Altered cerebral white matter network topology and cognition in children with obstructive sleep apnea.

OBJECTIVES: The study aimed to explore the underlying mechanisms of OSA-related cognitive impairment by investigating the altered topology of brain white matter networks in children with OSA. METHODS: Graph theory was used to examine white matter networks' network topological properties in 46 OSA and 31 non-OSA children. All participants underwent MRI, polysomnography, and cognitive testing. The effects of the obstructive apnea-hypopnea index (OAHI) on topological properties of white matter networks and network properties on cognition were studied using hierarchical linear regression. Mediation analyses were used to explore whether white matter network properties mediated the effects of OAHI on cognition. RESULTS: Children with OSA had significantly higher assortativity than non-OSA children. Furthermore, OAHI was associated with the nodal properties of several brain regions, primarily in the frontal and temporal lobes. The relationship between OAHI and verbal comprehension index was mediated through clustering coefficients in the right temporal pole of the superior temporal gyrus. CONCLUSIONS: OSA affects the development of white matter networks in children's brains. Besides, the mediating role of white matter network properties between the OAHI and the verbal comprehension index provided neuroimaging evidence of impaired cognitive function in children with OSA.

Association between functional network connectivity, retina structure and microvasculature, and visual performance in patients after thalamic stroke: An exploratory multi-modality study.

BACKGROUND AND OBJECTIVE: Neuro-ophthalmologic symptoms and retinal changes have been increasingly observed following thalamic stroke, and there is mounting evidence indicating distinct alterations occurring in the vision-related functional network. However, the intrinsic correlations between these changes are not yet fully understood. Our objective was to explore the altered patterns of functional network connectivity and retina parameters, and their correlations with visual performance in patients with thalamic stroke. METHODS: We utilized resting-state functional MRI to obtain multi-modular functional connectivity (FC), and optical coherence tomography-angiography to measure various retina parameters, such as the retinal nerve fiber layer (RNFL), ganglion cell-inner plexiform layer (GCIPL), superficial vascular complex (SVC), and deep vascular complex. Visual acuity (VA) was used as a metric for visual performance. RESULTS: We included 46 patients with first-ever unilateral thalamic stroke (mean age 59.74 ± 10.02 years, 33 males). Significant associations were found between FC of attention-to-default mode and SVC, RNFL, and GCIPL, as well as between FC of attention-to-visual and RNFL (p < .05). Both RNFL and GCIPL exhibited significant associations with FC of visual-to-visual (p < .05). Only GCIPL showed an association with VA (p = .038). Stratified analysis based on a disease duration of 6 months revealed distinct and significant linking patterns in multi-modular FC and specific retina parameters, with varying correlations with VA in each subgroup. CONCLUSION: These findings provide valuable insight into the neural basis of the associations between brain network dysfunction and impaired visual performance in patients with thalamic stroke. Our novel findings have the potential to inform future targeted and individualized therapies. However, further comprehensive studies are necessary to validate our results.

Choroid plexus volume enlargement in first-episode antipsychotic-naïve schizophrenia.

Investigation of the choroid plexus in schizophrenia has seen growing interest due to its role in the interaction between neuroinflammation and brain dysfunction. Most previous studies included treated and long-term ill patients, while antipsychotics and illness course might both affect the choroid plexus. Here, we recruited first-episode antipsychotic-naïve schizophrenia patients, performed high-resolution structural brain scan and manually extracted choroid plexus volume. Choroid plexus volume was compared between patients and healthy controls after controlling for age, sex and intracranial volume. Age and sex effects were examined on choroid plexus volume in patient and healthy control groups respectively. In patients, we also examined the correlation of choroid plexus volume with volume measures of cortical and subcortical gray matter, white matter, lateral ventricular as well as symptom severity and cognitive function. Schizophrenia patients showed significantly enlarged choroid plexus volume compared with healthy controls. Choroid plexus volume was positively correlated with age in only patient group and we found significantly larger choroid plexus volumes in males than females in both patient and healthy control groups, while the sex effects did not differ between groups. Choroid plexus volume was only found correlated with lateral ventricular volume among the brain volume measures. No significant correlation between choroid plexus volume and clinical ratings or cognitive performance was observed. Without potential confounding effects of pharmacotherapy or illness course, our findings indicated the enlargement of choroid plexus in schizophrenia might be an enduring trait for schizophrenia.

