Sex matters: The MouseX DW-ALLEN Atlas for mice diffusion-weighted MR imaging.

Overcoming sex bias in preclinical research requires not only including animals of both sexes in the experiments, but also developing proper tools to handle such data. Recent work revealed sensitivity of diffusion-weighted MRI to glia morphological changes in response to inflammatory stimuli, opening up exciting possibilities to characterize inflammation in a variety of preclinical models of pathologies, the great majority of them available in mice. However, there are limited resources dedicated to mouse imaging, like those required for the data processing and analysis. To fill this gap, we build a mouse MRI template of both structural and diffusion contrasts, with anatomical annotation according to the Allen Mouse Brain Atlas, the most detailed public resource for mouse brain investigation. To achieve a standardized resource, we use a large cohort of animals in vivo, and include animals of both sexes. To prove the utility of this resource to integrate imaging and molecular data, we demonstrate significant association between the mean diffusivity from MRI and gene expression-based glia density. To demonstrate the need of equitable sex representation, we compared across sexes the warp fields needed to match a male-based template, and our template built with both sexes. Then, we use both templates for analysing mice imaging data obtained in animals of different ages, demonstrating that using a male-based template creates spurious significant sex effects, not present otherwise. All in all, our MouseX DW-ALLEN Atlas will be a widely useful resource getting us one step closer to equitable healthcare.

Repetitive deep TMS in alcohol dependent patients halts progression of white matter changes in early abstinence.

AIM: Alcohol use disorder (AUD) is the most prevalent form of addiction, with a great burden on society and limited treatment options. A recent clinical trial reported significant clinical benefits of deep transcranial magnetic stimulations (Deep TMS) targeting midline frontocortical areas. However, the underlying biological substrate remained elusive. Here, we report the effect of Deep TMS on the microstructure of white matter. METHODS: A total of 37 (14 females) AUD treatment-seeking patients were randomized to sham or active Deep TMS. Twenty (six females) age-matched healthy controls were included. White matter integrity was evaluated by fractional anisotropy (FA). Secondary measures included brain functional connectivity and self-reports of craving and drinking units in the 3 months of follow-up period. RESULTS: White matter integrity was compromised in patients with AUD relative to healthy controls, as reflected by the widespread reduction in FA. This alteration progressed during early abstinence (3 weeks) in the absence of Deep TMS. However, stimulation of midline frontocortical areas arrested the progression of FA changes in association with decreased craving and relapse scores. Reconstruction of axonal tracts from white-matter regions showing preserved FA values identified cortical regions in the posterior cingulate and dorsomedial prefrontal cortices where functional connectivity was persistently modulated. These effects were absent in the sham-stimulated group. CONCLUSIONS: By integrating brain structure and function to characterize the alcohol-dependent brain, this study provides mechanistic insights into the TMS effect, pointing to myelin plasticity as a possible mediator.

Multishell diffusion MRI reveals whole-brain white matter changes in HIV.

Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) have been previously used to explore white matter related to human immunodeficiency virus (HIV) infection. While DTI and DKI suffer from low specificity, the Combined Hindered and Restricted Model of Diffusion (CHARMED) provides additional microstructural specificity. We used these three models to evaluate microstructural differences between 35 HIV-positive patients without neurological impairment and 20 healthy controls who underwent diffusion-weighted imaging using three b-values. While significant group effects were found in all diffusion metrics, CHARMED and DKI analyses uncovered wider involvement (80% vs. 20%) of all white matter tracts in HIV infection compared with DTI. In restricted fraction (FR) analysis, we found significant differences in the left corticospinal tract, middle cerebellar peduncle, right inferior cerebellar peduncle, right corticospinal tract, splenium of the corpus callosum, left superior cerebellar peduncle, left superior cerebellar peduncle, pontine crossing tract, left posterior limb of the internal capsule, and left/right medial lemniscus. These are involved in language, motor, equilibrium, behavior, and proprioception, supporting the functional integration that is frequently impaired in HIV-positivity. Additionally, we employed a machine learning algorithm (XGBoost) to discriminate HIV-positive patients from healthy controls using DTI and CHARMED metrics on an ROIwise basis, and unique contributions to this discrimination were examined using Shapley Explanation values. The CHARMED and DKI estimates produced the best performance. Our results suggest that biophysical multishell imaging, combining additional sensitivity and built-in specificity, provides further information about the brain microstructural changes in multimodal areas involved in attentive, emotional and memory networks often impaired in HIV patients.

