A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla.

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

Probing muscle recovery following downhill running using precise mapping of MRI T2 relaxation times.

PURPOSE: Postexercise recovery rate is a vital component of designing personalized training protocols and rehabilitation plans. Tracking exercise-induced muscle damage and recovery requires sensitive tools that can probe the muscles' state and composition noninvasively. METHODS: Twenty-four physically active males completed a running protocol consisting of a 60-min downhill run on a treadmill at -10% incline and 65% of maximal heart rate. Quantitative mapping of MRI T2 was performed using the echo-modulation-curve algorithm before exercise, and at two time points: 1 h and 48 h after exercise. RESULTS: T2 values increased by 2%-4% following exercise in the primary mover muscles and exhibited further elevation of 1% after 48 h. For the antagonist muscles, T2 values increased only at the 48-h time point (2%-3%). Statistically significant decrease in the SD of T2 values was found following exercise for all tested muscles after 1 h (16%-21%), indicating a short-term decrease in the heterogeneity of the muscle tissue. CONCLUSION: MRI T2 relaxation time constitutes a useful quantitative marker for microstructural muscle damage, enabling region-specific identification for short-term and long-term systemic processes, and sensitive assessment of muscle recovery following exercise-induced muscle damage. The variability in T2 changes across different muscle groups can be attributed to their different role during downhill running, with immediate T2 elevation occurring in primary movers, followed by delayed elevation in both primary and antagonist muscle groups, presumably due to secondary damage caused by systemic processes.

Estimation of subvoxel fat infiltration in neurodegenerative muscle disorders using quantitative multi-T2 analysis.

MRI's T2 relaxation time is a valuable biomarker for neuromuscular disorders and muscle dystrophies. One of the hallmarks of these pathologies is the infiltration of adipose tissue and a loss of muscle volume. This leads to a mixture of two signal components, from fat and from water, to appear in each imaged voxel, each having a specific T2 relaxation time. In this proof-of-concept work, we present a technique that can separate the signals from water and from fat within each voxel, measure their separate T2 values, and calculate their relative fractions. The echo modulation curve (EMC) algorithm is a dictionary-based technique that offers accurate and reproducible mapping of T2 relaxation times. We present an extension of the EMC algorithm for estimating subvoxel fat and water fractions, alongside the T2 and proton-density values of each component. To facilitate data processing, calf and thigh anatomy were automatically segmented using a fully convolutional neural network and FSLeyes software. The preprocessing included creating two signal dictionaries, for water and for fat, using Bloch simulations of the prospective protocol. Postprocessing included voxelwise fitting for two components, by matching the experimental decay curve to a linear combination of the two simulated dictionaries. Subvoxel fat and water fractions and relaxation times were generated and used to calculate a new quantitative biomarker, termed viable muscle index, and reflecting disease severity. This biomarker indicates the fraction of remaining muscle out of the entire muscle region. The results were compared with those using the conventional Dixon technique, showing high agreement (R = 0.98, p < 0.001). It was concluded that the new extension of the EMC algorithm can be used to quantify abnormal fat infiltration as well as identify early inflammatory processes corresponding to elevation in the T2 value of the water (muscle) component. This new ability may improve the diagnostic accuracy of neuromuscular diseases, help stratification of patients according to disease severity, and offer an efficient tool for tracking disease progression.

Psychophysical Evaluation of Visual vs. Computer-Aided Detection of Brain Lesions on Magnetic Resonance Images.

