Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder

Assessing changes in brain structure in new-onset children with acute lymphoblastic leukemia

BACKGROUND

Brain structure injury was presented in acute lymphoblastic leukemia (ALL) after treatment; however, its alterations in new-onset stage are still unclear. We aim to explore white matter (WM) and grey matter (GM) alterations using surface-based morphometry (SBM) and tract-based spatial statistics (TBSS) in new-onset pediatric ALL.

METHODS

Thirty-five ALL and 33 typically developing (TD) children were prospectively recruited and underwent three-dimensional T1-weighted and diffusion tensor (DTI) imaging. DTI metrics, cortical GM features, and deep GM nuclei volume were compared between groups differences.

RESULTS

In ALL, the only increased FA in the body of corpus callosum (PFWE-corrected = 0.023) and left superior corona radiata (PFWE-corrected = 0.045) were presented. Relative to TDs, pediatric ALL presented a significant decrease in cortical surface area (CSA), thickness (CT), and volume in orbital gyri, supramarginal gyrus, middle temporal gyrus, and superior temporal gyrus (all CWP = 0.01). Additionally, increased CT and CSA were found in lingual gyrus and left sulcus intermedius primus, respectively (all CWP = 0.01). Smaller volumes in pediatric ALL were observed in bilateral thalamus, caudate, hippocampus, and right putamen (PFDR-corrected < 0.05).

CONCLUSION

Widespread brain structural abnormalities were found in new-onset pediatric ALL, which suggest disease itself can cause brain structural injury.

IMPACT

This study revealed the altered white matter integrity and gray matter morphology characteristics in childhood acute lymphoblastic leukemia on new-onset stage. It is suggested that there may be structural impairment before chemotherapy. MRI is a sensitive way for early detection on brain structural damage in childhood acute lymphoblastic leukemia.

The Modern Concept of Schizoaffective Disorder: A Narrative Review

BACKGROUND

Schizoaffective disorder (SAD) is one of the most complex and controversial diagnoses in clinical psychiatry. Despite the significant changes that have occurred in the conceptualization of SAD in modern classifications and the publications of recent years, many unresolved issues remain regarding the disease, from the point of view of clinical psychiatry and basic neuroscience.

AIM

The purpose of this paper is to summarize published data on the concept of SAD, its clinical characteristics, cognitive profile, potential biomarkers, as well as the place of the disease in the following modern international classifications: the International Classification of Diseases (ICD) 9th, 10th and 11th revisions, and the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5).

METHODS

We undertook a review of the scientific studies in the relevant bibliographic systems and databases (eLIBRARY, PubMed) of the past 15 years. The descriptive analysis method was used to summarize the collected information. A total of 70 publications were selected for review, including different versions of international classifications of diseases (ICD and DSM-5).

RESULTS

There has been some improvement in the inter-rater reliability of SAD criteria in modern classifications, but this has not yet led to a clearer understanding among mental health specialists, while the various subtypes of SAD identified so far fail to account for the heterogeneity in the clinical presentation of the disorder. The dimensional approach to diagnosing SAD, according to which the intensity of psychotic and affective symptoms can fluctuate over time and they can influence one another, more accurately reflects the disease's ability to embody different forms. Basic research does not support the identification of a distinct cognitive, neuroimaging, or immunological SAD endophenotype that differs qualitatively from schizophrenia and affective psychoses.

CONCLUSION

The conceptualization of SAD remains incomplete, and new approaches rooted in neuroscience are needed to better understand the coexistence of affective and psychotic symptoms.

Psychosis superspectrum II: neurobiology, treatment, and implications

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.

