Resting state networks activity in euthymic bipolar disorder.

OBJECTIVES: Bipolar disorder (BD) is a psychiatric condition causing shifts in mood, energy and activity levels severely altering the quality of life of the patients even in the euthymic phase. Although widely accepted, the neurobiological bases of the disorder in the euthymic phase remain elusive. This study aims at characterizing resting state functional activity of the BD euthymic phase in order to better understand the pathogenesis of the disease and build future neurobiological models. METHODS: Fifteen euthymic BD patients (10 females; mean age 40.2; standard deviation 13.5; range 20-61) and 27 healthy controls (HC) (21 females; mean age 37; standard deviation 10.6; range 22-60) underwent a 3T functional MRI scan at rest. Resting state activity was extracted through independent component analysis (ICA) run with automatic dimensionality estimation. RESULTS: ICA identified 22 resting state networks (RSNs). Within-network analysis revealed decreased connectivity in the visual, temporal, motor and cerebellar RSNs of BD patients vs HC. Between-network analysis showed increased connectivity between motor area and the default mode network (DMN) partially overlapping with the fronto-parietal network (FPN) in BD patients. CONCLUSION: Within-network analysis confirmed existing evidence of altered cerebellar, temporal, motor and visual networks in BD. Increased connectivity between the DMN and the motor area network suggests the presence of alterations of the fronto-parietal regions, precuneus and cingulate cortex in the euthymic condition. These findings indicate that specific connectivity alterations might persist even in the euthymic state suggesting the importance of examining both within and between-network connectivity to achieve a global understanding of the BD euthymic condition.

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques.

First episode psychosis (FEP) patients are of particular interest for neuroimaging investigations because of the absence of confounding effects due to medications and chronicity. Nonetheless, imaging data are prone to heterogeneity because for example of age, gender or parameter setting differences. With this work, we wanted to take into account possible nuisance effects of age and gender differences across dataset, not correcting the data as a pre-processing step, but including the effect of nuisance covariates in the classification phase. To this aim, we developed a method which, based on multiple kernel learning (MKL), exploits the effect of these confounding variables with a subject-depending kernel weighting procedure. We applied this method to a dataset of cortical thickness obtained from structural magnetic resonance images (MRI) of 127 FEP patients and 127 healthy controls, who underwent either a 3Tesla (T) or a 1.5T MRI acquisition. We obtained good accuracies, notably better than those obtained with standard SVM or MKL methods, up to more than 80% for frontal and temporal areas. To our best knowledge, this is the largest classification study in FEP population, showing that fronto-temporal cortical thickness can be used as a potential marker to classify patients with psychosis.

Free water elimination improves test-retest reproducibility of diffusion tensor imaging indices in the brain: A longitudinal multisite study of healthy elderly subjects.

Free water elimination (FWE) in brain diffusion MRI has been shown to improve tissue specificity in human white matter characterization both in health and in disease. Relative to the classical diffusion tensor imaging (DTI) model, FWE is also expected to increase sensitivity to microstructural changes in longitudinal studies. However, it is not clear if these two models differ in their test-retest reproducibility. This study compares a bi-tensor model for FWE with DTI by extending a previous longitudinal-reproducibility 3T multisite study (10 sites, 7 different scanner models) of 50 healthy elderly participants (55-80 years old) scanned in two sessions at least 1 week apart. We computed the reproducibility of commonly used DTI metrics (FA: fractional anisotropy, MD: mean diffusivity, RD: radial diffusivity, and AXD: axial diffusivity), derived either using a DTI model or a FWE model. The DTI metrics were evaluated over 48 white-matter regions of the JHU-ICBM-DTI-81 white-matter labels atlas, and reproducibility errors were assessed. We found that relative to the DTI model, FWE significantly reduced reproducibility errors in most areas tested. In particular, for the FA and MD metrics, there was an average reduction of approximately 1% in the reproducibility error. The reproducibility scores did not significantly differ across sites. This study shows that FWE improves sensitivity and is thus promising for clinical applications, with the potential to identify more subtle changes. The increased reproducibility allows for smaller sample size or shorter trials in studies evaluating biomarkers of disease progression or treatment effects. Hum Brain Mapp 38:12-26, 2017. © 2016 Wiley Periodicals, Inc.

