The correlation between dynamic functional architecture and response to electroconvulsive therapy combined with antipsychotics in schizophrenia.

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.

Abnormal dynamic functional connectivity after sleep deprivation from temporal variability perspective.

Sleep deprivation (SD) is very common in modern society and regarded as a potential causal mechanism of several clinical disorders. Previous neuroimaging studies have explored the neural mechanisms of SD using magnetic resonance imaging (MRI) from static (comparing two MRI sessions [one after SD and one after resting wakefulness]) and dynamic (using repeated MRI during one night of SD) perspectives. Recent SD researches have focused on the dynamic functional brain organization during the resting-state scan. Our present study adopted a novel metric (temporal variability), which has been successfully applied to many clinical diseases, to examine the dynamic functional connectivity after SD in 55 normal young subjects. We found that sleep-deprived subjects showed increased regional-level temporal variability in large-scale brain regions, and decreased regional-level temporal variability in several thalamus subregions. After SD, participants exhibited enhanced intra-network temporal variability in the default mode network (DMN) and increased inter-network temporal variability in numerous subnetwork pairs. Furthermore, we found that the inter-network temporal variability between visual network and DMN was negative related with the slowest 10% respond speed (ß = -.42, p = 5.57 × 10-4 ) of the psychomotor vigilance test after SD following the stepwise regression analysis. In conclusion, our findings suggested that sleep-deprived subjects showed abnormal dynamic brain functional configuration, which provides new insights into the neural underpinnings of SD and contributes to our understanding of the pathophysiology of clinical disorders.

Baseline structural and functional magnetic resonance imaging predicts early treatment response in schizophrenia with radiomics strategy.

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.

Neuroimaging-based brain-age prediction of first-episode schizophrenia and the alteration of brain age after early medication.

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.

MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma.

OBJECTIVES: To establish and validate a radiomics nomogram for prediction of induction chemotherapy (IC) response and survival in nasopharyngeal carcinoma (NPC) patients. METHODS: One hundred twenty-three NPC patients (100 in training and 23 in validation cohort) with multi-MR images were enrolled. A radiomics nomogram was established by integrating the clinical data and radiomics signature generated by support vector machine. RESULTS: The radiomics signature consisting of 19 selected features from the joint T1-weighted (T1-WI), T2-weighted (T2-WI), and contrast-enhanced T1-weighted MRI images (T1-C) showed good prognostic performance in terms of evaluating IC response in two cohorts. The radiomics nomogram established by integrating the radiomics signature with clinical data outperformed clinical nomogram alone (C-index in validation cohort, 0.863 vs 0.549; p < 0.01). Decision curve analysis demonstrated the clinical utility of the radiomics nomogram. Survival analysis showed that IC responders had significant better PFS (progression-free survival) than non-responders (3-year PFS 84.81% vs 39.75%, p < 0.001). Low-risk groups defined by radiomics signature had significant better PFS than high-risk groups (3-year PFS 76.24% vs 48.04%, p < 0.05). CONCLUSIONS: Multiparametric MRI-based radiomics could be helpful for personalized risk stratification and treatment in NPC patients receiving IC. KEY POINTS: • MRI Radiomics can predict IC response and survival in non-endemic NPC. • Radiomics signature in combination with clinical data showed excellent predictive performance. • Radiomics signature could separate patients into two groups with different prognosis.

The Prevalence of Cavum Septum Pellucidum in Mental Disorders Revealed by MRI: A Meta-Analysis.

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.

Learning curve of double-guidewire technique by trainees during hands-on endoscopic retrograde cholangiopancreatography training.

