CONCLUSIONS

The conduction velocity distributions in high resolution on a peripheral motor and mixed nerve are different and this can be measured with the collision test.

SIGNIFICANCE

We provided ground truth data to verify the neuroimaging pipelines for the measurements of latency connectome in the peripheral nervous system.

Retaining information from multidimensional correlation MRI using a spectral regions of interest generator

Multidimensional correlation magnetic resonance imaging (MRI) is an emerging imaging modality that is capable of disentangling highly heterogeneous and opaque systems according to chemical and physical interactions of water within them. Using this approach, the conventional three dimensional MR scalar images are replaced with spatially resolved multidimensional spectra. The ensuing abundance in microstructural and chemical information is a blessing that incorporates a real challenge: how does one distill and refine it into images while retaining its significant components? In this paper we introduce a general framework that preserves the spectral information from spatially resolved multidimensional data. Equal weight is given to significant spectral components at the single voxel level, resulting in a summarized image spectrum. This spectrum is then used to define spectral regions of interest that are utilized to reconstruct images of sub-voxel components. Using numerical simulations we first show that, contrary to the conventional approach, the proposed framework preserves spectral resolution, and in turn, sensitivity and specificity of the reconstructed images. The retained spectral resolution allows, for the first time, to observe an array of distinct [Formula: see text]-[Formula: see text]-[Formula: see text] components images of the human brain. The robustly generated images of sub-voxel components overcome the limited spatial resolution of MRI, thus advancing multidimensional correlation MRI to fulfilling its full potential.

Magnetic resonance measurements of cellular and sub-cellular membrane structures in live and fixed neural tissue

We develop magnetic resonance (MR) methods for real-time measurement of tissue microstructure and membrane permeability of live and fixed excised neonatal mouse spinal cords. Diffusion and exchange MR measurements are performed using the strong static gradient produced by a single-sided permanent magnet. Using tissue delipidation methods, we show that water diffusion is restricted solely by lipid membranes. Most of the diffusion signal can be assigned to water in tissue which is far from membranes. The remaining 25% can be assigned to water restricted on length scales of roughly a micron or less, near or within membrane structures at the cellular, organelle, and vesicle levels. Diffusion exchange spectroscopy measures water exchanging between membrane structures and free environments at 100 s^-1.

Effects of mono- and divalent cations on the structure and thermodynamic properties of polyelectrolyte gels

Measurements are reported on the effect of monovalent and divalent salts on the swelling behavior and supramolecular structure of sodium polyacrylate gels (NaPA) made by osmotic swelling pressure and small angle neutron scattering measurements. The swelling response of the gels in solutions of ten different monovalent salts is found to be practically identical indicating that the principal effect of monovalent ions is screening the electrostatic repulsion among the charged groups on the polyelectrolyte chains; i.e., chemical differences between the monovalent ions do not play a significant role. Introducing Ca2+ ions into the equilibrium NaCl solution results in a sharp volume transition of the gels. The threshold Ca2+ ion concentration at which the transition occurs increases with increasing NaCl concentration in the surrounding bath. It is demonstrated that the swelling behavior of NaPA gels exhibits universal properties in solutions containing both NaCl and CaCl2. Osmotic swelling pressure measurements reveal that both the second and third virial coefficients decrease with increasing CaCl2 concentration until the volume transition is reached. The macroscopic measurements are complemented by small angle neutron scattering that reveals the variation of the thermodynamic length scales as the volume transition is approached. The thermodynamic correlation length L increases with increasing CaCl2 concentration.

Generalized Mean Apparent Propagator MRI to Measure and Image Advective and Dispersive Flows in Medicine and Biology

Water transport in biological systems spans different regimes with distinct physical behaviors: diffusion, advection, and dispersion. Identifying these regimes is of paramount importance in many in vivo applications, among them, measuring microcirculation of blood in capillary networks and cerebrospinal fluid transport in the glymphatic system. Diffusion magnetic resonance imaging (dMRI) can be used to encode water displacements, and a Fourier transform of the acquired signal furnishes a displacement probability density function known as the propagator. This transformation normally requires the use of a fast Fourier transform (FFT), which presents major feasibility challenges when scanning in vivo, mainly because of dense signal sampling, resulting in long acquisition times. A second approach to reconstruct the propagator is by using analytical representation of the signal, overcoming many of the FFT's limitations. In all analytical implementations of dMRI to date, the translational motion of water has been assumed to be exclusively diffusive, which is the case only in the absence of flow. However, retaining the phase information from the diffusion signal provides the ability to measure both mean coherent velocity and random diffusion from a single experiment. We implement and extend an analytical framework, mean apparent propagator (MAP), which can account for non-zero flow conditions. We call this method generalized MAP or GMAP. We describe a numerical optimization scheme and implement it on data from an MRI flow phantom constructed from a pack of 10- [Formula: see text] beads. The advantages of GMAP over the FFT-based method in the context of sampling density and low-flow detection were demonstrated, and analytically derived propagator moments were shown to agree with theoretical values even after data subsampling. GMAP would enable the detection of microflow in vivo that could help elucidate many important biological processes.

