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Poster #50 STRUCTURAL BRAIN HETEROGENEITY IN SCHIZOPHRENIA: A GRAY MATTER TEXTURE ANALYSIS ON MR IMAGES
Abstracts of the 3rd Biennial Schizophrenia International Research Conference / Schizophrenia Research 136, Supplement 1 (2012) S1–S375
Poster #48 NEUROBIOLOGICAL CORRELATES OF SLOW WAVE SLEEP REDUCTION IN FIRST EPISODE SCHIZOPHRENIA Julie Poulin, Konsale M.R. Prasad, Jeffrey A. Nutche, Jean M. Miewald, Debra Montrose, Matcheri S. Keshavan University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Background: The aim of the present study was to examine the neurobiological correlates of slow wave sleep reduction in first episode schizophrenia. Our hypothesis was that slow wave sleep reduction would be associated with gray matter reduction in the prefrontal cortex. Methods: Twenty-nine patients with first episode schizophrenia who had never been previously treated with neuroleptics spent 3 nights in a sleep laboratory. Sleep stages of the third night of polysomnographic recording were visually scored and the total duration of slow wave sleep was used for the present analysis. High resolution structural MRI scans were also obtained using 1.5T GE whole body scanner. Whole-brain automated voxel-by-voxel analysis was performed using SPM2 (Ashburner, 2000). Correlations between slow wave sleep duration and gray matter intensity were performed using regression analysis. Specific regions of interest were examined using VOI intensity plotting. Gray matter intensity was compared between patients with longer slow wave sleep duration and those with shorter slow wave sleep duration using ANOVA. Results: A positive correlation between slow wave sleep duration and gray matter intensity was observed. More specifically, positive correlations were observed for the prefrontal cortex (FDRc p=0.057), superior temporal gyrus and insula (FRDc p=0.007) and the hippocampus (FDRc p=0.018). Moreover, patients with longer slow wave sleep duration had more gray matter intensity compared to patient with shorter slow wave sleep duration. Discussion: This study shows that slow wave sleep duration correlate with gray matter intensity in regions of interest for the etiopathogenesis of schizophrenia. On one hand, frontotemporal gray matter loss may have lead to reduced generation of slow wave sleep. On the other hand, it is also possible that slow wave sleep deficits may contribute to gray matter reductions by impacting neuroplasticity. Further studies will observe gray matter intensity after interventions that pharmacologically manipulate slow wave sleep.
Poster #49 CHANGES IN DLPFC-STRIATUM CONNECTIONS IN FIRST EPISODE SCHIZOPHRENIA: A CROSS-SECTIONAL AND LONGITUDINAL DTI STUDY Meina Quan 1,2,3 , Marek Kubicki 1,2,3 , Ryan Eckbo 1 , Zora Kikinis 1,2 , Robert W. McCarley 1,2,3 , James J. Levitt 1,2 , Martha E. Shenton 1,2,3 1 Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 2 Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, Boston VA Healthcare System, Brockton Division and Harvard Medical School, Brockton, MA, USA; 3 Boston CIDAR Boston, MA, USA Background: Many structural and functional studies have linked frontostriatal circuitry to cognitive dysfunction in schizophrenia, yet little is known about the change of this circuitry over time in the early stages of schizophrenia. This study examines structural changes in white matter tracts connecting the dorsolateral prefrontal cortex (DLPFC) and striatum in first-episode schizophrenia (FESZ), and their cognitive correlates. Methods: Diffusion tensor images were acquired twice for each subject on a 3T GE Echospeed system for 16 FESZ patients and 10 age/gender matched controls, with an average 1.2 years interval. FreeSurfer software was used to parcellate striatum and rostral middle frontal gyrus, representing DLPFC region of interest (ROI). Streamline tractography was used to extract fibers connecting regions. Repeated measures ANOVA was used to compare group difference in ROI volumes and diffusion indices in the tracts, including fractional anisotropy (FA), and axial and radial diffusivity; the two within subject factors were hemisphere and time. We then tested correlations of these indices with the Wisconsin Card Sorting Test (WCST). Results: Repeated measures ANOVA showed significant group difference and group by time interactions for FA and radial diffusivity in bilateral DLPFC-striatum tracts, but no differences in axial diffusivity or ROI volumes. Cross-sectionally, in time 1, repeated measures ANOVA showed
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significantly reduced FA, and increased radial diffusivity in FESZ. Longitudinally, pairwise t tests showed increased FA, and decreased radial diffusivity in time 2 compared with time 1 in FESZ, but no change over time in controls. In FESZ, Pearson correlations showed “learning to learn” in the WCST correlated significantly negatively with percent change of radial diffusivity in bilateral tracts. Discussion: These data suggest that DLPFC-striatum white matter tracts abnormalities are present in FESZ, and these abnormalities were reduced over time. Higher cognitive function was correlated with more improved diffusion indices from time 1 to time 2. Further investigation will be needed for the exact nature of such white matter structural changes in early stage of schizophrenia.
