From EEG to BOLD: Brain mapping and estimating transfer functions in simultaneous EEG-fMRI acquisitions

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.

Characterization of Superparamagnetic Iron Oxide Coated with Silicone Used as Contrast Agent for Magnetic Resonance Image for the Gastrointestinal Tract

The present work is a report of the characterization of superparamagnetic iron oxide nanoparticles coated with silicone used as a contrast agent in magnetic resonance imaging of the gastrointestinal tract. The hydrodynamic size of the contrast agent is 281.2 rim, where it was determined by transmission electron microscopy and a Fe(3)O(4) crystalline structure was identified by X-ray diffraction, also confirmed by Mossbauer Spectroscopy. The blocking temperature of 190 K was determined from magnetic measurements based on the Zero Field Cooled and Field Cooled methods. The hysteresis loops were measured at different temperatures below and above the blocking temperature. Ferromagnetic resonance analysis indicated the superparamagnetic nature of the nanoparticles and a strong temperature dependence of the peak-to-peak linewidth Delta H(pp), giromagnetic factor g, number of spins N(S) and relaxation time T(2) were observed. This behavior can be attributed to an increase in the superexchange interaction.

Cortical Thickness Reduction of Normal Appearing Cortex in Patients with Polymicrogyria

OBJECTIVE To examine cortical thickness and volumetric changes in the cortex of patients with polymicrogyria, using an automated image analysis algorithm. METHODS Cortical thickness of patients with polymicrogyria was measured using magnetic resonance imaging (MRI) cortical surface-based analysis and compared with age-and sex-matched healthy subjects. We studied 3 patients with disorder of cortical development (DCD), classified as polymicrogyria, and 15 controls. Two experienced neuroradiologists performed a conventional visual assessment of the MRIs. The same data were analyzed using an automated algorithm for tissue segmentation and classification. Group and individual average maps of cortical thickness differences were produced by cortical surface-based statistical analysis. RESULTS Patients with polymicrogyria showed increased thickness of the cortex in the same areas identified as abnormal by radiologists. We also identified a reduction in the volume and thickness of cortex within additional areas of apparently normal cortex relative to controls. CONCLUSIONS Our findings indicate that there may be regions of reduced cortical thickness, which appear normal from radiological analysis, in the cortex of patients with polymicrogyria. This finding suggests that alterations in neuronal migration may have an impact in the cortical formation of the cortical areas that are visually normal. These areas are associated or occur concurrently with polymicrogyria.

Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

Renal Cell Carcinoma: T1 and T2 Signal Intensity Characteristics of Papillary and Clear Cell Types Correlated with Pathology

OBJECTIVE. The objective of our study was to describe the T1 and T2 signal intensity characteristics of papillary renal cell carcinoma (RCC) and clear cell RCC with pathologic correlation. MATERIALS AND METHODS. Of 539 RCCs, 49 tumors (21 papillary RCCs and 28 clear cell RCCs) in 45 patients were examined with MRI. Two radiologists retrospectively and independently assessed each tumor`s T1 and T2 signal intensity qualitatively and quantitatively (i.e., the signal intensity [SI] ratio [tumor SI/renal cortex SI]). Of the 49 tumors, 37 (76%) were assessed for pathology features including tumor architecture and the presence of hemosiderin, ferritin, necrosis, and fibrosis. MRI findings and pathology features were correlated. Statistical methods included summary statistics and Wilcoxon`s rank sum test for signal intensity, contingency tables for assessing reader agreement, concordance rate between the two readers with 95% CIs, and Fisher`s exact test for independence, all stratified by RCC type. RESULTS. Papillary RCCs and clear cell RCCs had a similar appearance and signal intensity ratio on T1-weighted images. On T2-weighted images, most papillary RCCs were hypointense (reader 1, 13/21; reader 2, 14/21), with an average mean signal intensity ratio for both readers of 0.67 +/- 0.2, and none was hyperintense, whereas most clear cell RCCs were hyperintense (reader 1, 21/28; reader 2, 17/28), with an average mean signal intensity ratio for both readers of 1.41 +/- 0.4 (p < 0.05). A tumor T2 signal intensity ratio of <= 0.66 had a specificity of 100% and sensitivity of 54% for papillary RCC. Most T2 hypointense tumors exhibited predominant papillary architecture; most T2 hyperintense tumors had a predominant nested architecture (p < 0.05). CONCLUSION. On T2-weighted images, most papillary RCCs are hypointense and clear cell RCCs, hyperintense. The T2 hypointense appearance of papillary RCCs correlated with a predominant papillary architecture at pathology.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Quantitative ferromagnetic resonance analysis of CD133 stem cells labeled with iron oxide nanoparticles