BACKGROUND: Magnetic resonance imaging (MRI) diagnosis is usually performed by analyzing contrast-weighted images, where pathology is detected once it reached a certain visual threshold. Computer-aided diagnosis (CAD) has been proposed as a way for achieving higher sensitivity to early pathology. PURPOSE: To compare conventional (i.e., visual) MRI assessment of artificially generated multiple sclerosis (MS) lesions in the brain's white matter to CAD based on a deep neural network. STUDY TYPE: Prospective. POPULATION: A total of 25 neuroradiologists (15 males, age 39 ± 9, 9 ± 9.8 years of experience) independently assessed all synthetic lesions. FIELD STRENGTH/SEQUENCE: A 3.0 T, T2 -weighted multi-echo spin-echo (MESE) sequence. ASSESSMENT: MS lesions of varying severity levels were artificially generated in healthy volunteer MRI scans by manipulating T2 values. Radiologists and a neural network were tasked with detecting these lesions in a series of 48 MR images. Sixteen images presented healthy anatomy and the rest contained a single lesion at eight increasing severity levels (6%, 9%, 12%, 15%, 18%, 21%, 25%, and 30% elevation in T2 ). True positive (TP) rates, false positive (FP) rates, and odds ratios (ORs) were compared between radiological diagnosis and CAD across the range lesion severity levels. STATISTICAL TESTS: Diagnostic performance of the two approaches was compared using z-tests on TP rates, FP rates, and the logarithm of ORs across severity levels. A P-value <0.05 was considered statistically significant. RESULTS: ORs of identifying pathology were significantly higher for CAD vis-à-vis visual inspection for all lesions' severity levels. For a 6% change in T2 value (lowest severity), radiologists' TP and FP rates were not significantly different (P = 0.12), while the corresponding CAD results remained statistically significant. DATA CONCLUSION: CAD is capable of detecting the presence or absence of more subtle lesions with greater precision than the representative group of 25 radiologists chosen in this study. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Mapping of magnetic resonance imaging's transverse relaxation time at low signal-to-noise ratio using Bloch simulations and principal component analysis image denoising.

High-resolution mapping of magnetic resonance imaging (MRI)'s transverse relaxation time (T2 ) can benefit many clinical applications by offering improved anatomic details, enhancing the ability to probe tissues' microarchitecture, and facilitating the identification of early pathology. Increasing spatial resolutions, however, decreases data's signal-to-noise ratio (SNR), particularly at clinical scan times. This impairs imaging quality, and the accuracy of subsequent radiological interpretation. Recently, principal component analysis (PCA) was employed for denoising diffusion-weighted MR images and was shown to be effective for improving parameter estimation in multiexponential relaxometry. This study combines the Marchenko-Pastur PCA (MP-PCA) signal model with the echo modulation curve (EMC) algorithm for denoising multiecho spin-echo (MESE) MRI data and improving the precision of EMC-generated single T2 relaxation maps. The denoising technique was validated on simulations, phantom scans, and in vivo brain and knee data. MESE scans were performed on a 3-T Siemens scanner. The acquired images were denoised using the MP-PCA algorithm and were then provided as input for the EMC T2 -fitting algorithm. Quantitative analysis of the denoising quality included comparing the standard deviation and coefficient of variation of T2 values, along with gold standard SNR estimation of the phantom scans. The presented denoising technique shows an increase in T2 maps' precision and SNR, while successfully preserving the morphological features of the tissue. Employing MP-PCA denoising as a preprocessing step decreases the noise-related variability of T2 maps produced by the EMC algorithm and thus increases their precision. The proposed method can be useful for a wide range of clinical applications by facilitating earlier detection of pathologies and improving the accuracy of patients' follow-up.

Age Differences in Recovery Rate Following an Aerobic-Based Exercise Protocol Inducing Muscle Damage Among Amateur, Male Athletes.

