Profiles of cortical inflammation in multiple sclerosis by 11C-PBR28 MR-PET and 7 Tesla imaging.

BACKGROUND: Neuroinflammation with microglia activation is thought to be closely related to cortical multiple sclerosis (MS) lesion pathogenesis. OBJECTIVE: Using 11C-PBR28 and 7 Tesla (7T) imaging, we assessed in 9 relapsing-remitting multiple sclerosis (RRMS) and 10 secondary progressive multiple sclerosis (SPMS) patients the following: (1) microglia activation in lesioned and normal-appearing cortex, (2) cortical lesion inflammatory profiles, and (3) the relationship between neuroinflammation and cortical integrity. METHODS: Mean 11C-PBR28 uptake was measured in focal cortical lesions, cortical areas with 7T quantitative T2* (q-T2*) abnormalities, and normal-appearing cortex. The relative difference in cortical 11C-PBR28 uptake between patients and 14 controls was used to classify cortical lesions as either active or inactive. Disease burden was investigated according to cortical lesion inflammatory profiles. The relation between q-T2* and 11C-PBR28 uptake along the cortex was assessed. RESULTS: 11C-PBR28 uptake was abnormally high in cortical lesions in RRMS and SPMS; in SPMS, tracer uptake was significantly increased also in normal-appearing cortex. 11C-PBR28 uptake and q-T2* correlated positively in many cortical areas, negatively in some regions. Patients with high cortical lesion inflammation had worse clinical outcome and higher intracortical lesion burden than patients with low inflammation. CONCLUSION: 11C-PBR28 and 7T imaging reveal distinct profiles of cortical inflammation in MS, which are related to disease burden.

Heterogeneous pathological processes account for thalamic degeneration in multiple sclerosis: Insights from 7 T imaging.

BACKGROUND: Thalamic degeneration impacts multiple sclerosis (MS) prognosis. OBJECTIVE: To investigate heterogeneous thalamic pathology, its correlation with white matter (WM), cortical lesions and thickness, and as function of distance from cerebrospinal fluid (CSF). METHODS: In 41 MS subjects and 17 controls, using 3 and 7 T imaging, we tested for (1) differences in thalamic volume and quantitative T2* (q-T2*) (2) globally and (3) within concentric bands originating from the CSF/thalamus interface; (4) the relation between thalamic, cortical, and WM metrics; and (5) the contribution of magnetic resonance imaging (MRI) metrics to clinical scores. We also assessed MS thalamic lesion distribution as a function of distance from CSF. RESULTS: Thalamic lesions were mainly located next to the ventricles. Thalamic volume was decreased in MS versus controls ( p < 10-2); global q-T2* was longer in secondary progressive multiple sclerosis (SPMS) only ( p < 10-2), indicating myelin and/or iron loss. Thalamic atrophy and longer q-T2* correlated with WM lesion volume ( p < 0.01). In relapsing-remitting MS, q-T2* thalamic abnormalities were located next to the WM ( p < 0.01 (uncorrected), p = 0.09 (corrected)), while they were homogeneously distributed in SPMS. Cortical MRI metrics were the strongest predictors of clinical outcome. CONCLUSION: Heterogeneous pathological processes affect the thalamus in MS. While focal lesions are likely mainly driven by CSF-mediated factors, overall thalamic degeneration develops in association with WM lesions.

Neuroinflammatory component of gray matter pathology in multiple sclerosis.

OBJECTIVE: In multiple sclerosis (MS), using simultaneous magnetic resonance-positron emission tomography (MR-PET) imaging with 11 C-PBR28, we quantified expression of the 18kDa translocator protein (TSPO), a marker of activated microglia/macrophages, in cortex, cortical lesions, deep gray matter (GM), white matter (WM) lesions, and normal-appearing WM (NAWM) to investigate the in vivo pathological and clinical relevance of neuroinflammation. METHODS: Fifteen secondary-progressive MS (SPMS) patients, 12 relapsing-remitting MS (RRMS) patients, and 14 matched healthy controls underwent 11 C-PBR28 MR-PET. MS subjects underwent 7T T2*-weighted imaging for cortical lesion segmentation, and neurological and cognitive evaluation. 11 C-PBR28 binding was measured using normalized 60- to 90-minute standardized uptake values and volume of distribution ratios. RESULTS: Relative to controls, MS subjects exhibited abnormally high 11 C-PBR28 binding across the brain, the greatest increases being in cortex and cortical lesions, thalamus, hippocampus, and NAWM. MS WM lesions showed relatively modest TSPO increases. With the exception of cortical lesions, where TSPO expression was similar, 11 C-PBR28 uptake across the brain was greater in SPMS than in RRMS. In MS, increased 11 C-PBR28 binding in cortex, deep GM, and NAWM correlated with neurological disability and impaired cognitive performance; cortical thinning correlated with increased thalamic TSPO levels. INTERPRETATION: In MS, neuroinflammation is present in the cortex, cortical lesions, deep GM, and NAWM, is closely linked to poor clinical outcome, and is at least partly linked to neurodegeneration. Distinct inflammatory-mediated factors may underlie accumulation of cortical and WM lesions. Quantification of TSPO levels in MS could prove to be a sensitive tool for evaluating in vivo the inflammatory component of GM pathology, particularly in cortical lesions. Ann Neurol 2016;80:776-790.

