Andres Server

Cortical Volume, Surface Area, and Thickness in Schizophrenia and Bipolar Disorder

BACKGROUND Magnetic resonance imaging studies have shown that structural brain abnormalities are present in both schizophrenia and bipolar disorder. Most previous studies have focused on brain tissue volumes, but advances in neuroimaging data processing have made it possible to separate cortical area and cortical thickness. The purpose of the present study was to provide a more complete picture of cortical morphometric differences in schizophrenia and bipolar disorder, decomposing cortical volume into its constituent parts, cortical thickness and cortical area. METHODS We analyzed magnetic resonance imaging images from a sample of 173 patients with schizophrenia, 139 patients with bipolar disorder, and 207 healthy control subjects. Maps of cortical volume, area, and thickness across the continuous cortical surface were generated within groups and compared between the groups. RESULTS There were widespread reductions in cortical volume in schizophrenia relative to healthy control subjects and patients with bipolar disorder type I. These reductions were mainly driven by cortical thinning, but there were also cortical area reductions in more circumscribed regions, which contributed to the observed volume reductions. CONCLUSIONS The current surface-based methodology allows for a distinction between cortical thinning and reduction in cortical area and reveals that cortical thinning is the most important factor in volume reduction in schizophrenia. Cortical area reduction was not observed in bipolar disorder type I and may be unique to schizophrenia.

SLC9A6 Mutations Cause X-Linked Mental Retardation, Microcephaly, Epilepsy, and Ataxia, a Phenotype Mimicking Angelman Syndrome

Linkage analysis and DNA sequencing in a family exhibiting an X-linked mental retardation (XLMR) syndrome, characterized by microcephaly, epilepsy, ataxia, and absent speech and resembling Angelman syndrome, identified a deletion in the SLC9A6 gene encoding the Na(+)/H(+) exchanger NHE6. Subsequently, other mutations were found in a male with mental retardation (MR) who had been investigated for Angelman syndrome and in two XLMR families with epilepsy and ataxia, including the family designated as having Christianson syndrome. Therefore, mutations in SLC9A6 cause X-linked mental retardation. Additionally, males with findings suggestive of unexplained Angelman syndrome should be considered as potential candidates for SLC9A6 mutations.

Quantitative Apparent Diffusion Coefficients in the Characterization of Brain Tumors and Associated Peritumoral Edema

Background: Conventional magnetic resonance (MR) imaging has a number of limitations in the diagnosis of the most common intracranial brain tumors, including tumor specification and the detection of tumoral infiltration in regions of peritumoral edema. Purpose: To prospectively assess if diffusion-weighted MR imaging (DWI) could be used to differentiate between different types of brain tumors and to distinguish between peritumoral infiltration in high-grade gliomas, lymphomas, and pure vasogenic edema in metastases and meningiomas. Material and Methods: MR imaging and DWI was performed on 93 patients with newly diagnosed brain tumors: 59 patients had histologically verified high-grade gliomas (37 glioblastomas multiforme, 22 anaplastic astrocytomas), 23 patients had metastatic brain tumors, five patients had primary cerebral lymphomas, and six patients had meningiomas. Apparent diffusion coefficient (ADC) values of tumor (enhancing regions or the solid portion of tumor) and peritumoral edema, and ADC ratios (ADC of tumor or peritumoral edema to ADC of contralateral white matter, ADC of tumor to ADC of peritumoral edema) were compared with the histologic diagnosis. ADC values and ratios of high-grade gliomas, primary cerebral lymphomas, metastases, and meningiomas were compared by using ANOVA and multiple comparisons. Optimal thresholds of ADC values and ADC ratios for distinguishing high-grade gliomas from metastases were determined by receiver operating characteristic (ROC) curve analysis. Results: Statistically significant differences were found for minimum and mean of ADC tumor and ADC tumor ratio values between metastases and high-grade gliomas when including only one factor at a time. Including a combination of in total four parameters (mean ADC tumor, and minimum, maximum and mean ADC tumor ratio) resulted in sensitivity, specificity, positive (PPV), and negative predictive values (NPV) of 72.9, 82.6, 91.5, and 54.3% respectively. In the ROC curve analysis, the area under the curve of the combined four parameters was the largest (0.84), indicating a good test. Conclusion: Our results suggest that ADC values and ADC ratios (minimum and mean of ADC tumor and ADC tumor ratio) may be helpful in the differentiation of metastases from high-grade gliomas. It cannot distinguish high-grade gliomas from lymphomas, and lymphomas from metastases. ADC values and ADC ratios in peritumoral edema cannot be used to differentiate edema with infiltration of tumor cells from vasogenic edema when measurements for high-grade gliomas, lymphomas, metastases, and meningiomas were compared.

