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It was previously reported that normobaric oxygen therapy (NBO) significantly affected T2 ∗ -weighted imaging in a mouse model of intracerebral hemorrhage (ICH). However, it is unclear whether a similar phenomenon exists in large volume ICH as seen in human pathology. We investigated the effects of NBO on T2 ∗ -weighted images in a pig model of ICH. Our data show that NBO makes disappear a peripheral crown of the hematoma, which in turn decreases the apparent volume of ICH by 18%. We hypothesized that this result could be translated to ICH in human, and subsequently could lead to inaccurate diagnostic., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The alleviation of hypoxia in glioblastoma with carbogen to improve treatment has met with limited success. Our hypothesis is that the eventual benefits of carbogen depend on the capacity for vasodilation. We examined, with MRI, changes in fractional cerebral blood volume, blood oxygen saturation, and blood oxygenation level dependent signals in response to carbogen. The analyses were performed in two xenograft models of glioma (U87 and U251) recognized to have different vascular patterns. Carbogen increased fractional cerebral blood volume, blood oxygen saturation, and blood oxygenation level dependent signals in contralateral tissues. In the tumor core and peritumoral regions, changes were dependent on the capacity to vasodilate rather than on resting fractional cerebral blood volume. In the highly vascularised U87 tumor, carbogen induced a greater increase in fractional cerebral blood volume and blood oxygen saturation in comparison to the less vascularized U251 tumor. The blood oxygenation level dependent signal revealed a delayed response in U251 tumors relative to the contralateral tissue. Additionally, we highlight the considerable heterogeneity of fractional cerebral blood volume, blood oxygen saturation, and blood oxygenation level dependent within U251 tumor in which multiple compartments co-exist (tumor core, rim and peritumoral regions). Finally, our study underlines the complexity of the flow/metabolism interactions in different models of glioblastoma. These irregularities should be taken into account in order to palliate intratumoral hypoxia in clinical trials.

Background: Atlases of brain anatomical ROIs are widely used for functional MRI data analysis. Recently, it was proposed that an atlas of ROIs derived from a functional brain parcellation could be advantageous, in particular for understanding how different regions share information. However, functional atlases so far proposed do not account for a crucial aspect of cerebral organization, namely homotopy, i.e. that each region in one hemisphere has a homologue in the other hemisphere., New Method: We present AICHA (for Atlas of Intrinsic Connectivity of Homotopic Areas), a functional brain ROIs atlas based on resting-state fMRI data acquired in 281 individuals. AICHA ROIs cover the whole cerebrum, each having 1-homogeneity of its constituting voxels intrinsic activity, and 2-a unique homotopic contralateral counterpart with which it has maximal intrinsic connectivity. AICHA was built in 4 steps: (1) estimation of resting-state networks (RSNs) using individual resting-state fMRI independent components, (2) k-means clustering of voxel-wise group level profiles of connectivity, (3) homotopic regional grouping based on maximal inter-hemispheric functional correlation, and (4) ROI labeling., Results: AICHA includes 192 homotopic region pairs (122 gyral, 50 sulcal, and 20 gray nuclei). As an application, we report inter-hemispheric (homotopic and heterotopic) and intra-hemispheric connectivity patterns at different sparsities., Comparison With Existing Method: ROI functional homogeneity was higher for AICHA than for anatomical ROI atlases, but slightly lower than for another functional ROI atlas not accounting for homotopy., Conclusion: AICHA is ideally suited for intrinsic/effective connectivity analyses, as well as for investigating brain hemispheric specialization., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Purpose: Conventional MRI based on contrast enhancement is often not sufficient in differentiating grade II from grade III and grade III from grade IV diffuse gliomas. We assessed advanced MRI, MR spectroscopy and [(18)F]-fluoro-l-thymidine ([(18)F]-FLT) PET as tools to overcome these limitations., Methods: In this prospective study, thirty-nine patients with diffuse gliomas of grades II, III or IV underwent conventional MRI, perfusion, diffusion, proton MR spectroscopy ((1)H-MRS) and [(18)F]-FLT-PET imaging before surgery. Relative cerebral blood volume (rCBV), apparent diffusion coefficient (ADC), Cho/Cr, NAA/Cr, Cho/NAA and FLT-SUV were compared between grades., Results: Cho/Cr showed significant differences between grade II and grade III gliomas (p = 0.03). To discriminate grade II from grade IV and grade III from grade IV gliomas, the most relevant parameter was the maximum value of [(18)F]-FLT uptake FLTmax (respectively, p < 0.001 and p < 0.0001). The parameter showing the best correlation with the grade was the mean value of [(18)F]-FLT uptake FLTmean (R(2) = 0.36, p < 0.0001) and FLTmax (R(2) = 0.5, p < 0.0001)., Conclusion: Whereas advanced MRI parameters give indications for the grading of gliomas, the addition of [(18)F]-FLT-PET could be of interest for the accurate preoperative classification of diffuse gliomas, particularly for identification of doubtful grade III and IV gliomas.