Is the Relationship between Cortical and White Matter Pathologic Changes in Multiple Sclerosis Spatially Specific? A Multimodal 7-T and 3-T MR Imaging Study with Surface and Tract-based Analysis.

PURPOSE: To investigate in vivo the spatial specificity of the interdependence between intracortical and white matter (WM) pathologic changes as function of cortical depth and distance from the cortex in multiple sclerosis (MS), and their independent contribution to physical and cognitive disability. MATERIALS AND METHODS: This study was institutional review board-approved and participants gave written informed consent. In 34 MS patients and 17 age-matched control participants, 7-T quantitative T2* maps, 3-T T1-weighted anatomic images for cortical surface reconstruction, and 3-T diffusion tensor images (DTI) were obtained. Cortical quantitative T2* maps were sampled at 25%, 50%, 75% depth from pial surface. Tracts of interest were reconstructed by using probabilistic tractography. The relationship between DTI metrics voxelwise of the tracts and cortical integrity in the projection cortex was tested by using multilinear regression models. RESULTS: In MS, DTI abnormal findings along tracts correlated with quantitative T2* changes (suggestive of iron and myelin loss) at each depth of the cortical projection area (P < .01, corrected). This association, however, was not spatially specific because abnormal findings in WM tracts also related to cortical pathologic changes outside of the projection cortex of the tract (P < .001). Expanded Disability Status Scale pyramidal score was predicted by axial diffusivity along the corticospinal tract (ß = 4.6 × 10(3); P < .001), Symbol Digit Modalities Test score by radial diffusivity along the cingulum (ß = -4.3 × 10(4); P < .01), and T2* in the cingulum cortical projection at 25% depth (ß = -1.7; P < .05). CONCLUSION: Intracortical and WM injury are concomitant pathologic processes in MS, which are not uniquely distributed according to a tract-cortex-specific pattern; their association may reflect a common stage-dependent mechanism.

A gradient in cortical pathology in multiple sclerosis by in vivo quantitative 7 T imaging.

We used a surface-based analysis of T2* relaxation rates at 7 T magnetic resonance imaging, which allows sampling quantitative T2* throughout the cortical width, to map in vivo the spatial distribution of intracortical pathology in multiple sclerosis. Ultra-high resolution quantitative T2* maps were obtained in 10 subjects with clinically isolated syndrome/early multiple sclerosis (≤ 3 years disease duration), 18 subjects with relapsing-remitting multiple sclerosis (≥ 4 years disease duration), 13 subjects with secondary progressive multiple sclerosis, and in 17 age-matched healthy controls. Quantitative T2* maps were registered to anatomical cortical surfaces for sampling T2* at 25%, 50% and 75% depth from the pial surface. Differences in laminar quantitative T2* between each patient group and controls were assessed using general linear model (P < 0.05 corrected for multiple comparisons). In all 41 multiple sclerosis cases, we tested for associations between laminar quantitative T2*, neurological disability, Multiple Sclerosis Severity Score, cortical thickness, and white matter lesions. In patients, we measured, T2* in intracortical lesions and in the intracortical portion of leukocortical lesions visually detected on 7 T scans. Cortical lesional T2* was compared with patients' normal-appearing cortical grey matter T2* (paired t-test) and with mean cortical T2* in controls (linear regression using age as nuisance factor). Subjects with multiple sclerosis exhibited relative to controls, independent from cortical thickness, significantly increased T2*, consistent with cortical myelin and iron loss. In early disease, T2* changes were focal and mainly confined at 25% depth, and in cortical sulci. In later disease stages T2* changes involved deeper cortical laminae, multiple cortical areas and gyri. In patients, T2* in intracortical and leukocortical lesions was increased compared with normal-appearing cortical grey matter (P < 10(-10) and P < 10(-7)), and mean cortical T2* in controls (P < 10(-5) and P < 10(-6)). In secondary progressive multiple sclerosis, T2* in normal-appearing cortical grey matter was significantly increased relative to controls (P < 0.001). Laminar T2* changes may, thus, result from cortical pathology within and outside focal cortical lesions. Neurological disability and Multiple Sclerosis Severity Score correlated each with the degree of laminar quantitative T2* changes, independently from white matter lesions, the greatest association being at 25% depth, while they did not correlate with cortical thickness and volume. These findings demonstrate a gradient in the expression of cortical pathology throughout stages of multiple sclerosis, which was associated with worse disability and provides in vivo evidence for the existence of a cortical pathological process driven from the pial surface.