Free water alterations in different inflammatory subgroups in schizophrenia.

BACKGROUND: Accumulating evidence suggests that inflammatory dysregulation both in blood and the brain is implicated in the pathogenesis of schizophrenia. Alterations in peripheral cytokines are not evident in all patients and there may be discrete altered inflammatory subgroups in schizophrenia. Recent studies using a novel and in vivo free-water imaging to detect inflammatory processes, have shown increased free water in white matter in schizophrenia. However, no studies to date have investigated the free water alterations in different inflammatory subgroups in schizophrenia. METHODS: Forty-four patients with schizophrenia and 49 controls were recruited. The serum levels of interleukin-1 beta (IL-1ß), IL-6, IL-10, and IL-12p70 were measured and used for cluster analysis with K-means and hierarchical algorithms. Diffusion tensor imaging (DTI) images were collected for all participants and voxel-wise free water and fractional anisotropy of tissue (FA-t) were compared between groups with Randomise running in FSL. Partial correlation analysis was employed to explore the association of the peripheral cytokine levels with free water. RESULTS: We identified two statistically quantifiable discrete subgroups of patients based on the cluster analysis of cytokine measures. The peripheral levels of IL-1ß (P < 0.001), IL-10 (P = 0.041), and IL-12p70 (P < 0.001) showed significant differences between the two different inflammatory subgroups. In the inflammatory subgroup with a predominantly higher IL-1ß level, increased free water values in white matter were found mainly in the left posterior limb of the internal capsule, posterior corona radiata, and partly in the left sagittal stratum. These affected areas did not overlap with the regions that showed significant free water differences between patients and healthy controls. In the inflammatory subgroup with lower IL-1ß levels, peripheral IL-1ß was significantly associated with free water values in white matter while no such association was detected in the patient group. CONCLUSIONS: Localized free water differences were demonstrated between the two identified inflammatory subgroups in our data, and free water appears to be a feasible in vivo neuroimaging biomarker guiding the target of inflammatory intervention and development of new therapeutic strategies in an individualized manner in schizophrenia.

Construction and evaluation of a gated high-resolution neural network for automatic brain metastasis detection and segmentation.

OBJECTIVES: To construct and evaluate a gated high-resolution convolutional neural network for detecting and segmenting brain metastasis (BM). METHODS: This retrospective study included craniocerebral MRI scans of 1392 patients with 14,542 BMs and 200 patients with no BM between January 2012 and April 2022. A primary dataset including 1000 cases with 11,686 BMs was employed to construct the model, while an independent dataset including 100 cases with 1069 BMs from other hospitals was used to examine the generalizability. The potential of the model for clinical use was also evaluated by comparing its performance in BM detection and segmentation to that of radiologists, and comparing radiologists' lesion detecting performances with and without model assistance. RESULTS: Our model yielded a recall of 0.88, a dice similarity coefficient (DSC) of 0.90, a positive predictive value (PPV) of 0.93 and a false positives per patient (FP) of 1.01 in the test set, and a recall of 0.85, a DSC of 0.89, a PPV of 0.93, and a FP of 1.07 in dataset from other hospitals. With the model's assistance, the BM detection rates of 4 radiologists improved significantly, ranging from 5.2 to 15.1% (all p < 0.001), and also for detecting small BMs with diameter ≤ 5 mm (ranging from 7.2 to 27.0%, all p < 0.001). CONCLUSIONS: The proposed model enables accurate BM detection and segmentation with higher sensitivity and less time consumption, showing the potential to augment radiologists' performance in detecting BM. CLINICAL RELEVANCE STATEMENT: This study offers a promising computer-aided tool to assist the brain metastasis detection and segmentation in routine clinical practice for cancer patients. KEY POINTS: • The GHR-CNN could accurately detect and segment BM on contrast-enhanced 3D-T1W images. • The GHR-CNN improved the BM detection rate of radiologists, including the detection of small lesions. • The GHR-CNN enabled automated segmentation of BM in a very short time.