Longitudinal reproducibility of default-mode network connectivity in healthy elderly participants: A multicentric resting-state fMRI study.

To date, limited data are available regarding the inter-site consistency of test-retest reproducibility of functional connectivity measurements, in particular with regard to integrity of the Default Mode Network (DMN) in elderly participants. We implemented a harmonized resting-state fMRI protocol on 13 clinical scanners at 3.0T using vendor-provided sequences. Each site scanned a group of 5 healthy elderly participants twice, at least a week apart. We evaluated inter-site differences and test-retest reproducibility of both temporal signal-to-noise ratio (tSNR) and functional connectivity measurements derived from: i) seed-based analysis (SBA) with seed in the posterior cingulate cortex (PCC), ii) group independent component analysis (ICA) separately for each site (site ICA), and iii) consortium ICA, with group ICA across the whole consortium. Despite protocol harmonization, significant and quantitatively important inter-site differences remained in the tSNR of resting-state fMRI data; these were plausibly driven by hardware and pulse sequence differences across scanners which could not be harmonized. Nevertheless, the tSNR test-retest reproducibility in the consortium was high (ICC=0.81). The DMN was consistently extracted across all sites and analysis methods. While significant inter-site differences in connectivity scores were found, there were no differences in the associated test-retest error. Overall, ICA measurements were more reliable than PCC-SBA, with site ICA showing higher reproducibility than consortium ICA. Across the DMN nodes, the PCC yielded the most reliable measurements (≈4% test-retest error, ICC=0.85), the medial frontal cortex the least reliable (≈12%, ICC=0.82) and the lateral parietal cortices were in between (site ICA). Altogether these findings support usage of harmonized multisite studies of resting-state functional connectivity to characterize longitudinal effects in studies that assess disease progression and treatment response.

Test-retest reliability of the default mode network in a multi-centric fMRI study of healthy elderly: Effects of data-driven physiological noise correction techniques.

Understanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within-site test-retest reliability and the across-site reproducibility consistency of DMN-derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue-based regression, PESTICA and FSL-FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z-scores and, albeit less markedly, the cluster-size in the DMN; in particular, FSL-FIX tended to increase the DMN z-scores compared to others. Within-site test-retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5-11% for DMN z-scores and cluster-size reliability. DMN pattern overlap was in the range 60-65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL-FIX and Tissue-based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC = 0.67) for the DMN z-scores relative to NPC. Overall these findings support the use of rPNC methods like tissue-based or FSL-FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. Hum Brain Mapp 37:2114-2132, 2016. © 2016 Wiley Periodicals, Inc.

Longitudinal reproducibility of automatically segmented hippocampal subfields: A multisite European 3T study on healthy elderly.

Recently, there has been an increased interest in the use of automatically segmented subfields of the human hippocampal formation derived from magnetic resonance imaging (MRI). However, little is known about the test-retest reproducibility of such measures, particularly in the context of multisite studies. Here, we report the reproducibility of automated Freesurfer hippocampal subfields segmentations in 65 healthy elderly enrolled in a consortium of 13 3T MRI sites (five subjects per site). Participants were scanned in two sessions (test and retest) at least one week apart. Each session included two anatomical 3D T1 MRI acquisitions harmonized in the consortium. We evaluated the test-retest reproducibility of subfields segmentation (i) to assess the effects of averaging two within-session T1 images and (ii) to compare subfields with whole hippocampus volume and spatial reliability. We found that within-session averaging of two T1 images significantly improved the reproducibility of all hippocampal subfields but not that of the whole hippocampus. Volumetric and spatial reproducibility across MRI sites were very good for the whole hippocampus, CA2-3, CA4-dentate gyrus (DG), subiculum (reproducibility error∼2% and DICE > 0.90), good for CA1 and presubiculum (reproducibility error ∼ 5% and DICE ∼ 0.90), and poorer for fimbria and hippocampal fissure (reproducibility error ∼ 15% and DICE < 0.80). Spearman's correlations confirmed that test-retest reproducibility improved with volume size. Despite considerable differences of MRI scanner configurations, we found consistent hippocampal subfields volumes estimation. CA2-3, CA4-DG, and sub-CA1 (subiculum, presubiculum, and CA1 pooled together) gave test-retest reproducibility similar to the whole hippocampus. Our findings suggest that the larger hippocampal subfields volume may be reliable longitudinal markers in multisite studies.

Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects.

Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm(3), b = 700 s/mm(2), 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.

Mild cognitive impairment in patients with moderate to severe chronic plaque psoriasis.

BACKGROUND: Psoriasis is frequently associated with cardiometabolic comorbidities and depression that are risk factors for cognitive impairment. OBJECTIVE: To investigate cognitive performance in psoriatic patients. METHOD: Cognitive performances were assessed by neuropsychological tests in 41 patients with psoriasis and 37 controls. Diagnostic criteria for mild cognitive impairment (MCI) were (1) subjective complaint of a memory deficit, confirmed by a relative or caregiver, (2) pathological performance on neuropsychological tests investigating cognitive domains, (3) normal performance of daily living activities and (4) no dementia. Neuroimaging was studied by high-field magnetic resonance imaging and cortical thickness analysis. RESULTS: MCI was found in 18 out of 41 (44%) patients with psoriasis compared to 4 out of 37 (11%) controls (p = 0.002). In particular, patients with psoriasis had lower scores in the delayed recall of the Rey Auditory Verbal Learning Test (p = 0.04), Backwards Digit Span Test (p = 0.002), Weigl's Sorting Test (p = 0.01) and Trail Making Test B (p = 0.008). In the 7 patients submitted to cortical thickness analysis, a reduction in brain thickness in parahippocampal, superior temporal and frontal gyri of the left hemisphere was observed. CONCLUSIONS: Patients with psoriasis may have a precocious impairment of long-term verbal memory, executive functions and attention.

Brain morphometry reproducibility in multi-center 3T MRI studies: a comparison of cross-sectional and longitudinal segmentations.

Large-scale longitudinal multi-site MRI brain morphometry studies are becoming increasingly crucial to characterize both normal and clinical population groups using fully automated segmentation tools. The test-retest reproducibility of morphometry data acquired across multiple scanning sessions, and for different MR vendors, is an important reliability indicator since it defines the sensitivity of a protocol to detect longitudinal effects in a consortium. There is very limited knowledge about how across-session reliability of morphometry estimates might be affected by different 3T MRI systems. Moreover, there is a need for optimal acquisition and analysis protocols in order to reduce sample sizes. A recent study has shown that the longitudinal FreeSurfer segmentation offers improved within session test-retest reproducibility relative to the cross-sectional segmentation at one 3T site using a nonstandard multi-echo MPRAGE sequence. In this study we implement a multi-site 3T MRI morphometry protocol based on vendor provided T1 structural sequences from different vendors (3D MPRAGE on Siemens and Philips, 3D IR-SPGR on GE) implemented in 8 sites located in 4 European countries. The protocols used mild acceleration factors (1.5-2) when possible. We acquired across-session test-retest structural data of a group of healthy elderly subjects (5 subjects per site) and compared the across-session reproducibility of two full-brain automated segmentation methods based on either longitudinal or cross-sectional FreeSurfer processing. The segmentations include cortical thickness, intracranial, ventricle and subcortical volumes. Reproducibility is evaluated as absolute changes relative to the mean (%), Dice coefficient for volume overlap and intraclass correlation coefficients across two sessions. We found that this acquisition and analysis protocol gives comparable reproducibility results to previous studies that used longer acquisitions without acceleration. We also show that the longitudinal processing is systematically more reliable across sites regardless of MRI system differences. The reproducibility errors of the longitudinal segmentations are on average approximately half of those obtained with the cross sectional analysis for all volume segmentations and for entorhinal cortical thickness. No significant differences in reliability are found between the segmentation methods for the other cortical thickness estimates. The average of two MPRAGE volumes acquired within each test-retest session did not systematically improve the across-session reproducibility of morphometry estimates. Our results extend those from previous studies that showed improved reliability of the longitudinal analysis at single sites and/or with non-standard acquisition methods. The multi-site acquisition and analysis protocol presented here is promising for clinical applications since it allows for smaller sample sizes per MRI site or shorter trials in studies evaluating the role of potential biomarkers to predict disease progression or treatment effects.