Reproducibility of T2 * mapping in the human cerebral cortex in vivo at 7 tesla MRI.

BACKGROUND: To assess the test-retest reproducibility of cortical mapping of T2 * relaxation rates at 7 Tesla (T) MRI. T2 * maps have been used for studying cortical myelo-architecture patterns in vivo and for characterizing conditions associated with changes in iron and/or myelin concentration. METHODS: T2 * maps were calculated from 7T multi-echo T2 *-weighted images acquired during separate scanning sessions on 8 healthy subjects. The reproducibility of surface-based cortical T2 * mapping was assessed at different depths of the cortex; from pial surface (0% depth) towards gray/white matter boundary (100% depth), across cortical regions and hemispheres, using coefficients of variation (COVs = SD/mean) between each couple (scan-rescan) of average T2 * measurements. RESULTS: Average cortical T2 * was significantly different among 25%, 50%, and 75% depths (analysis of variance, P < 0.001). Coefficient of variations were very low within cortical regions, and whole cortex (average COV = 0.83-1.79%), indicating a high degree of reproducibility in T2 * measures. CONCLUSION: Surface-based mapping of T2 * relaxation rates as a function of cortical depth is reproducible and could prove useful for studying the laminar architecture of the cerebral cortex in vivo, and for investigating physiological and pathological states associated with changes in iron and/or myelin concentration.

Gene-SGAN: discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering.

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and single nucleotide polymorphism data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-associated neuroimaging phenotypes.

Brain aging patterns in a large and diverse cohort of 49,482 individuals.

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.

Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering.

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and SNP data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-driven neuroimaging phenotypes.

Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures.

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.

Gray Matter Morphometry Correlates with Attentional Efficiency in Young-Adult Multiple Sclerosis.

Slowed processing on the alerting, orienting and executive control components of attention measured using the Attention Network Test-Interactions (ANT-I) have been widely reported in multiple sclerosis (MS). Despite the assumption that these components correspond to specific neuroanatomical networks in the brain, little is known about gray matter changes that occur in MS and their association with ANT-I performance. We investigated vertex-wise cortical thickness changes and deep gray matter volumetric changes in young MS participants (N = 21, age range: 18-35) with pediatric or young-adult onset and mild disease severity. ANT-I scores and cortical thickness were not significantly different between MS participants and healthy volunteers (N = 19, age range: 18-35), but thalamic volumes were significantly lower in MS. Slowed reaction times on the alerting component in MS correlated significantly with reduced volume of the right pallidum in MS. Slowed reaction times on executive control component correlated significantly with reduced thickness in the frontal, parietal and visual cortical areas and with reduced volume of the left putamen in MS. These findings demonstrate associations between gray matter changes and attentional performance even in the absence of widespread atrophy or slowed attentional processes.

Development of an MRI-Compatible Nasal Drug Delivery Method for Probing Nicotine Addiction Dynamics.