Dynamics of White Matter Plasticity Underlying Working Memory Training: Multimodal Evidence from Diffusion MRI and Relaxometry.

Adaptive working memory (WM) training may lead to cognitive benefits that are associated with white matter plasticity in parietofrontal networks, but the underlying mechanisms remain poorly understood. We investigated white matter microstructural changes after adaptive WM training relative to a nonadaptive comparison group. Microstructural changes were studied in the superior longitudinal fasciculus, the main parietofrontal connection, and the cingulum bundle as a comparison pathway. MRI-based metrics were the myelin water fraction and longitudinal relaxation rate R1 from multicomponent relaxometry (captured with the mcDESPOT approach) as proxy metrics of myelin, the restricted volume fraction from the composite hindered and restricted model of diffusion as an estimate of axon morphology, and fractional anisotropy and radial diffusivity from diffusion tensor imaging. PCA was used for dimensionality reduction. Adaptive training was associated with benefits in a "WM capacity" component and increases in a microstructural component (increases in R1, restricted volume fraction, fractional anisotropy, and reduced radial diffusivity) that predominantly loaded on changes in the right dorsolateral superior longitudinal fasciculus and the left parahippocampal cingulum. In contrast, nonadaptive comparison activities were associated with the opposite pattern of reductions in WM capacity and microstructure. No group differences were observed for the myelin water fraction metric suggesting that R1 was a more sensitive "myelin" index. These results demonstrate task complexity and location-specific white matter microstructural changes that are consistent with tissue alterations underlying myelination in response to training.

Including diffusion time dependence in the extra-axonal space improves in vivo estimates of axonal diameter and density in human white matter.

Axonal density and diameter are two fundamental properties of brain white matter. Recently, advanced diffusion MRI techniques have made these two parameters accessible in vivo. However, the techniques available to estimate such parameters are still under development. For example, current methods to map axonal diameters capture relative trends over different structures, but consistently over-estimate absolute diameters. Axonal density estimates are more accessible experimentally, but different modeling approaches exist and the impact of the experimental parameters has not been thoroughly quantified, potentially leading to incompatibility of results obtained in different studies using different techniques. Here, we characterise the impact of diffusion time on axonal density and diameter estimates using Monte Carlo simulations and STEAM diffusion MRI at 7 T on 9 healthy volunteers. We show that axonal density and diameter estimates strongly depend on diffusion time, with diameters almost invariably overestimated and density both over and underestimated for some commonly used models. Crucially, we also demonstrate that these biases are reduced when the model accounts for diffusion time dependency in the extra-axonal space. For axonal density estimates, both upward and downward bias in different situations are removed by modeling extra-axonal time-dependence, showing increased accuracy in these estimates. For axonal diameter estimates, we report increased accuracy in ground truth simulations and axonal diameter estimates decreased away from high values given by earlier models and towards known values in the human corpus callosum when modeling extra-axonal time-dependence. Axonal diameter feasibility under both advanced and clinical settings is discussed in the light of the proposed advances.

T1 relaxometry of crossing fibres in the human brain.

A comprehensive tract-based characterisation of white matter should include the ability to quantify myelin and axonal attributes irrespective of the complexity of fibre organisation within the voxel. Recently, a new experimental framework that combines inversion recovery and diffusion MRI, called inversion recovery diffusion tensor imaging (IR-DTI), was introduced and applied in an animal study. IR-DTI provides the ability to assign to each unique fibre population within a voxel a specific value of the longitudinal relaxation time, T1, which is a proxy for myelin content. Here, we apply the IR-DTI approach to the human brain in vivo on 7 healthy subjects for the first time. We demonstrate that the approach is able to measure differential tract properties in crossing fibre areas, reflecting the different myelination of tracts. We also show that tract-specific T1 has less inter-subject variability compared to conventional T1 in areas of crossing fibres, suggesting increased specificity to distinct fibre populations. Finally we show in simulations that changes in myelination selectively affecting one fibre bundle in crossing fibre areas can potentially be detected earlier using IR-DTI.