BACKGROUND AND AIMS: Double-guidewire technique (DWT) has been successfully performed by experts in difficult biliary cannulation as an advanced technique. This study aimed to define the learning curve and safety of DWT by trainees during hands-on endoscopic retrograde cholangiopancreatography (ERCP) training. METHODS: Patients were eligible for inclusion in the study if the biliary cannulation was difficult and the pancreatic duct was inadvertently cannulated. DWT was performed by two trainees randomly under trainers' guidance. The primary outcome was the success rate of DWT biliary cannulation of trainees. Cumulative sum analysis was used to generate visual learning curves. RESULTS: A total of 60 patients with difficult cannulation were enrolled. The main indications for ERCP were common bile duct stones (65%) and biliary stricture (31.7%). The learning curve analysis showed that to achieve a 70% rate of successful DWT, 12 procedures were needed for trainee A and 15 for trainee B. Higher targeted success rate of DWT could be achieved if the number of DWT procedures increased. Compared with the early stage of learning DWT (case 1 to 15 for each trainee), trainees had significantly higher DWT success rate in the late stage (36.7% [11/30] vs 80% [24/30], P = 0.001). The final success rate of cannulation was 98.3% (59/60). The overall rate of post-ERCP pancreatitis and adverse events was 6.7% (4/60) and 8.3% (5/60), respectively. CONCLUSIONS: Double-guidewire technique was safely performed by two novel trainees during hands-on ERCP training. Fifteen procedures may be enough for trainees to achieve the competency of performing DWT. (Clinicaltrials.gov number: NCT03707613).

Grading of Glioma: combined diagnostic value of amide proton transfer weighted, arterial spin labeling and diffusion weighted magnetic resonance imaging.

BACKGROUND: To investigate the ability of amide proton transfer (APT) weighted magnetic resonance imaging (MRI), arterial spin labeling (ASL), diffusion weighted imaging (DWI) and the combination for differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs). METHODS: Twenty-seven patients including nine LGGs and eighteen HGGs underwent conventional, APT, ASL and DWI MRI with a 3.0-T MR scanner. Histogram analyses was performed and quantitative parameters including mean apparent diffusion coefficient (ADC mean), 20th-percentile ADC (ADC 20th), mean APT (APT mean), 90th-percentile APT (APT 90th), relative mean cerebral blood flow (rCBF mean) and relative 90th-percentile CBF (rCBF 90th) were compared between HGGs and LGGs. The diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis of each parameter and their combination. Correlations were analyzed among the MRI parameters and Ki-67. RESULTS: The APT values were significantly higher in the HGGs compared to the LGGs (p <  0.005), whereas ADC values were significantly lower in HGGs than LGGs (P <  0.0001). The ADC 20th and APT mean had higher discrimination abilities compared with other single parameters, with the area under the ROC curve (AUC) of 0.877 and 0.840. Adding ADC parameter, the discrimination ability of APT and rCBF significantly improved. The ADC was negatively correlated with the APT and rCBF value, respectively, while APT value was positively correlated with rCBF value. Significant correlations between ADC values and Ki-67 were also observed. CONCLUSIONS: APT and DWI are valuable in differentiating HGGs from LGGs. The combination of APT, DWI and ASL imaging could improve the ability for discriminating HGGs from LGGs.

Neural correlates of dynamic changes in working memory performance during one night of sleep deprivation.

Total sleep deprivation (TSD) is common in modern society leading to deterioration of multiple aspects of cognition. Dynamic interaction effect of circadian rhythmicity and homeostatic sleep pressure on sustained attention have been intensively investigated, while how this effect was represented on performance and cerebral responses to working memory, another important element of many neurobehavioral tasks, was not well elucidated. Thirty-six healthy subjects with intermediate chronotype performed the Sternberg working-memory task (SWMT) while undergoing functional magnetic resonance imaging every 2 hr from 10:00 p.m. on the first day to 6:00 a.m. on the second day. Using data from three imaging sessions (10:00 p.m., 04:00 a.m., and 06:00 a.m.), we found that the slowest SWMT reaction time and weakest cerebral responses were not at the end of TSD (06:00 a.m.) but during the early morning (04:00 a.m.) hours of the TSD. In addition, during this worst period of TSD, reaction time for the SWMT were found to be negatively correlated with task-related activation in the angular gyrus and positively correlated with the degree of negative correlation between the control and default networks. Our results revealed a rebound of SWMT reaction time and cerebral responses after the mid-time point of regular biological sleep night and provided more evidence that different cognitive tasks are differentially affected by sleep loss and circadian rhythmicity.