THE HUMAN AMYGDALA IS INVOLVED IN GENERAL BEHAVIORAL RELEVANCE DETECTION: EVIDENCE FROM AN EVENT-RELATED FUNCTIONAL MAGNETIC RESONANCE IMAGING Go-NoGo TASK

The amygdala is classically regarded as a detector of potential threat and as a critical component of the neural circuitry mediating conditioned fear responses. However, it has been reported that the human amygdala responds to multiple expressions of emotions as well as emotionally neutral stimuli of a novel, uncertain or ambiguous nature. Thus, it has been proposed that the function of the amygdala may be of a more general art, i.e. as a detector of behaviorally relevant stimuli [Sander D, Grafman J, Zalla T (2003) The human amygdala: an evolved system for relevance detection. Rev Neurosci 14:303-316]. To investigate this putative function of the amygdala, we used event related functional magnetic resonance imaging (fMRI) and a modified Go-NoGo task composed of behaviorally relevant and irrelevant letter and number stimuli. Analyses revealed bilateral amygdala activation in response to letter stimuli that were behaviorally relevant as compared with letters with less behavioral relevance. Similar results were obtained for relatively infrequent NoGo relevant stimuli as compared with more frequent Go stimuli. Our findings support a role for the human amygdala in general detection of behaviorally relevant stimuli.

Proton magnetic resonance spectroscopy in the distinction of high-grade cerebral gliomas from single metastatic brain tumors.

Background: Brain metastases and primary high-grade gliomas, including glioblastomas multiforme (GBM) and anaplastic astrocytomas (AA), may be indistinguishable by conventional magnetic resonance (MR) imaging. Identification of these tumors may have therapeutic consequences. Purpose: To assess the value of MR spectroscopy (MRS) using short and intermediate echo time (TE) in differentiating solitary brain metastases and high-grade gliomas on the basis of differences in metabolite ratios in the intratumoral and peritumoral region. Material and Methods: We performed MR imaging and MRS in 73 patients with histologically verified intraaxial brain tumors: 53 patients with high-grade gliomas (34 GBM and 19 AA) and 20 patients with metastatic brain tumors. The metabolite ratios of Cho/Cr, Cho/NAA, and NAA/Cr at intermediate TE and the presence of lipids at short TE were assessed from spectral maps in the tumoral core, peritumoral edema, and contralateral normal-appearing white matter. The differences in the metabolite ratios between high-grade gliomas/GBM/AA and metastases were analyzed statistically. Cutoff values of Cho/Cr, Cho/NAA, and NAA/Cr ratios in the peritumoral edema, as well as Cho/Cr and NAA/Cr ratios in the tumoral core for distinguishing high-grade gliomas/GBM/AA from metastases were determined by receiver operating characteristic (ROC) curve analysis. Results: Significant differences were noted in the peritumoral Cho/Cr, Cho/NAA, and NAA/ Cr ratios between high-grade gliomas/GBM/AA and metastases. ROC analysis demonstrated a cutoff value of 1.24 for peritumoral Cho/Cr ratio to provide sensitivity, specificity, positive (PPV), and negative predictive values (NPV) of 100%, 88.9%, 80.0%, and 100%, respectively, for discrimination between high-grade gliomas and metastases. By using a cutoff value of 1.11 for peritumoral Cho/NAA ratio, the sensitivity was 100%, the specificity was 91.1%, the PPV was 83.3%, and the NPV was 100%. Conclusion: The results of this study demonstrate that MRS can differentiate high-grade gliomas from metastases, especially with peritumoral measurements, supporting the hypothesis that MRS can detect infiltration of tumor cells in the peritumoral edema.