Poster #50 STRUCTURAL BRAIN HETEROGENEITY IN SCHIZOPHRENIA: A GRAY MATTER TEXTURE ANALYSIS ON MR IMAGES Eugenia Radulescu 1,2 , Balaji Ganeshan 2 , Nicholas Medford 1,2,3 , Sukhwinder S. Shergill 4 , Hugo D. Critchley 1,2,3 1 BSMS Psychiatry& Sackler Centre for Consciousness Science University of Sussex, Brighton, United Kingdom; 2 CISC, BSMS University of Sussex, Brighton, United Kingdom; 3 Sussex Partnership NHS Foundation Trust, Brighton, United Kingdom; 4 Institute of Psychiatry, King’s College London, London, United Kingdom Background: A preliminary textural analysis (TA) of structural MR brains scans has shown to reveal subtle abnormalities in the homogeneity of cerebral gray matter (GM) in schizophrenia (SCZ) (Ganeshan et al 2010). Using a modified TA algorithm with a voxel-based morphometry analysis (VBM), we tested an independent larger sample of patients with schizophrenia and matched control subjects. The anatomical basis of differences in brain texture were localised using the textural measures that distinguished schizophrenia scans from those of controls as regressors-of-interest in a VBM, thereby identifying regional GM volumes influenced by textural heterogeneity. Methods: Fifty-one T1-weighted structural MR images from schizophrenia subjects (SCZ=27; females=2) and healthy controls (HC=24; females=1) were obtained. Segmented GM images were analysed with a dedicated program written in MATLAB. Textural features of the MR images were extracted by performing whole brain filtration with a 2-D Laplacian of Gaussian (LoG) filter. Main extracted parameters were: mean-gray level intensity, entropy (a measure of intensity and inhomogeneity), uniformity (assessing the distribution of gray level). Additional parameters were the total number, mean and proportion of positive pixels. Texture parameters quantified at fine, medium and coarse spatial levels were compared statistically between SCZ and HC groups and entered into VBM analyses of grey matter images (performed within SPM8, optimized using DARTEL) after data reduction (principal component analysis- PCA). Results: When the positive and negative pixels were used in texture analysis, the fine entropy (E) and uniformity (U) significantly differed between SCZ and HC (for E: F(1,49)=6.64; p=0.013, respectively for U: F(1,49)=7.8, p=0.007). When only positive pixels were used in texture analysis several parameters showed statistically significant or at trend level differences between SCZ and HC. PCA on these parameters resulted in three factors whose scores were saved and used in VBM. The most striking results of VBM showed significant effects of texture parameters on hippocampal formation and fusiform gyrus (MNI: -24 -15 -18; Z score=3.56, p=0.031, respectively MNI: 24 -63 -13, Z score=3.75, p=0.017 after FWE correction) in schizophrenia subjects. Discussion: Our study shows GM textural heterogeneity in schizophrenia patients compared with healthy controls. The textural abnormalities were associated with GM volume in two regions widely implicated in pathogenesis of schizophrenia, hippocampal formation and fusiform gyrus. This possibly translates into a greater heterogeneity of gray-level distribution in GM images of schizophrenia subjects. The interpretation of the results relies on the capability of TA to better capturing the microstructural organization than the more traditional MR approaches. From this perspective, we speculate that our results especially in hippocampus may reflect subtle cellular and local connectivity disorganization.
