Dataset Information

Heterogeneity of structural brain changes in subtypes of schizophrenia revealed using magnetic resonance imaging pattern analysis.

ABSTRACT:

Background

Schizophrenia is a multifaceted mental disorder characterized by cognitive, perceptual, and affective symptom dimensions. This heterogeneity at the phenomenological level may be subserved by complex and heterogeneous patterns of structural abnormalities. Thus, delineating such patterns may improve the insight into the variability of disease and facilitate future magnetic resonance imaging-based diagnosis.

Methods

We aimed to identify structurally complex signatures that directly differentiate patients with predominantly negative (pNEG), positive (pPOS), and disorganized (pDIS) symptoms using Optimally-Discriminative Voxel-Based Analysis (ODVBA). ODVBA is a new analytical framework for group analysis, which showed to have superior sensitivity and specificity over conventional voxel-based morphometric approaches, thus facilitating the identification of subtle neuroanatomical signatures delineating different subgroups.

Results

pPOS were characterized by pronounced gray matter (GM) volume reductions in the ventromedial prefrontal cortex (vmPFC), which herein is defined to include the orbitofrontal cortex, and in occipitotemporal GM and parts of the lingual gyrus. pNEG was found to have vmPFC reduction but to a lesser degree than pPOS and with a relative sparing of the more medial vmPFC regions, compared to pDIS; it also had significantly less cerebellar GM. pDIS showed relatively highest GM volume preservation among three subtypes.

Conclusions

Although a common prefronto-perisylvian GM reduction pattern was present at the whole-group level, marked morphometric differences emerged between the three subgroups, including reduced cerebellar GM in pNEG and reduced vmPFC and occipitotemporal GM in pPOS. Besides deepening our insight into the neurobiological underpinnings of clinical heterogeneity, these results also identify important imaging biomarkers that may aid patient stratification.

SUBMITTER: Zhang T

PROVIDER: S-EPMC4266302 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Publications

Heterogeneity of structural brain changes in subtypes of schizophrenia revealed using magnetic resonance imaging pattern analysis.

Zhang Tianhao T Koutsouleris Nikolaos N Meisenzahl Eva E Davatzikos Christos C

Schizophrenia bulletin 20140926 1

<h4>Background</h4>Schizophrenia is a multifaceted mental disorder characterized by cognitive, perceptual, and affective symptom dimensions. This heterogeneity at the phenomenological level may be subserved by complex and heterogeneous patterns of structural abnormalities. Thus, delineating such patterns may improve the insight into the variability of disease and facilitate future magnetic resonance imaging-based diagnosis.<h4>Methods</h4>We aimed to identify structurally complex signatures that ...[more]

PMID: 25261565

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Project description:Background:Determining the early changes of brain structure that occur from vegetative state/unresponsive wakefulness syndrome (VS/UWS) to a minimally conscious state (MCS) is important for developing our understanding of the processes underlying disorders of consciousness (DOC), particularly during spontaneous recovery from severe brain damage. Objective:This study used a multi-modal neuroimaging approach to investigate early structural changes during spontaneous recovery from VS/UWS to MCS. Methods:The Coma Recovery Scale-Revised (CRS-R) score, 24-h electroencephalography (EEG), and ultra-high field 7-T magnetic resonance imaging were used to investigate a male patient with severe brain injury when he was in VS/UWS compared to MCS. Using white matter connectometry analysis, fibers in MCS were compared with the same fibers in VS/UWS. Whole-brain analysis was used to compare all fibers showing a 10% increase in density with each other as a population. Results:Based on connectometry analysis, the number of fibers with increased density, and the magnitude of increase in MCS compared to VS/UWS, was greatest in the area of the temporoparietal junction (TPJ), and was mostly located in the right hemisphere. These results are in accordance with the active areas observed on 24-h EEG recordings. Moreover, analysis of different fibers across the brain, showing at least a 10% increase in density, revealed that altered white matter connections with higher discriminative weights were located within or across visual-related areas, including the cuneus_R, calcarine_R, occipital_sup_R, and occipital_mid_R. Furthermore, the temporal_mid_R, which is related to the auditory cortex, showed the highest increase in connectivity to other areas. This was consistent with improvements in the visual and auditory components of the CRS-R, which were greater than other improvements. Conclusion:These results provide evidence to support the important roles for the TPJ and the visual and auditory sensory systems in the early recovery of a patient with severe brain injury. Our findings may facilitate a much deeper understanding of the mechanisms underlying conscious-related processes and enlighten treatment strategies for patients with DOC.

Project description:Although the functional connectivity of patients with disorders of consciousness (DOC) has been widely examined, less is known about brain white matter connectivity. The aim of this study was to explore structural network alterations for the diagnosis and prognosis of patients with chronic DOC. Eleven DOC patients and 11 sex- and age-matched controls were included in the study. Participants underwent diffusion magnetic resonance imaging (MRI) and T1-weighted structural MRI at 7 tesla (7 T). Graph-theoretical analysis and network-based statistics were used to analyze the group differences. Two patients were scanned twice for a longitudinal study to examine the relationship between connectome metrics and the patients' prognoses. Compared with healthy controls, DOC patients showed significantly elevated transitivity (p < .001), local efficiency (p = .009), and clustering coefficient (p = .039). When comparing the connectome metrics within the three groups (healthy controls, minimally conscious state (MCS), and vegetative state/unresponsive wakefulness syndrome (VS/UWS)), significant group differences were observed in transitivity (p < .001) and local efficiency (p = .031). Significantly increased transitivity was observed in vegetative state/unresponsive wakefulness syndrome compared with minimally conscious state (p = .0217, Bonferroni corrected). Transitivity showed significant negative correlations with the Coma Recovery Scale-Revised score (r = -0.6902, p = .023), consistent with the longitudinal study results. A subnetwork with significantly decreased structural connections was identified using network-based statistical analysis comparing DOC patients with healthy controls, which was mainly located in the frontal cortex, limbic system, and occipital and parietal lobes. This preliminary study suggests that graph theoretical approaches for assessing white matter connectivity may enable various states of DOC to be distinguished. Of the metrics analyzed, transitivity had a critical role in distinguishing the diagnostic groups. Larger cohorts will be necessary to confirm the predictive value of 7 T MRI in the prognosis of DOC patients.

Dataset Information

Heterogeneity of structural brain changes in subtypes of schizophrenia revealed using magnetic resonance imaging pattern analysis.

Background

Methods

Results

Conclusions

Publications

Heterogeneity of structural brain changes in subtypes of schizophrenia revealed using magnetic resonance imaging pattern analysis.

Similar Datasets

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