[Anatomic Abnormalities of Hippocampal Subfields in First-Episode Drug-Naïve Schizophrenia and Major Depressive Disorder: A Structural MRI Comparative Study].

Objective: To compare the structural changes along the longitudinal axis of hippocampus subfields between schizophrenia (SCZ) patients and major depressive disorder (MDD) patients in the early stage of their SCZ and MDD. Methods: Seventy-nine first-episode drug-naïve patients with SCZ, 48 first-episode drug-naïve patients with MDD, and 79 healthy controls (HC) were recruited and underwent assessment of clinical symptoms and magnetic resonance imaging (MRI) of the head. Following the calculation of hippocampal and subfield volumes with FreeSurfer, the volume of longitudinal subfields were summed up. Inter-group comparison of these indicators was made with the data of different groups and the correlation between clinical symptoms and the volumes of longitudinal subfields was analyzed. Results: Compared with HC, SCZ patients had smaller bilateral posterior hippocampus (left: t=－2.69, P=0.01; right: t=－2.90, P=0.004), while MDD patients exhibited no changes along the longitudinal axis of hippocampal subfields. In SCZ patients, the volume of bilateral posterior hippocampus was negatively correlated with the negative symptom scores of Positive and Negative Syndrome Scale (left: r=－0.29, P=0.01; right: r=－0.23, P=0.04). Conclusion: The smaller posterior hippocampus may be an imaging feature for distinguishing SCZ from MDD and may have contributed to the neuropathophysiological mechanism of SCZ in the early stage of the onset of the disease.

Altered controllability of white matter networks and related brain function changes in first-episode drug-naive schizophrenia.

Understanding how structural connectivity alterations affect aberrant dynamic function using network control theory will provide new mechanistic insights into the pathophysiology of schizophrenia. The study included 140 drug-naive schizophrenia patients and 119 healthy controls (HCs). The average controllability (AC) quantifying capacity of brain regions/networks to shift the system into easy-to-reach states was calculated based on white matter connectivity and was compared between patients and HCs as well as functional network topological and dynamic properties. The correlation analysis between AC and duration of untreated psychosis (DUP) were conducted to characterize the controllability progression pattern without treatment effects. Relative to HCs, patients exhibited reduced AC in multiple nodes, mainly distributed in default mode network (DMN), visual network (VN), and subcortical regions, and increased AC in somatomotor network. These networks also had impaired functional topology and increased temporal variability in dynamic functional connectivity analysis. Longer DUP was related to greater reductions of AC in VN and DMN. The current study highlighted potential structural substrates underlying altered functional dynamics in schizophrenia, providing a novel understanding of the relationship of anatomic and functional network alterations.

Hippocampal subfield alterations in schizophrenia and major depressive disorder: a systematic review and network meta-analysis of anatomic MRI studies.

BACKGROUND: Hippocampal disturbances are important in the pathophysiology of both schizophrenia and major depressive disorder (MDD). Imaging studies have shown selective volume deficits across hippocampal subfields in both disorders. We aimed to investigate whether these volumetric alterations in hippocampal subfields are shared or divergent across disorders. METHODS: We searched PubMed and Embase from database inception to May 8, 2021. We identified MRI studies in patients with schizophrenia, MDD or both, in which hippocampal subfield volumes were measured. We excluded nonoriginal, animal or postmortem studies, and studies that used other imaging modalities or overlapping data. We conducted a network meta-analysis to estimate and contrast alterations in subfield volumes in the 2 disorders. RESULTS: We identified 45 studies that met the initial criteria for systematic review, of which 15 were eligible for network metaanalysis. Compared to healthy controls, patients with schizophrenia had reduced volumes in the bilateral cornu ammonis (CA) 1, granule cell layer of the dentate gyrus, subiculum, parasubiculum, molecular layer, hippocampal tail and hippocampus-amygdala transition area (HATA); in the left CA4 and presubiculum; and in the right fimbria. Patients with MDD had decreased volumes in the left CA3 and CA4 and increased volumes in the right HATA compared to healthy controls. The bilateral parasubiculum and right HATA were smaller in patients with schizophrenia than in patients with MDD. LIMITATIONS: We did not investigate medication effects because of limited information. Study heterogeneity was noteworthy in direct comparisons between patients with MDD and healthy controls. CONCLUSION: The volumes of multiple hippocampal subfields are selectively altered in patients with schizophrenia and MDD, with overlap and differentiation in subfield alterations across disorders. Rigorous head-to-head studies are needed to validate our findings.