Poster #48 NEUROBIOLOGICAL CORRELATES OF SLOW WAVE SLEEP REDUCTION IN FIRST EPISODE SCHIZOPHRENIA Julie Poulin, Konsale M.R. Prasad, Jeffrey A. Nutche, Jean M. Miewald, Debra Montrose, Matcheri S. Keshavan University of Pittsburgh School of Medicine, Pittsburgh, PA, USA Background: The aim of the present study was to examine the neurobiological correlates of slow wave sleep reduction in first episode schizophrenia. Our hypothesis was that slow wave sleep reduction would be associated with gray matter reduction in the prefrontal cortex. Methods: Twenty-nine patients with first episode schizophrenia who had never been previously treated with neuroleptics spent 3 nights in a sleep laboratory. Sleep stages of the third night of polysomnographic recording were visually scored and the total duration of slow wave sleep was used for the present analysis. High resolution structural MRI scans were also obtained using 1.5T GE whole body scanner. Whole-brain automated voxel-by-voxel analysis was performed using SPM2 (Ashburner, 2000). Correlations between slow wave sleep duration and gray matter intensity were performed using regression analysis. Specific regions of interest were examined using VOI intensity plotting. Gray matter intensity was compared between patients with longer slow wave sleep duration and those with shorter slow wave sleep duration using ANOVA. Results: A positive correlation between slow wave sleep duration and gray matter intensity was observed. More specifically, positive correlations were observed for the prefrontal cortex (FDRc p=0.057), superior temporal gyrus and insula (FRDc p=0.007) and the hippocampus (FDRc p=0.018). Moreover, patients with longer slow wave sleep duration had more gray matter intensity compared to patient with shorter slow wave sleep duration. Discussion: This study shows that slow wave sleep duration correlate with gray matter intensity in regions of interest for the etiopathogenesis of schizophrenia. On one hand, frontotemporal gray matter loss may have lead to reduced generation of slow wave sleep. On the other hand, it is also possible that slow wave sleep deficits may contribute to gray matter reductions by impacting neuroplasticity. Further studies will observe gray matter intensity after interventions that pharmacologically manipulate slow wave sleep.
Poster #49 CHANGES IN DLPFC-STRIATUM CONNECTIONS IN FIRST EPISODE SCHIZOPHRENIA: A CROSS-SECTIONAL AND LONGITUDINAL DTI STUDY Meina Quan 1,2,3 , Marek Kubicki 1,2,3 , Ryan Eckbo 1 , Zora Kikinis 1,2 , Robert W. McCarley 1,2,3 , James J. Levitt 1,2 , Martha E. Shenton 1,2,3 1 Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 2 Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, Boston VA Healthcare System, Brockton Division and Harvard Medical School, Brockton, MA, USA; 3 Boston CIDAR Boston, MA, USA Background: Many structural and functional studies have linked frontostriatal circuitry to cognitive dysfunction in schizophrenia, yet little is known about the change of this circuitry over time in the early stages of schizophrenia. This study examines structural changes in white matter tracts connecting the dorsolateral prefrontal cortex (DLPFC) and striatum in first-episode schizophrenia (FESZ), and their cognitive correlates. Methods: Diffusion tensor images were acquired twice for each subject on a 3T GE Echospeed system for 16 FESZ patients and 10 age/gender matched controls, with an average 1.2 years interval. FreeSurfer software was used to parcellate striatum and rostral middle frontal gyrus, representing DLPFC region of interest (ROI). Streamline tractography was used to extract fibers connecting regions. Repeated measures ANOVA was used to compare group difference in ROI volumes and diffusion indices in the tracts, including fractional anisotropy (FA), and axial and radial diffusivity; the two within subject factors were hemisphere and time. We then tested correlations of these indices with the Wisconsin Card Sorting Test (WCST). Results: Repeated measures ANOVA showed significant group difference and group by time interactions for FA and radial diffusivity in bilateral DLPFC-striatum tracts, but no differences in axial diffusivity or ROI volumes. Cross-sectionally, in time 1, repeated measures ANOVA showed
S109
significantly reduced FA, and increased radial diffusivity in FESZ. Longitudinally, pairwise t tests showed increased FA, and decreased radial diffusivity in time 2 compared with time 1 in FESZ, but no change over time in controls. In FESZ, Pearson correlations showed “learning to learn” in the WCST correlated significantly negatively with percent change of radial diffusivity in bilateral tracts. Discussion: These data suggest that DLPFC-striatum white matter tracts abnormalities are present in FESZ, and these abnormalities were reduced over time. Higher cognitive function was correlated with more improved diffusion indices from time 1 to time 2. Further investigation will be needed for the exact nature of such white matter structural changes in early stage of schizophrenia.