Isocitrate dehydrogenase1 mutation reduces the pericyte coverage of microvessels in astrocytic tumours.

INTRODUCTION: Tumour-associated angiogenesis is associated with the malignancy and poor prognosis of glioma. Isocitrate dehydrogenase (IDH) mutations are present in the majority of lower-grade (WHO grade II and III) and secondary glioblastomas, but their roles in tumour angiogenesis remain unclear. METHODS: Using magnetic resonance imaging (MRI), the cerebral blood flow (CBF) of IDH-mutated glioma was measured and compared with the IDH-wildtype glioma. The densities of microvessels in IDH-mutated and wildtype astrocytoma and glioblastoma were assessed by immunohistochemical (IHC) staining with CD34, and the pericytes were labelled with α-smooth muscle antigen (α-SMA), neural-glial antigen 2 (NG2) and PDGF receptor-ß (PDGFR-ß), respectively. Furthermore, glia-specific mutant IDH1 knock-in mice were generated to evaluate the roles of mutant IDH1 on brain vascular architectures. The transcriptions of the angiogenesis-related genes were assessed in TCGA datasets, including ANGPT1, PDGFB and VEGFA. The expressions of these genes were further determined by western blot in U87-MG cells expressing a mutant IDH1 or treated with 2-HG. RESULTS: The MRI results indicated that CBF was reduced in the IDH-mutated gliomas. The IHC staining showed that the pericyte coverages of microvessels were significantly decreased, but the microvessel densities (MVDs) were only slightly decreased in IDH-mutated glioma. The mutant IDH1 knock-in also impeded the pericyte coverage of brain microvessels in mice. Moreover, the TCGA database showed the mRNA levels of angiogenesis factors, including ANGPT1, PDGFB and VEGFA, were downregulated, and their promoters were also highly hyper-methylated in IDH-mutated gliomas. In addition, both mutant IDH1 and D-2-HG could downregulate the expression of these genes in U87-MG cells. CONCLUSIONS: Our results suggested that IDH mutations could reduce the pericyte coverage of microvessels in astrocytic tumours by inhibiting the expression of angiogenesis factors. As vascular pericytes play an essential role in maintaining functional blood vessels to support tumour growth, our findings imply a potential avenue of therapeutic strategy for IDH-mutated gliomas.

Primary central nervous system small lymphocytic lymphoma in the bilateral ventricles: two case reports.

BACKGROUND: Primary central nervous system (CNS) small lymphocytic lymphoma (SLL), as a type of low-grade lymphoma, is extremely rare. The diagnosis of CNS SLL is challenging due to its variable clinical and radiological features, which may overlap with those of diffuse large B-cell lymphoma (DLBCL). Primary CNS SLL differs from DLBCL in that it has an indolent clinical course and a good prognosis. Thus, it is important to distinguish SLL from DLBCL. By reviewing the literature, only two cases of low-grade SLL, primarily located in the CNS and involving the brain parenchyma and dura, have been reported. To our knowledge, primary CNS SLL in the bilateral ventricles has never been reported. Interestingly, the two cases in our report are identical in terms of the clinical presentations, magnetic resonance imaging (MRI) features, pathological results and prognoses. CASE PRESENTATION: Both patients presented with headaches. MRI suggested solid lesions located in the bilateral ventricles that were isointense on T1-weighted images and hypointense on T2-weighted images. After the injection of contrast agent (gadolinium, Gd), the intraventricular lesions were homogeneously enhanced and hyperperfused. CSF cytology revealed malignant cells. Brain biopsy revealed diffuse proliferation of small lymphocytes with positive labelling of B-cell immunomarkers. The primary origin in the CNS was confirmed with no evidence of systemic lymphoma. Two patients were given high doses of methotrexate-based chemotherapy and were free from symptoms and progression for more than 1-year of follow-up. CONCLUSIONS: The presence of homogeneously enhanced intraventricular MRI lesions should raise the suspicion of primary CNS SLL.

Alterations in cortical thickness in nonmedicated premature ejaculation patients: A morphometric MRI study.

