Diffusion kurtosis imaging of gray matter in schizophrenia

End-stage renal disease accompanied by mild cognitive impairment: A study and analysis of trimodal brain network fusion

The function and structure of brain networks (BN) may undergo changes in patients with end-stage renal disease (ESRD), particularly in those accompanied by mild cognitive impairment (ESRDaMCI). Many existing methods for fusing BN focus on extracting interaction features between pairs of network nodes from each mode and combining them. This approach overlooks the correlation between different modal features during feature extraction and the potentially valuable information that may exist between more than two brain regions. To address this issue, we propose a model using a multi-head self-attention mechanism to fuse brain functional networks, white matter structural networks, and gray matter structural networks, which results in the construction of brain fusion networks (FBN). Initially, three networks are constructed: the brain function network, the white matter structure network, and the individual-based gray matter structure network. The multi-head self-attention mechanism is then applied to fuse the three types of networks, generating attention weights that are transformed into an optimized model. The optimized model introduces hypergraph popular regular term and L1 norm regular term, leading to the formation of FBN. Finally, FBN is employed in the diagnosis and prediction of ESRDaMCI to evaluate its classification performance and investigate the correlation between discriminative brain regions and cognitive dysfunction. Experimental results demonstrate that the optimal classification accuracy achieved is 92.80%, which is at least 3.63% higher than the accuracy attained using other methods. This outcome confirms the effectiveness of our proposed method. Additionally, the identification of brain regions significantly associated with scores on the Montreal cognitive assessment scale may shed light on the underlying pathogenesis of ESRDaMCI.

Common Relationship Between Causality Orientation and the Prefrontal Region in Psychiatric Disorders as Revealed by Diffusional Kurtosis Imaging

Background Motivation dysregulation is common in several psychiatric disorders. However, little is known about the relationships between motivation and the regional brain areas involved. We evaluated the relationships between brain microstructural features and causality orientation in patients with schizophrenia, major depressive disorder (MDD), and bipolar disorder (BD) using diffusional kurtosis imaging (DKI) techniques. Methods Forty patients with MDD, 36 with BD, and 30 with schizophrenia underwent DKI and assessment using the General Causality Orientation Scale (GCOS). We analyzed the DKI index and the GCOS subscales. Results The psychiatric patients showed significant positive correlations between the GCOS-autonomy orientation score and the mean kurtosis (MK) values in the prefrontal regions, orbitofrontal regions, and posterior cingulate cortex. When the analyses were performed separately by disease and gender, a positive correlation was found between the GCOS-autonomy orientation score and the MK values in the left prefrontal regions transdiagnostically, especially among female patients with MDD, BD, and schizophrenia. Conclusions A similar association between intrinsic motivation and MK value in the left prefrontal cortex was suggested in patients with schizophrenia, MDD, and BD. The commonality of this association among these disorders might lead to the discovery of a new biomarker for psychiatric clinical research.

MR imaging and outcome in neonatal HIBD models are correlated with sex: the value of diffusion tensor MR imaging and diffusion kurtosis MR imaging

Objective

Hypoxic-ischemic encephalopathy can lead to lifelong morbidity and premature death in full-term newborns. Here, we aimed to determine the efficacy of diffusion kurtosis (DK) [mean kurtosis (MK)] and diffusion tensor (DT) [fractional anisotropy (FA), mean diffusion (MD), axial diffusion (AD), and radial diffusion (RD)] parameters for the early diagnosis of early brain histopathological changes and the prediction of neurodegenerative events in a full-term neonatal hypoxic-ischemic brain injury (HIBD) rat model.

Methods

The HIBD model was generated in postnatal day 7 Sprague-Dawley rats to assess the changes in DK and DT parameters in 10 specific brain structural regions involving the gray matter, white matter, and limbic system during acute (12 h) and subacute (3 d and 5 d) phases after hypoxic ischemia (HI), which were validated against histology. Sensory and cognitive parameters were assessed by the open field, novel object recognition, elevated plus maze, and CatWalk tests.

