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Background and Purpose: The detection and characterization of functional activities in the gray matter of schizophrenia (SZ) have been widely explored. However, the relationship between resting‐state functional signals in the white matter of first‐episode SZ and short‐term treatment response remains unclear. Methods: Thirty‐six patients with first‐episode SZ and 44 matched healthy controls were recruited in this study. Patients were classified as nonresponders and responders based on response to antipsychotic medication during a single hospitalization. The fractional amplitude of low‐frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) of white matter were calculated. The relationships between functional changes and clinical features were analyzed. In addition, voxel‐based morphometry was performed to analyze the white matter volume. Results: One‐way analysis of variance showed significant differences of fALFF and ReHo in the left posterior thalamic radiation and left cingulum (hippocampus) in the patient group, and the areas were regarded as seeds. The FC was calculated between seeds and other white matter networks. Compared with responders, nonresponders showed significantly increased FC between the left cingulum (hippocampus) and left posterior thalamic radiation, splenium of corpus callosum, and left tapetum, and were associated with the changes of clinical assessment. However, there was no difference in white matter volume between groups. Conclusion: Our work provides a novel insight that psycho‐neuroimaging‐based white matter function holds promise for influencing the clinical diagnosis and treatment of SZ. [ABSTRACT FROM AUTHOR]

Background: Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear. Aims: To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age. Method: The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed. Results: The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = −0.326, P = 0.014). Conclusions: The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia. [ABSTRACT FROM AUTHOR]

Attempts to determine why some patients respond to electroconvulsive therapy (ECT) are valuable in schizophrenia. Schizophrenia is associated with aberrant dynamic functional architecture, which might impact the efficacy of ECT. We aimed to explore the relationship between pre‐treatment temporal variability and ECT acute efficacy. Forty‐eight patients with schizophrenia and 30 healthy controls underwent functional magnetic resonance imaging to examine whether patterns of temporary variability of functional architecture differ between high responders (HR) and low responders (LR) at baseline. Compared with LR, HR exhibited significantly abnormal temporal variability in right inferior front gyrus (IFGtriang.R), left temporal pole (TPOsup.L) and right middle temporal gyrus (MTG.R). In the pooled patient group, ∆PANSS was correlated with the temporal variability of these regions. Patients with schizophrenia with a distinct dynamic functional architecture appear to reveal differential response to ECT. Our findings provide not only an understanding of the neural functional architecture patterns that are found in schizophrenia but also the possibility of using these measures as moderators for ECT selection. [ABSTRACT FROM AUTHOR]

Background and Purpose: It is sometimes difficult to effectively distinguish non-neoplastic from neoplastic intracranial enhancement lesions using conventional magnetic resonance imaging (MRI). This study aimed to evaluate the diagnostic performance of three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL) to differentiate non-neoplastic from neoplastic enhancement lesions intracranially. Materials and Methods: This prospective study included thirty-five patients with high-grade gliomas (HGG), twelve patients with brain metastasis, and fifteen non-neoplastic patients who underwent conventional, contrast enhancement and 3D-pCASL imaging at 3.0-T MR; all lesions were significantly enhanced. Quantitative parameters including cerebral blood flow (CBF) and relative cerebral blood flow (rCBF) were compared between neoplastic and non-neoplastic using Student's t -test. In addition, the area under the receiver operating characteristic (ROC) curve (AUC) was measured to assess the differentiation diagnostic performance of each parameter. Results: The non-neoplastic group demonstrated significantly lower rCBF values of lesions and perilesional edema compared with the neoplastic group. For the ROC analysis, both relative cerebral blood flow of lesion (rCBF-L) and relative cerebral blood flow of perilesional edema (rCBF-PE) had good diagnostic performance for discriminating non-neoplastic from neoplastic lesions, with an AUC of 0.994 and 0.846, respectively. Conclusion: 3D-pCASL may contribute to differentiation of non-neoplastic from neoplastic lesions. [ABSTRACT FROM AUTHOR]