Poster #50 STRUCTURAL BRAIN HETEROGENEITY IN SCHIZOPHRENIA: A GRAY MATTER TEXTURE ANALYSIS ON MR IMAGES Eugenia Radulescu 1,2 , Balaji Ganeshan 2 , Nicholas Medford 1,2,3 , Sukhwinder S. Shergill 4 , Hugo D. Critchley 1,2,3 1 BSMS Psychiatry& Sackler Centre for Consciousness Science University of Sussex, Brighton, United Kingdom; 2 CISC, BSMS University of Sussex, Brighton, United Kingdom; 3 Sussex Partnership NHS Foundation Trust, Brighton, United Kingdom; 4 Institute of Psychiatry, King’s College London, London, United Kingdom Background: A preliminary textural analysis (TA) of structural MR brains scans has shown to reveal subtle abnormalities in the homogeneity of cerebral gray matter (GM) in schizophrenia (SCZ) (Ganeshan et al 2010). Using a modified TA algorithm with a voxel-based morphometry analysis (VBM), we tested an independent larger sample of patients with schizophrenia and matched control subjects. The anatomical basis of differences in brain texture were localised using the textural measures that distinguished schizophrenia scans from those of controls as regressors-of-interest in a VBM, thereby identifying regional GM volumes influenced by textural heterogeneity. Methods: Fifty-one T1-weighted structural MR images from schizophrenia subjects (SCZ=27; females=2) and healthy controls (HC=24; females=1) were obtained. Segmented GM images were analysed with a dedicated program written in MATLAB. Textural features of the MR images were extracted by performing whole brain filtration with a 2-D Laplacian of Gaussian (LoG) filter. Main extracted parameters were: mean-gray level intensity, entropy (a measure of intensity and inhomogeneity), uniformity (assessing the distribution of gray level). Additional parameters were the total number, mean and proportion of positive pixels. Texture parameters quantified at fine, medium and coarse spatial levels were compared statistically between SCZ and HC groups and entered into VBM analyses of grey matter images (performed within SPM8, optimized using DARTEL) after data reduction (principal component analysis- PCA). Results: When the positive and negative pixels were used in texture analysis, the fine entropy (E) and uniformity (U) significantly differed between SCZ and HC (for E: F(1,49)=6.64; p=0.013, respectively for U: F(1,49)=7.8, p=0.007). When only positive pixels were used in texture analysis several parameters showed statistically significant or at trend level differences between SCZ and HC. PCA on these parameters resulted in three factors whose scores were saved and used in VBM. The most striking results of VBM showed significant effects of texture parameters on hippocampal formation and fusiform gyrus (MNI: -24 -15 -18; Z score=3.56, p=0.031, respectively MNI: 24 -63 -13, Z score=3.75, p=0.017 after FWE correction) in schizophrenia subjects. Discussion: Our study shows GM textural heterogeneity in schizophrenia patients compared with healthy controls. The textural abnormalities were associated with GM volume in two regions widely implicated in pathogenesis of schizophrenia, hippocampal formation and fusiform gyrus. This possibly translates into a greater heterogeneity of gray-level distribution in GM images of schizophrenia subjects. The interpretation of the results relies on the capability of TA to better capturing the microstructural organization than the more traditional MR approaches. From this perspective, we speculate that our results especially in hippocampus may reflect subtle cellular and local connectivity disorganization.