PURPOSE: Premature ejaculation (PE) is one of the most common sexual dysfunctions in men. However, there has been little research evaluating alterations in brain structure related to PE. We aimed to investigate the characteristics of nonmedicated PE patients in terms of brain morphometry. MATERIALS AND METHODS: The sample consisted with 32 medication-naïve adult men with clinical diagnosed PE and matched 31 healthy controls. All participants received diagnostic interviews and 3.0 Tesla MRI scans. Automatic segmentation processing of MRI structure images was performed using FreeSurfer software and cerebral cortical thickness between groups was compared. RESULTS: The PE group had thicker cortex in widespread regions, including the frontal, parietal and occipital lobe, and limbic system, compared with the healthy control group (P < 0.05). Moreover, the duration is negatively correlated with the mean cortical thickness of the right medial orbitofrontal cortex, right precentral gyrus and left superior frontal cortex (R2 = 0.29, P < 0.003; R2 = 0.163, P < 0.04; R2 = 0.2, P < 0.02), while the Premature Ejaculation Diagnostic Tool score is negatively correlated with the mean cortical thickness of the left caudal middle frontal cortex (R2 = 0.33, P < 0.005). CONCLUSION: The result highlights the structural features of PE and suggests the relationship with the severity of impairment is related to the severity of anatomic abnormality with the relevant brain region. These results support the value of imaging measures as markers for understanding the physiopathology of PE. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:656-662.

Radiomics signature: A potential biomarker for the prediction of MGMT promoter methylation in glioblastoma.

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.

Abnormal White Matter Microstructure in Lifelong Premature Ejaculation Patients Identified by Tract-Based Spatial Statistical Analysis.

INTRODUCTION: Several recent neuroimaging studies have identified functional and structural abnormalities in the cerebral cortex of lifelong premature ejaculation (LPE) patients, including task-related and resting-state brain function, and cortical thickness, although changes in white matter microstructure have not been reported. AIM: To assess the differences in white matter microstructure between LPE patients and healthy controls. METHODS: Diffusion tensor imaging (DTI) and tract-based spatial statistical analysis were used to detect differences in white matter microstructure between 32 LPE patients and 32 matched healthy controls. We also analyzed correlations of clinical indices with significant DTI-based features. MAIN OUTCOME MEASURES: DTI-based features (including fractional anisotropy [FA], mean diffusivity, axial diffusivity, and radial diffusivity) were assessed in LPE patients and controls, as well as the correlation of white matter changes in LPE patients with clinical data (including the premature ejaculation diagnostic tool score and the International Index of Erectile Function). RESULTS: LPE patients showed widespread increases in FA and axial diffusivity values compared with controls, including in the right posterior thalamic radiation, posterior corona radiata, bilateral posterior limb of the internal capsule, superior corona radiata, and external capsule. Further, FA in the right posterior thalamic radiation was positively correlated with the premature ejaculation diagnostic tool score in LPE patients. CLINICAL IMPLICATIONS: Changes of white matter microstructure may be an underlying marker for evaluating sensory conduction efficiency in LPE patients. STRENGTHS & LIMITATIONS: There are no previous studies examining white matter microstructure in LPE patients. The present study furthers our understanding of the etiology of LPE. Limitations include a cross-sectional study design without causal information, and no measurement of conduction efficiencies such as cortical somatosensory-evoked potential from the penis, or psychosocial factors. CONCLUSION: Our findings show potential microstructural white matter abnormalities related to LPE, suggesting that changes in fiber pathways connecting the cerebral cortex and the thalamus may play roles in the etiology of LPE. Gao M, Yang X, Liu L, et al. Abnormal White Matter Microstructure in Lifelong Premature Ejaculation Patients Identified by Tract-Based Spatial Statistical Analysis. J Sex Med 2018;15:1272-1279.

Dynamics of cerebral responses to sustained attention performance during one night of sleep deprivation.