Early MRI changes in glioblastoma in the period between surgery and adjuvant therapy.

To investigate the increase in MRI contrast enhancement (CE) occurring in glioblastoma during the period between surgery and initiation of chemo-radiotherapy, thirty-seven patients with newly diagnosed glioblastoma were analyzed by early post-operative magnetic resonance (EPMR) imaging within three days of surgery and by pre-adjuvant magnetic resonance (PAMR) examination before adjuvant therapy. Areas of new CE were investigated by use of EPMR diffusion-weighted imaging and PAMR perfusion imaging (by arterial spin-labeling). PAMR was acquired, on average, 29.9 days later than EPMR (range 20-37 days). During this period an increased area of CE was observed for 17/37 patients. For 3/17 patients these regions were confined to areas of reduced EPMR diffusion, suggesting postsurgical infarct. For the other 14/17 patients, these areas suggested progression. For 11/17 patients the co-occurrence of hyperperfusion in PAMR perfusion suggested progression. PAMR perfusion and EPMR diffusion did not give consistent results for 3/17 patients for whom small new areas of CE were observed, presumably because of the poor spatial resolution of perfusion imaging. Before initiation of adjuvant therapy, areas of new CE of resected glioblastomas are frequently observed. Most of these suggest tumor progression, according to EPMR diffusion and PAMR perfusion criteria.

Inefficient white matter activity in Schizophrenia evoked during intra and inter-hemispheric communication.

Intensive cognitive tasks induce inefficient regional and network responses in schizophrenia (SCZ). fMRI-based studies have naturally focused on gray matter, but appropriately titrated visuo-motor integration tasks reliably activate inter- and intra-hemispheric white matter pathways. Such tasks can assess network inefficiency without demanding intensive cognitive effort. Here, we provide the first application of this framework to the study of white matter functional responses in SCZ. Event-related fMRI data were acquired from 28 patients (nine females, mean age 43.3, ±11.7) and 28 age- and gender-comparable controls (nine females, mean age 42.1 ± 10.1), using the Poffenberger paradigm, a rapid visual detection task used to induce intra- (ipsi-lateral visual and motor cortex) or inter-hemispheric (contra-lateral visual and motor cortex) transfer. fMRI data were pre- and post-processed to reliably isolate activations in white matter, using probabilistic tractography-based white matter tracts. For intra- and inter-hemispheric transfer conditions, SCZ evinced hyper-activations in longitudinal and transverse white matter tracts, with hyper-activation in sub-regions of the corpus callosum primarily observed during inter-hemispheric transfer. Evidence for the functional inefficiency of white matter was observed in conjunction with small (~50 ms) but significant increases in response times. Functional inefficiencies in SCZ are (1) observable in white matter, with the degree of inefficiency contextually related to task-conditions, and (2) are evoked by simple detection tasks without intense cognitive processing. These cumulative results while expanding our understanding of this dys-connection syndrome, also extend the search of biomarkers beyond the traditional realm of fMRI studies of gray matter.

Incidental findings on brain MRI in patients with first-episode and chronic psychosis.