Gray matter atrophy and white matter lesions burden in delayed cognitive decline following carbon monoxide poisoning

Gray matter (GM) atrophy and white matter (WM) lesions may contribute to cognitive decline in patients with delayed neurological sequelae (DNS) after carbon monoxide (CO) poisoning. However, there is currently a lack of evidence supporting this relationship. This study aimed to investigate the volume of GM, cortical thickness, and burden of WM lesions in 33 DNS patients with dementia, 24 DNS patients with mild cognitive impairment, and 51 healthy controls. Various methods, including voxel-based, deformation-based, surface-based, and atlas-based analyses, were used to examine GM structures. Furthermore, we explored the connection between GM volume changes, WM lesions burden, and cognitive decline. Compared to the healthy controls, both patient groups exhibited widespread GM atrophy in the cerebral cortices (for volume and cortical thickness), subcortical nuclei (for volume), and cerebellum (for volume) (p < .05 corrected for false discovery rate [FDR]). The total volume of GM atrophy in 31 subregions, which included the default mode network (DMN), visual network (VN), and cerebellar network (CN) (p < .05, FDR-corrected), independently contributed to the severity of cognitive impairment (p < .05). Additionally, WM lesions impacted cognitive decline through both direct and indirect effects, with the latter mediated by volume reduction in 16 subregions of cognitive networks (p < .05). These preliminary findings suggested that both GM atrophy and WM lesions were involved in cognitive decline in DNS patients following CO poisoning. Moreover, the reduction in the volume of DMN, VN, and posterior CN nodes mediated the WM lesions-induced cognitive decline.

Cortical and subcortical grey matter correlates of psychopathic traits in a Japanese community sample of young adults: sex and configurations of factors' level matter!

While neuroimaging research has examined the structural brain correlates of psychopathy predominantly in clinical/forensic male samples from western countries, much less is known about those correlates in non-western community samples. Here, structural magnetic resonance imaging data were analyzed using voxel- and surface-based morphometry to investigate the neuroanatomical correlates of psychopathic traits in a mixed-sex sample of 97 well-functioning Japanese adults (45 males, 21-39 years; M = 27, SD = 5.3). Psychopathic traits were assessed using the Self-Report Psychopathy Scale (SRP-SF; 4th Edition). Multiple regression analysis showed greater Factor 1 scores were associated with higher gyrification in the lingual gyrus, and gray matter volume in the anterior cingulate cortex and amygdala/hippocampus border. Total psychopathy and Factor 1 scores interacted with sex to, respectively, predict cortical thickness in the precuneus and gyrification in the superior temporal gyrus. Finally, Factor 1 and Factor 2 traits interacted to predict gyrification in the posterior cingulate cortex. These preliminary data suggest that, while there may be commonalities in the loci of structural brain correlates of psychopathic traits in clinical/forensic and community samples, the nature of that association might be different (i.e. positive) and may vary according to sex and configurations of factors' level.

Cortical Thickness Abnormalities at Different Stages of the Illness Course in Schizophrenia: A Systematic Review and Meta-analysis

Importance

Questions of whether and how cortical thickness (CTh) alterations differ over the course of schizophrenia (SCZ) have yet to be resolved.

Objective

To characterize CTh alterations across illness stages in SCZ.

Data Sources

PubMed, Embase, Web of Science, and Science Direct were screened for CTh studies published before June 15, 2021.

Study Selection

Original studies comparing whole-brain CTh alterations from healthy controls in individuals at clinical high-risk (CHR), first episode of psychosis (FEP), and long-term illness stages of SCZ were included.

Data Extraction and Synthesis

This preregistered systematic review and meta-analysis followed PRISMA reporting guidelines. Separate and pooled meta-analyses were performed using seed-based d mapping. Meta-regression analyses were conducted.

Main Outcomes and Measures

Cortical thickness differences from healthy control individuals across illness stages.

