Juan J. Lull

MRI denoising using Non-Local Means

Magnetic Resonance (MR) images are affected by random noise which limits the accuracy of any quantitative measurements from the data. In the present work, a recently proposed filter for random noise removal is analyzed and adapted to reduce this noise in MR magnitude images. This parametric filter, named Non-Local Means (NLM), is highly dependent on the setting of its parameters. The aim of this paper is to find the optimal parameter selection for MR magnitude image denoising. For this purpose, experiments have been conducted to find the optimum parameters for different noise levels. Besides, the filter has been adapted to fit with specific characteristics of the noise in MR image magnitude images (i.e. Rician noise). From the results over synthetic and real images we can conclude that this filter can be successfully used for automatic MR denoising.

Schizophrenia with auditory hallucinations: a voxel-based morphometry study.

Many studies have shown widespread but subtle pathological changes in gray matter in patients with schizophrenia. Some of these studies have related specific alterations to the genesis of auditory hallucinations, particularly in the left superior temporal gyrus, but none has analysed the relationship between morphometric data and a specific scale for auditory hallucinations. The present study aims to define the presence and characteristics of structural abnormalities in relation with the intensity and phenomenology of auditory hallucinations by means of magnetic resonance voxel-based morphometry (MR-VBM) method applied on a highly homogeneous group of 18 persistent hallucinatory patients meeting DSM-IV criteria for schizophrenia compared to 19 healthy matched controls. Patients were evaluated using the PSYRATS scale for auditory hallucinations. Reductions of gray matter concentration in patients to controls were observed in bilateral insula, bilateral superior temporal gyri and left amygdala. In addition, specific relationships between left inferior frontal and right postcentral gyri reductions and the severity of auditory hallucinations were observed. All these areas might be implicated in the genesis and/or persistence of auditory hallucinations through specific mechanisms. Precise morphological abnormalities may help to define reliable MR-VBM biomarkers for the genesis and persistence of auditory hallucinations.

Left orbitofrontal and superior temporal gyrus structural changes associated to suicidal behavior in patients with schizophrenia

Suicidal attempts are relatively frequent and clinically relevant in patients with schizophrenia. Recent studies have found gray matter differences in suicidal and non-suicidal depressive patients. However, no previous neuroimaging study has investigated possible structural abnormalities associated to suicidal behaviors in patients with schizophrenia. A whole-brain magnetic resonance voxel-based morphometric examination was performed on 37 male patients meeting the DSM-IV criteria for schizophrenia. Thirteen (35.14%) patients had attempted suicide. A non-parametric permutation test was computed to perform the comparability between groups. An analysis of covariance (AnCova) model was constructed with a statistical threshold of p<0.05 corrected for multiple comparisons. After controlling for age and severity of illness, results showed significant gray matter density reduction in left superior temporal lobe (p=0.03) and left orbitofrontal cortex (p=0.04) in patients who had attempted suicide when comparing with non-suicidal patients. Although sample size limitations and potential clinical heterogeneity preclude definitive conclusions, these data point to structural differences in key cerebral areas. Neuroimaging studies are necessary to expand our knowledge of biological mechanisms underlying suicide in schizophrenia.

A nonparametric MRI inhomogeneity correction method

Magnetic resonance images are commonly affected by intensity inhomogeneities which make it difficult to obtain any quantitative measures from them. We present a new method of automatically correcting this artifact using a nonparametric coarse to fine approach which allows bias fields to be modeled with different frequency ranges without user supervision. We also propose a new entropy-related cost function based on the combination of intensity and gradient image features for more robust homogeneity measurement. The proposed methodology has been evaluated for both synthetic and real data and compared with state of the art methods, showing the best results in the comparison. The proposed method is fully automatic and has no input parameters, making it very easy to use in a clinical environment.

Emotional words induce enhanced brain activity in schizophrenic patients with auditory hallucinations

Neuroimaging studies of emotional response in schizophrenia have mainly used visual (faces) paradigms and shown globally reduced brain activity. None of these studies have used an auditory paradigm. Our principal aim is to evaluate the emotional response of patients with schizophrenia to neutral and emotional words. An auditory emotional paradigm based on the most frequent words heard by psychotic patients with auditory hallucinations was designed. This paradigm was applied to evaluate cerebral activation with functional magnetic resonance imaging (fMRI) in 11 patients with schizophrenia with persistent hallucinations and 10 healthy subjects. We found a clear enhanced activity of the frontal lobe, temporal cortex, insula, cingulate, and amygdala (mainly right side) in patients when hearing emotional words in comparison with controls. Our findings are consistent with other studies suggesting a relevant role for emotional response in the pathogenesis and treatment of auditory hallucinations.

A voxel-based analysis of FDG-PET in traumatic brain injury: regional metabolism and relationship between the thalamus and cortical areas.

The objective was to study the correlations and the differences in glucose metabolism between the thalamus and cortical structures in a sample of severe traumatic brain injury (TBI) patients with different neurological outcomes. We studied 49 patients who had suffered a severe TBI and 10 healthy control subjects using 18F-fluorodeoxyglucose positron emission tomography (18F-FDG-PET). The patients were divided into three groups: a vegetative or minimally-conscious state (MCS&VS) group (n=17), which included patients who were in a vegetative or a minimally conscious state; an In-post-traumatic amnesia (In-PTA) group (n=12), which included patients in PTA; and an Out-PTA group (n=20), which included patients who had recovered from PTA. SPM5 software was used to determine the metabolic differences between the groups. FDG-PET images were normalized and four regions of interest were generated around the thalamus, precuneus, and the frontal and temporal lobes. The groups were parameterized using Students t-test. Principal component analysis was used to obtain an intensity-estimated-value per subject to correlate the function between the structures. Differences in glucose metabolism in all structures were related to the neurological outcome, and the most severe patients showed the most severe hypometabolism. We also found a significant correlation between the cortico-thalamo-cortical metabolism in all groups. Voxel-based analysis suggests a functional correlation between these four areas, and decreased metabolism was associated with less favorable outcomes. Higher levels of activation of the cortico-cortical connections appear to be related to better neurological condition. Differences in the thalamo-cortical correlations between patients and controls may be related to traumatic dysfunction due to focal or diffuse lesions.