Schizophrenia is a mental disorder characterized by language disorders. Studies reveal that both a functional dysconnectivity and a disturbance in the integrity of white matter fibers are implicated in the language process in patients with schizophrenia. Here, we investigate the relationship between functional connectivity within a language-comprehension network and anatomical connectivity using fiber tracking in schizophrenia. We hypothesized that patients would present an impaired functional connectivity in the language network due to anatomical dysconnectivity. Participants comprised 20 patients with DSM-IV schizophrenia and 20 healthy controls who were studied with functional magnetic resonance imaging and diffusion tensor imaging. The temporal correlation coefficient and diffusion values between the left frontal and temporal clusters, belonging to the language network, were individually extracted, in order to study the relationships of anatomo-functional connectivity. In patients, functional connectivity was positively correlated with fractional anisotropy, but was negatively correlated with radial diffusivity and/or mean diffusivity, in the left arcuate fasciculus and part of the inferior occipitofrontal fasciculus, determined as the fronto-temporal tracts. Our findings indicate a close relationship between functional and anatomical dysconnectivity in patients with schizophrenia. The disturbance in the integrity of the left fronto-temporal tracts might be one origin of the functional dysconnectivity in the language-comprehension network in schizophrenia., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Functional connectivity-based analysis of functional magnetic resonance imaging data (fMRI) is an emerging technique for human brain mapping. One powerful method for the investigation of functional connectivity is independent component analysis (ICA) of concatenated data. However, this research field is evolving toward processing increasingly larger database taking into account inter-individual variability. Concatenated data analysis only handles these features using some additional procedures such as bootstrap or including a model of between-subject variability during the preprocessing step of the ICA. In order to alleviate these limitations, we propose a method based on group analysis of individual ICA components, using a multi-scale clustering (MICCA). MICCA start with two steps repeated several times: 1) single subject data ICA followed by 2) clustering of all subject independent components according to a spatial similarity criterion. A final third step consists in selecting reproducible clusters across the repetitions of the two previous steps. The core of the innovation lies in the multi-scale and unsupervised clustering algorithm built as a chain of three processes: robust proto-cluster creation, aggregation of the proto-clusters, and cluster consolidation. We applied MICCA to the analysis of 310 fMRI resting state dataset. MICCA identified 28 resting state brain networks. Overall, the cluster neuroanatomical substrate included 98% of the cerebrum gray matter. MICCA results proved to be reproducible in a random splitting of the data sample and more robust than the classical concatenation method.

During conscious rest, the mind switches into a state of wandering. Although this rich inner experience occupies a large portion of the time spent awake, how it relates to brain activity has not been well explored. Here, we report the results of a behavioral and functional magnetic resonance imaging (fMRI) study of the continuous resting state in 307 healthy participants. The analysis focused on the relationship between the nature of inner experience and the temporal correlations computed between the low-frequency blood oxygen level-dependent (BOLD) fluctuations (0.01-0.1 Hz) of five large-scale modules. The subjects' self-reported time spontaneously spent on visual mental imagery and/or inner language was used as the behavioral variable. Decreased temporal correlations between modules were revealed when subjects reported more time spent thinking in mental images and inner language. These changes segregated the three modules supporting inner-oriented activities from those associated with sensory-related and externally guided activities. Among the brain areas associated with inner-oriented processing, the module including the lateral parietal and frontal regions (commonly described as being engaged in the manipulation and maintenance of internal information) was implicated in the majority of these effects. The preponderance of segregation appears to be the signature of the spontaneous sequence of thoughts during rest that are not constrained by logic, causality, or even a rigorous temporal organization. In other words, though goal-directed tasks have been demonstrated to rely on specific regional integration, mind wandering can be characterized by widespread modular segregation. Overall, the present study provides evidence that modulation of spontaneous low-frequency fluctuations in the brain is at least partially explained by spontaneous conscious cognition while at rest., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Jean Piaget's theory is a central reference point in the study of logico-mathematical development in children. One of the most famous Piagetian tasks is number conservation. Failures and successes in this task reveal two fundamental stages in children's thinking and judgment, shifting at approximately 7 years of age from visuospatial intuition to number conservation. In the current study, preschool children (nonconservers, 5-6 years of age) and school-age children (conservers, 9-10 years of age) were presented with Piaget's conservation-of-number task and monitored by functional magnetic resonance imaging (fMRI). The cognitive change allowing children to access conservation was shown to be related to the neural contribution of a bilateral parietofrontal network involved in numerical and executive functions. These fMRI results highlight how the behavioral and cognitive stages Piaget formulated during the 20th century manifest in the brain with age., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Background: Subjective memory deficit (SMD) is one of few potential presenting symptoms for people with early cognitive impairment. However, associations with underlying brain changes are unclear., Methods: In a community sample of 1,779 people without dementia, and with neuroimaging (MRI) data, associations were investigated for SMD with white matter lesion volume and with the following volumetric measures: gray and white matter, CSF, hippocampal, parahippocampal, and amygdalar. Covariates included depressive symptoms (Center for Epidemiologic Studies Depression Scale), a battery of cognitive tests, physical health, and social activity., Results: SMD was present in 26.4% of the sample. Of the neuroimaging measures analyzed, SMD was most strongly associated with temporal WML (OR for highest quintile compared to the remainder 1.44, 95% CI 1.12-1.85), and lower hippocampal volume (OR per decreasing quintile 1.22, 1.11-1.35). These associations were independent of all other covariates, including cognitive function., Conclusions: Subjective memory deficit (SMD) was associated with neuroimaging characteristics in the temporal and hippocampal regions, suggesting that SMD may, at least in some cases, represent a realistic appraisal of underlying brain function independent of measured cognition. However, further research is required for volumetric measures and SMD to establish whether the association reflects lifelong structure or neurodegenerative changes.