Purpose: Compare recovery rates between active young (Y) and middle-aged (MA) males up to 48H post aerobically based, exercise-induced muscle damage (EIMD) protocol. A secondary aim was to explore the relationships between changes in indices associated with EIMD and recovery throughout this timeframe. Methods: Twenty-eight Y (n = 14, 26.1 ± 2.9y, 74.5 ± 9.3 kg) and MA (n = 14, 43.6 ± 4.1y, 77.3 ± 12.9 kg) physically active males, completed a 60-min downhill running (DHR) on a treadmill at -10% incline and at 65% of maximal heart rate (HR). Biochemical, biomechanical, psychological, force production and muscle integrity (using MRI diffusion tensor imaging) markers were measured at baseline, immediately-post, and up to 48H post DHR. Results: During the DHR, HR was lower (p < 0.05) in MA compared to Y, but running pace and distance covered were comparable between groups. No statistical or meaningful differences were observed between groups for any of the outcomes. Yet, Significant (p < 0.05) time-effects within each group were observed: markers of muscle damage, cadence and perception of pain increased, while TNF-a, isometric and dynamic force production and stride-length decreased. Creatine-kinase at 24H-post and 48H-post were correlated (p < 0.05, r range = -0.57 to 0.55) with pain perception, stride-length, and cadence at 24H-post and 48H-post. Significant (p < 0.05) correlations were observed between isometric force production at all time-points and IL-6 at 48H-post DHR (r range = -0.62 to (-0.74). Conclusion: Y and MA active male amateur athletes recover in a comparable manner following an EIMD downhill protocol. These results indicate that similar recovery strategies can be used by trainees from both age groups following an aerobic-based EIMD protocol.

Correcting for imaging gradients-related bias of T2 relaxation times at high-resolution MRI.

PURPOSE: High-resolution animal imaging is an integral part of preclinical drug development and the investigation of diseases' pathophysiology. Quantitative mapping of T2 relaxation times (qT2 ) is a valuable tool for both preclinical and research applications, providing high sensitivity to subtle tissue pathologies. High-resolution T2 mapping, however, suffers from severe underestimation of T2 values due to molecular diffusion. This affects both single-echo and multi-echo spin echo (SSE and MESE), on top of the well-known contamination of MESE signals by stimulated echoes, and especially on high-field and preclinical scanners in which high imaging gradients are used in comparison to clinical scanners. METHODS: Diffusion bias due to imaging gradients was analyzed by quantifying the effective b-value for each coherence pathway in SSE and MESE protocols, and incorporating this information in a joint T2 -diffusion reconstruction algorithm. Validation was done on phantoms and in vivo mouse brain using a 9.4T and a 7T MRI scanner. RESULTS: Underestimation of T2 values due to strong imaging gradients can reach up to 70%, depending on scan parameters and on the sample's diffusion coefficient. The algorithm presented here produced T2 values that agreed with reference spectroscopic measurements, were reproducible across scan settings, and reduced the average bias of T2 values from -33.5 ± 20.5% to -0.1 ± 3.6%. CONCLUSIONS: A new joint T2 -diffusion reconstruction algorithm is able to negate imaging gradient-related underestimation of T2 values, leading to reliable mapping of T2 values at high resolutions.

Determining the internal orientation, degree of ordering, and volume of elongated nanocavities by NMR: Application to studies of plant stem.

This study investigates the fibril nanostructure of fresh celery samples by modeling the anisotropic behavior of the transverse relaxation time (T2) in nuclear magnetic resonance (NMR). Experimental results are interpreted within the framework of a previously developed theory, which was successfully used to model the nanostructures of several biological tissues as a set of water filled nanocavities, hence explaining the anisotropy the T2 relaxation time in vivo. An important feature of this theory is to determine the degree of orientational ordering of the nanocavities, their characteristic volume, and their average direction with respect to the macroscopic sample. Results exhibit good agreement between theory and experimental data, which are, moreover, supported by optical microscopic resolution. The quantitative NMR approach presented herein can be potentially used to determine the internal ordering of biological tissues noninvasively.

Data-driven algorithm for myelin water imaging: Probing subvoxel compartmentation based on identification of spatially global tissue features.