Rapid detection of the presence of diffusion exchange

Diffusion exchange spectroscopy (DEXSY) provides a detailed picture of how fluids in different microenvironments communicate with one another but requires a large amount of data. For DEXSY MRI, a simple measure of apparent exchanging fractions may suffice to characterize and differentiate materials and tissues. Reparameterizing signal intensity from a PGSE-storage-PGSE experiment as a function of the sum, b_s=b₁+b₂, and difference b_d=b₂-b₁ of the diffusion encodings separates diffusion weighting from exchange weighting. Exchange leads to upward curvature along a slice of constant b_s. Exchanging fractions can be measured rapidly by a finite difference approximation of the curvature using four data points. The method is generalized for non-steady-state and multi-site exchange. We apply the method to image exchanging fractions and calculate exchange rates of water diffusing across the bulk water interface of a glass capillary array.

Ionic effects in semi-dilute biopolymer solutions: A small angle scattering study

Systematic investigations using neutron and X-ray small angle scattering in near-physiological salt solutions were made to reveal the effect of polymer concentration, pH, and calcium ion concentration on the structure of semi-dilute solutions of four model biopolymers [polyaspartic acid, DNA, chondroitin sulfate, and hyaluronic acid (HA)] representing typical backbone structures. In the low q range (<0.01 Å-1), the scattering response I(q) is dominated by scattering from large clusters. In the intermediate q range, I(q) varies approximately as q -1, exposing the linear nature of the scatterers. In these polyelectrolyte solutions, the correlation length L displays a power law dependence on the polymer concentration c that resembles that of neutral polymer solutions. L increases with increasing calcium chloride concentration and with decreasing pH. The effect of the different divalent cations, Ba, Mg, Ca, Sr, and Mn, on the structure of DNA solutions is practically identical. However, in mixed salt conditions at the same ionic strength, the combined effect of mono- and divalent counter-ions on the structure of the polymer solutions deviates significantly from additivity. Anomalous small angle X-ray scattering observations on both DNA and HA solutions reveal that the divalent strontium counter-ions form a tight sheath around the polymer chain. The shape of the divalent ion cloud is similar in these two systems.

Measuring non-parametric distributions of intravoxel mean diffusivities using a clinical MRI scanner

We measure spectra of water mobilities (i.e., mean diffusivities) from intravoxel pools in brain tissues of healthy subjects with a non-parametric approach. Using a single-shot isotropic diffusion encoding (IDE) preparation, we eliminate signal confounds caused by anisotropic diffusion, including microscopic anisotropy, and acquire in vivo diffusion-weighted images (DWIs) over a wide range of diffusion sensitizations. We analyze the measured IDE signal decays using a regularized inverse laplace transform (ILT) to derive a probability distribution of mean diffusivities of tissue water in each voxel. Based on numerical simulations we assess the sensitivity and accuracy of our ILT analysis and optimize an experimental protocol for use with clinical MRI scanners. In vivo spectra of intravoxel mean diffusivities measured in healthy subjects generally show single-peak distributions throughout the brain parenchyma, with small differences in peak location and shape among white matter, cortical and subcortical gray matter, and cerebrospinal fluid. Mean diffusivity distributions (MDDs) with multiple peaks are observed primarily in voxels at tissue interfaces and are likely due to partial volume contributions. To quantify tissue-specific MDDs with improved statistical power, we average voxel-wise normalized MDDs in corresponding regions-of-interest (ROIs). This non-parametric, rotation-invariant assessment of isotropic diffusivities of tissue water may reflect important microstructural information, such as cell packing and cell size, and active physiological processes, such as water transport and exchange, which may enhance biological specificity in the clinical diagnosis and characterization of ischemic stroke, cancer, neuroinflammation, and neurodegenerative disorders and diseases.

Using double pulsed-field gradient MRI to study tissue microstructure in traumatic brain injury (TBI)

Double pulsed-field gradient (dPFG) MRI is proposed as a new sensitive tool to detect and characterize tissue microstructure following diffuse axonal injury. In this study dPFG MRI was used to estimate apparent mean axon diameter in a diffuse axonal injury animal model and in healthy fixed mouse brain. Histological analysis was used to verify the presence of the injury detected by MRI.

