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Objective: We aimed to evaluate the functional network properties in first-episode schizophrenia (SZ) patients at baseline and after 4-months treatment with second-generation antipsychotic drugs., Methods: Resting-state functional magnetic resonance imaging and graph theory approaches were utilized to evaluate the functional integration and segregation of brain networks in 36 first-episode patients (20 male/16 female) with SZ and 36 age and sex matched healthy controls (20 male/16 female)., Results: Compared with healthy controls, SZ at baseline showed lower clustering coefficient (C p ) and local network efficiency (E loc ), and this abnormal pattern was modulated with treatment of antipsychotic drugs at follow-up. Longitudinally, the increase of C p was associated with the improvement of negative symptom. We found that the strength of functional connectivity between brain regions were significantly increased in three connections after treatment, mainly involving the frontal, parietal and occipital lobes., Conclusion: The current study suggested that antipsychotic drugs could modulate the faulty local clustering of the functional connectome in SZ. Furthermore, C p , the parameter that reflects local clustering of topological organization, demonstrated the potential to be a connectome-based biomarker of treatment response to second-generation antipsychotics in patients with SZ., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Introduction: Treatment response at an early stage of schizophrenia is of considerable value with regard to future management of the disorder; however, there are currently no biomarkers that can inform physicians about the likelihood of response., Objects: We aim to develop and validate regional brain activity derived from functional magnetic resonance imaging (fMRI) as a potential signature to predict early treatment response in schizophrenia., Methods: Amplitude of low-frequency fluctuation (ALFF) was measured at the start of the first/single episode resulting in hospitalization. Inpatients were included in a principal dataset (n = 79) and a replication dataset (n = 44). Two groups of healthy controls (n = 87; n = 106) were also recruited for each dataset. The clinical response was assessed at discharge from the hospital. The predictive capacity of normalized ALFF in patients by healthy controls, ALFF ratio , was evaluated based on diagnostic tests and clinical correlates., Results: In the principal dataset, responders exhibited increased baseline ALFF in the left postcentral gyrus/inferior parietal lobule relative to non-responders. ALFF ratio of responders before treatment was significantly higher than that of non-responders (p < 0.001). The area under the receiver operating characteristic curve was 0.746 for baseline ALFF ratio to distinguish responders from non-responders, and the sensitivity, specificity, and accuracy were 72.7%, 68.6%, and 70.9%, respectively. Similar results were found in the independent replication dataset., Conclusions: Baseline regional activity of the brain seems to be predictive of early response to treatment for schizophrenia. This study shows that psycho-neuroimaging holds promise for influencing the clinical treatment and management of schizophrenia., (© 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.)

Despite evidence of structural brain abnormalities in schizophrenia, the current study aimed to explore the effects of antipsychotic treatment on gray matter (GM) volume using structural magnetic resonance imaging (MRI) and investigate the relationship between brain structure and treatment response. The GM volumes of 33 patients with first-episode schizophrenia were calculated with voxel-based morphometry (VBM), with 33 matched healthy controls. Longitudinal volume changes within subjects after 4-month antipsychotic treatment were also evaluated. Correlation between volumetric changes and clinical symptoms derived from the Positive and Negative Syndrome Scale (PANSS) were further investigated. Compared with healthy controls, decreased GM volumes in the frontal gyrus were observed in schizophrenia patients. After 4-month treatment, patients showed significantly decreased GM volume primarily in the bilateral frontal, temporal and left parietal brain regions. In addition, the GM volume changes of the left postcentral gyrus was positively correlated with negative symptoms improvement, and the correlation analysis revealed the total PANSS scores changes were associated with GM volume changes in the right inferior frontal gyrus and the right superior temporal gyrus. Besides, non-responders had reduced GM volume in the bilateral middle frontal gyrus and the right superior frontal gyrus compared with responders and healthy controls. Our results suggest that the abnormality in the right frontal gyrus exists in the early stage of schizophrenia. Moreover, the relationship between antipsychotics and structural changes was identified. The GM volume might have the potential to reflect the symptom improvement in schizophrenia patients. And MRI may assist in predicting the antipsychotic treatment response in first-episode schizophrenia patients. [ABSTRACT FROM AUTHOR]

Objective: The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients.Methods: We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS).Results: We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS.Conclusions: Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia. [ABSTRACT FROM AUTHOR]

Background and Purpose: Conventional magnetic resonance imaging (MRI) is sometimes difficult to distinguish primary central nervous system lymphoma (PCNSL) from other malignant brain tumors effectively. The study aimed to evaluate the diagnostic performance of arterial spin labeling (ASL) and dynamic contrast-enhanced (DCE)-derived permeability parameters to differentiate PCNSL from high-grade glioma (HGG) and brain metastasis.Materials and Methods: Eight patients with PCNSL, twenty one patients with HGG and six brain metastasis underwent preoperative 3.0-T MR imaging including conventional, ASL and DCE. Quantitative parameters including relative cerebral blood flow (rCBF), extravascular extracellular volume fraction (Ve) and the volume transfer constant (Ktrans) among PCNSL, HGG and metastasis were compared with a one-way analysis of variance. In addition, the area under the receiver-operating characteristic (ROC) curve (AUC) was constructed to evaluate the differentiation diagnostic performance of each parameter and the combination.Results: The PCNSL demonstrated significantly lower rCBF, higher Ktrans and Ve compared with HGG and metastasis. For the ROC analyses, both Ktrans and rCBF had good diagnostic performance for discriminating PCNSL from HGG and metastasis, with the AUC of 0.880 and 0.889. With the combination of rCBF and Ktrans, the diagnostic ability for PCNSL was improved with AUC of 0.986.Conclusion: rCBF and Ktrans are useful parameters for differentiating PCNSL from HGG and brain metastasis. The combination of rCBF and Ktrans further helps to improve the diagnostic performance of PCNSL. [ABSTRACT FROM AUTHOR]