Radiomic features of gray matter in never-treated first-episode schizophrenia.

Alterations of radiomic features (RFs) in gray matter are observed in schizophrenia, of which the results may be limited by small study samples and confounding effects of drug therapies. We tested for RFs alterations of gray matter in never-treated first-episode schizophrenia (NT-FES) patients and examined their associations with known gene expression profiles. RFs were examined in the first sample with 197 NT-FES and 178 healthy controls (HCs) and validated in the second independent sample (90 NT-FES and 74 HCs). One-year follow-up data were available from 87 patients to determine whether RFs were associated with treatment outcomes. Associations between identified RFs in NT-FES and gene expression profiles were evaluated. NT-FES exhibited alterations of 30 RFs, with the greatest involvement of microstructural heterogeneity followed by measures of brain region shape. The identified RFs were mainly located in the central executive network, frontal-temporal network, and limbic system. Two baseline RFs with the involvement of microstructural heterogeneity predicted treatment response with moderate accuracy (78% for the first sample, 70% for the second sample). Exploratory analyses indicated that RF alterations were spatially related to the expression of schizophrenia risk genes. In summary, the present findings link brain abnormalities in schizophrenia with molecular features and treatment response.

Detecting brain lesions in suspected acute ischemic stroke with CT-based synthetic MRI using generative adversarial networks.

Background: Difficulties in detecting brain lesions in acute ischemic stroke (AIS) have convinced researchers to use computed tomography (CT) to scan for and magnetic resonance imaging (MRI) to search for these lesions. This work aimed to develop a generative adversarial network (GAN) model for CT-to-MR image synthesis and evaluate reader performance with synthetic MRI (syn-MRI) in detecting brain lesions in suspected patients. Methods: Patients with primarily suspected AIS were randomly assigned to the training (n=140) or testing (n=53) set. Emergency CT and follow-up MR images in the training set were used to develop a GAN model to generate syn-MR images from the CT data in the testing set. The standard reference was the manual segmentations of follow-up MR images. Image similarity was evaluated between syn-MRI and the ground truth using a 4-grade visual rating scale, the peak signal-to-noise ratio (PSNR), and the structural similarity index measure (SSIM). Reader performance with syn-MRI and CT was evaluated and compared on a per-patient (patient detection) and per-lesion (lesion detection) basis. Paired t-tests or Wilcoxon signed-rank tests were used to compare reader performance in lesion detection between the syn-MRI and CT data. Results: Grade 2-4 brain lesions were observed on syn-MRI in 92.5% (49/53) of the patients, while the remaining syn-MRI data showed no lesions compared to the ground truth. The GAN model exhibited a weak PSNR of 24.30 dB but a favorable SSIM of 0.857. Compared with CT, syn-MRI led to an increase in the overall sensitivity from 38% (57/150) to 82% (123/150) in patient detection and from 4% (68/1,620) to 16% (262/1,620) in lesion detection (R=0.32, corrected P<0.001), but the specificity in patient detection decreased from 67% (6/9) to 33% (3/9). An additional 75% (70/93) of patients and 15% (77/517) of lesions missed on CT were detected on syn-MRI. Conclusions: The GAN model holds potential for generating synthetic MR images from noncontrast CT data and thus could help sensitively detect individuals among patients with suspected AIS. However, the image similarity performance of the model needs to be improved, and further expert discrimination is strongly recommended.

Age-associated network controllability changes in first episode drug-naïve schizophrenia.