Introduction: An automated procedure for the detection, quantification, localization and statistical mapping of white matter hyperintensities (WMH) on T2-weighted magnetic resonance (MR) images is presented and validated based on the results of a between-centre reproducibility study., Methods: The first step is the identification of white matter (WM) tissue using a multispectral (T1, T2, PD) segmentation. In a second step, WMH are identified within the WM tissue by segmenting T2 images, isolating two different classes of WMH voxels - low- and high-contrast WMH voxels, respectively. The reliability of the whole procedure was assessed by applying it to the analysis of two large MR imaging databases (n = 650 and n= 710, respectively) of healthy elderly subjects matched for demographic characteristics., Results: Average overall WMH load and spatial distribution were found to be similar in the two samples, (1.81 and 1.79% of the WM volume, respectively). White matter hyperintensity load was found to be significantly associated with both age and high blood pressure, with similar effects in both samples. With specific reference to the 650 subject cohort, we also found that WMH load provided by this automated procedure was significantly associated with visual grading of the severity of WMH, as assessed by a trained neurologist., Conclusion: The results show that this method is sensitive, well correlated with semi-quantitative visual rating and highly reproducible.

An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute (MNI) (D. L. Collins et al., 1998, Trans. Med. Imag. 17, 463-468) was performed. The MNI single-subject main sulci were first delineated and further used as landmarks for the 3D definition of 45 anatomical volumes of interest (AVOI) in each hemisphere. This procedure was performed using a dedicated software which allowed a 3D following of the sulci course on the edited brain. Regions of interest were then drawn manually with the same software every 2 mm on the axial slices of the high-resolution MNI single subject. The 90 AVOI were reconstructed and assigned a label. Using this parcellation method, three procedures to perform the automated anatomical labeling of functional studies are proposed: (1) labeling of an extremum defined by a set of coordinates, (2) percentage of voxels belonging to each of the AVOI intersected by a sphere centered by a set of coordinates, and (3) percentage of voxels belonging to each of the AVOI intersected by an activated cluster. An interface with the Statistical Parametric Mapping package (SPM, J. Ashburner and K. J. Friston, 1999, Hum. Brain Mapp. 7, 254-266) is provided as a freeware to researchers of the neuroimaging community. We believe that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain in which deformations are well known. However, this tool does not alleviate the need for more sophisticated labeling strategies based on anatomical or cytoarchitectonic probabilistic maps.

This exploratory study investigated the functional connectivity (FC) in the language network in schizophrenia patients (SZ) with auditory verbal hallucinations (AVHs), and the therapeutic efficacy of rTMS on it. Eleven SZ with AVHs and 10 healthy controls (HC) underwent two fMRI sessions using a speech listening paradigm. SZ received 20Hz rTMS following the first fMRI session. Compared to HC, SZ showed a reduced FC in the language network. While AVHs improved after 12days, no changes in FC were observed. This suggests the efficacy of high-frequency rTMS on AVH without any impact for rTMS on FC within the language network. [ABSTRACT FROM AUTHOR]