The aim of this work is to provide a quantitative method for analysis of the concentration of superparamagnetic iron oxide nanoparticles (SPION), determined by means of ferromagnetic resonance (FMR), with the nanoparticles coupled to a specific antibody (AC133), and thus to express the antigenic labeling evidence for the stem cells C D133(+). The FMR efficiency and sensitivity were proven adequate for detecting and quantifying the low amounts of iron content in the C D133(+) cells (similar to 6.16 x 10(5) pg in the volume of 2 mu l containing 4.5 x 1011 SPION). The quantitative method led to the result of 1.70 x 10(-13) mol of Fe (9.5 pg), or 7.0 x 10(6) nanoparticles per cell. For the quantification analysis via the FMR technique it was necessary to carry out a preliminary quantitative visualization of iron oxide-labeled cells in order to ensure that the nanoparticles coupled to the antibodies are indeed tied to the antigen at the stem cell surface and that the cellular morphology was conserved, as proof of the validity of this method. The quantitative analysis by means of FMR is necessary for determining the signal intensity for the study of molecular imaging by means of magnetic resonance imaging (MRI).

Extremely late development of pituitary carcinoma after surgery and radiotherapy

Introduction Pituitary carcinomas account for 0.1 or 0.2% of pituitary tumors. The authors report a rare case of a pituitary carcinoma mimicking a radio-induced meningioma. Case report Fifty-five years-old male presents a previous history of transcranial surgery in 1983 for invasive pituitary adenoma followed by whole-brain radiotherapy (5100 cGy). After three years he presented worsening of visual deficits and MRI evidenced recurrence of the lesion. In 1992, he underwent a transcranial approach to treat recurrent supraselar disease, followed by stereoctatic radiotherapy. In 2006, clinical condition was stable; however three right frontal extra-axial lesions were diagnosed by MRI, compatible with meningioma. The histological examination revealed pituitary adenoma. No lesions were found in craniospinal axis. Further treatment was not recommended by radiotherapists due previous actinic treatments. Two years radiological follow-up revealed no recurrence. Conclusion In these high risk cases, active and constant surveillance must be pertained, regardless the time of follow-up.

Accuracy of magnetic resonance imaging for diagnosis and preoperative assessment of deeply infiltrating endometriosis

Objective: To evaluate the accuracy of preoperative magnetic resonance imaging (MRI) findings relative to surgical presence of deeply infiltrating endometriosis (DIE). Methods: This prospective study included 92 women with clinical suspicion of DIE. The MR images were compared with laparoscopy and pathology findings. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MRI for diagnosis of DIE were assessed. Results: DIE was confirmed at histopathology in 77 of the 92 patients (83.7%). Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MRI to diagnose DIE at each of the specific sites evaluated were as follows: retrocervical space (89.4%, 92.3%, 96.7%, 77.4%, 90.2%); rectosigmoid (86.0%, 92.9%, 93.5%, 84.8%, 89.1%); bladder (23.1%, 100%,100%, 88.8%, 89.1%); ureters (50.0%, 100%, 95.5%, 95.7%); and vagina (72.7%, 100%, 100%, 96.4%, 96.7%). Conclusion: MRI demonstrates high accuracy in diagnosing DIE in the retrocervical region, rectosigmoid. bladder, ureters, and vagina. (C) 2009 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Lid. All rights reserved.

Transvaginal ultrasound for diagnosis of deeply infiltrating endometriosis

Deeply infiltrating endometriosis is the clinical form of the disease that is generally associated with conditions of more intense pain and may require more complex surgical management, consequently resulting in greater risks to the patient. In recent years, various investigators have confirmed the usefulness of methods such as magnetic resonance imaging (MRI), transrectal ultrasound and transvaginal ultrasound (TVUS) for the diagnosis of deep endometriotic lesions. The objectives of the present study are to describe the method used to perform TVUS for the detection of deeply infiltrating endometriosis, and to discuss the clinical benefits that the data obtained may offer clinicians providing care for patients suspected of having this type of endometriosis. (C) 2008 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Vascular diseases and old age mental disorders: an update of neuroimaging findings

