Biology subjects

Benjamini, D.

Publications and source records attributed to Benjamini, D..

17 recordsLinked to original sources

bioRxiv2026

Multidimensional T1-T2 Relaxation Imaging In Vivo on a Portable 0.064~T MRI Scanner

Purpose: To demonstrate the feasibility of whole-brain multidimensional T1-T2 relaxation imaging on a portable 0.064 T MRI scanner. Methods: A two-dimensional inversion-recovery, fast spin-echo acquisition was used to jointly encode T1 and T2 relaxation. Joint relaxation distributions were reconstructed voxel-wise using marginal-distribution constrained optimization (MADCO). The approach was evaluated in a quantitative relaxation MRI phantom and subsequently applied in vivo in a healthy volunteer. Joint distributions, marginal distributions, distribution-derived measures, and statistical dependencies between the two relaxation dimensions were examined. Results: Phantom joint relaxation estimates showed good overall agreement with mono-exponential relaxation measurements and previously reported values at 0.064 T. The in vivo acquisition provided whole-brain coverage over a broad range of relaxation weightings and tissue contrasts. Reconstructed joint T1-T2 distributions showed spatially organized features across the relaxation space, including broad and overlapping relaxation components that were not fully represented by single-value relaxation maps or by either 1D marginal distribution alone. Selected regions of the joint relaxation space produced component maps with distinct spatial patterns. Statistical analysis further showed a dependence between the two relaxation dimensions, supporting the presence of added information in the joint distribution that is lost when treating T1 and T2 separately. Conclusion: Whole-brain multidimensional T1-T2 relaxation imaging is clinically feasible on a portable 0.064 T MRI scanner. Joint relaxation distributions provide information beyond single-value relaxation mapping and may support further developments of quantitative multidimensional imaging at ultra-low field.

bioengineering↗

bioRxiv2026

Multidimensional diffusion MRI reveals heterogeneous microstructural remodeling associated with amyloid pathology

Alzheimer's disease (AD) pathology involves amyloid deposition, reactive gliosis, and localized tissue alterations that coexist within the same brain regions, creating heterogeneous microstructural environments within individual imaging voxels. Conventional diffusion MRI averages these environments into aggregate measures, potentially obscuring their distinct contributions. Frequency-dependent multidimensional MRI ({omega}MD-MRI) resolves distributions of water components with different diffusion length scales, anisotropies, and relaxation properties, providing sensitivity to microstructural restriction, heterogeneity, and shape-size correlations within a voxel. Whether these measurements reveal microstructural complexity associated with AD pathology remains unclear. Here, we performed {omega}MD-MRI on ex vivo brain specimens from approximately 8-month-old 5xFAD and wild-type mice and interpreted the imaging findings alongside complementary histology. {omega}MD-MRI revealed widespread but spatially nonuniform differences between 5xFAD and wild-type brains. Measurements sensitive to microstructural restriction, heterogeneity, and shape-size correlations consistently indicated greater microstructural heterogeneity in 5xFAD brains, with the most prominent differences in the hippocampal formation and major cerebral white matter tracts. Complementary qualitative histology demonstrated extensive amyloid deposition and glial activation in affected regions, while overall cytoarchitecture and myelin organization remained largely preserved. Thus, the {omega}MD-MRI abnormalities occurred in tissue characterized by multiple coexisting pathological and relatively preserved microstructural environments rather than widespread structural degeneration. These findings demonstrate that {omega}MD-MRI can reveal the spatial and microstructural heterogeneity associated with amyloid pathology and provide a more comprehensive characterization of AD-related tissue alterations.

neuroscience↗

bioRxiv2026

Separable multidimensional MRI signatures of cellular and structural pathology in Alzheimer's disease