Multimodal neuroimaging features provide opportunities for accurate classification and personalized treatment options in the psychiatric domain. This study aimed to investigate whether brain features predict responses to the overall treatment of schizophrenia at the end of the first or a single hospitalization. Structural and functional magnetic resonance imaging (MRI) data from two independent samples (N = 85 and 63, separately) of schizophrenia patients at baseline were included. After treatment, patients were classified as responders and non‐responders. Radiomics features of gray matter morphology and functional connectivity were extracted using Least Absolute Shrinkage and Selection Operator. Support vector machine was used to explore the predictive performance. Prediction models were based on structural features (cortical thickness, surface area, gray matter regional volume, mean curvature, metric distortion, and sulcal depth), functional features (functional connectivity), and combined features. There were 12 features after dimensionality reduction. The structural features involved the right precuneus, cuneus, and inferior parietal lobule. The functional features predominately included inter‐hemispheric connectivity. We observed a prediction accuracy of 80.38% (sensitivity: 87.28%; specificity 82.47%) for the model using functional features, and 69.68% (sensitivity: 83.96%; specificity: 72.41%) for the one using structural features. Our model combining both structural and functional features achieved a higher accuracy of 85.03%, with 92.04% responder and 80.23% non‐responders to the overall treatment to be correctly predicted. These results highlight the power of structural and functional MRI‐derived radiomics features to predict early response to treatment in schizophrenia. Prediction models of the very early treatment response in schizophrenia could augment effective therapeutic strategies. [ABSTRACT FROM AUTHOR]

Objective: Neuroimaging-based brain signatures may be informative in identifying patients with psychosis who will respond to antipsychotics. However, signatures that inform the electroconvulsive therapy (ECT) health care professional about the response likelihood remain unclear in psychosis with radiomics strategy. This study investigated whether brain structure-based signature in the prediction of ECT response in a sample of schizophrenia patients using radiomics approach. Methods: This high-resolution structural magnetic resonance imaging study included 57 patients at baseline. After ECT combined with antipsychotics, 28 and 29 patients were classified as responders and non-responders. Features of gray matter were extracted and compared. The logistic regression model/support vector machine (LRM/SVM) analysis was used to explore the predictive performance. Results: The regularized multivariate LRM accurately discriminated responders from non-responders, with an accuracy of 90.91%. The structural features were further confirmed in the validating data set, resulting in an accuracy of 87.59%. The accuracy of the SVM in the training set was 90.91%, and the accuracy in the validation set was 91.78%. Conclusion: Our results support the possible use of structural brain feature-based radiomics as a potential tool for predicting ECT response in patients with schizophrenia undergoing antipsychotics, paving the way for utilization of markers in psychosis. [ABSTRACT FROM AUTHOR]

Emerging evidence indicates that a disruption in brain network organization may play an important role in the pathophysiology of schizophrenia. The neuroimaging fingerprint reflecting the pathophysiology of first-episode schizophrenia remains to be identified. Here, we aimed at characterizing the connectome organization of first-episode medication-naïve patients with schizophrenia. A cross-sectional structural and functional neuroimaging study using two independent samples (principal dataset including 42 medication-naïve, previously untreated patients and 48 healthy controls; replication dataset including 39 first-episode patients [10 untreated patients] and 66 healthy controls) was performed. Brain network architecture was assessed by means of white matter fiber integrity measures derived from diffusion-weighted imaging (DWI) and by means of structural-functional (SC-FC) coupling measured by combining DWI and resting-state functional magnetic resonance imaging. Connectome rich club organization was found to be significantly disrupted in medication-naïve patients as compared with healthy controls (P =.012, uncorrected), with rich club connection strength (P =.032, uncorrected) and SC-FC coupling (P <.001, corrected for false discovery rate) decreased in patients. Similar results were found in the replication dataset. Our findings suggest that a disruption of rich club organization and functional dynamics may reflect an early feature of schizophrenia pathophysiology. These findings add to our understanding of the neuropathological mechanisms of schizophrenia and provide new insights into the early stages of the disorder. [ABSTRACT FROM AUTHOR]