Brain incidental findings (IFs) are unexpected brain abnormalities detected by a structural magnetic resonance (MRI) examination. We conducted a study to assess whether brain IFs are associated with first-episode psychosis (FEP) and chronic psychosis (affective vs. non-affective) compared to healthy controls (HC). Chi-squared analyses were run to compare the frequency of several IFs across groups. Logistic regression analyses were run to explore the association between group and IFs, accounting for sex, age, MRI field strength. We observed a higher frequency of most IFs in both FEP and chronic psychosis groups compared to HC, however most of the chi-squared tests did not reach significance. Patients with FEP and chronic psychosis were 3-4 times more likely to show deep white matter hyperintensities (WMH) than HC. Patients with FEP and affective chronic psychosis were 3-4 times more likely to show ventricular asymmetries than HC. All chronic patients were more likely to show periventricular WMH, liquoral spaces enlargements and ventricular system enlargements respectively. Our results suggest that deep WMH and ventricular asymmetries are associated with both the early and the chronic stages of psychosis, thus representing potential vulnerability factors already present before the onset of the symptoms, possibly due to neurodevelopmental insults.

Assessment of metabolic brain damage and recovery following mild traumatic brain injury: a multicentre, proton magnetic resonance spectroscopic study in concussed patients.

Concussive head injury opens a temporary window of brain vulnerability due to the impairment of cellular energetic metabolism. As experimentally demonstrated, a second mild injury occurring during this period can lead to severe brain damage, a condition clinically described as the second impact syndrome. To corroborate the validity of proton magnetic resonance spectroscopy in monitoring cerebral metabolic changes following mild traumatic brain injury, apart from the magnetic field strength (1.5 or 3.0 T) and mode of acquisition, we undertook a multicentre prospective study in which a cohort of 40 athletes suffering from concussion and a group of 30 control healthy subjects were admitted. Athletes (aged 16-35 years) were recruited and examined at three different institutions between September 2007 and June 2009. They underwent assessment of brain metabolism at 3, 15, 22 and 30 days post-injury through proton magnetic resonance spectroscopy for the determination of N-acetylaspartate, creatine and choline-containing compounds. Values of these representative brain metabolites were compared with those observed in the group of non-injured controls. Comparison of spectroscopic data, obtained in controls using different field strength and/or mode of acquisition, did not show any difference in the brain metabolite ratios. Athletes with concussion exhibited the most significant alteration of metabolite ratios at Day 3 post-injury (N-acetylaspartate/creatine: -17.6%, N-acetylaspartate/choline: -21.4%; P < 0.001 with respect to controls). On average, metabolic disturbance gradually recovered, initially in a slow fashion and, following Day 15, more rapidly. At 30 days post-injury, all athletes showed complete recovery, having metabolite ratios returned to values detected in controls. Athletes self-declared symptom clearance between 3 and 15 days after concussion. Results indicate that N-acetylaspartate determination by proton magnetic resonance spectroscopy represents a non-invasive tool to accurately measure changes in cerebral energy metabolism occurring in mild traumatic brain injury. In particular, this metabolic evaluation may significantly improve, along with other clinical assessments, the management of athletes suffering from concussion. Further studies to verify the effects of a second concussive event occurring at different time points of the recovery curve of brain metabolism are needed.

Highly focal BOLD activation on functional MRI in a patient with progressive myoclonic epilepsy and diffuse giant somatosensory evoked potentials.

We analyzed the effect of afferent input on patterns of brain electrical activation in a 31-year-old man with progressive myoclonic epilepsy (PME) by measuring the somatosensory evoked potential (SSEP) amplitude at the scalp after median nerve stimulation and examining the changes in the functional magnetic resonance imaging blood oxygen level-dependent (fMRI BOLD) signal. High-amplitude SSEPs were elicited at the wrist in association with highly focal BOLD activation of the contralateral sensorimotor areas. By contrast, no diffuse activation of either the frontal or the posterior parietal cortical areas was observed, as seen in previously recorded data on SSEPs from a healthy control group. The highly focal BOLD activation in this patient suggests that cortex hyperexcitability might be limited to the sensorimotor cortex in PME. The combined EEG-fMRI findings highlight a dissociation between BOLD activation and neurophysiological findings.