Cognitive decline in Alzheimers disease (AD) reflects progressive disruption of cellular and microstructural organization, yet the biological specificity of MRI signals remains incompletely understood. Multidimensional diffusion-relaxation MRI (MD-MRI) resolves sub-voxel tissue heterogeneity, offering a potential framework to link imaging signals to underlying pathology. We tested the hypothesis that neuronal, glial and white matter pathologies in AD occupy separable regions of diffusion-relaxation space and generate spatially organized imaging signatures linked to cognitive impairment. We integrated ex vivo MD-MRI with co-registered histology from 12 human donors spanning a range of Braak stages and pathological severity. Using nested cross-validated elastic net modeling, we predicted voxelwise A{beta}, pTau, microglia and myelin burden from the multidimensional diffusion-relaxation density distribution. Regional associations were assessed across hippocampal subfields and white matter, and clinical relevance was evaluated by relating MRI-predicted pathology to Mini-Mental State Examination (MMSE) scores. Distinct diffusion-relaxation components were preferentially associated with different pathological markers, indicating separable microstructural signatures. Voxelwise MRI-derived predictions were significantly associated with histological measures of myelin ({rho} = 0.77), pTau ({rho} = 0.62), and microglia ({rho} = 0.61), with weaker correspondence for A{beta} ({rho} = 0.45). Regionally, predicted pathology recapitulated known patterns of selective vulnerability, with elevated pTau and microglial signal in hippocampal subfields and dominant myelin-associated signal in white matter (p < 0.0001). Importantly, higher predicted pTau density in the hippocampus was strongly associated with worse cognitive performance ({rho} = -0.88, p = 0.0014), with a moderate association in white matter ({rho} = -0.66, p = 0.036), suggesting that tau-related microstructural alterations within both gray and white matter contribute to cognitive impairment. By directly linking multidimensional MRI signatures to histologically verified cellular pathology, this study demonstrates that AD-related processes manifest as distinct and spatially organized diffusion-relaxation signatures. These findings provide mechanistic insight into the microstructural basis of MRI contrasts and support the potential of MD-MRI to map regionally specific neuropathological processes in AD. As clinically feasible MD-MRI acquisition protocols continue to emerge, translation of these spectral signatures to in vivo imaging may enable more mechanistically informed assessment of aging and dementia.

neuroscience↗

bioRxiv2026

Multidimensional MRI reveals cellular-scale microstructural phenotypes in human brain aging

Brain aging is accompanied by profound cellular and microstructural changes that precede overt tissue loss, yet in vivo MRI studies largely emphasize macroscopic measures or isolated diffusion and relaxation metrics, providing limited insight into how cellular-scale tissue architecture is altered across the adult lifespan. Here, we apply multidimensional diffusion-relaxation MRI (MD-MRI) to map voxel-wise microstructural phenotypes in cognitively unimpaired adults spanning early adulthood to late life (23-77 years). Rather than relying on predefined compartment models, MD-MRI resolves continuous voxel-wise distributions in a joint diffusion-relaxation space, enabling an integrated, model-free description of how cellular shape, size, restriction, and chemical environment vary with age. Using this approach, we reveal age-related multilateral shifts within a complex microstructural landscape, marked by increasing heterogeneity and disorder across brain tissue. With age, cellular-scale features showed a systematic transition from small to larger length-scale structures accompanied by reduced microscopic restriction, indicating a loss of fine cellular barriers and expansion of extracellular space. In parallel, we show tissue-dependent alterations in fast-relaxing properties aligned with known gray- and white-matter aging processes, including iron accumulation and myelin loss. Together, these findings indicate that normative brain aging involves progressive reorganization of structure and composition at the cellular level, rather than uniform shifts in bulk tissue properties. By decoupling cellular-scale shape, size, restriction, and chemical environment in vivo, MD-MRI identifies increasing cellular heterogeneity and breakdown of microscopic restriction as central features of human brain aging and provides a biologically interpretable framework for linking microstructural reorganization to age-related functional decline.

neuroscience↗

bioRxiv2025

Widespread gray and white matter microstructural alterations in dual cognitive-motor impairment

INTRODUCTIONDual cognitive-motor impairment in aging is a strong predictor of dementia, yet its effects on vulnerable gray matter regions microstructure remain unexplored. METHODSThis study classified 582 individuals aged 36-90 into cognitive-motor impairment, isolated cognitive or motor impairment, and control groups. Microstructural differences in 27 temporal and motor-related gray matter regions and white matter tracts were assessed using DTI and mean apparent propagator (MAP-MRI), a technique well-suited for gray matter analysis. RESULTSWe found widespread microstructural alterations in gray and white matter among individuals with dual cognitive-motor impairment. These changes were not observed in isolated cognitive or motor impairment after multiple comparisons correction. DISCUSSIONDual cognitive-motor impairment is associated with reduced cellular density in temporal gray matter, decreased fiber coherence, and potential demyelination in white matter tracts, suggesting widespread microstructural disruption. These findings could help understand brain aging and facilitate interventions to slow neurodegeneration and delay dementia onset.

neuroscience↗

bioRxiv2025

Data Processing in Multidimensional MRI For BiomarkerIdentification: Is It Necessary?