Background: In glioblastoma (GBM), promoter methylation of the DNA repair gene O-methylguanine-DNA methyltransferase (MGMT) is associated with beneficial chemotherapy.Purpose/hypothesis: To analyze radiomics features for utilizing the full potential of medical imaging as biomarkers of MGMT promoter methylation.Study Type: Retrospective.Population/subjects: In all, 98 GBM patients with known MGMT (48 methylated and 50 unmethylated tumors).Field Strength/sequence: 3.0T magnetic resonance (MR) images, containing T1 -weighted image (T1 WI), T2 -weighted image (T2 WI), and enhanced T1 WI.Assessment: A region of interest (ROI) of the tumor was delineated. A total of 1665 radiomics features were extracted and quantized, and were reduced using least absolute shrinkage and selection operator (LASSO) regularization.Statistical Testing: After the support vector machine construction, accuracy, sensitivity, and specificity were computed for different sequences. An independent validation cohort containing 20 GBM patients was utilized to further evaluate the radiomics model performance.Results: Radiomics features of T1 WI reached an accuracy of 67.54%. Enhanced T1 WI features reached an accuracy of 82.01%, while T2 WI reached an accuracy of 69.25%. The best classification system for predicting MGMT promoter methylation status originated from the combination of 36 T1 WI, T2 WI, and enhanced T1 WI images features, with an accuracy of 86.59%. Further validation on the independent cohort of 20 patients produced similar results, with an accuracy of 80%.Data Conclusion: Our results provide further evidence that radiomics MR features could predict MGMT methylation status in preoperative GBM. Multiple imaging modalities together can yield putative noninvasive biomarkers for the identification of MGMT.Level Of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1380-1387. [ABSTRACT FROM AUTHOR]

Background: Hippocampal dysconnectivity has been detected in schizophrenia patients with auditory verbal hallucinations (AVHs). Neuroanatomical evidence has indicated distinct sub-regions in the hippocampus, but which sub-regions within the hippocampus may emerge dysfunction in the brain network, and the relationship between connection strength and the severity of this debilitating disorder have yet to be revealed. Masked independent component analysis (mICA), i.e., ICA restricted to a defined region of interest, can provide insight into observing local functional connectivity in a particular brain region. We aim to map out the sub-regions in the hippocampus with dysconnectivity linked to AVHs in schizophrenia. Methods: In this functional magnetic resonance imaging study of schizophrenia patients with (n = 57) and without (n = 83) AVHs, and 71 healthy controls, we first examined hippocampal connectivity using mICA, and then the correlation between connection metric and clinical severity was generated. Results: As compared with patients without AVHs, mICA showed a group of hyper-connections for the left middle part, as well as another group of hypo-connections for the bilateral antero-lateral and right antero-medial parts in patients with AVHs. Connectivity was linked to the clinical symptoms scores in the sample of patients with AVHs. Conclusion: These findings demonstrate that the left middle part is more densely connected, but the bilateral antero-lateral and right antero-medial parts are more sparsely connected in schizophrenia patients with AVHs. The findings in the present study show proof of precious location in the hippocampus mediating the neural mechanism behind AVHs in schizophrenia. [ABSTRACT FROM AUTHOR]

As a special movement disorder, hepatic myelopathy (HM) is characterized by spastic paraperesis and may be secondary to transjugular intrahepatic portosystemic shunt (TIPS). The prediction and diagnosis of HM is difficult due to largely unknown neuropathological underpinnings and a lack of specific biomarkers. We aimed to delve into the alterations in motor system of HM patients' brain and their potential clinical implication. Twenty-three patients with HM and 23 without HM after TIPS and 24 demographically matched healthy controls were enrolled. High-spatial-resolution structural imaging and functional data at rest were acquired. Motor areas were included as seed regions for functional connectivity analysis. Then, we performed brain volume analysis. We found decreased right supplementary motor area (SMA)-seeded functional connectivity with bilateral insula, thalamus and midbrain, left cerebellum and middle temporal gyrus, and right middle cingulate gyrus in HM compared to non-HM patients (p < 0.001). The right insula revealed decreased volume (p < 0.001), and white matter volume reduced in the right corona radiata beneath the right SMA (p < 0.001) in HM relative to non-HM patients. Furthermore, the strength of right SMA-seeded connectivity with insula was positively correlated with folic acid level in HM patients (r = 0.60, p = 0.03), showing an accuracy of 0.87 to distinguish HM from non-HM. Our study demonstrates the HM-specific dysconnectivity with an anatomical basis, and its correlation with laboratory findings and diagnostic value. Detecting these abnormalities might help to predict and diagnose post-TIPS HM. [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]