Resolving relaxometry and diffusion properties within the same voxel in the presence of crossing fibres by combining inversion recovery and diffusion-weighted acquisitions.

PURPOSE: A comprehensive image-based characterization of white matter should include the ability to quantify myelin and axonal attributes irrespective of the complexity of fibre organization within the voxel. While progress has been made with diffusion MRI-based approaches to measure axonal morphology, to date available myelin metrics simply assign a single scalar value to the voxel, reflecting some form of average of its constituent fibres. Here, a new experimental framework that combines diffusion MRI and relaxometry is introduced. It provides, for the first time, the ability to assign to each unique fibre system within a voxel, a unique value of the longitudinal relaxation time, T1, which is largely influenced by the myelin content. METHODS: We demonstrate the method through simulations, in a crossing fibres phantom, in fixed brains and in vivo. RESULTS: The method is capable of recovering unique values of T1 for each fibre population. CONCLUSION: The ability to extract fibre-specific relaxometry properties will provide enhanced specificity and, therefore, sensitivity to differences in white matter architecture, which will be invaluable in many neuroimaging studies. Further the enhanced specificity should ultimately lead to earlier diagnosis and access to treatment in a range of white matter diseases where axons are affected.

Why diffusion tensor MRI does well only some of the time: variance and covariance of white matter tissue microstructure attributes in the living human brain.

Fundamental to increasing our understanding of the role of white matter microstructure in normal/abnormal function in the living human is the development of MR-based metrics that provide increased specificity to distinct attributes of the white matter (e.g., local fibre architecture, axon morphology, and myelin content). In recent years, different approaches have been developed to enhance this specificity, and the Tractometry framework was introduced to combine the resulting multi-parametric data for a comprehensive assessment of white matter properties. The present work exploits that framework to characterise the statistical properties, specifically the variance and covariance, of these advanced microstructural indices across the major white matter pathways, with the aim of giving clear indications on the preferred metric(s) given the specific research question. A cohort of healthy subjects was scanned with a protocol that combined multi-component relaxometry with conventional and advanced diffusion MRI acquisitions to build the first comprehensive MRI atlas of white matter microstructure. The mean and standard deviation of the different metrics were analysed in order to understand how they vary across different brain regions/individuals and the correlation between them. Characterising the fibre architectural complexity (in terms of number of fibre populations in a voxel) provides clear insights into correlation/lack of correlation between the different metrics and explains why DT-MRI is a good model for white matter only some of the time. The study also identifies the metrics that account for the largest inter-subject variability and reports the minimal sample size required to detect differences in means, showing that, on the other hand, conventional DT-MRI indices might still be the safest choice in many contexts.

A translational MRI approach to validate acute axonal damage detection as an early event in multiple sclerosis.

Axonal degeneration is a central pathological feature of multiple sclerosis and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity and clinical applicability, and by the lack of proper validation. We aimed to validate an MRI framework based on multicompartment modeling of the diffusion signal (AxCaliber) in rats in the presence of axonal pathology, achieved through injection of a neurotoxin damaging the neuronal terminal of axons. We then applied the same MRI protocol to map axonal integrity in the brain of multiple sclerosis relapsing-remitting patients and age-matched healthy controls. AxCaliber is sensitive to acute axonal damage in rats, as demonstrated by a significant increase in the mean axonal caliber along the targeted tract, which correlated with neurofilament staining. Electron microscopy confirmed that increased mean axonal diameter is associated with acute axonal pathology. In humans with multiple sclerosis, we uncovered a diffuse increase in mean axonal caliber in most areas of the normal-appearing white matter, preferentially affecting patients with short disease duration. Our results demonstrate that MRI-based axonal diameter mapping is a sensitive and specific imaging biomarker that links noninvasive imaging contrasts with the underlying biological substrate, uncovering generalized axonal damage in multiple sclerosis as an early event.