Substance abuse is a fundamentally dynamic disease, characterized by repeated oscillation between craving, drug self-administration, reward, and satiety. To model nicotine addiction as a control system, a magnetic resonance imaging (MRI)-compatible nicotine delivery system is needed to elicit cyclical cravings. Using a concentric nebulizer, inserted into one nostril, we delivered each dose equivalent to a single cigarette puff by a syringe pump. A control mechanism permits dual modes: one delivers puffs on a fixed interval programmed by researchers; with the other, subjects press a button to self-administer each nicotine dose. We tested the viability of this delivery method for studying the brain's response to nicotine addiction in three steps. First, we established the pharmacokinetics of nicotine delivery, using a dosing scheme designed to gradually achieve saturation. Second, we lengthened the time between microdoses to elicit craving cycles, using both fixed-interval and subject-driven behavior. Finally, we demonstrate a potential application of our device by showing that a fixed-interval protocol can reliably identify neuromodulatory targets for pharmacotherapy or brain stimulation. Our MRI-compatible nasal delivery method enables the measurement of neural circuit responses to drug doses on a single-subject level, allowing the development of data-driven predictive models to quantify individual dysregulations of the reward control circuit causing addiction.

Functional, anatomical and diffusion tensor MRI study of radiology expertise.

BACKGROUND: Repeated practice to acquire expertise could result in the structural and functional changes in relevant brain circuits as a result of long-term potentiation, neurogenesis, glial genesis, and remodeling. PURPOSE: The goal of this study is to use task fMRI to study the brain of expert radiologists performing a diagnosis task where a series of medical images were presented during fMRI acquisition for 12s and participants were asked to choose a diagnosis. Structural and diffusion-tensor MRI were also acquired. METHODS: Radiologists (N = 12, 11M, 38.2±10.3 years old) and non-radiologists (N = 17, 15M, 30.6±5.5 years old) were recruited with informed consent. Medical images were presented for 12 s and three multiple choices were displayed and the participants were asked to choose a diagnosis. fMRI, structural and diffusion-tensor MRI were acquired. fMRI analysis used FSL to determine differences in fMRI responses between groups. Voxel-wise analysis was performed to determine if subcortical volume, cortical thickness and fractional anisotropy differed between groups. Correction for multiple comparisons used false discovery rate. RESULTS: Radiologists showed overall lower task-related brain activation than non-radiologists. Radiologists showed significantly lower activation in the left lateral occipital cortex, left superior parietal lobule, occipital pole, right superior frontal and precentral gyri, lingual gyrus, and the left intraparietal sulcus (p<0.05). There were no significant differences between groups in cortical thickness, subcortical volume and fractional anisotropy (p>0.05). CONCLUSIONS: Radiologists and non-radiologists had no significant difference in structural metrics. However, in diagnosis tasks, radiologists showed markedly lower task-related brain activations overall as well as a number of high-order visual and non-visual brain regions than non-radiologists. Some brain circuits appear to be uniquely associated with differential-diagnosis paradigm expertise that are not involved in simpler object-recognition cases. Improved understanding of the brain circuitry involved in acquisition of expertise might be used to design optimal training paradigms.

Resting-state functional connectivity networks associated with fatigue in multiple sclerosis with early age onset.

BACKGROUND: Fatigue is one of the most commonly experienced symptoms in multiple sclerosis (MS). The neural correlates of fatigue in MS, in general and specifically in early onset, remain poorly understood. This study employed resting-state fMRI (rsfMRI) to investigate the functional connectivity of fatigue in MS patients with early age onset. METHODS: Twenty-seven relapsing-remitting MS patients (20 ± 7yo at the age of diagnosis and 26.0 ±â€¯5.5yo at the time of study) were recruited and 22 patients were studied. Structural and rsfMRI sequences were performed on a 3-Tesla Seimens MRI scanner. Seed-based analysis was performed using CONN Functional Connectivity Toolbox for Statistic Parametric Mapping. The Fatigue Severity Scale (FSS) and the Modified Fatigue Impact scale (MFIS) as well as EDSS, Beck Depression Inventory, and symptomatology were measured. Non-fatigued (N = 12) and fatigued patients (N = 10) were separated based on FSS scores, with a score of 5 or greater being classified as fatigued. Group differences in rsfMRI between non-fatigued and fatigued patients were analyzed. Correlations between these functional connectivity differences and behavioral fatigue scores were also analyzed. RESULTS: Ages, disease duration, lesion load, lesion volume, and neurologic disability were not significantly different between non-fatigued and fatigued patients (p > 0.05). Fatigued patients showed significantly stronger connectivity between the right thalamus and right precentral gyrus (T = 4.58, p = 0.015), and a trending increase in connectivity between the left hippocampus and left precentral gyrus (T = 7.55, p = 0.051). Patients with fatigue showed significantly reduced connectivity between the right thalamus and left parietal operculum (T= -4.28, p = 0.0002), left thalamus and right superior frontal gyrus (T=-5.54, p = 0.046), and between the left insula and posterior cingulate (T=-9.4, p = 0.003). The connectivity between the left insula and posterior cingulate was significantly correlated with the cognitive score of MFIS (R2 = -0.471, p = 0.027) and FSS (R2 = -0.719, p = 0.0001). The connectivity between the right thalamus and left parietal operculum was significantly correlated with MFIS cognitive scores (R2 = -0.431, p = 0.045) and with FSS scores (R2 = 0.402, p = 0.006). Correlations remained significant after accounting for depression scores. CONCLUSIONS: rsfMRI identified Alterations in two distinct connections (the connectivity between insula and posterior cingulate gyrus and between the right thalamus and right precentral gyrus) that differed between fatigued and non-fatigued patients, as well as correlated with cognitive fatigue severity. These findings suggest that disruption of sensorimotor, high-order motor, and non-motor executive function likely contributes to the neural mechanism of fatigue in MS. Knowledge of the neural mechanisms of underlying MS fatigue could inform more effective treatment strategies.