Summary: Background: Disturbances in emotion regulation are the hallmarks of major depressive disorder (MDD). The incapacity to control negative emotion in patients has been associated with abnormal hyperactivation of the limbic system and hypoactivation of the frontal cortex. The amygdala and orbital frontal cortex (OFC) are two critical regions of the emotion regulation neural systems. Methods: This study investigated the anatomical basis of abnormal emotion regulation by tracking the fiber tracts connecting the amygdala and OFC. In addition, using dynamic casual modeling on resting‐state fMRI data of 20 MDD patients and equivalent controls, we investigated the exact neural mechanism through which abnormal communications between these two nodes were mediated in MDD. Key Results: The results revealed disrupted white matter integrity of fiber tracts in MDD, suggesting that functional abnormalities were accompanied by underlying anatomical basis. We also detected a failure of inhibition of the OFC on the activity of the amygdala in MDD, suggesting dysconnectivity was mediated through "top‐down" influences from the frontal cortex to the amygdala. Following 8 weeks of antidepressant treatment, the patients showed significant clinical improvement and normalization of the abnormal OFC‐amygdala structural and effective connectivity in the left hemisphere. Conclusions & Inferences: Our findings suggest that pathways connecting these two nodes may be core targets of the antidepressant treatment. In particular, it raised the intriguing question: Does the reversal of structural markers of connectivity reflect a response to antidepressant medication or activity‐dependent myelination following a therapeutic restoration of effective connectivity? [ABSTRACT FROM AUTHOR]

Specific biomarker reflecting neurobiological substrates of schizophrenia (SZ) is required for its diagnosis and treatment selection of SZ. Evidence from neuroimaging has implicated disrupted functional connectivity in the pathophysiology. We aimed to develop and validate a method of disease definition for SZ by resting-state functional connectivity using radiomics strategy. This study included 2 data sets collected with different scanners. A total of 108 first-episode SZ patients and 121 healthy controls (HCs) participated in the current study, among which 80% patients and HCs (n = 183) and 20% (n = 46) were selected for training and testing in intra-data set validation and 1 of the 2 data sets was selected for training and the other for testing in inter-data set validation, respectively. Functional connectivity was calculated for both groups, features were selected by Least Absolute Shrinkage and Selection Operator (LASSO) method, and the clinical utility of its features and the generalizability of effects across samples were assessed using machine learning by training and validating multivariate classifiers in the independent samples. We found that the accuracy of intra-data set training was 87.09% for diagnosing SZ patients by applying functional connectivity features, with a validation in the independent replication data set (accuracy = 82.61%). The inter-data set validation further confirmed the disease definition by functional connectivity features (accuracy = 83.15% for training and 80.07% for testing). Our findings demonstrate a valid radiomics approach by functional connectivity to diagnose SZ, which is helpful to facilitate objective SZ individualized diagnosis using quantitative and specific functional connectivity biomarker. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: As a special movement disorder, hepatic myelopathy (HM) is characterized by spastic paraperesis and may be secondary to transjugular intrahepatic portosystemic shunt (TIPS). The prediction and diagnosis of HM is difficult due to largely unknown neuropathological underpinnings and a lack of specific biomarkers. We aimed to delve into the alterations in motor system of HM patients' brain and their potential clinical implication.Material and Methods: Twenty-three patients with HM and 23 without HM after TIPS and 24 demographically matched healthy controls were enrolled. High-spatial-resolution structural imaging and functional data at rest were acquired. Motor areas were included as seed regions for functional connectivity analysis. Then, we performed brain volume analysis.Results: We found decreased right supplementary motor area (SMA)-seeded functional connectivity with bilateral insula, thalamus and midbrain, left cerebellum and middle temporal gyrus, and right middle cingulate gyrus in HM compared to non-HM patients (p < 0.001). The right insula revealed decreased volume (p < 0.001), and white matter volume reduced in the right corona radiata beneath the right SMA (p < 0.001) in HM relative to non-HM patients. Furthermore, the strength of right SMA-seeded connectivity with insula was positively correlated with folic acid level in HM patients (r = 0.60, p = 0.03), showing an accuracy of 0.87 to distinguish HM from non-HM.Conclusion: Our study demonstrates the HM-specific dysconnectivity with an anatomical basis, and its correlation with laboratory findings and diagnostic value. Detecting these abnormalities might help to predict and diagnose post-TIPS HM. [ABSTRACT FROM AUTHOR]