BACKGROUND: Recent neuroimaging studies revealed dysregulated neurodevelopmental, or/and neurodegenerative trajectories of both structural and functional connections in schizophrenia. However, how the alterations in the brain's structural connectivity lead to dynamic function changes in schizophrenia with age remains poorly understood. METHODS: Combining structural magnetic resonance imaging and a network control theory approach, the white matter network controllability metric (average controllability) was mapped from age 16 to 60 years in 175 drug-naïve schizophrenia patients and 155 matched healthy controls. RESULTS: Compared with controls, the schizophrenia patients demonstrated the lack of age-related decrease on average controllability of default mode network (DMN), as well as the right precuneus (a hub region of DMN), suggesting abnormal maturational development process in schizophrenia. Interestingly, the schizophrenia patients demonstrated an accelerated age-related decline of average controllability in the subcortical network, supporting the neurodegenerative model. In addition, compared with controls, the lack of age-related increase on average controllability of the left inferior parietal gyrus in schizophrenia patients also suggested a different pathway of brain development. CONCLUSIONS: By applying the control theory approach, the present study revealed age-related changes in the ability of white matter pathways to control functional activity states in schizophrenia. The findings supported both the developmental and degenerative hypotheses of schizophrenia, and suggested a particularly high vulnerability of the DMN and subcortical network possibly reflecting an illness-related early marker for the disorder.

Linked brain connectivity patterns with psychopathological and cognitive phenotypes in drug-naïve first-episode schizophrenia.

Background: Schizophrenia is considered to be a disorder of dysconnectivity characterized by abnormal functional integration between distinct brain regions. Different brain connection abnormalities were found to be correlated with various clinical manifestations, but whether a common deficit in functional connectivity (FC) in relation to both clinical symptoms and cognitive impairments could present in first-episode patients who have never received any medication remains elusive. Objective: To find a core deficit in the brain connectome that is related to both psychopathological and cognitive manifestations. Methods: A total of 75 patients with first-episode schizophrenia and 51 healthy control participants underwent scanning of the brain and clinical ratings of behaviors. A principal component analysis was performed on the clinical ratings of symptom and cognition. Partial correlation analyses were conducted between the main psychopathological components and resting-state FC that were found abnormal in schizophrenia patients. Results: Using the principal component analysis, the first principal component (PC1) explained 37% of the total variance of seven clinical features. The ratings of GAF and BACS contributed negatively to PC1, while those of PANSS, HAMD, and HAMA contributed positively. The FCs positively correlated with PC1 mainly included connections related to the insula, precuneus gyrus, and some frontal brain regions. FCs negatively correlated with PC1 mainly included connections between the left middle cingulate cortex and superior and middle occipital regions. Conclusion: In conclusion, we found a linked pattern of FC associated with both psychopathological and cognitive manifestations in drug-naïve first-episode schizophrenia characterized as the dysconnection related to the frontal and visual cortex, which may represent a core deficit of brain FC in patients with schizophrenia.

A Multimodal Fusion Analysis of Pretreatment Anatomical and Functional Cortical Abnormalities in Responsive and Non-responsive Schizophrenia.

Background: Antipsychotic medications provide limited long-term benefit to ~30% of schizophrenia patients. Multimodal magnetic resonance imaging (MRI) data have been used to investigate brain features between responders and nonresponders to antipsychotic treatment; however, these analytical techniques are unable to weigh the interrelationships between modalities. Here, we used multiset canonical correlation and joint independent component analysis (mCCA + jICA) to fuse MRI data to examine the shared and specific multimodal features between the patients and healthy controls (HCs) and between the responders and non-responders. Method: Resting-state functional and structural MRI data were collected from 55 patients with drug-naïve first-episode schizophrenia (FES) and demographically matched HCs. Based on the decrease in Positive and Negative Syndrome Scale scores from baseline to the 1-year follow-up, FES patients were divided into a responder group (RG) and a non-responder group (NRG). Gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) maps were used as features in mCCA + jICA. Results: Between FES patients and HCs, there were three modality-specific discriminative independent components (ICs) showing the difference in mixing coefficients (GMV-IC7, GMV-IC8, and fALFF-IC5). The fusion analysis indicated one modality-shared IC (GMV-IC2 and ReHo-IC2) and three modality-specific ICs (GMV-IC1, GMV-IC3, and GMV-IC6) between the RG and NRG. The right postcentral gyrus showed a significant difference in GMV features between FES patients and HCs and modality-shared features (GMV and ReHo) between responders and nonresponders. The modality-shared component findings were highlighted by GMV, mainly in the bilateral temporal gyrus and the right cerebellum associated with ReHo in the right postcentral gyrus. Conclusions: This study suggests that joint anatomical and functional features of the cortices may reflect an early pathophysiological mechanism that is related to a 1-year treatment response.