Multidimensional MRI (MD-MRI) is an emerging technique that holds promise for identifying tissue characteristics that could be indicative of pathologies. Before these characteristics can be interpreted, MD-MRI measurements are converted into an spectrum. These spectra are then utilized to obtain some understanding of the underlying tissue microstructure, often through the use of statistical, machine learning, and mathematical modeling methods. The aim of this study was to compare outcomes of using unprocessed MDMRI signals for statistical regression in comparison to the corresponding spectra. Backed by a theoretical argument, we described an experimental procedure regressing both MDMRI signals and spectra to histological outcomes intrasubject. Through using multiple conventional ML methods, and a proposed method using convex sets, we aimed to see which yielded the highest accuracy. Both theory and experimental evidence suggest that, without a priori information, statistical regression was best performed on the MDMRI signal. We conclude, barring any a priori information regarding tissue changes, there is no significant advantage to performing regression analysis on reconstructed spectra in the process of biomarker identification.

bioengineering↗

bioRxiv2025

Ex vivo massively multidimensional diffusion-relaxation correlation MRI: scan-rescan reproducibility and caveats

Massively multidimensional diffusion-relaxation correlation MRI (MMD-MRI) provides information beyond the traditional voxel-averaged metric that may better characterize the microstructural characteristics of biological tissues. MMD-MRI reproducibility has been established in clinical settings, but has yet to be thoroughly evaluated under preclinical conditions, where superior hardware and modulated gradient waveforms enhance its performance. In this study, we investigate the reproducibility of MMD-MRI on a micro-imaging system using ex vivo mouse brains. Notably, the estimated signal fractions of intra-voxel spectral components in the MD-MRI distribution, corresponding to white and gray matter, along with the frequency-dependent parameters, demonstrated high reproducibility. We identified bias between scan and rescan in some of the metrics, which we attribute to the time gap between repeated scans pointing to a long-time progressive fixation effect. We compare our results with in vivo results from clinical scanners and show the reproducibility of diffusion frequency-dependent metrics to benefit from the improved gradient hardware on our preclinical setup. Our results inform future micro-imaging ex vivo MMD-MRI studies of the reproducibility of MMD-MRI metrics and their dependence on fixation time.

biophysics↗

bioRxiv2024

The variability of multidimensional diffusion-relaxation MRI estimates in the human brain

Diffusion-relaxation correlation multidimensional MRI (MD-MRI) replaces voxel-averaged diffusion tensor quantities and R1 and R2 relaxation rates with their multidimensional distributions, enabling the selective extraction and mapping of specific diffusion-relaxation spectral ranges that correspond to different cellular features. This approach has the potential of achieving high sensitivity and specificity in detecting subtle changes that would otherwise be averaged out. Here, the whole brain characterization of MD-MRI distributions and derived parameters is presented and the intrascanner test-retest reliability, repeatability, and reproducibility are evaluated to promote the further development of these quantities as neuroimaging biomarkers. We compared white matter tracts and cortical and subcortical gray matter regions, revealing notable variations in their diffusion-relaxation profiles, indicative of unique microscopic morphological characteristics. We found that the reliability and repeatability of MD-MRI-derived diffusion and relaxation mean parameters were comparable to values expected in conventional diffusion tensor imaging and relaxometry studies. Importantly, the estimated signal fractions of intra-voxel spectral components in the MD-MRI distribution, corresponding to white matter, gray matter, and cerebrospinal fluid, were found to be reproducible. This underscores the viability of employing a spectral analysis approach to MD-MRI data. Our results show that a clinically feasible MD-MRI protocol can reliably deliver information of the rich structural and chemical variety that exists within each imaging voxel, creating potential for new MRI biomarkers with enhanced sensitivity and specificity.

