Background In schizophrenia, the structural changes in the cerebellum are associated with patients’ cognition and motor deficits. However, the findings are inconsistent owing to the heterogeneity in sample size, magnetic resonance imaging (MRI) scanners, and other factors among them. In this study, we conducted a meta-analysis to characterize the anatomical changes in cerebellar subfields in patients with schizophrenia. Methods Systematic research was conducted to identify studies that compare the gray matter volume (GMV) differences in the cerebellum between patients with schizophrenia and healthy controls with a voxel-based morphometry (VBM) method. A coordinate-based meta-analysis was adopted based on seed-based d mapping (SDM) software. An exploratory meta-regression analysis was conducted to associate clinical and demographic features with cerebellar changes. Results Of note, 25 studies comprising 996 patients with schizophrenia and 1,109 healthy controls were included in the present meta-analysis. In patients with schizophrenia, decreased GMVs were demonstrated in the left Crus II, right lobule VI, and right lobule VIII, while no increased GMV was identified. In the meta-regression analysis, the mean age and illness duration were negatively associated with the GMV in the left Crus II in patients with schizophrenia. Conclusion The most significant structural changes in the cerebellum are mainly located in the posterior cerebellar hemisphere in patients with schizophrenia. The decreased GMVs of these regions might partly explain the cognitive deficits and motor symptoms in patients with schizophrenia.

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Cerebellar gray matter volume changes in patients with schizophrenia: A voxel-based meta-analysis

“First-episode psychosis: Structural covariance deficits in salience network correlate with symptoms severity”

BACKGROUND
The importance of identifying the structural and functional abnormalities in the brain in early prediction and diagnosis of schizophrenia has grabbed the attention of both the neuroimaging scientist and clinician.


OBJECTIVE
The purpose of this study is to structure a review paper that find out the condition and recognize specific biomarkers of the schizophrenic brain.


METHOD
Neuroimaging can be used to characterize brain structure, function, and chemistry by different non-invasive techniques such as computed tomography, magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography. The abnormalities in the brain can be used to discriminate the psychic disorder like schizophrenia from others. To find disease-related brain alterations in neuroimaging, structural neuroimaging studies provide the most consistent evidence in most of the studies. The review discusses the major issues and findings in structural neuroimaging studies of schizophrenia. In particular, the data is collected from different papers where they concentrated on the brain affected regions of different subjects and made a conclusion out of it.


RESULT
In this work, a detailed survey has been made for finding the structural abnormalities in the brain from different neuroimaging techniques. Several image processing methods are used to acquire the brain images. Different Machine learning techniques, Optimization methods and Pattern recognition methods are used to predict the disease with specific biomarkers, and their results are emphasized. Thus, in this work, it is also highlighted the deep learning which shows a promising role in obtaining neuroimaging data to characterize disease-related alterations in brain structure.

Survey on Structural Neuro imaging for the Identification of brain Abnormalities in Schizophrenia.

Abstract Understanding the neuroanatomy of schizophrenia remains elusive due to heterogenous findings across neuroimaging studies. Here, we investigated whether patterns of brain atrophy associated with schizophrenia would localize to a common brain network. Using the human connectome as a wiring diagram, we identified a connectivity pattern, a schizophrenia network, uniting heterogenous results from 90 published studies of atrophy in schizophrenia (total n&gt;8,000). This network was specific to schizophrenia, differentiating it from atrophy in high-risk individuals (n=3038), normal aging (n=4,195), neurodegenerative disorders (n=3,707), and other psychiatric conditions (n=3,432). The network was also stable with disease progression and across different clusters of schizophrenia symptoms. Patterns of brain atrophy in schizophrenia were negatively correlated with lesions linked to psychosis-related thought processes in an independent cohort (n=181). Our results propose a unique, stable, and unified schizophrenia network, addressing a significant portion of the heterogeneity observed in prior atrophy studies. 

Heterogenous Patterns of Brain Atrophy in Schizophrenia Localize to A Common Brain Network

Objective: Schizophrenia is known to be quite a heterogeneous disorder in terms of etiological factors, clinical features and, treatment response. Changes in gray matter areas with structural imaging studies seem to be a reflection of this diversity. The relationship of duration of illness, active psychosis periods,&#x0D; and antipsychotic treatment with structural changes in the brain has not been clarified yet. The aim of our study is to investigate the effects of the disease and disease-related processes (duration of illness, antipsychotic treatment, number of the psychotic episodes) on the brain structures.&#x0D; Material and Methods: Thirty three schizophrenic patients and 35 age, gender and education matched healthy volunteers participated in our study. Life-time antipsychotic exposure determined for the patients and inverted dose/year unit over equivalent chlorpromazine doses. Magnetic resonance images were acquired with a 3 Tesla-powered imaging unit. By using Statistical Parametric Mapping 8, images were compared with voxel-based morphometry (VBM) analysis. Independent samples t-test for statistical evaluation based on the data characteristics were used. By using the general linear model (GLM) age, gender, and total brain volume were included as confounding factors in the analyze matrix in VBM. In GLM, t-test was used to compare two groups and to investigate disease process-related GM changes, multiple regression analysis were applied. In VBM, p values of less than 0.001 and areas with a minimum expected number of voxels per cluster of 50 are required.&#x0D; Results: Compared to controls, patients showed decrements in gray matter density in the right middle and inferior temporal gyrus, bilateral middle frontal gyrus, left cingulate gyrus, left precentral gyrus, left supramarginal gyrus. Nevertheless, patients showed increased GM density in the right uncus, left caudate, and left posterior cingulate cortex as compared to controls. In the patient group, duration of illness was negatively associated with GM density in the left precentral gyrus and left postcentral gyrus. The lifetime exposure to antipsychotics correlated negatively and positively with gray matter density in, respectively; left inferior frontal gyrus and right precuneus. The number of psychotic episodes was positively associated with GM density in the left medial frontal gyrus, right precentral gyrus and left paracentral lobule whereas negatively in the uvula (cerebellum).&#x0D; Conclusion: It can be said that GM deficits in schizophrenic patients are prominent in frontal and temporal areas. Besides illness duration, antipsychotic treatment, and number of psychotic episodes seem to be associated with changes in brain GM. Further studies are needed to clarify the increase in the limbic lobe GM density. 

Şi̇zofreni̇ tanili hastalarda hastalik süresi̇, psi̇koti̇k atak sayisi, yaşam boyu anti̇psi̇koti̇k kullanimiyla i̇li̇şki̇li̇ bölgesel gri̇ madde deği̇şi̇kli̇kleri̇ni̇n voksel tabanli morfometri̇k anali̇zi̇

Background: Although some Magnetic Resonance Imaging (MRI) studies have investigated the relationship between clinical severity and neuroanatomical alterations in patients with schizophrenia (SCZ), the biological signature associated with illness severity in schizophrenia is still uncertain. Therefore, this study aims to investigate structural brain abnormalities in SCZ, with particular regards to the identification of potential deficits associated with the severity of illness.Methods: In total, 1.5T MRI data were acquired for 61 subjects with SCZ and 59 matched healthy controls (HC). The patient group was divided in two sub-groups based on clinical severity, one composed of 34 mild-to-moderately ill patients, and the other of 27 severely ill patients, and compared with matched HC.Results: The whole group of patients with SCZ had significantly reduced grey matter (GM) volumes in the left inferior and middle temporal gyrus compared to HC (p < 0.05, pFWE corrected). Furthermore, compared to HC, pati...

Brain anatomy of symptom stratification in schizophrenia: a voxel-based morphometry study.

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Brain anatomy of symptom stratification in schizophrenia: a voxel-based morphometry study.