Characterization of gray-matter multiple sclerosis lesions using double inversion recovery, diffusion, contrast-enhanced, and volumetric MRI.

PURPOSE: To investigate gray-matter (GM) lesions in relapsing-remitting multiple sclerosis (MS) using double-inversion recovery (DIR) MRI, determine GM lesions prevalence, spatial distribution and characterize their contrast-enhancement, diffusion characteristics and compare them to white-matter (WM) lesions. This is the first study, to our knowledge, to investigate GM MS lesions using double-inversion recovery MRI, to determine GM lesion prevalence and location, and characterize contrast-enhancement and diffusion characteristics, compared to WM lesion characteristics in the same patients. We also correlated GM lesion counts, volume and apparent diffusion coefficient (ADC) with total brain, WM, and GM volumes, as well as 25-foot walk test as a clinical disability. MATERIALS AND METHODS: This retrospective study included 44 relapsing-remitting MS patients (12M/32F, 41 ± 13 years) and 24 age-matched healthy controls (14M/10F, 36 ± 13 years). Lesions were segmented based on DIR and grouped into GM, subcortical WM, and periventricular WM lesions. ADC was tabulated for contrast-enhancing and non-enhancing lesions. Unpaired two sample t-tests were used for comparison between groups. Linear regression was used to evaluate the relationship between number of GM lesions, number of total lesions, total GM lesion volume, and total WM lesion volume with brain volumes and clinical data. RESULTS: GM MS lesions were present in the majority (86.4%, 38/44) of RRMS patients based on DIR, suggesting GM damage plays an important role in MS pathogenesis. The majority of the GM lesions were located in the frontal lobe. The percentage of lesions in GM that were contrast-enhanced was similar to those in WM, suggesting that blood-brain barrier integrity is likely affected similarly in GM and WM. Contrast-enhanced GM lesions showed higher ADC. GM lesion count and volume were correlated with global and regional brain atrophy, and with more severe disability group. CONCLUSION: This study characterized GM MS lesions using double-inversion recovery, contrast-enhanced and diffusion MRI. Understanding GM lesion pathophysiology using MRI in vivo, may prove useful for improving targeted therapy and monitoring disease progression.

The association between intra- and juxta-cortical pathology and cognitive impairment in multiple sclerosis by quantitative T2* mapping at 7 T MRI.

Using quantitative T2* at 7 Tesla (T) magnetic resonance imaging, we investigated whether impairment in selective cognitive functions in multiple sclerosis (MS) can be explained by pathology in specific areas and/or layers of the cortex. Thirty-one MS patients underwent neuropsychological evaluation, acquisition of 7 T multi-echo T2* gradient-echo sequences, and 3 T anatomical images for cortical surfaces reconstruction. Seventeen age-matched healthy subjects served as controls. Cortical T2* maps were sampled at various depths throughout the cortex and juxtacortex. Relation between T2*, neuropsychological scores and a cognitive index (CI), calculated from a principal component analysis on the whole battery, was tested by a general linear model. Cognitive impairment correlated with T2* increase, independently from white matter lesions and cortical thickness, in cortical areas highly relevant for cognition belonging to the default-mode network (p < 0.05 corrected). Dysfunction in different cognitive functions correlated with longer T2* in selective cortical regions, most of which showed longer T2* relative to controls. For most tests, this association was strongest in deeper cortical layers. Executive dysfunction, however, was mainly related with pathology in juxtameningeal cortex. T2* explained up to 20% of the variance of the CI, independently of conventional imaging metrics (adjusted-R2: 52-67%, p < 5.10- 4). Location of pathology across the cortical width and mantle showed selective correlation with impairment in differing cognitive domains. These findings may guide studies at lower field strength designed to develop surrogate markers of cognitive impairment in MS.

