TIFFANY MOUKBEL CHAIM AVANCINI
Projetos de Pesquisa
Unidades Organizacionais
LIM/21 - Laboratório de Neuroimagem em Psiquiatria, Hospital das Clínicas, Faculdade de Medicina
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conferenceObject Neuroanatomical Pattern Classification in Unmedicated First-Episode Psychosis: Influence of Different Imaging Feature Selection(2012) SERPA, Mauricio H.; ZANETTI, Marcus V.; VAROL, Erdem; CHAIM, Tiffany M.; GAONKAR, Bilwaj; DOSHI, Jimit; BILT, Martinus T. van de; SALLET, Paulo C.; GATTAZ, Wagner F.; BUSATTO, Geraldo F.; DAVATZIKOS, ChristosBackground: The application of pattern classification approaches is thought to hold promise as an auxiliary tool to aid clinical diagnoses in psychiatric practice. However, few neuroimaging studies to date have investigated the usefulness of these methods in the evaluation of schizophrenia and related psychoses. Moreover, most of patients enrolled in such studies were already receiving antipsychotic medication, an important confounding factor for brain measures. Methods: Eleven treatment-naïve first-episode psychosis (FEP) individuals and 19 controls underwent T1-MPRAGE and 64-direction diffusion tensor imaging (DTI) acquisitions using a 1.5T MRI scanner. Volumetric maps of gray matter, white matter and ventricular compartments were generated through a robust routine of deformation-based morphometry. A new approach adequate for spatial normalization of tensor fields was used to generate fractional anisotropy (FA) and mean diffusivity maps. A multivariate classifier based on support vector machine was employed to identify the best set of morphological and DTI features that discriminate FEP individuals from controls. Diagnostic measures were obtained through ROC curve analyses. Results: The discrimination performance of the classifier varied according to the combination of different features, and the greater area under the curve value (0.68) was obtained when the FA map was employed in isolation. The resulting spatial map revealed a predominant pattern of increased FA in the right parietal region of FEP patients relative to controls, which may reflect differences in functional activity. Conclusions: This preliminary report suggests that FA indices afford the best discrimination between treatment-naïve FEP patients and controls relative to other morphometric and DTI features.conferenceObject Longitudinal Study of State-Dependent Microstructural Brain Changes in Bipolar Disorder: Preliminary Report(2012) ZANETTI, Marcus V.; MACHADO-VIEIRA, Rodrigo; DOSHI, Jimit; CHAIM, Tiffany M.; SERPA, Mauricio; SOUSA, Rafael T. de; GATTAZ, Wagner F.; DAVATZIKOS, Christos; BUSATTO, Geraldo F.Background: Recent findings from cross-sectional studies suggest that mood disorders might be associated with state-dependent microstructural brain changes. Nevertheless, no study to date has evaluated this hypothesis using a longitudinal within-subject design. Methods: Seven treatment-naïve patients with recent-onset bipolar disorder (BD) in the acute phase of their illness (i.e., acute depressive, mixed or manic episode) underwent 64- direction diffusion tensor imaging (DTI) at two time points: at baseline (T0) and after clinical response (T1). Seven age and gender matched controls were also studied at two different time points. The time interval between scans ranged from 6 to 8 weeks. Whole-brain fractional anisotropy (FA) and mean diffusivity (MD) indices were obtained through a new routine adequate for spatial normalization of tensor fields. Preliminary voxelwise comparisons of FA and MD maps were conducted at an exploratory p≤0.001 threshold (uncorrected). Only resulting clusters with a minimum of 10 voxels and located in the white matter were considered significant. Results: At baseline, BD patients showed a focus of MD reduction affecting the right superior longitudinal fasciculus (SLF) relative to controls. Both longitudinal within-group and time versus diagnosis analyses revealed the following significant findings in the BD group over time: FA decrease in the right inferior longitudinal fasciculus (ILF); and MD increase in the left SLF. Conclusions: These preliminary results suggest that dynamic MD changes affecting the SLF may underlie the acute manifestations of BD as well as the transition to mood stabilization. Lithium treatment might be associated to FA decrease in the right ILF.conferenceObject High-Dimensional Pattern Classification of Brain Morphometric and DTI Data of Adult ADHD(2012) CHAIM, Tiffany M.; SILVA, Maria Aparecida; VAROL, Erdem; DOSHI, Jimit; ZANETTI, Marcus V.; GAONKAR, Bilwaj; SERPA, Mauricio; VIEIRA, Rodrigo M.; CAETANO, Sheila C.; LOUZA, Mario R.; DAVATZIKOS, Christos; BUSATTO, Geraldo F.Background: Despite its high prevalence, adult Attention-Deficit/Hyperactivity Disorder (ADHD) has been sparsely investigated with neuroimaging methods. The application of high-dimensional pattern classification methods appears as a promising auxiliary approach to aid in the clinical diagnosis of psychiatric disorders, but such strategy has not yet been applied to the investigation of adult ADHD. Methods: Twenty-two adult, never-treated ADHD patients and 19 age- and gender-matched healthy controls underwent T1-MPRAGE and 64-direction diffusion tensor imaging (DTI) acquisitions using 1.5T MRI scanner. Volumetric maps of gray matter, white matter and ventricular compartments were generated through a robust routine of deformation-based morphometry, whereas a new DTI analysis approach for spatial normalization of tensor fields was used to generate fractional anisotropy (FA) and mean diffusivity (MD) maps. A multivariate classification method based on support vector machine was employed to identify the best set of morphological features that discriminate ADHD patients from controls. Diagnostic measures were obtained through ROC analyses. Results: The best discrimination performance of the classifier was obtained when the FA map was employed in isolation (area under the curve, AUC=0.61). The regions primarily used in the FA classifier were the orbitofrontal cortex and cerebellum. These brain areas were also those with larger differences when voxelwise between-group comparisons of FA data were performed (p<0.001, uncorrected for multiple comparisons). Conclusions: These preliminary results suggest that FA measures are the best indices of brain dysfunction in pattern classification investigations of adult ADHD using MRI. This reinforces the notion of brain connectivity abnormalities underlying the symptoms of ADHD.