PURPOSE: Multicomponent analysis of MRI T2 relaxation time (mcT2 ) is commonly used for estimating myelin content by separating the signal at each voxel into its underlying distribution of T2 values. This voxel-based approach is challenging due to the large ambiguity in the multi-T2 space and the low SNR of MRI signals. Herein, we present a data-driven mcT2 analysis, which utilizes the statistical strength of identifying spatially global mcT2 motifs in white matter segments before deconvolving the local signal at each voxel. METHODS: Deconvolution is done using a tailored optimization scheme, which incorporates the global mcT2 motifs without additional prior assumptions regarding the number of microscopic components. The end results of this process are voxel-wise myelin water fraction maps. RESULTS: Validations are shown for computer-generated signals, uniquely designed subvoxel mcT2 phantoms, and in vivo human brain. Results demonstrated excellent fitting accuracy, both for the numerical and the physical mcT2 phantoms, exhibiting excellent agreement between calculated myelin water fraction and ground truth. Proof-of-concept in vivo validation is done by calculating myelin water fraction maps for white matter segments of the human brain. Interscan stability of myelin water fraction values was also estimated, showing good correlation between scans. CONCLUSION: We conclude that studying global tissue motifs prior to performing voxel-wise mcT2 analysis stabilizes the optimization scheme and efficiently overcomes the ambiguity in the T2 space. This new approach can improve myelin water imaging and the investigation of microstructural compartmentation in general.

T2 Mapping Values in Postmeniscectomy Knee Articular Cartilage after Running: Early Signs of Osteoarthritis?

Loading on the joints during running may have a deleterious effect on post-partial meniscectomy knee cartilage, leading to osteoarthritis. Utilizing T2-mapping measurements before and after running may enable the observation of changes in the articular cartilage of the postmeniscectomy knees compared with healthy knees. After medial partial meniscectomy, 12 volunteers underwent magnetic resonance imaging (MRI) of the both knees, before and immediately after 30 minutes of running. Quantitative assessment of articular cartilage was performed using a T2-mapping technique. In the medial compartment of the operated knees, significantly lower T2 values were found in anterior tibial plateau (pre- vs. postrun: 33.85 vs. 30.45 ms; p = 0.003) and central tibial plateau (33.33 vs. 30.63 ms; p = 0.007). Similar differences were found in lateral regions of central femur (post- vs. prerun: 35.86 vs. 40.35 ms; p = 0.015), posterior femur (34.89 vs. 37.73 ms; p = 0.001), and anterior tibia (24.66 vs. 28.70 ms, p = 0.0004). In lateral compartment, postrun values were significantly lower in operated compared with healthy knees, in central femur (34.89 vs. 37.59 ms; p = 0.043), posterior femoral (36.88 vs. 39.36 ms; p = 0.017), anterior tibia (24.66 vs. 30.20 ms; p = 0.009), and posterior tibia (28.84 vs. 33.17 ms; p = 0.006). No statistical difference was found while comparing postrun to prerun healthy knees. Lower T2 values were found in operated knees after 30 minutes of running. These changes were seen in medial and lateral compartments. We suspect that running may subject the articular cartilage to excessive loads in the post-partial meniscectomy knee, loads that in healthy knee do not cause any changes.

Neuronal Activity in the Sciatic Nerve Is Accompanied by Immediate Cytoskeletal Changes.

Mechanical events and alterations in neuronal morphology that accompany neuronal activity have been observed for decades. However, no clear neurophysiological role, nor an agreed molecular mechanism relating these events to the electrochemical process, has been found. Here we hypothesized that intense, yet physiological, electrical activity in neurons triggers cytoskeletal depolymerization. We excited the sciatic nerve of anesthetized mice with repetitive electric pulses (5, 10, and 100 Hz) for 1 and 2 min and immediately fixed the excised nerves. We then scanned the excised nerves with high-resolution transmission electron microscopy, and quantified cytoskeletal changes in the resulting micrographs. We demonstrate that excitation with a stimulation frequency that is within the physiological regime is accompanied by a significant reduction in the density of cytoskeletal proteins relative to the baseline values recorded in control nerves. After 10 Hz stimulation with durations of 1 and 2 min, neurofilaments density dropped to 55.8 and 51.1% of the baseline median values, respectively. In the same experiments, microtubules density dropped to 23.7 and 38.5% of the baseline median values, respectively. These changes were also accompanied by a reduction in the cytoskeleton-to-cytoplasm contrast that we attribute to the presence of depolymerized electron-dense molecules in the lumen. Thus, we demonstrate with an in vivo model a link between electrical activity and immediate cytoskeleton rearrangement at the nano-scale. We suggest that this cytoskeletal plasticity reduces cellular stiffness and allows cellular homeostasis, maintenance of neuronal morphology and that it facilitates in later stages growth of the neuronal projections.