neuroscience↗

bioRxiv2024

Resiliency to Alzheimer's disease neuropathology can be distinguished from dementia using cortical astrogliosis imaging

Despite the presence of significant Alzheimers disease (AD) pathology, characterized by amyloid {beta} (A{beta}) plaques and phosphorylated tau (pTau) tangles, some cognitively normal elderly individuals do not inevitably develop dementia. These findings give rise to the notion of cognitive resilience, suggesting maintained cognitive function despite the presence of AD neuropathology, highlighting the influence of factors beyond classical pathology. Cortical astroglial inflammation, a ubiquitous feature of symptomatic AD, shows a strong correlation with cognitive impairment severity, potentially contributing to the diversity of clinical presentations. However, noninvasively imaging neuroinflammation, particularly astrogliosis, using MRI remains a significant challenge. Here we sought to address this challenge and to leverage multidimensional (MD) MRI, a powerful approach that combines relaxation with diffusion MR contrasts, to map cortical astrogliosis in the human brain by accessing sub-voxel information. Our goal was to test whether MD-MRI can map astroglial pathology in the cerebral cortex, and if so, whether it can distinguish cognitive resiliency from dementia in the presence of hallmark AD neuropathological changes. We adopted a multimodal approach by integrating histological and MRI analyses using human postmortem brain samples. Ex vivo cerebral cortical tissue specimens derived from three groups comprised of non-demented individuals with significant AD pathology postmortem, individuals with both AD pathology and dementia, and non-demented individuals with minimal AD pathology postmortem as controls, underwent MRI at 7 T. We acquired and processed MD-MRI, diffusion tensor, and quantitative T1 and T2 MRI data, followed by histopathological processing on slices from the same tissue. By carefully co-registering MRI and microscopy data, we performed quantitative multimodal analyses, leveraging targeted immunostaining to assess MD-MRI sensitivity and specificity towards A{beta}, pTau, and glial fibrillary acidic protein (GFAP), a marker for astrogliosis. Our findings reveal a distinct MD-MRI signature of cortical astrogliosis, enabling the creation of predictive maps for cognitive resilience amid AD neuropathological changes. Multiple linear regression linked histological values to MRI changes, revealing that the MD-MRI cortical astrogliosis biomarker was significantly associated with GFAP burden (standardized {beta}=0.658, pFDR<0.0001), but not with A{beta} (standardized {beta}=0.009, pFDR=0.913) or pTau (standardized {beta}=-0.196, pFDR=0.051). Conversely, none of the conventional MRI parameters showed significant associations with GFAP burden in the cortex. While the extent to which pathological glial activation contributes to neuronal damage and cognitive impairment in AD is uncertain, developing a noninvasive imaging method to see its affects holds promise from a mechanistic perspective and as a potential predictor of cognitive outcomes.

neuroscience↗

bioRxiv2024

Neuronal microstructural changes in the human brain are associated with neurocognitive aging

Gray matter (GM) alterations play a role in aging-related disorders like Alzheimers disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 unimpaired participants (394 female; median age = 58, range = 36-90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.

neuroscience↗

bioRxiv2023

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency,{omega} , in addition to the diffusion tensor, D, and relaxation, R1, R2, correlations. A D({omega})-R1-R2 clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D({omega})-R1-R2 distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