"First-episode psychosis: Structural covariance deficits in salience network correlate with symptoms severity".

BACKGROUND: Patterns of coordinated variations of gray matter (GM) morphology across individuals are promising indicators of disease. However, it remains unclear if they can help characterize first-episode psychosis (FEP) and symptoms' severity. METHODS: Sixty-seven FEP and 67 matched healthy controls (HC) were assessed with structural MRI to evaluate the existence of distributed GM structural covariance patterns associated to brain areas belonging to salience network. Voxel-based morphometry (VBM) and structural covariance differences, investigated with salience network seed-based Partial Least Square, were applied to explore differences between groups. GM density associations with Raven's intelligent quotient (IQ) and Positive and Negative Syndrome Scale (PANSS) scores were investigated. RESULTS: Univariate VBM results gave trend without significant GM differences across groups. GM and IQ correlated positively in both groups: in FEP, mostly in hippocampus, insula, and fronto-temporal structures, while in HC mostly in amygdala, thalamus and fronto-temporal regions. GM and PANSS scores correlated negatively in FEP, with widespread clusters located in limbic regions. Multivariate analysis showed strong and opposite structural GM covariance with salience network for FEP and HC. Moreover, structural covariance of the salience network in FEP correlated negatively with severity of clinical symptoms. CONCLUSION: Our study provides evidence supporting the insular dysfunction model of psychosis. Reduced structural GM covariance of the salience network, with its association to symptom's severity, appears a promising morphometry feature for FEP detection.

Word and position interference in stroop tasks: a behavioral and fMRI study.

One of the main features of the attentional system is the capability to select between relevant and irrelevant information. However, irrelevant information interferes with the processing of the relevant one. Using high-field magnetic resonance imaging, we examined the interference effect of a verbal (color-word) and a spatial (arrow-position) Stroop task on the activation of cortical areas known to be dedicated to the attentional control. Behaviorally, we found costs from the irrelevant information in both tasks; in the brain, we found a common neural network of activation that mainly involved the dorsolateral prefrontal cortex and the anterior cingulate cortex. However, the neural circuits involved in the two tasks overlapped only partially, since processing of words in the color-word Stroop task showed a wider and more right-lateralized activation, while spatial processing in the arrow-position Stroop task resulted in a more restricted and left-lateralized activation.

Magnetic Resonance Spectroscopy in Adolescent Cannabis Users: Metabolites in the Anterior Cingulate Cortex Reflects Individual Differences in Personality Traits and can Affect Rehabilitation Compliance.

INTRODUCTION: The anterior cingulate cortex (ACC) has shown to play a role in impulsivity, fear, and anxiety. Considering, its high glutamate receptor density, it was chosen as a region of interest to investigate the role of glutamate transmission in drug dependance. We investigated the correlations between personality trait scores and glutamate-to-glutamine (Glx) ratio concentrations in the ACC in order to evaluate if (1) personality traits may increase the probability of drug use and (2) drug use can modify cerebral metabolic pattern contributing to addictive behaviors. MATERIALS AND METHODS: Glx ratio concentrations in the ACC region were measured with high-resolution multivoxel proton magnetic resonance spectroscopy (1H-MRS). Personality traits were evaluated utilizing Cloninger's TCI-revised test. Bivariate correlations between personality scores of 28 teens cannabis users (males, mean age = 18.54 ± 2.80) were evaluated. RESULTS: In the ACC, we observed negative correlation between GG concentrations (r = -0.44, P = 0.05) and co-operativeness values (CO), choline (cho), and novelty seeking (NS) values (r = -0,45, P = 0.05). Low levels of glutamate and high levels of cho in the ACC were closely related to the CO and NS personality traits. CONCLUSIONS: Metabolic and personality patterns seems to be related to the risk of substance predisposition in adolescents. Our data contribute a possible support to the "top-down" control of the ACC on brain metabolism, due to the particular cerebral metabolic pattern found in "drug-using" adolescents.