Quantitative platform for accurate and reproducible assessment of transverse (T2 ) relaxation time.

MRI's transverse relaxation time (T2 ) is sensitive to tissues' composition and pathological state. While variations in T2 values can be used as clinical biomarkers, it is challenging to quantify this parameter in vivo due to the complexity of the MRI signal model, differences in protocol implementations, and hardware imperfections. Herein, we provide a detailed analysis of the echo modulation curve (EMC) platform, offering accurate and reproducible mapping of T2 values, from 2D multi-slice multi-echo spin-echo (MESE) protocols. Computer simulations of the full Bloch equations are used to generate an advanced signal model, which accounts for stimulated echoes and transmit field (B1+ ) inhomogeneities. In addition to quantifying T2 values, the EMC platform also provides proton density (PD) maps, and fat-water fraction maps. The algorithm's accuracy, reproducibility, and insensitivity to T1 values are validated on a phantom constructed by the National Institute of Standards and Technology and on in vivo human brains. EMC-derived T2 maps show excellent agreement with ground truth values for both in vitro and in vivo models. Quantitative values are accurate and stable across scan settings and for the physiological range of T2 values, while showing robustness to main field (B0 ) inhomogeneities, to variations in T1 relaxation time, and to magnetization transfer. Extension of the algorithm to two-component fitting yields accurate fat and water T2 maps along with their relative fractions, similar to a reference three-point Dixon technique. Overall, the EMC platform allows to generate accurate and stable T2 maps, with a full brain coverage using a standard MESE protocol and at feasible scan times. The utility of EMC-based T2 maps was demonstrated on several clinical applications, showing robustness to variations in other magnetic properties. The algorithm is available online as a full stand-alone package, including an intuitive graphical user interface.

Analysis of magnetization transfer (MT) influence on quantitative mapping of T2 relaxation time.

PURPOSE: Multi-echo spin-echo (MESE) protocol is the most effective tool for mapping T2 relaxation in vivo. Still, MESE extensive use of radiofrequency pulses causes magnetization transfer (MT)-related bias of the water signal, instigated by the presence of macromolecules (MMP). Here, we analyze the effects of MT on MESE signal, alongside their impact on quantitative T2 measurements. METHODS: Study used 3 models: in vitro urea phantom, ex vivo horse brain, and in vivo human brain. MT ratio (MTR) was measured between single-SE and MESE protocols under different scan settings including varying echo train lengths, number of slices, and inter-slice gap. MTR and T2 values were extracted for each model and protocol. RESULTS: MT interactions biased MESE signals, and in certain settings, the corresponding T2 values. T2 underestimation of up to 4.3% was found versus single-SE values in vitro and up to 13.8% ex vivo, correlating with the MMP content. T2 bias originated from intra-slice saturation of the MMP, rather than from indirect saturation in multi-slice acquisitions. MT-related signal attenuation was caused by slice crosstalk and/or partial T1 recovery, whereas smaller contribution was caused by MMP interactions. Inter-slice gap had a similar effect on in vivo MTR (21.2%), in comparison to increasing the number of slices (18.9%). CONCLUSIONS: MT influences MESE protocols either by uniformly attenuating the entire echo train or by cumulatively attenuating the signal along the train. Although both processes depend on scan settings and MMP content, only the latter will cause underestimation of T2 .