neuroscience↗

bioRxiv2022

Novel Pore Size-Controlled, Susceptibility Matched, 3D-Printed MRI Phantoms

Diffusion magnetic resonance imaging (dMRI) methods are commonly employed to infer changes in tissue microstructure. Quantities like the apparent diffusion coefficient (mADC), and the fractional anisotropy (FA), derived from diffusion tensor imaging (DTI) data, characterize voxel-averaged diffusion properties, whereas double pulse field gradient (dPFG) or double diffusion encoded (DDE) MR methods can be used to characterize heterogeneous diffusion processes occurring within the voxel. Owing to its unique modular design, our novel 3D-printed dMRI phantom exhibits both macroscopic and microscopic anisotropy and can serve to calibrate measures of them. Our phantom susceptibility is close to that of waters, enabling fast diffusion weighted echo-planar image (DW-EPI) acquisitions to be used to scan it. 3D printed microstructures offer a new medium with which to vet and validate theoretical models of diffusion and pipelines used to estimate it. HighlightsO_LIResearch highlight 1: We report the design concept and fabrication of dimensionally stable, uniformly oriented blocks or modules that can be assembled into large-scale MRI phantoms. Waffle-like structures containing blocks of aligned microcapillaries can be stacked into even larger arrays to construct diameter distribution phantoms, or fractured, to create a "powder-averaged" emulsion of randomly oriented blocks. C_LIO_LIResearch highlight 2: This phantom can be used to vet and calibrate various MRI methods, such as DTI, AxCaliber MRI, MAP-MRI, and various multiple pulsed field gradient (PFG) or multiple diffusion-encoded microstructure imaging methods. C_LI Graphical Abstract

biophysics↗

bioRxiv2022

Astrogliosis mapping in individual brains using multidimensional MRI

There are currently no noninvasive imaging methods available for astrogliosis mapping in the central nervous system despite its essential role in the response to injury, disease, and infection. We have developed a machine learning-based multidimensional MRI framework that provides a signature of astrogliosis, distinguishing it from normative brain at the individual level. We investigated ex vivo cortical tissue specimen derived from subjects who sustained blast induced injuries, which resulted in scar-border forming astrogliosis without being accompanied by other types of neuropathology. By performing a combined postmortem radiology and histopathology correlation study we found that astrogliosis induces microstructural changes that are robustly detected using our framework, resulting in MRI neuropathology maps that are significantly and strongly correlated with co-registered histological images of increased glial fibrillary a cidic protein deposition. The demonstrated high spatial sensitivity in detecting reactive astrocytes at the individual level has great potential to significantly impact neuroimaging studies in diseases, injury, repair, and aging.

neuroscience↗

bioRxiv2021

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.

neuroscience↗

bioRxiv2020

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

We describe a practical two-dimensional (2D) diffusion MRI framework to deliver specificity and improve sensitivity to axonal injury in the spinal cord. This approach provides intravoxel distributions of correlations of water mobilities in orthogonal directions, revealing sub-voxel diffusion components. Here we use it to investigate water diffusivities along axial and radial orientations within spinal cord specimens with confirmed, tract-specific axonal injury. First, we show using transmission electron microscopy and immunohistochemistry that tract-specific axonal beading occurs following Wallerian degeneration in the cortico-spinal tract as direct sequelae to closed head injury. We demonstrate that although some voxel-averaged diffusion tensor imaging (DTI) metrics are sensitive to this axonal injury, they are non-specific, i.e., they do not reveal an underlying biophysical mechanism of injury. Then we employ 2D diffusion correlation imaging (DCI) to improve discrimination of different water microenvironments by measuring and mapping the joint water mobility distributions perpendicular and parallel to the spinal cord axis. We determine six distinct diffusion spectral components that differ according to their microscopic anisotropy and mobility. We show that at the injury site a highly anisotropic diffusion component completely disappears and instead becomes more isotropic. Based on these findings, an injury-specific MR image of the spinal cord was generated, and a radiological-pathological correlation with histological silver staining % area was performed. The resulting strong and significant correlation (r = 0.70, p < 0.0001) indicates the high specificity with which DCI detects injury-induced tissue alterations. We predict that the ability to selectively image microstructural changes following axonal injury in the spinal cord can be useful in clinical and research applications by enabling specific detection and increased sensitivity to injury-induced microstructural alterations. These results also encourage us to translate DCI to higher spatial dimensions to enable assessment of traumatic axonal injury, and possibly other diseases and disorders in the brain.

neuroscience↗

bioRxiv2020

Limits to flow detection in pulsed gradient spin echo NMR

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 [Formula] rather than the velocity encoding parameter venc = {pi}/(q{Delta}). The minimum detectable mean velocity using the difference between the phase at +qslow and -qslow is [Formula]. 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 {micro}m/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.

biophysics↗

bioRxiv2019

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

We develop magnetic resonance (MR) methods for measuring real-time changes of tissue microstructure and membrane permeability of live and fixed neural tissue. Diffusion and exchange MR measurements are performed using the large 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.

biophysics↗