Measurements of diagnostic examination performance using quantitative apparent diffusion coefficient and proton MR spectroscopic imaging in the preoperative evaluation of tumor grade in cerebral gliomas.

PURPOSE Tumor grading is very important both in treatment decision and evaluation of prognosis. While tissue samples are obtained as part of most therapeutic approaches, factors that may result in inaccurate grading due to sampling error (namely, heterogeneity in tissue sampling, as well as tumor-grade heterogeneity within the same tumor specimen), have led to a desire to use imaging better to ascertain tumor grade. The purpose in our study was to evaluate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC), and accuracy of diffusion-weighted MR imaging (DWI), proton MR spectroscopic imaging (MRSI) or both in grading primary cerebral gliomas. MATERIALS AND METHODS We performed conventional MR imaging (MR), DWI, and MRSI in 74 patients with newly diagnosed brain gliomas: 59 patients had histologically verified high-grade gliomas: 37 glioblastomas multiform (GBM) and 22 anaplastic astrocytomas (AA), and 15 patients had low-grade gliomas. Apparent diffusion coefficient (ADC) values of tumor and peritumoral edema, and ADC ratios (ADC in tumor or peritumoral edema to ADC of contralateral white matter, as well as ADC in tumor to ADC in peritumoral edema) were determined from three regions of interest. The average of the mean, maximum, and minimum for ADC variables was calculated for each patient. The metabolite ratios of Cho/Cr and Cho/NAA at intermediate TE were assessed from spectral maps in the solid portion of tumor, peritumoral edema and contralateral normal-appearing white matter. Tumor grade determined with the two methods was then compared with that from histopathologic grading. Logistic regression and receiver operating characteristic (ROC) curve analysis were performed to determine optimum thresholds for tumor grading. Measures of diagnostic examination performance, such as sensitivity, specificity, PPV, NPV, AUC, and accuracy for identifying high-grade gliomas were also calculated. RESULTS Statistical analysis demonstrated a threshold minimum ADC tumor value of 1.07 to provide sensitivity, specificity, PPV, and NPV of 79.7%, 60.0%, 88.7%, and 42.9% respectively, in determining high-grade gliomas. Threshold values of 1.35 and 1.78 for peritumoral Cho/Cr and Cho/NAA metabolite ratios resulted in sensitivity, specificity, PPV, and NPV of 83.3%, 85.1%, 41.7%, 97.6%, and 100%, 57.4%, 23.1% and 100% respectively for determining high-grade gliomas. Significant differences were noted in the ADC tumor values and ratios, peritumoral Cho/Cr and Cho/NAA metabolite ratios, and tumoral Cho/NAA ratio between low- and high-grade gliomas. The combination of mean ADC tumor value, maximum ADC tumor ratio, peritumoral Cho/Cr and Cho/NAA metabolite ratios resulted in sensitivity, specificity, PPV, and NPV of 91.5%, 100%, 100% and 60% respectively. CONCLUSION Combining DWI and MRSI increases the accuracy of preoperative imaging in the determination of glioma grade. MRSI had superior diagnostic performance in predicting glioma grade compared with DWI alone. The predictive values are helpful in the clinical decision-making process to evaluate the histologic grade of tumors, and provide a means of guiding treatment.

Working memory networks and activation patterns in schizophrenia and bipolar disorder : comparison with healthy controls

BACKGROUND Schizophrenia and bipolar disorder are severe mental disorders with overlapping genetic and clinical characteristics, including cognitive impairments. An important question is whether these disorders also have overlapping neuronal deficits. AIMS To determine whether large-scale brain networks associated with working memory, as measured with functional magnetic resonance imaging (fMRI), are the same in both schizophrenia and bipolar disorder, and how they differ from those in healthy individuals. METHOD Patients with schizophrenia (n = 100) and bipolar disorder (n = 100) and a healthy control group (n = 100) performed a 2-back working memory task while fMRI data were acquired. The imaging data were analysed using independent component analysis to extract large-scale networks of task-related activations. RESULTS Similar working memory networks were activated in all groups. However, in three out of nine networks related to the experimental task there was a graded response difference in fMRI signal amplitudes, where patients with schizophrenia showed greater activation than those with bipolar disorder, who in turn showed more activation than healthy controls. Secondary analysis of the patient groups showed that these activation patterns were associated with history of psychosis and current elevated mood in bipolar disorder. CONCLUSIONS The same brain networks were related to working memory in schizophrenia, bipolar disorder and controls. However, some key networks showed a graded hyperactivation in the two patient groups, in line with a continuum of neuronal abnormalities across psychotic disorders.