Towards clinically feasible relaxation-diffusion correlation MRI using MADCO

Multidimensional relaxation-diffusion correlation (REDCO) NMR is an assumption-free method that measures how water is distributed within materials. Although highly informative, REDCO had never been used in clinical MRI applications because of the large amount of data it requires, leading to infeasible scan times. A recently suggested novel experimental design and processing framework, marginal distributions constrained optimization (MADCO), was used here to accelerate and improve the reconstruction of such MRI correlations. MADCO uses the 1D marginal distributions as a priori information, which provide powerful constraints when 2D spectra are reconstructed, while their estimation requires an order of magnitude less data than conventional 2D approaches. In this work we experimentally examined the impact the complexity of the correlation distribution has on the accuracy and robustness of the estimates. MADCO and a conventional method were compared using two T1-D phantoms that differ in the proximity of their peaks, leading to a relatively simple case as opposed to a more challenging one. The phantoms were used to vet the achievable data compression using MADCO under these conditions. MADCO required ~43 and ~30 less data than the conventional approach for the simple and complex spectra, respectively, making it potentially feasible for preclinical and even clinical applications.

Brain active transmembrane water cycling measured by MR is associated with neuronal activity

PURPOSE

fMRI is widely used to study brain activity. Unfortunately, conventional fMRI methods assess neuronal activity only indirectly, through hemodynamic coupling. Here, we show that active, steady-state transmembrane water cycling (AWC) could serve as a basis for a potential fMRI mechanism for direct neuronal activity detection.

METHODS

AWC and neuronal actitivity in rat organotypic cortical cultures were simultaneously measured with a hybrid MR-fluorescence system. Perfusion with a paramagnetic MRI contrast agent, Gadoteridol, allows NMR determination of the kinetics of transcytolemmal water exchange. Changes in intracellular calcium concentration, [Ca_i ²⁺ ] were used as a proxy of neuronal activity and were monitored by fluorescence imaging.

RESULTS

When we alter neuronal activity by titrating with extracellular [K⁺ ] near the normal value, we see an AWC response resembling Na⁺ -K⁺ -ATPase (NKA) Michaelis-Menten behavior. When we treat with the voltage-gated sodium channel inhibitor, or with an excitatory postsynaptic inhibitor cocktail, we see AWC decrease by up to 71%. AWC was found also to be positively correlated with the basal level of spontaneous activity, which varies in different cultures.

CONCLUSIONS

These results suggest that AWC is associated with neuronal activity and NKA activity is a major contributor in coupling AWC to neuronal activity. Although AWC comprises steady-state, homeostatic transmembrane water exchange, our analysis also yields a simultaneous measure of the average cell volume, which reports any slower net transmembrane water transport.

Single- and Multiple-Shell Uniform Sampling Schemes for Diffusion MRI Using Spherical Codes

In diffusion MRI (dMRI), a good sampling scheme is important for efficient acquisition and robust reconstruction. Diffusion weighted signal is normally acquired on single or multiple shells in q-space. Signal samples are typically distributed uniformly on different shells to make them invariant to the orientation of structures within tissue, or the laboratory coordinate frame. The Electrostatic Energy Minimization (EEM) method, originally proposed for single shell sampling scheme in dMRI, was recently generalized to multi-shell schemes, called Generalized EEM (GEEM). GEEM has been successfully used in the Human Connectome Project (HCP). However, EEM does not directly address the goal of optimal sampling, i.e., achieving large angular separation between sampling points. In this paper, we propose a more natural formulation, called Spherical Code (SC), to directly maximize the minimal angle between different samples in single or multiple shells. We consider not only continuous problems to design single or multiple shell sampling schemes, but also discrete problems to uniformly extract sub-sampled schemes from an existing single or multiple shell scheme, and to order samples in an existing scheme. We propose five algorithms to solve the above problems, including an incremental SC (ISC), a sophisticated greedy algorithm called Iterative Maximum Overlap Construction (IMOC), an 1-Opt greedy method, a Mixed Integer Linear Programming (MILP) method, and a Constrained Non-Linear Optimization (CNLO) method. To our knowledge, this is the first work to use the SC formulation for single or multiple shell sampling schemes in dMRI. Experimental results indicate that SC methods obtain larger angular separation and better rotational invariance than the state-of-the-art EEM and GEEM. The related codes and a tutorial have been released in DMRITool.