Grey matter connectome abnormalities and age-related effects in antipsychotic-naive schizophrenia.

BACKGROUND: Convergent evidence is increasing to indicate progressive brain abnormalities in schizophrenia. Knowing the brain network features over the illness course in schizophrenia, independent of effects of antipsychotic medications, would extend our sight on this question. METHODS: We recruited 237 antipsychotic-naive patients with schizophrenia range from 16 to 73 years old, and 254 healthy controls. High-resolution T1 weighted images were obtained with a 3.0T MR scanner. Grey matter networks were constructed individually based on the similarities of regional grey matter measurements. Network metrics were compared between patient groups and healthy controls, and regression analyses with age were conducted to determine potential differential rate of age-related changes between them. FINDINGS: Nodal centrality abnormalities were observed in patients with untreated schizophrenia, particularly in the central executive, default mode and salience networks. Accelerated age-related declines and illness duration-related declines were observed in global assortativity, and in nodal metrics of left superior temporal pole in schizophrenia patients. Although no significant intergroup differences in age-related regression were observed, the pattern of network metric alternation of left thalamus indicated higher nodal properties in early course patients, which decreased in long-term ill patients. INTERPRETATIONS: Global and nodal alterations in the grey matter connectome related to age and duration of illness in antipsychotic-naive patients, indicating potentially progressive network organizations mainly involving temporal regions and thalamus in schizophrenia independent from medication effects. FUNDING: The National Natural Science Foundation of China, Sichuan Science and Technology Program, the Fundamental Research Funds for the Central Universities, Post-Doctor Research Project, West China Hospital, Sichuan University , the Science and Technology Project of the Health Planning Committee of Sichuan, Postdoctoral Interdisciplinary Research Project of Sichuan University and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University.

Pretreatment abnormalities in white matter integrity predict one-year clinical outcome in first episode schizophrenia.

Schizophrenia is a serious mental illness for which the mainstay of treatment is antipsychotics. Up to 30% of schizophrenia patients show limited response to antipsychotics. Identifying these patients before treatment could guide individualized treatment for improving outcomes in those not likely to show robust benefit from antipsychotics. Diffusion tensor imaging was performed with 56 drug-naïve first-episode schizophrenia patients and 69 matched healthy controls. Patients were followed clinically after one-year of antipsychotic treatment and classified at that point into groups of 17 poor outcome and 39 good outcome patients based on whether they showed at least a 50% reduction of Positive and Negative Syndrome Scale (PANSS) scores from baseline. Tract-based spatial statistics were applied to assess white matter microstructure in the two patient subgroups and healthy controls. Poor outcome patients showed reduced pretreatment fractional anisotropy (FA) in left cingulum and anterior thalamic radiation and increased FA in right superior and inferior longitudinal fasciculus compared with good outcome patients. FA in each of these four tracts was decreased in both patient subgroups relative to healthy controls. Considered together, the four altered tracts showed promising ability to differentiate poor from good outcome patients (sensitivity = 74.4%, specificity = 95.2%, AUC = 0.90, p < 0.001), and superior prediction of clinical outcome to baseline PANSS scores (p < 0.015). Prediction of outcomes using DTI features was not related to duration of untreated psychosis. Baseline alterations in white matter integrity may identify schizophrenia patients less likely to respond to treatment, which could be useful information for stratification in clinical trials and for individualized treatment planning.

[A preliminary study on schizophrenia of distinct antipsychotic response based on diffusion tensor imaging].