Evidence from behavioral, electrophysiological and diffusion-weighted imaging studies suggest that schizophrenia patients suffer from deficiencies in bilateral brain communication, and this disruption may be related to the occurrence of auditory verbal hallucinations (AVH). To increase our understanding of aberrant inter-hemispheric communication in relation to AVH, we recruited two groups of first-episode schizophrenia patients: one group with AVH (N = 18 AVH patients) and one without hallucinations (N = 18 Non-AVH patients), and 20 healthy controls. All participants received T1 structural imaging and resting-state fMRI scanning. We adopted a newly developed index, voxel-mirrored homotopic connectivity (VMHC), to quantitatively describe bilateral functional connectivity. The whole-brain VMHC measure was compared among the three groups and correlation analyses were conducted between symptomology scores and neurological measures. Our findings suggest all patients shared abnormalities in parahippocampus and striatum. Aberrant bilateral connectivity of default mode network (DMN), inferior frontal gyrus and cerebellum only showed in AVH patients, whereas aberrances in superior temporal gyrus and precentral gyrus were specific to Non-AVH patients. Meanwhile, inter-hemispheric connectivity of DMN correlated with patients' symptomatology scores. This study corroborates that schizophrenia is characterized by inter-hemispheric dysconnectivity, and suggests the localization of such abnormalities may be crucial to whether auditory verbal hallucinations develop. [ABSTRACT FROM AUTHOR]

Diffuse midline glioma H3 K27M mutant is a new tumor entity described in the revised 2016 World Health Organization classification. It is most frequently observed in children and develops in midline structures, including the brainstem, thalamus, and spine. We describe a rare diffuse midline glioma with an H3 K27M mutation arising in the hypothalamus of an adult. A 27-year-old woman was admitted to our department complaining of amenorrhea, polydipsia, and diuresis for the previous 3 months, and headache and lethargy for approximately 10 days. Computed tomography scan showed an oval isodense solid mass extending from the pituitary toward the suprasellar cistern. A gadolinium-enhanced magnetic resonance imaging (MRI) showed a strongly heterogeneous enhanced solid lesion and nonenhanced cystic lesion. The patient underwent surgery and chemoradiotherapy with temozolomide. Histologic and immunohistochemical analyses revealed H3 K27M–mutant diffuse midline glioma. The patient underwent another resection for a recurrent tumor 5 months after the first surgery. Three months after the second operation, the patient relapsed, with MRI revealing spinal cord and meningeal metastases; she died shortly afterward. Diffuse midline glioma with an H3 K27M mutation occurring in the hypothalamus of an adult is rare but should be considered in differential diagnoses. Because histone H3 K27M mutations are associated with aggressive clinical behavior and poor prognosis, molecular analyses should be used to determine the clinical and histopathologic features of such tumors. This will contribute to developing targeted drugs and gene therapy going forward. [ABSTRACT FROM AUTHOR]

Background: Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear., Aims: To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age., Method: The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed., Results: The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = -0.326, P = 0.014)., Conclusions: The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.

Objective: The prevalence of cavum septum pellucidum (CSP) in mental disorders, particularly schizophrenia spectrum disorders and mood disorders, remains uncertain. The authors used a meta-analytical approach to determine the prevalence of CSP in mental disorders and to compare these with the prevalence of CSP in psychiatrically healthy comparison subjects., Methods: PubMed and Embase were systematically searched for relevant articles published as of January 9, 2018. After a quality assessment of individual studies using the Newcastle-Ottawa Scale, a random-effects model within Stata statistical software was used to synthesize 25 eligible studies that included 2,392 patients with mental disorders and 1,445 psychiatrically healthy comparison subjects., Results: The prevalence of CSP of any size and large CSP was found to be significantly higher in individuals with mental disorders compared with healthy comparison subjects, and the prevalence of CSP in schizophrenia spectrum and mood disorders did not differ between the groups., Conclusions: The meta-regression with predefined covariance indicated that imaging parameters were not associated with the heterogeneity among original studies; however, the mean age of enrolled subjects was identified as a possible source of heterogeneity. No publication bias was found.