The CONNECT project: Combining macro- and micro-structure.

In recent years, diffusion MRI has become an extremely important tool for studying the morphology of living brain tissue, as it provides unique insights into both its macrostructure and microstructure. Recent applications of diffusion MRI aimed to characterize the structural connectome using tractography to infer connectivity between brain regions. In parallel to the development of tractography, additional diffusion MRI based frameworks (CHARMED, AxCaliber, ActiveAx) were developed enabling the extraction of a multitude of micro-structural parameters (axon diameter distribution, mean axonal diameter and axonal density). This unique insight into both tissue microstructure and connectivity has enormous potential value in understanding the structure and organization of the brain as well as providing unique insights to abnormalities that underpin disease states. The CONNECT (Consortium Of Neuroimagers for the Non-invasive Exploration of brain Connectivity and Tracts) project aimed to combine tractography and micro-structural measures of the living human brain in order to obtain a better estimate of the connectome, while also striving to extend validation of these measurements. This paper summarizes the project and describes the perspective of using micro-structural measures to study the connectome.

Alcohol-induced damage to the fimbria/fornix reduces hippocampal-prefrontal cortex connection during early abstinence.

INTRODUCTION: Alcohol dependence is characterized by a gradual reduction in cognitive control and inflexibility to contingency changes. The neuroadaptations underlying this aberrant behavior are poorly understood. Using an animal model of alcohol use disorders (AUD) and complementing diffusion-weighted (dw)-MRI with quantitative immunohistochemistry and electrophysiological recordings, we provide causal evidence that chronic intermittent alcohol exposure affects the microstructural integrity of the fimbria/fornix, decreasing myelin basic protein content, and reducing the effective communication from the hippocampus (HC) to the prefrontal cortex (PFC). Using a simple quantitative neural network model, we show how disturbed HC-PFC communication may impede the extinction of maladaptive memories, decreasing flexibility. Finally, combining dw-MRI and psychometric data in AUD patients, we discovered an association between the magnitude of microstructural alteration in the fimbria/fornix and the reduction in cognitive flexibility. Overall, these findings highlight the vulnerability of the fimbria/fornix microstructure in AUD and its potential contribution to alcohol pathophysiology. Fimbria vulnerability to alcohol underlies hippocampal-prefrontal cortex dysfunction and correlates with cognitive impairment.

Using the biophysical CHARMED model to elucidate the underpinnings of contrast in diffusional kurtosis analysis of diffusion-weighted MRI.

OBJECT: The aim of this work was to understand biophysical substrate underpinning contrast in diffusional kurtosis imaging (DKI) in white matter, using the composite hindered and restricted model of diffusion (CHARMED). MATERIALS AND METHODS: A theoretical relationship between the kurtosis function K and the CHARMED parameters, i.e., the restricted volume fraction RF and the axonal longitudinal diffusivity D was derived for the propagator used in the CHARMED model. Evidence for a similar correlation between these measures was then investigated in vivo across different WM regions in five healthy young subjects that underwent a CHARMED protocol at 3T. RESULTS: Our theoretical treatment shows that K has an increasing trend for both increasing RF values and increasing D. In vivo, a significant positive correlation (P < 0.001) was found between the kurtosis orthogonal to the fibre orientation K (⊥) and RF. A multilinear regression showed that K (⊥) values are better explained by a mixed contribution of both RF and D. CONCLUSIONS: The CHARMED model was used to understand whether and where DKI contrast can be explained in terms of the underlying axonal geometry. This work demonstrates that the information contained in DKI overlaps with the information extracted by CHARMED in areas of higher intra-voxel directional coherence.

Mapping microglia and astrocyte activation in vivo using diffusion MRI.