The study aims to investigate whether there is difference in pre-treatment white matter parameters in treatment-resistant and treatment-responsive schizophrenia. Diffusion tensor imaging (DTI) was acquired from 60 first-episode drug-naïve schizophrenia (39 treatment-responsive and 21 treatment-resistant schizophrenia patients) and 69 age- and gender-matched healthy controls. Imaging data was preprocessed via FSL software, then diffusion parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were extracted. Besides, structural network matrix was constructed based on deterministic fiber tracking. The differences of diffusion parameters and topology attributes between three groups were analyzed using analysis of variance (ANOVA). Compared with healthy controls, treatment-responsive schizophrenia showed altered white matter mainly in anterior thalamus radiation, splenium of corpus callosum, cingulum bundle as well as superior longitudinal fasciculus. While treatment-resistant schizophrenia patients showed white matter abnormalities in anterior thalamus radiation, cingulum bundle, fornix and pontine crossing tract relative to healthy controls. Treatment-resistant schizophrenia showed more severe white matter abnormalities in anterior thalamus radiation compared with treatment-responsive patients. There was no significant difference in white matter network topological attributes among the three groups. The performance of support vector machine (SVM) showed accuracy of 63.37% in separating the two patient subgroups ( P = 0.04). In this study, we showed different patterns of white matter alterations in treatment-responsive and treatment-resistant schizophrenia compared with healthy controls before treatment, which may help guiding patient identification, targeted treatment and prognosis improvement at baseline drug-naïve state.

Characteristics of gray matter alterations in never-treated and treated chronic schizophrenia patients.

Though gray matter deficits have been consistently revealed in chronic treated schizophrenia, it is still not clear whether there are different brain alterations between chronic never treated and treated patients. To explore the different patterns of gray matter alterations among chronic never treated patients and those treated with monotherapy, we recruited 35 never-treated chronic schizophrenia patients with illness durations ranging from 5 to 48 years, 20 illness duration-matched risperidone monotherapy and 20 clozapine monotherapy patients, and 55 healthy controls. GM (surface area, cortical thickness, and cortical volume) measures were extracted and compared using ANCOVA across the four groups followed by post hoc tests. Relative to controls, both treated and never-treated chronic schizophrenia patients showed reduced GM mainly involving the bilateral medial and rostral middle frontal, left banks superior temporal sulcus, left fusiform, and left pericalcarine cortex and increased in the left cuneus. Compared with the untreated patient group, the two treated groups showed reductions mainly in the bilateral prefrontal, temporal, and left inferior parietal lobules. The clozapine monotherapy patients demonstrated more severe decreases in the bilateral prefrontal cortex and left cuneus and less severe decreases in the left ventral temporal lobe than risperidone monotherapy patients. These findings provide new insights into the long-term effects of antipsychotic treatment on gray matter alterations in schizophrenia patients. Furthermore, the characteristic findings of reductions in the inferior parietal lobule might be specific for long-term antipsychotic treatment, which could be a possible target for medication development in the future.

Changes of Brain Structure in Patients With Metastatic Non-Small Cell Lung Cancer After Long-Term Target Therapy With EGFR-TKI.

PURPOSE: Epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) therapy is the routine treatment for patients with metastatic non-small cell lung cancer (NSCLC) harboring positive EGFR mutations. Patients who undergo such treatment have reported cognitive decline during follow-up. This study, therefore, aimed to evaluate brain structural changes in patients receiving EGFR-TKI to increase understanding of this potential symptom. METHOD: The medical records of 75 patients with metastatic NSCLC (without brain metastasis or other co-morbidities) who received EGFR-TKI therapy from 2010 to 2017 were reviewed. The modified Scheltens Visual Scale and voxel-based morphometry were used to evaluate changes in white matter lesions (WML) and gray matter volume (GMV), respectively. RESULTS: The WML scores were higher at the 12-month [8.65 ± 3.86; 95% confidence interval (CI), 1.60-2.35; p < 0.001] and 24-month follow-ups (10.11 ± 3.85; 95% CI, 2.98-3.87; p < 0.001) compared to baseline (6.68 ± 3.64). At the 24-month follow-up, the visual scores were also significantly higher in younger patients (3.89 ± 2.04) than in older patients (3.00 ± 1.78; p = 0.047) and higher in female patients (3.80 ± 2.04) than in male patients (2.73 ± 1.56; p = 0.023). Additionally, significant GMV loss was observed in sub-regions of the right occipital lobe (76.71 voxels; 95% CI, 40.740-112.69 voxels), left occipital lobe (93.48 voxels; 95% CI, 37.48-149.47 voxels), and left basal ganglia (37.57 voxels; 95% CI, 21.58-53.57 voxels) (all p < 0.005; cluster-level false discovery rate < 0.05). CONCLUSIONS: An increase in WMLs and loss of GMV were observed in patients with metastatic NSCLC undergoing long-term EGFR-TKI treatment. This might reflect an unknown side-effect of EGFR-TKI treatment. Further prospective studies are necessary to confirm our findings.