Hepatic myelopathy is a complication seen in patients with chronic liver failure with physiologic or iatrogenic portosystemic shunting. The main symptom is progressive lower limb dyskinesia. The role of the brain motor control center in hepatic myelopathy is unknown. This study aimed to investigate the gray matter changes in patients with hepatic myelopathy secondary to transjugular intrahepatic portosystemic shunt and to examine their clinical relevance. This was a cross-sectional study. Twenty-three liver failure patients with hepatic myelopathy (hepatic myelopathy group), 23 liver failure patients without hepatic myelopathy (non-hepatic myelopathy group) after transjugular intrahepatic portosystemic shunt, and 23 demographically matched healthy volunteers were enrolled from March 2014 to November 2016 at Xijing Hospital, Air Force Military Medical University (Fourth Military Medical University), China. High-resolution magnetization-prepared rapid gradient-echo brain imaging was acquired. Group differences in regional gray matter were assessed using voxel-based morphometry analysis. The relationship between aberrant gray matter and motor characteristics was investigated. Results demonstrated that compared with the non-hepatic myelopathy group, gray matter volume abnormalities were asymmetric, with decreased volume in the left insula (P = 0.003), left thalamus (P = 0.029), left superior frontal gyrus (P = 0.006), and right middle cingulate cortex (P = 0.021), and increased volume in the right caudate nucleus (P = 0.017), corrected with open-source software. The volume of the right caudate nucleus in the hepatic myelopathy group negatively correlated with the lower limb clinical rating of the Fugl-Meyer Assessment (r = -0.53, P = 0.01). Compared with healthy controls, patients with and without hepatic myelopathy exhibited overall increased gray matter volume in both thalami, and decreased gray matter volume in both putamen, as well as in the globus pallidus, cerebellum, and vermis. The gray matter abnormalities we found predominantly involved motor-related regions, and may be associated with motor dysfunction. An enlarged right caudate nucleus might help to predict weak lower limb motor performance in patients with preclinical hepatic myelopathy after transjugular intrahepatic portosystemic shunt. This study was approved by the Ethics Committee of Xijing Hospital, Air Force Military Medical University (Fourth Military Medical University), China (approval No. 20140227-6) on February 27, 2014., Competing Interests: The authors declare that the article content was composed in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Neural substrates behind schizophrenia (SZ) and its heritability mediated by brain function are largely unknown. Cerebral blood flow (CBF), as a biomarker of activation in the brain, reflects the neuronal metabolism, and is promisingly used to detect cerebral alteration thereby shedding light on the features of individuals at high genetic risk. We performed a cross-sectional functional magnetic resonance imaging (MRI) study enrolling 45 first-episode drug-naïve patients with SZ, 32 unaffected first-degree relatives of these patients, and 51 healthy controls (HCs). We examined CBF, CBF connectivity, and CBF topological properties. SZ patients showed increased CBF in the left medial superior frontal gyrus and right precuneus compared with HCs, and decreased CBF in the left middle temporal gyrus compared with their relatives. Furthermore, unaffected relatives revealed higher level of CBF pronounced in regions within default mode network (DMN). Both SZ patients and their relatives exhibited dysconnectivity patterns. Notably, as for the network properties, unaffected relatives were with an intermediate level between SZ patients and HCs in the local efficiency and global efficiency. Our findings demonstrate the aberrant CBF of areas within DMN and the CBF connectivity pattern might be a familial feature in the brain of first-episode SZ patients and their relatives.