Results

Ten studies comprising 859 individuals with CHR (mean [SD] age, 21.02 [2.66] years; male, 573 [66.7%]), 12 studies including 671 individuals with FEP (mean [SD] age, 22.87 [3.99] years; male, 439 [65.4%]), and 10 studies comprising 579 individuals with long-term SCZ (mean [SD] age, 41.58 [6.95] years; male, 396 [68.4%]) were included. Compared with healthy control individuals, individuals with CHR showed cortical thinning in bilateral medial prefrontal cortex (z = -1.01; P < .001). Individuals with FEP showed cortical thinning in right lateral superior temporal cortex (z = -1.34; P < .001), right anterior cingulate cortex (z = -1.44; P < .001), and right insula (z = -1.14; P = .002). Individuals with long-term SCZ demonstrated CTh reductions in right insula (z = -3.25; P < .001), right inferior frontal cortex (z = -2.19; P < .001), and left (z = -2.37; P < .001) and right (z = -1.94; P = .002) temporal pole. There were no significant CTh differences between CHR and FEP. Individuals with long-term SCZ showed greater cortical thinning in right insula (z = -2.58; P < .001), right inferior frontal cortex (z = -2.32; P < .001), left lateral temporal cortex (z = -1.91; P = .002), and right temporal pole (z = -1.82; P = .002) than individuals with FEP. Combining all studies on SCZ, accelerated age-related CTh reductions were found in bilateral lateral middle temporal cortex and right pars orbitalis in inferior frontal cortex.

Conclusions and Relevance

The absence of significant differences between FEP and CHR noted in this systematic review and meta-analysis suggests that the onset of psychosis was not associated with robust CTh reduction. The greater cortical thinning in long-term SCZ compared with FEP with accelerated age-related reduction in CTh suggests progressive neuroanatomic alterations following illness onset. Caution in interpretation is needed because heterogeneity in samples and antipsychotic treatment may confound these results.

Structural abnormality in schizophrenia versus bipolar disorder: A whole brain cortical thickness, surface area, volume and gyrification analyses

OBJECTIVES

The profiles of cortical abnormalities in schizophrenia and bipolar disorder, and how far they resemble each other, have only been studied to a limited extent. The aim of this study was to identify and compare the changes in cortical morphology associated with these pathologies.

METHODS

A total of 384 subjects, including 128 patients with schizophrenia, 128 patients with bipolar disorder and 127 sex-age-matched healthy subjects, were examined using cortical surface-based morphology. Four cortical structural measures were studied: cortical volume (CV), cortical thickness (CT), surface area (SA) and gyrification index (GI). Group comparisons for each separate cortical measure were conducted.

RESULTS

At a threshold of P = 0.05 corrected, both patient groups showed significant widespread CV and CT reductions in similar areas compared to healthy subjects. However, the changes in schizophrenia were more pronounced. While CV decrease in bipolar disorder was exclusively explained by cortical thinning, in schizophrenia it was driven by changes in CT and partially by SA. Reduced GI was only found in schizophrenia. The direct comparison between both disorders showed significant reductions in all measures in patients with schizophrenia.

CONCLUSIONS

Cortical volume and cortical thickness deficits are shared between patients with schizophrenia and bipolar disorder, suggesting that both pathologies may be affected by similar environmental and neurodegenerative factors. However, the exclusive alteration in schizophrenia of metrics related to the geometry and curvature of the brain cortical surface (SA, GI) suggests that this group is influenced by additional neurodevelopmental and genetic factors.

Effective connectivity within a triple network brain system discriminates schizophrenia spectrum disorders from psychotic bipolar disorder at the single-subject level

OBJECTIVE

Schizophrenia spectrum disorders (SSD) and psychotic bipolar disorder share a number of genetic and neurobiological features, despite a divergence in clinical course and outcome trajectories. We studied the diagnostic classification potential that can be achieved on the basis of the structure and connectivity within a triple network system (the default mode, salience and central executive network) in patients with SSD and psychotic bipolar disorder.

METHODS

Directed static connectivity and its dynamic variance was estimated among 8 nodes of the three large-scale networks. Multivariate autoregressive models of deconvolved resting state functional magnetic resonance imaging time series were obtained from 57 patients (38 with SSD and 19 with bipolar disorder and psychosis). We used 2/3 of the patients for training and validation of the classifier and the remaining 1/3 as an independent hold-out test data for performance estimation.

