Navegando por Palavras-chave "Magnetic resonance imaging (MRI)"

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    Gamma ventral capsulotomy for treatment of resistant obsessive-compulsive disorder: A structural MRI pilot prospective study
    (Elsevier B.V., 2008-12-12) Cecconia, Janaina Philippi; Lopes, Antonio Carlos; Duran, Fabio Luis de Souza; Santos, Luciana Cristina; Hoexter, Marcelo Queiroz [UNIFESP]; Gentil, Andre Felix; Canteras, Miguel Montes; Castro, Claudio Campi de; Noren, George; Greenberg, Benjamin D.; Rauch, Scott L.; Busatto, Geraldo F.; Miguel, Euripedes Constantino; Universidade de São Paulo (USP); Universidade Federal de São Paulo (UNIFESP); Hosp Santa Paula; Brown Univ; Harvard Univ; Massachusetts Gen Hosp
    Objective: the purpose of this study was to investigate regional structural abnormalities in the brains of five patients with refractory obsessive-compulsive disorder (OCD) submitted to gamma ventral capsulotomy. Methods: We acquired morphometric magnetic resonance imaging (MRI) data before and after 1 year of radiosurgery using a 1.5-T MRI scanner. Images were spatially normalized and segmented using optimized voxel-based morphometry (VBM) methods. Voxelwise statistical comparisons between pre- and post-surgery MRI scans were performed using a general linear model. Findings in regions predicted a priori to show volumetric changes (orbitofrontal cortex, anterior cingulate gyrus, basal ganglia and thalamus) were reported as significant if surpassing a statistical threshold of p<0.001 (uncorrected for multiple comparisons). Results: We detected a significant regional postoperative increase in gray matter volume in the right inferior frontal gyri (Brodmann area 47, BA47) when comparing all patients pre and postoperatively. Conclusions: Our results support the current theory of frontal-striatal-thalamic-cortical (FSTC) circuitry involvement in OCD pathogenesis. Gamma ventral capsulotomy is associated with neurobiological changes in the inferior orbitofrontal cortex in refractory OCD patients. (C) 2008 Elsevier Ireland Ltd. All rights reserved.
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    How useful is preoperative imaging for tumor, node, metastasis (TNM) staging of gastric cancer? A meta-analysis
    (Springer, 2012-09-01) Seevaratnam, Rajini; Cardoso, Roberta; Mcgregor, Caitlin; Lourenço, Laércio Gomes [UNIFESP]; Mahar, Alyson; Sutradhar, Rinku; Law, Calvin; Paszat, Lawrence; Coburn, Natalie; Sunnybrook Hlth Sci Ctr; Universidade Federal de São Paulo (UNIFESP); Queens Univ; Univ Toronto; Inst Clin Evaluat Sci
    Background Surgery is the fundamental curative option for gastric cancer patients. Imaging scans are routinely prescribed in an attempt to stage the disease prior to surgery. Consequently, the correlation between radiology exams and pathology is crucial for appropriate treatment planning.Methods Systematic searches were conducted using Medline, Embase, and the Cochrane Central Register of Controlled Trials from January 1, 1998 to December 1, 2009. We calculated the accuracy, overstaging rate, understaging rate, Kappa statistic, sensitivity, and specificity for abdominal ultrasound (AUS), computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) with respect to the gold standard (pathology). We also compared the performance of CT by detector number and image type. A meta-analysis was performed.Results for pre-operative T staging MRI scans had better performance accuracy than CT and AUS; CT scanners using >= 4 detectors and multi-planar reformatted (MPR) images had higher staging performances than scanners with <4 detectors and axial images only. for pre-operative N staging PET had the lowest sensitivity, but the highest specificity among modalities; CT performance did not significantly differ by detector number or addition of MPR images. for pre-operative M staging performance did not significantly differ by modality, detector number, or MPR images.Conclusions the agreement between pre-operative TNM staging by imaging scans and post-operative staging by pathology is not perfect and may affect treatment decisions. Operator dependence and heterogeneity of data may account for the variations in staging performance. Physicians should consider this discrepancy when creating their treatment plans.