Purpose To investigate auditory verbal hallucination (AVH)-specific patterns of brain activity within the resting-state networks (RSNs) that have been proposed to underpin the neural mechanisms of schizophrenia (SZ). Materials and Methods This cross-sectional study was approved by the local ethics committee, and written informed consent was obtained from all participants prospectively recruited. Independent component analysis was used to investigate RSNs in 17 patients with first-episode untreated SZ with AVHs, 15 patients with SZ without AVHs, and 19 healthy control subjects who underwent resting-state functional magnetic resonance imaging. Dual regression was implemented to perform between-group analysis. Regional brain function was then explored within RSNs by using the amplitude of low-frequency fluctuation. Two-sample t tests were used to compare regional brain function between the two patient groups, and Pearson correlation analysis was used to characterize the relationship between imaging findings and severity of AVHs. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of these brain function measures. Results Independent component analysis demonstrated symptom-specific abnormal disrupted coactivation within the auditory, default mode, executive, motor, and frontoparietal networks and was pronounced in the auditory cortex, supramarginal gyrus, insula, putamen, dorsolateral prefrontal cortex, angular gyrus, precuneus, and thalamus (P < .05 with false discovery rate correction). Amplitude of low-frequency fluctuation analysis demonstrated similar patterns within these RSNs (P < .05 with false discovery rate correction). Furthermore, a positive correlation between the degree of coactivation within the motor network and the severity of AVHs was observed in patients with SZ with AVHs (r = 0.67, P = .003). The area under the receiver operating characteristic curve was 0.76-0.90 for all RSNs. Conclusion These findings indicate that dysfunctional brain regions are involved in auditory processing, language production and monitoring, and sensory information filtering in patients with SZ with AVHs, which may be helpful in furthering the understanding of pathophysiological correlates of AVHs in SZ. Online supplemental material is available for this article.

Familial risk plays a significant role in the etiology of schizophrenia (SZ). Many studies using neuroimaging have demonstrated structural and functional alterations in relatives of SZ patients, with significant results found in diverse brain regions involving the anterior cingulate cortex (ACC), caudate, dorsolateral prefrontal cortex (DLPFC), and hippocampus. This study investigated whether unaffected relatives of first episode SZ differ from healthy controls (HCs) in effective connectivity measures among these regions. Forty-six unaffected first-degree relatives of first episode SZ patients-according to the DSM-IV-were studied. Fifty HCs were included for comparison. All subjects underwent resting state functional magnetic resonance imaging (fMRI). We used stochastic dynamic causal modeling (sDCM) to estimate the directed connections between the left ACC, right ACC, left caudate, right caudate, left DLPFC, left hippocampus, and right hippocampus. We used Bayesian parameter averaging (BPA) to characterize the differences. The BPA results showed hyperconnectivity from the left ACC to right hippocampus and hypoconnectivity from the right ACC to right hippocampus in SZ relatives compared to HCs. The pattern of anterior cingulate cortico-hippocampal connectivity in SZ relatives may be a familial feature of SZ risk, appearing to reflect familial susceptibility for SZ.

Understanding the neural basis of schizophrenia (SZ) is important for shedding light on the neurobiological mechanisms underlying this mental disorder. Structural and functional alterations in the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, and medial prefrontal cortex (MPFC) have been implicated in the neurobiology of SZ. However, the effective connectivity among them in SZ remains unclear. The current study investigated how neuronal pathways involving these regions were affected in first-episode SZ using functional magnetic resonance imaging (fMRI). Forty-nine patients with a first-episode of psychosis and diagnosis of SZ-according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision-were studied. Fifty healthy controls (HCs) were included for comparison. All subjects underwent resting state fMRI. We used spectral dynamic causal modeling (DCM) to estimate directed connections among the bilateral ACC, DLPFC, hippocampus, and MPFC. We characterized the differences using Bayesian parameter averaging (BPA) in addition to classical inference (t-test). In addition to common effective connectivity in these two groups, HCs displayed widespread significant connections predominantly involved in ACC not detected in SZ patients, but SZ showed few connections. Based on BPA results, SZ patients exhibited anterior cingulate cortico-prefrontal-hippocampal hyperconnectivity, as well as ACC-related and hippocampal-dorsolateral prefrontal-medial prefrontal hypoconnectivity. In summary, spectral DCM revealed the pattern of effective connectivity involving ACC in patients with first-episode SZ. This study provides a potential link between SZ and dysfunction of ACC, creating an ideal situation to associate mechanisms behind SZ with aberrant connectivity among these cognition and emotion-related regions.