Quantitative oxygen extraction fraction from 7-Tesla MRI phase: reproducibility and application in multiple sclerosis.

Quantitative oxygen extraction fraction (OEF) in cortical veins was studied in patients with multiple sclerosis (MS) and healthy subjects via magnetic resonance imaging (MRI) phase images at 7 Tesla (7 T). Flow-compensated, three-dimensional gradient-echo scans were acquired for absolute OEF quantification in 23 patients with MS and 14 age-matched controls. In patients, we collected T2*-weighted images for characterization of white matter, deep gray matter, and cortical lesions, and also assessed cognitive function. Variability of OEF across readers and scan sessions was evaluated in a subset of volunteers. OEF was averaged from 2 to 3 pial veins in the sensorimotor, parietal, and prefrontal cortical regions for each subject (total of ~10 vessels). We observed good reproducibility of mean OEF, with intraobserver coefficient of variation (COV)=2.1%, interobserver COV=5.2%, and scan-rescan COV=5.9%. Patients exhibited a 3.4% reduction in cortical OEF relative to controls (P=0.0025), which was not different across brain regions. Although oxygenation did not relate with measures of structural tissue damage, mean OEF correlated with a global measure of information processing speed. These findings suggest that cortical OEF from 7-T MRI phase is a reproducible metabolic biomarker that may be sensitive to different pathologic processes than structural MRI in patients with MS.

Beyond focal cortical lesions in MS: An in vivo quantitative and spatial imaging study at 7T.

OBJECTIVES: Using quantitative T2* 7-tesla (7T) MRI as a marker of demyelination and iron loss, we investigated, in patients with relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS), spatial and tissue intrinsic characteristics of cortical lesion(s) (CL) types, and structural integrity of perilesional normal-appearing cortical gray matter (NACGM) as a function of distance from lesions. METHODS: Patients with MS (18 RRMS, 11 SPMS), showing at least 2 CL, underwent 7T T2* imaging to obtain (1) magnitude images for segmenting focal intracortical lesion(s) (ICL) and leukocortical lesion(s) (LCL), and (2) cortical T2* maps. Anatomical scans were collected at 3T for cortical surface reconstruction using FreeSurfer. Seventeen age-matched healthy participants served as controls. RESULTS: ICL were predominantly located in sulci of frontal, parietal, and cingulate cortex; LCL distribution was more random. In MS, T2* was higher in both ICL and LCL, indicating myelin and iron loss, than in NACGM (p < 0.00003) irrespective of CL subtype and MS phenotype. T2* was increased in perilesional cortex, tapering away from CL toward NACGM, the wider changes being for LCL in SPMS. NACGM T2* was higher in SPMS relative to RRMS (p = 0.006) and healthy cortex (p = 0.02). CONCLUSIONS: CL had the same degree of demyelination and iron loss regardless of lesion subtype and disease stage. Cortical damage expanded beyond visible CL, close to lesions in RRMS, and more diffusely in SPMS. Evaluation of NACGM integrity, beyond focal CL, could represent a surrogate marker of MS progression.

Active behavioral coping alters the behavioral but not the endocrine response to stress.

Exposure to traumatic stressors typically causes lasting changes in emotionality and behavior. However, coping strategies have been shown to prevent and alleviate many stress consequences and the biological mechanisms that underlie coping are of great interest. Whereas the laboratory stressor inescapable tail-shock induces anxiety-like behaviors, here we demonstrate that permitting a rat to chew on a wooden dowel during administration of tail-shock prevented the development of anxiety like behaviors in the open field and juvenile social exploration tests. Uncontrollable stressors increase corticosterone and decrease thyroid hormone, and we hypothesized that coping would blunt these changes. While tail-shock did produce these effects, active coping did not alter hormone levels. The dissociation between behavioral resilience and circulating hormones is discussed with regard to the utility of these molecules as biomarkers for psychiatric disease.