POST-TRAUMATIC CEREBRAL INFARCTION: Neuroimaging findings, etiology and outcome

Purpose: To assess the radiological characteristics of post-traumatic cerebral infarctions (PTCIs), the etiology and site of infarction, and to provide neuroimaging indicators of a poor clinical outcome. Material and Methods: A retrospective study of 16 patients with the neuroimaging-based diagnosis of PTCI was carried out. All CT, MR examinations, cerebral angiograms and medical records of the patients were reviewed. Results: Infarcts were diagnosed in the territory of the posterior cerebral artery in 9 patients, in the middle cerebral artery in 5, in the anterior cerebral artery in 3, lenticulostriate-thalamoperforating in 2, vertebrobasilar in 3, and cortical infarcts in 2 patients. Neuroimaging studies suggested focal mass effect and/or acquired intracranial herniations as the cause of infarction in 13/16 patients (81.2%). In 3/16 patients (18.8%), PTCI was due to vascular injury of which 2 were angiographically documented (carotid artery dissection). Eight of the 16 patients in this study died or were left in a persistent vegetative state. Patients with associated subdural hematoma, brain swelling/edema and traumatic subarachnoid hemorrhage (tSAH) exhibited the worst outcome. Conclusion: Gross mechanical shift of the brain and herniation across the falx and/or tentorium accounted for infarction in a majority of cases in our study. The overall death rate was 43.8% and this result suggests that PTCI is an indication of a poor clinical outcome, especially among patients with associated subdural hematoma, brain swelling/edema and tSAH.

Diagnostic performance of texture analysis on MRI in grading cerebral gliomas

BACKGROUND AND PURPOSE Grading of cerebral gliomas is important both in treatment decision and assessment of prognosis. The purpose of this study was to determine the diagnostic accuracy of grading cerebral gliomas by assessing the tumor heterogeneity using MRI texture analysis (MRTA). MATERIAL AND METHODS 95 patients with gliomas were included, 27 low grade gliomas (LGG) all grade II and 68 high grade gliomas (HGG) (grade III=34 and grade IV=34). Preoperative MRI examinations were performed using a 3T scanner and MRTA was done on preoperative contrast-enhanced three-dimensional isotropic spoiled gradient echo images in a representative ROI. The MRTA was assessed using a commercially available research software program (TexRAD) that applies a filtration-histogram technique for characterizing tumor heterogeneity. Filtration step selectively filters and extracts texture features at different anatomical scales varying from 2mm (fine features) to 6mm (coarse features), the statistical parameter standard deviation (SD) was obtained. Receiver operating characteristics (ROC) was performed to assess sensitivity and specificity for differentiating between the different grades and calculating a threshold value to quantify the heterogeneity. RESULTS LGG and HGG was best discriminated using SD at fine texture scale, with a sensitivity and specificity of 93% and 81% (AUC 0.910, p<0.0001). The diagnostic ability for MRTA to differentiate between the different sub-groups (grade II-IV) was slightly lower but still significant. CONCLUSIONS Measuring heterogeneity in gliomas to discriminate HGG from LGG and between different histological sub-types on already obtained images using MRTA can be a useful tool to augment the diagnostic accuracy in grading cerebral gliomas and potentially hasten treatment decision.

Conventional and Diffusion‐Weighted MRI in the Evaluation of Methanol Poisoning

Cerebral lesions were studied in 2 methanol-poisoned patients using conventional magnetic resonance imaging (MRI). In 1 patient, diffusion-weighted MRI (DWI) was also performed. In this patient, conventional MRI showed symmetrical, bilateral increased signal in the lentiform nuclei, involving predominantly putamina, but also extending into the corona radiata, centrum semiovale and subcortical white matter. DWI showed decreased diffusion, which most probably reflects cytotoxic edema. In the other patient, fluid attenuated-inversion recovery (FLAIR) and T2-weighted images showed hyperintensity in the putamina, characteristic of post-necrotic changes.