Mapping local hippocampal changes in Alzheimer's disease and normal ageing with MRI at 3 Tesla.

Histological studies have suggested differing involvement of the hippocampal subfields in ageing and in Alzheimer's disease. The aim of this study was to assess in vivo local hippocampal changes in ageing and Alzheimer's disease based on high resolution MRI at 3 Tesla. T(1)-weighted images were acquired from 19 Alzheimer's disease patients [age 76 +/- 6 years, three males, Mini-Mental State Examination 13 +/- 4] and 19 controls (age 74 +/- 5 years, 11 males, Mini-Mental State Examination 29 +/- 1). The hippocampal formation was isolated by manual tracing. Radial atrophy mapping was used to assess group differences and correlations by averaging hippocampal shapes across subjects using 3D parametric surface mesh models. Percentage difference, Pearson's r, and significance maps were produced. Hippocampal volumes were inversely correlated with age in older healthy controls (r = 0.56 and 0.6 to the right and left, respectively, P < 0.05, corresponding to 14% lower volume for every 10 years of older age from ages 65 to 85 years). Ageing-associated atrophy mapped to medial and lateral areas of the tail and body corresponding to the CA1 subfield and ventral areas of the head corresponding to the presubiculum. Significantly increased volume with older age mapped to a few small spots mainly located to the CA1 sector of the right hippocampus. Volumes were 35% and 30% smaller in Alzheimer's disease patients to the right and left (P < 0.0005). Alzheimer's disease-associated atrophy mapped not only to CA1 areas of the body and tail corresponding to those also associated with age, but also to dorsal CA1 areas of the head unaffected by age. Regions corresponding to the CA2-3 fields were relatively spared in both ageing and Alzheimer's disease. Hippocampal atrophy in Alzheimer's disease maps to areas in the body and tail that partly overlap those affected by normal ageing. Specific areas in the anterior and dorsal CA1 subfield involved in Alzheimer's disease were not in normal ageing. These patterns might relate to differential neural systems involved in Alzheimer's disease and ageing.

Magnetic resonance diffusion-tensor imaging metrics in High Grade Gliomas: Correlation with IDH1 gene status in WHO 2016 era.

PURPOSE: To evaluate any possible correlation between the presence of Isocitrate DeHydrogenase 1 mutation (IDH1m) and specific DTI (Diffusion Tensor Imaging) metrics, such as Fractional Anisotropy (FA), Mean Diffusivity (MD), Radial Diffusivity (RD) and Axial Diffusivity (AD). METHODS: We retrospectively analyzed 47 patients who underwent an advanced-MR study with DTI followed by surgical intervention with a subsequent histologic diagnosis of High-Grade Glioma (HGG) and immunohistochemical evaluation of IDH1 (Isocitrate DeHydrogenase) mutation status. For each DTI metrics we measured the ratio between tumor and normal tissue and we evaluated the correlation with IDH1 mutation. RESULTS: We observed a positive correlation with IDH1 status and RD and MD data. No correlation was demonstrated between IDH1 status and FA and AD. DISCUSSION: Our results support the hypothesis that the number of residual axonal fibers, extracellular matrix composition and the presence of colliquated tissue, may together contribute to a global RD increase in HGG, with a relatively higher increase in IDH1m tumors. CONCLUSIONS: Our data are in favor of a need for multimodal advance evaluation of HGG. DTI metrics help to analyze IDH1 mutation status, in order to better characterize the lesions and to tailor treatment and follow up.

Erratum to: Activations in gray and white matter are modulated by uni-manual responses during within and inter-hemispheric transfer: effects of response hand and right-handedness.

The original version of this article unfortunately contained a mistake. The family name of Paolo Brambilla was incorrectly spelled as Bambilla.