White matter lesions, cerebral inflammation and cognitive function in a mouse model of cerebral hypoperfusion.

Development of specific treatments for vascular dementia requires appropriate animal models. Bilateral carotid artery stenosis (BCAS) employs metal coils wrapped around both common carotid arteries to induce cerebral hypoperfusion, white matter lesions and memory impairment in mice. We focused on the relationship of memory impairment induced by BCAS to white matter lesions demonstrated by ex vivo magnetic resonance imaging (MRI). We found a significant effect of BCAS on perceptual learning in the novel object recognition test and on number of errors and latency to platform in the radial arm water maze. MRI analysis revealed a significant effect of BCAS on diffusion tensor imaging (DTI) parameters in white matter areas. After correction for multiple testing, significantly lower fractional anisotropy (FA) values were found in the corpus callosum and anterior commissure and significantly higher mean diffusivity values in the internal capsule. Focusing on the corpus callosum, we found that correlations between FA and number of errors on the RAWM test were significant after controlling for treatment. We further found that the effects of BCAS on cognition were partly mediated by its effects on white matter integrity. Immunofluorescence studies demonstrated significantly higher microglia cell density and soma size in the corpus callosum of BCAS mice compared to controls, and these parameters were correlated with the imaging data. The results of this study indicate that cognitive deficits induced by cerebral hypoperfusion due to BCAS result in part from microglia activation and disruption of white matter integrity, supporting the face and construct validity of this unique model of vascular dementia.

A Phosphatidylserine Source of Docosahexanoic Acid Improves Neurodevelopment and Survival of Preterm Pigs.

The amount, composition, and sources of nutrition support provided to preterm infants is critical for normal growth and development, and particularly for structural and functional neurodevelopment. Although omega-3 long chain polyunsaturated fatty acids (LC-PUFA), and particularly docosahexanoic acid (DHA), are considered of particular importance, results from clinical trials with preterm infants have been inconclusive because of ethical limitations and confounding variables. A translational large animal model is needed to understand the structural and functional responses to DHA. Neurodevelopment of preterm pigs was evaluated in response to feeding formulas to term-equivalent age supplemented with DHA attached to phosphatidylserine (PS-DHA) or sunflower oil as the placebo. Newborn term pigs were used as a control for normal in utero neurodevelopment. Supplementing formula with PS-DHA increased weight of the brain, and particularly the cerebellum, at term-equivalent age compared with placebo preterm pigs (P's < 0.10 and 0.05 respectively), with a higher degree of myelination in all regions of the brain examined (all p < 0.06). Brains of pigs provided PS-DHA were similar in weight to newborn term pigs. Event-related brain potentials and performance in a novel object recognition test indicated the PS-DHA supplement accelerated development of sensory pathways and recognition memory compared with placebo preterm pigs. The PS-DHA did not increase weight gain, but was associated with higher survival. The benefits of PS-DHA include improving neurodevelopment and possibly improvement of survival, and justify further studies to define dose-response relations, compare benefits associated with other sources of DHA, and understand the mechanisms underlying the benefits and influences on the development of other tissues and organ systems.

Neurodegeneration of lateral habenula efferent fibers after intermittent cocaine administration: implications for deep brain stimulation.

Deep brain stimulation (DBS) is an emerging technique for effective, non-pharmacological intervention in the course of neurological and neuropsychiatric diseases. Several brain targets have been suggested as suitable for DBS treatment of drug addiction. Previously, we showed that DBS of the lateral habenula (LHb) can reduce cocaine intake, facilitate extinction and attenuate drug-induced relapse in rats trained to self-administrate cocaine. Herein, we demonstrated that cocaine self-administration dose-dependently decreased connectivity between the LHb and midbrain, as shown by neurodegeneration of the main LHb efferent fiber, the fasciculus retroflexus (FR). FR degeneration, in turn, may have caused lack of response to LHb stimulation in rats trained to self-administer high-dose cocaine (1.5 mg/kg; i.v.). Furthermore, we show that the micro-structural changes caused by cocaine can be non-invasively detected using magnetic resonance imaging and diffusion tensor imaging. Detection of cocaine-induced alterations in FR anatomy can aid the selection of potential responders to LHb stimulation for treatment of drug addiction.