Increased amygdala and parahippocampal gyrus activation in schizophrenic patients with auditory hallucinations: An fMRI study using independent component analysis

OBJECTIVE Hallucinations in patients with schizophrenia have strong emotional connotations. Functional neuroimaging techniques have been widely used to study brain activity in patients with schizophrenia with hallucinations or emotional impairments. However, few of these studies have investigated the association between hallucinations and emotional dysfunctions using an emotional auditory paradigm. Independent component analysis (ICA) is an analysis method that is especially useful for decomposing activation during complex cognitive tasks in which multiple operations occur simultaneously. Our aim in this study is to analyze brain activation after the presentation of emotional auditory stimuli in patients with schizophrenia with and without chronic auditory hallucinations using ICA methodology. It was hypothesized that functional connectivity differences in limbic regions responsible for emotional processing would be demonstrated. METHODS The present functional magnetic resonance imaging (fMRI) study compared neural activity in 41 patients with schizophrenia (27 with auditory hallucinations, 14 without auditory hallucinations) with 31 controls. Neural activity data was generated while participants were presented with an auditory paradigm containing emotional words. The comparison was performed using a multivariate approach, ICA. Differences in temporo-spatial aspects of limbic network were examined in three study groups. RESULTS Limbic networks responded differently in patients with auditory hallucinations compared to healthy controls and patients without auditory hallucinations. Unlike control subjects and non-hallucinators, the group of hallucinatory patients showed an increase of activity in the parahippocampal gyrus and the amygdala during the emotional session. CONCLUSIONS These findings may reflect an increase in parahippocampal gyrus and amygdala activity during passive listening of emotional words in patients with schizophrenia and auditory hallucinations.

Multicomponent MR image denoising

Magnetic Resonance images are normally corrupted by random noise from the measurement process complicating the automatic feature extraction and analysis of clinical data. It is because of this reason that denoising methods have been traditionally applied to improve MR image quality. Many of these methods use the information of a single image without taking into consideration the intrinsic multicomponent nature of MR images. In this paper we propose a new filter to reduce random noise in multicomponent MR images by spatially averaging similar pixels using information from all available image components to perform the denoising process. The proposed algorithm also uses a local Principal Component Analysis decomposition as a postprocessing step to remove more noise by using information not only in the spatial domain but also in the intercomponent domain dealing in a higher noise reduction without significantly affecting the original image resolution. The proposed method has been compared with similar state-of-art methods over synthetic and real clinical multicomponent MR images showing an improved performance in all cases analyzed.

Voxel-based statistical analysis of thalamic glucose metabolism in traumatic brain injury: relationship with consciousness and cognition

Objective: To study the relationship between thalamic glucose metabolism and neurological outcome after severe traumatic brain injury (TBI). Methods: Forty-nine patients with severe and closed TBI and 10 healthy control subjects with 18F-FDG PET were studied. Patients were divided into three groups: MCS&VS group (n = 17), patients in a vegetative or a minimally conscious state; In-PTA group (n = 12), patients in a state of post-traumatic amnesia (PTA); and Out-PTA group (n = 20), patients who had emerged from PTA. SPM5 software implemented in MATLAB 7 was used to determine the quantitative differences between patients and controls. FDG-PET images were spatially normalized and an automated thalamic ROI mask was generated. Group differences were analysed with two sample voxel-wise t-tests. Results: Thalamic hypometabolism was the most prominent in patients with low consciousness (MCS&VS group) and the thalamic hypometabolism in the In-PTA group was more prominent than that in the Out-PTA group. Healthy control subjects showed the greatest thalamic metabolism. These differences in metabolism were more pronounced in the internal regions of the thalamus. Conclusions: The results confirm the vulnerability of the thalamus to suffer the effect of the dynamic forces generated during a TBI. Patients with thalamic hypometabolism could represent a sub-set of subjects that are highly vulnerable to neurological disability after TBI.

Robust MRI brain tissue parameter estimation by multistage outlier rejection

This article addresses the problem of the tissue type parameter estimation in brain MRI in the presence of partial volume effects. Automatic MRI brain tissue classification is hampered by partial volume effects that are caused by the finite resolution of the acquisition process. Due to this effect intensity distributions in brain MRI cannot be well modeled by a simple mixture of Gaussians and therefore more complex models have been developed. Unfortunately, these models do not seem to be robust enough for clinical conditions, as the quality of the tissue classification decreases rapidly with the image quality. Also, the application of these methods for pathological images with unmodeled intensities (e.g. MS plaques, tumors, etc.) remains uncertain. In the present work a new robust method for brain tissue characterization is presented, treating the partial volume affected voxels as outliers of the pure tissue distributions. The proposed method estimates the tissue characteristics from a reduced set of intensities belonging to a particular pure tissue class. This reduced set is selected by using a trimming procedure based on local gradient information and distributional data. This feature makes the method highly tolerant of a large amount of unexpected intensities without degrading its performance. The proposed method has been evaluated using both synthetic and real MR data and compared with state‐of‐the‐art methods showing the best results in the comparative. Magn Reson Med 59:866–873, 2008.