While glia are increasingly implicated in the pathophysiology of psychiatric and neurodegenerative disorders, available methods for imaging these cells in vivo involve either invasive procedures or positron emission tomography radiotracers, which afford low resolution and specificity. Here, we present a noninvasive diffusion-weighted magnetic resonance imaging (MRI) method to image changes in glia morphology. Using rat models of neuroinflammation, degeneration, and demyelination, we demonstrate that diffusion-weighted MRI carries a fingerprint of microglia and astrocyte activation and that specific signatures from each population can be quantified noninvasively. The method is sensitive to changes in glia morphology and proliferation, providing a quantitative account of neuroinflammation, regardless of the existence of a concomitant neuronal loss or demyelinating injury. We prove the translational value of the approach showing significant associations between MRI and histological microglia markers in humans. This framework holds the potential to transform basic and clinical research by clarifying the role of inflammation in health and disease.

Citrate Regulates the Saccharomyces cerevisiae Mitochondrial GDP/GTP Carrier (Ggc1p) by Triggering Unidirectional Transport of GTP.

The yeast mitochondrial transport of GTP and GDP is mediated by Ggc1p, a member of the mitochondrial carrier family. The physiological role of Ggc1p in S. cerevisiae is probably to transport GTP into mitochondria in exchange for GDP generated in the matrix. ggc1Δ cells exhibit lower levels of GTP and increased levels of GDP in mitochondria, are unable to grow on nonfermentable substrates and lose mtDNA. Because in yeast, succinyl-CoA ligase produces ATP instead of GTP, and the mitochondrial nucleoside diphosphate kinase is localized in the intermembrane space, Ggc1p is the only supplier of mitochondrial GTP required for the maturation of proteins containing Fe-S clusters, such as aconitase [4Fe-4S] and ferredoxin [2Fe-2S]. In this work, it was demonstrated that citrate is a regulator of purified and reconstituted Ggc1p by trans-activating unidirectional transport of GTP across the proteoliposomal membrane. It was also shown that the binding site of Ggc1p for citrate is different from the binding site for the substrate GTP. It is proposed that the citrate-induced GTP uniport (CIGU) mediated by Ggc1p is involved in the homeostasis of the guanine nucleotide pool in the mitochondrial matrix.

Diffusion-weighted MRI in neurodegenerative and psychiatric animal models: Experimental strategies and main outcomes.

Preclinical MRI approaches constitute a key tool to study a wide variety of neurological and psychiatric illnesses, allowing a more direct investigation of the disorder substrate and, at the same time, the possibility of back-translating such findings to human subjects. However, the lack of consensus on the optimal experimental scheme used to acquire the data has led to relatively high heterogeneity in the choice of protocols, which can potentially impact the comparison between results obtained by different groups, even using the same animal model. This is especially true for diffusion-weighted MRI data, where certain experimental choices can impact not only on the accuracy and precision of the extracted biomarkers, but also on their biological meaning. With this in mind, we extensively examined preclinical imaging studies that used diffusion-weighted MRI to investigate neurodegenerative, neurodevelopmental and psychiatric disorders in rodent models. In this review, we discuss the main findings for each preclinical model, with a special focus on the analysis and comparison of the different acquisition strategies used across studies and their impact on the heterogeneity of the findings.

Multishell diffusion imaging reveals sex-specific trajectories of early white matter degeneration in normal aging.

During aging, human white matter (WM) is subject to dynamic structural changes which have a deep impact on healthy and pathological evolution of the brain through the lifespan; characterizing this pattern is of key importance for understanding brain development, maturation, and aging as well as for studying its pathological alterations. Diffusion magnetic resonance imaging (MRI) can provide a quantitative assessment of the white-matter microstructural organization that characterizes these trajectories. Here, we use both conventional and advanced diffusion MRI in a cohort of 91 individuals (age range: 13-62 years) to study region- and sex-specific features of WM microstructural integrity in healthy aging. We focus on the age at which microstructural imaging parameters invert their development trend as the time point which marks the onset of microstructural decline in WM. Importantly, our results indicate that age-related brain changes begin earlier in males than females and affect more frontal regions-in accordance with evolutionary theories and numerous evidences across non-MRI domains. Advanced diffusion MRI reveals age-related WM modification patterns which cannot be detected using conventional diffusion tensor imaging.