Evaluating the Prognosis of Ischemic Stroke Using Low-Dose Multimodal Computed Tomography Parameters in Hyperacute Phase.

PURPOSE: The aim of this study was to evaluate the potential value of low-dose multimodal computed tomography (CT) in predicting prognosis of acute ischemic stroke (AIS) within 6 hours. METHODS: The admission "one-stop-shop" multimodal CT examination, including noncontrast CT (NCCT), low-dose CT perfusion, and CT angiography (CTA), was performed in patients with symptoms of stroke within 6 hours. Noncontrast CT, CTA source image (CTA-SI), cerebral blood flow (CBF), cerebral blood volume (CBV), time to peak (TTP), and mean transit time (MTT) maps were studied using Alberta Stroke Program Early CT Score (ASPECTS). The regional leptomeningeal collateral (rLMC) score (0-20) was dichotomized into 2 groups: good (11-20) and poor (0-10) rLMC. Poor functional outcomes were defined by a modified Rankin scale score of 3 to 6. RESULTS: One hundred forty-four patients were ultimately selected; 43.8% of them showed poor functional outcomes. They had lower ASPECTSs on NCCT, CTA-SI, CBV, CBF, TTP, and MTT, and poor rLMC was more frequently associated with poor functional outcomes (all P < 0.001). In the multivariate analysis for AIS patients with conservative treatment, CTA-SI-ASPECTS 6 or less (odds ratio [OR], 5.9; 95% confidence interval [95% CI], 1.9-18.4; P = 0.002) and poor collaterals (OR, 5.0; 95% CI, 1.3-15.4; P = 0.017), CBV-ASPECTS 6 or less (OR, 8.0; 95% CI, 2.7-24.0; P < 0.001), CBF-ASPECTS 4 or less (OR, 8.0; 95% CI, 2.0-31.5; P = 0.003), MTT-ASPECTS≤3 (OR, 5.8; 95% CI, 1.8-18.1; P = 0.003), TTP-ASPECTS 4 or less (OR, 5.0; 95% CI, 1.6-15.1; P = 0.005), and NCCT-ASPECTS 8 or less (OR, 5.9; 95% CI, 1.7-20.4; P = 0.005) were significantly associated with poor functional outcome. In the multivariate analysis for AIS patients with thrombolysis, CTA-SI-ASPECTS 6 or less (OR, 27.5; 95% CI, 2.9-262.3; P = 0.004), poor collaterals (OR, 28.0; 95% CI, 2.8-283.0; P < 0.028), and CBV-ASPECTS 6 or less (OR, 18.0; 95% CI, 3.0-107.7; P = 0.002) were associated with poor functional outcomes. Furthermore, the area under the curve (AUC) of the combination of CTA-SI-ASPECTS 6 or less, poor collaterals, and CBV-ASPECTS 6 or less (AUC, 0.87) was greater than that for any single parameter alone: CTA-SI-ASPECTS 6 or less (AUC, 0.80; P < 0.001), poor collaterals (AUC, 0.76; P < 0.001), and CBV-ASPECTS 6 or less (AUC, 0.81; P = 0.002). CONCLUSIONS: The combination of CTA-SI-ASPECTS, collaterals, and CBV-ASPECTS may improve predictive power compared with a single parameter alone.