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.

Magnetic resonance imaging characterization of different experimental autoimmune encephalomyelitis models and the therapeutic effect of glatiramer acetate.

The roles of inflammation and degeneration as well as of gray matter abnormalities in multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE) are controversial. We analyzed the pathological manifestations in two EAE models, the chronic oligodendrocyte glycoprotein (MOG)-induced versus the relapsing-remitting proteolipid protein (PLP)-induced, along the disease progression, using advanced magnetic resonance imaging (MRI) parameters. The emphasis of this study was the overall assessment of the whole brain by histogram analysis, as well as the detection of specific affected regions by voxel based analysis (VBA) using quantitative T2, magnetization transfer ratio (MTR) and diffusion tensor imaging (DTI). Brains of EAE-inflicted mice from both models revealed multiple white and gray matter areas with significant changes from naïve mice for all MRI parameters. Ventricle swelling was more characteristic to the PLP-induced model. Decreased MTR values and increased apparent diffusion coefficient (ADC) were observed mainly in MOG-induced EAE, indicative of macromolecular loss and structural CNS damage involvement in the chronic disease. The MS drug glatiramer acetate (GA), applied either as prevention or therapeutic treatment, affected all the MRI pathological manifestations, resulting in reduced T2 values and ventricle volume, elevated MTR and decreased ADC, in comparison to untreated EAE-inflicted mice. In accord, immunohistochemical analysis indicated less histological damage and higher amount of proliferating oligodendrocyte progenitor cells after GA treatment. The higher brain tissue integrity reflected by the MRI parameters on the level of the whole brain and in specific regions supports the in situ anti-inflammatory and neuroprotective consequences of GA treatment.

Learning in the fast lane: new insights into neuroplasticity.

The timescale of structural remodeling that accompanies functional neuroplasticity is largely unknown. Although structural remodeling of human brain tissue is known to occur following long-term (weeks) acquisition of a new skill, little is known as to what happens structurally when the brain needs to adopt new sequences of procedural rules or memorize a cascade of events within minutes or hours. Using diffusion tensor imaging (DTI), an MRI-based framework, we examined subjects before and after a spatial learning and memory task. Microstructural changes (as reflected by DTI measures) of limbic system structures (hippocampus and parahippocampus) were significant after only 2 hr of training. This observation was also found in a supporting rat study. We conclude that cellular rearrangement of neural tissue can be detected by DTI, and that this modality may allow neuroplasticity to be localized over short timescales.

Immunotherapy of cerebrovascular amyloidosis in a transgenic mouse model.

Cerebrovascular amyloidosis is caused by amyloid accumulation in walls of blood vessel walls leading to hemorrhagic stroke and cognitive impairment. Transforming growth factor-ß1 (TGF-ß1) expression levels correlate with the degree of cerebrovascular amyloid deposition in Alzheimer's disease (AD) and TGF-ß1 immunoreactivity in such cases is increased along the cerebral blood vessels. Here we show that a nasally administered proteosome-based adjuvant activates macrophages and decreases vascular amyloid in TGF-ß1 mice. Animals were nasally treated with a proteosome-based adjuvant on a weekly basis for 3 months beginning at age 13 months. Using magnetic resonance imaging (MRI) we found that while control animals showed a significant cerebrovascular pathology, proteosome-based adjuvant prevents further brain damage and prevents pathological changes in the blood-brain barrier. Using an object recognition test and Y-maze, we found significant improvement in cognition in the treated group. Our findings support the potential use of a macrophage immunomodulator as a novel approach to reduce cerebrovascular amyloid, prevent microhemorrhage, and improve cognition.