Gray matter network reorganization in multiple sclerosis from 7-Tesla and 3-Tesla MRI data.

OBJECTIVE: The objective of this study was to determine the ability of 7T-MRI for characterizing brain tissue integrity in early relapsing-remitting MS patients compared to conventional 3T-MRI and to investigate whether 7T-MRI improves the performance for detecting cortical gray matter neurodegeneration and its associated network reorganization dynamics. METHODS: Seven early relapsing-remitting MS patients and seven healthy individuals received MRI at 7T and 3T, whereas 30 and 40 healthy controls underwent separate 3T- and 7T-MRI sessions, respectively. Surface-based cortical thickness (CT) and gray-to-white contrast (GWc) measures were used to model morphometric networks, analyzed with graph theory by means of modularity, clustering coefficient, path length, and small-worldness. RESULTS: 7T-MRI had lower CT and higher GWc compared to 3T-MRI in MS. CT and GWc measures robustly differentiated MS from controls at 3T-MRI. 7T- and 3T-MRI showed high regional correspondence for CT (r = 0.72, P = 2e-78) and GWc (r = 0.83, P = 5.5e-121) in MS patients. MS CT and GWc morphometric networks at 7T-MRI showed higher modularity, clustering coefficient, and small-worldness than 3T, also compared to controls. INTERPRETATION: 7T-MRI allows to more precisely quantify morphometric alterations across the cortical mantle and captures more sensitively MS-related network reorganization. Our findings open new avenues to design more accurate studies quantifying brain tissue loss and test treatment effects on tissue repair.

Chronic alcohol consumption alters extracellular space geometry and transmitter diffusion in the brain.

Already moderate alcohol consumption has detrimental long-term effects on brain function. However, how alcohol produces its potent addictive effects despite being a weak reinforcer is a poorly understood conundrum that likely hampers the development of successful interventions to limit heavy drinking. In this translational study, we demonstrate widespread increased mean diffusivity in the brain gray matter of chronically drinking humans and rats. These alterations appear soon after drinking initiation in rats, persist into early abstinence in both species, and are associated with a robust decrease in extracellular space tortuosity explained by a microglial reaction. Mathematical modeling of the diffusivity changes unveils an increased spatial reach of extrasynaptically released transmitters like dopamine that may contribute to alcohol's progressively enhanced addictive potency.

Radiomicrobiomics: Advancing Along the Gut-brain Axis Through Big Data Analysis.

The gut-brain axis communicates the brain with the gut microbiota, a bidirectional conduit that has received increasing attention in recent years thanks to its emerging role in brain development and function. Alterations in microbiota composition have been associated to neurological and psychiatric disorders, and several studies suggest that the immune system plays a fundamental role in the gut-brain interaction. Recent advances in brain imaging and in microbiome sequencing have generated a large amount of information, yet the data from both these sources need to be combined efficiently to extract biological meaning, and any diagnostic and/or prognostic benefit from these tools. In addition, the causal nature of the gut-brain interaction remains to be fully established, and preclinical findings translated to humans. In this "Perspective" article, we discuss recent efforts to combine data on the gut microbiota with the features that can be obtained from the conversion of brain images into mineable data. The subsequent analysis of these data for diagnostic and prognostic purposes is an approach we call radiomicrobiomics and it holds tremendous potential to enhance our understanding of this fascinating connection.

Detecting Alcohol-Induced Brain Damage Noninvasively Using Diffusion Tensor Imaging.

While alcohol's detrimental effects on the brain are widely acknowledged, diagnostic markers for detection and monitoring alcohol-induced brain damage are lacking. A recent study showed that diffusion tensor imaging can be used to monitor this damage and characterized the progression of the observed changes into early abstinence. Here, we discuss the main findings of that study and highlight current technical limitations which, once addressed, can pave the way to the development of new powerful diagnostic markers for alcohol-induced brain damage.