Purpose of review To review neuroimaging findings that have been reported in samples of patients with cardiovascular disorders and their association with the onset of Alzheimer`s disease, vascular dementia, depression and bipolar disorder in the elderly and to highlight the implications of these findings to the knowledge about the pathophysiology of psychiatric disorders in old age, as well as their potential clinical implications. Recent findings Vascular risk factors, such as hypertension, diabetes, dyslipidemia, smoking habits and heart failure, have all been associated with signs of cerebrovascular dysfunction, including structural MRI findings of signal hyperintensities, lacunes and stroke and functional imaging findings of brain regional hypoperfusion and hypometabolism. Such brain abnormalities have been found to increase the risk of onset of psychiatric disorder (depression, bipolar and dementia) in old age. Summary As vascular risk factors are potentially modifiable when detected in midlife, the early characterization of brain changes associated with the presence of cardiovascular diseases holds promise to afford clinical applications in psychiatry, providing new perspectives for the prevention of old age psychiatric disorders.

Lack of progression of brain abnormalities in first-episode psychosis: a longitudinal magnetic resonance imaging study

Background. Some neuroimaging studies have supported the hypothesis of progressive brain changes after a first episode of psychosis. We aimed to determine whether (i) first-episode psychosis patients would exhibit more pronounced brain volumetric changes than controls over time and (ii) illness course/treatment would relate to those changes. Method. Longitudinal regional grey matter volume and ventricle : brain ratio differences between 39 patients with first-episode psychosis (including schizophrenia and schizophreniform disorder) and 52 non-psychotic controls enrolled in a population-based case-control study. Results. While there was no longitudinal difference in ventricle : brain ratios between first-episode psychosis subjects and controls, patients exhibited grey matter volume changes, indicating a reversible course in the superior temporal cortex and hippocampus compared with controls. A remitting course was related to reversal of baseline temporal grey matter deficits. Conclusions. Our findings do not support the hypothesis of brain changes indicating a progressive course in the initial phase of psychosis. Rather, some brain volume abnormalities may be reversible, possibly associated with a better illness course.

State-dependent microstructural white matter changes in bipolar I depression

Abnormalities in fronto-limbic-striatal white matter (WM) have been reported in bipolar disorder (BD), but results have been inconsistent across studies. Furthermore, there have been no detailed investigations as to whether acute mood states contribute to microstructural changes in WM tracts. In order to compare fiber density and structural integrity within WM tracts between BD depression and remission, whole-brain fractional anisotropy (FA) and mean diffusivity (MD) were assessed in 37 bipolar I disorder (BD-I) patients (16 depressed and 21 remitted), and 26 healthy individuals with diffusion tensor imaging. Significantly decreased FA and increased MD in bilateral prefronto-limbic-striatal white matter and right inferior fronto-occipital, superior and inferior longitudinal fasciculi were shown in all BD-I patients versus controls, as well as in depressed BD-I patients compared to both controls and remitted BD-I patients. Depressed BD-I patients also exhibited increased FA in the ventromedial prefrontal cortex. Remitted BD-I patients did not differ from controls in FA or MD. These findings suggest that BD-I depression may be associated with acute microstructural WM changes.

Association between symptom severity and internal capsule volume in obsessive-compulsive disorder

Neurobiological models support an involvement of white matter tracts in the pathophysiology of obsessive-compulsive disorder (OCD), but there has been little systematic evaluation of white matter volumes in OCD using magnetic resonance imaging (MRI). We investigated potential differences in the volume of the cingulum bundle (CB) and anterior limb of internal capsule (ALIC) in OCD patients (n = 19) relative to asymptomatic control subjects (n = 15). White matter volumes were assessed using a 1.5T MRI scanner. Between-group comparisons were carried out after spatial normalization and image segmentation using optimized voxel-based morphometry. Correlations between regional white matter volumes in OCD subjects and symptom severity ratings were also investigated. We found significant global white matter reductions in OCD patients compared to control subjects. The voxel-based search for regional abnormalities (with covariance for total white matter volumes) showed no specific white matter volume deficits in brain portions predicted a priori to be affected in OCD (CB and ALIC). However, large clusters of significant positive correlation with OCD severity scores were found bilaterally on the ALIC. These findings provide evidence of OCD-related ALIC abnormalities and suggest a connectivity dysfunction within frontal-striatal-thalamic-cortical circuits. Further studies are warranted to better define the role of such white matter alterations in the pathophysiology of OCD, and may provide clues for a more effectively targeting of neurosurgical treatments for OCD. (C) 2009 Elsevier Ireland Ltd. All rights reserved.