Total sleep deprivation (TSD) is increasingly common in modern society bringing various neurobehavioural effects. Dynamic changes of behaviour performances during TSD have been reported extensively, while the cerebral activation underlying such changes have not been elucidated clearly. This study aimed to investigate dynamic changes in cerebral responses to the fastest and slowest psychomotor vigilance task (PVT) trials during TSD. Thirty-six healthy subjects with intermediate chronotype performed the PVT while undergoing functional magnetic resonance imaging every 2 h from 22:00 hours on the first day to 06:00 hours on the second day (i.e. 22:00, 12:00, 02:00, 04:00 and 06:00 hours; a total of five imaging sessions). Behaviourally, significant time effects were found for the PVT performance. For imaging results, significant activation alterations were found in the cognitive control network and the default mode network (DMN) for the fastest and slowest PVT trials, respectively. Time-course analysis indicated that the largest differences for behavioural results and imaging results happened in session 4 and became more prominent in session 5. Our findings provide more detailed information about the process of sustained attention activation during one night of TSD and add information regarding the effect of circadian rhythmicity and homeostatic sleep pressure on regional brain responses.

Noninvasively evaluating the grading and IDH1 mutation status of diffuse gliomas by three-dimensional pseudo-continuous arterial spin labeling and diffusion-weighted imaging.

PURPOSE: To noninvasively evaluate the value of three-dimensional pseudo-continuous arterial spin labeling (3D pCASL) and diffusion-weighted imaging (DWI) in diffuse gliomas grading as well as isocitrate dehydrogenase (IDH) 1 mutation status. METHODS: Fifty-six patients with pathologically confirmed diffuse gliomas with preoperative 3D pCASL and DWI were enrolled in this study. The Student's t test and Mann-Whitney U test were used to evaluate differences in parameters of DWI and 3D pCASL between low and high grade as well as between mutant and wild-type IDH1 diffuse gliomas; receiver operator characteristic (ROC) analysis was used to assess the diagnostic performance. Subsequently, a multivariate stepwise logistic regression analysis was used to identify the independent parameters. Besides, Kruskal-Wallis H test was used to examine the differences among grades II, III, and IV diffuse gliomas. RESULTS: All parameters but CBFmean showed significant differences between low- and high-grade diffuse gliomas. In ROC analysis, the AUC of CBFmax, rCBFmean, rCBFmax, ADCmean, and ADCmin were 0.701, 0.730, 0.746, 0.810, and 0.856 respectively. Only the value of ADCmin was identified as the independent parameter in the differentiation of low- from high-grade diffuse gliomas. All parameters but CBFmean showed significant differences among the three grades. And the values of CBFmean, CBFmax, rCBFmean, and ADCmean showed significant differences between mutant and wild-type IDH1 in grade II-III astrocytoma. CONCLUSION: Both 3D pCASL and DWI could be useful tools for distinguishing low- from high-grade diffuse gliomas and have the potential to differentiate different IDH1 mutation statuses of astrocytoma.

Disturbed Brain Activity in Resting-State Networks of Patients with First-Episode Schizophrenia with Auditory Verbal Hallucinations: A Cross-sectional Functional MR Imaging Study.

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.

Baseline white matter function predicts short-term treatment response in first-episode schizophrenia.

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.

Differentiation of Neoplastic and Non-neoplastic Intracranial Enhancement Lesions Using Three-Dimensional Pseudo-Continuous Arterial Spin Labeling.

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.

Altered functional connectivity of the dentate nuclei in patients with schizophrenia.

Dentate nuclei (DN) are vital structures in the anatomical circuits that link the cerebellum to the cerebrum. However, the characteristics of DN functional connectivity (FC) in schizophrenia remain largely unknown. In this study, we investigated the FC of the DN in patients with schizophrenia and examined their possible clinical correlates using resting-state functional magnetic imaging data. We found that the patient group had greater DN FC with the parietal lobe (e.g., postcentral gyrus and superior parietal lobule) and less DN FC with the prefrontal cortex (e.g., superior frontal gyrus), posterior cingulate cortex, and regional cerebellum (e.g., vermis 4-5 and crus I) than did the control group. Furthermore, some abnormal connectivities of the DN with these regions significantly correlated with psychiatric symptoms. These results suggest that the DN circuits are disturbed and may participate in the pathophysiology of schizophrenia.