RESULTS

A high level of discrimination between bipolar disorder with psychosis and SSD (combined balanced accuracy = 96.2%; class accuracies 100% for bipolar and 92.3% for SSD) was achieved when effective connectivity and morphometry of the triple network nodes was combined with symptom scores. Patients with SSD were discriminated from patients with bipolar disorder and psychosis as showing higher clinical severity of disorganization and higher variability in the effective connectivity between salience and executive networks.

CONCLUSIONS

Our results support the view that the study of network-level connectivity patterns can not only clarify the pathophysiology of SSD but also provide a measure of excellent clinical utility to identify discrete diagnostic/prognostic groups among individuals with psychosis.

Geometric Convolutional Neural Network for Analyzing Surface-Based Neuroimaging Data

In machine learning, one of the most popular deep learning methods is the convolutional neural network (CNN), which utilizes shared local filters and hierarchical information processing analogous to the brain’s visual system. Despite its popularity in recognizing two-dimensional (2D) images, the conventional CNN is not directly applicable to semi-regular geometric mesh surfaces, on which the cerebral cortex is often represented. In order to apply the CNN to surface-based brain research, we propose a geometric CNN (gCNN) that deals with data representation on a mesh surface and renders pattern recognition in a multi-shell mesh structure. To make it compatible with the conventional CNN toolbox, the gCNN includes data sampling over the surface, and a data reshaping method for the convolution and pooling layers. We evaluated the performance of the gCNN in sex classification using cortical thickness maps of both hemispheres from the Human Connectome Project (HCP). The classification accuracy of the gCNN was significantly higher than those of a support vector machine (SVM) and a 2D CNN for thickness maps generated by a map projection. The gCNN also demonstrated position invariance of local features, which rendered reuse of its pre-trained model for applications other than that for which the model was trained without significant distortion in the final outcome. The superior performance of the gCNN is attributable to CNN properties stemming from its brain-like architecture, and its surface-based representation of cortical information. The gCNN provides much-needed access to surface-based machine learning, which can be used in both scientific investigations and clinical applications.

Identifying dynamic functional connectivity biomarkers using GIG-ICA: Application to schizophrenia, schizoaffective disorder, and psychotic bipolar disorder

Functional magnetic resonance imaging (fMRI) studies have shown altered brain dynamic functional connectivity (DFC) in mental disorders. Here, we aim to explore DFC across a spectrum of symptomatically-related disorders including bipolar disorder with psychosis (BPP), schizoaffective disorder (SAD), and schizophrenia (SZ). We introduce a group information guided independent component analysis procedure to estimate both group-level and subject-specific connectivity states from DFC. Using resting-state fMRI data of 238 healthy controls (HCs), 140 BPP, 132 SAD, and 113 SZ patients, we identified measures differentiating groups from the whole-brain DFC and traditional static functional connectivity (SFC), separately. Results show that DFC provided more informative measures than SFC. Diagnosis-related connectivity states were evident using DFC analysis. For the dominant state consistent across groups, we found 22 instances of hypoconnectivity (with decreasing trends from HC to BPP to SAD to SZ) mainly involving post-central, frontal, and cerebellar cortices as well as 34 examples of hyperconnectivity (with increasing trends HC through SZ) primarily involving thalamus and temporal cortices. Hypoconnectivities/hyperconnectivities also showed negative/positive correlations, respectively, with clinical symptom scores. Specifically, hypoconnectivities linking postcentral and frontal gyri were significantly negatively correlated with the PANSS positive/negative scores. For frontal connectivities, BPP resembled HC while SAD and SZ were more similar. Three connectivities involving the left cerebellar crus differentiated SZ from other groups and one connection linking frontal and fusiform cortices showed a SAD-unique change. In summary, our method is promising for assessing DFC and may yield imaging biomarkers for quantifying the dimension of psychosis. Hum Brain Mapp 38:2683-2708, 2017. © 2017 Wiley Periodicals, Inc.