Results

Repeated-measures ANOVA revealed that specific brain structures showed similar trends to the lesion, and the temporal pattern of MK was substantially more varied than DT parameters, particularly in the deep gray matter. The change rate of MK in the acute phase (12 h) was significantly higher than that of DT parameters. We noted a delayed pseudo-normalization for MK. Additionally, MD, AD, and RD showed more pronounced differences between males and females after HI compared to MK, which was confirmed in behavioral tests. HI females exhibited anxiolytic hyperactivity-like baseline behavior, while the memory ability of HI males was affected in the novel object recognition test. CatWalk assessments revealed chronic deficits in limb gait parameters, particularly the left front paw and right hind paw, as well as poorer performance in HI males than HI females.

Conclusions

Our results suggested that DK and DT parameters were complementary in the immature brain and provided great value in assessing early tissue microstructural changes and predicting long-term neurobehavioral deficits, highlighting their ability to detect both acute and long-term changes. Thus, the various diffusion coefficient parameters estimated by the DKI model are powerful tools for early HIBD diagnosis and prognosis assessment, thus providing an experimental and theoretical basis for clinical treatment.

The contribution of the cingulate cortex: treating depressive symptoms in first-episode drug naïve schizophrenia

Background

Our previous study has shown the cingulate cortex abnormalities in first-episode drug naïve (FEDN) schizophrenia patients with comorbid depressive symptoms. However, it remains largely unknown whether antipsychotics may induce morphometric change in cingulate cortex and its relationship with depressive symptoms. The purpose of this study was to further clarify the important role of cingulate cortex in the treatment on depressive symptoms in FEDN schizophrenia patients.

Method

In this study, 42 FEDN schizophrenia patients were assigned into depressed patients group (DP, n = 24) and non-depressed patients group (NDP, n = 18) measured by the 24-item Hamilton Depression Rating Scale (HAMD). Clinical assessments and anatomical images were obtained from all patients before and after 12-week treatment with risperidone.

Results

Although risperidone alleviated psychotic symptoms in all patients, depressive symptoms were decreased only in DP. Significant group by time interaction effects were found in the right rostral anterior cingulate cortex (rACC) and other subcortical regions in the left hemisphere. After risperidone treatment, the right rACC were increased in DP. Further, the increasing volume of right rACC was negatively associated with improvement in depressive symptoms.

Conclusion

These findings suggested that the abnormality of the rACC is the typical characteristics in schizophrenia with depressive symptoms. It's likely key region contributing to the neural mechanisms underlying the effects of risperidone treatment on depressive symptoms in schizophrenia.

Aberrant brain gray matter and functional networks topology in end stage renal disease patients undergoing maintenance hemodialysis with cognitive impairment

Purpose

To characterize the topological properties of gray matter (GM) and functional networks in end-stage renal disease (ESRD) patients undergoing maintenance hemodialysis to provide insights into the underlying mechanisms of cognitive impairment.

Materials and methods

In total, 45 patients and 37 healthy controls were prospectively enrolled in this study. All subjects completed resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion kurtosis imaging (DKI) examinations and a Montreal cognitive assessment scale (MoCA) test. Differences in the properties of GM and functional networks were analyzed, and the relationship between brain properties and MoCA scores was assessed. Cognitive function was predicted based on functional networks by applying the least squares support vector regression machine (LSSVRM) and the whale optimization algorithm (WOA).

Results

We observed disrupted topological organizations of both functional and GM networks in ESRD patients, as indicated by significantly decreased global measures. Specifically, ESRD patients had impaired nodal efficiency and degree centrality, predominantly within the default mode network, limbic system, frontal lobe, temporal lobe, and occipital lobe. Interestingly, the involved regions were distributed laterally. Furthermore, the MoCA scores significantly correlated with decreased standardized clustering coefficient (γ), standardized characteristic path length (λ), and nodal efficiency of the right insula and the right superior temporal gyrus. Finally, optimized LSSVRM could predict the cognitive scores of ESRD patients with great accuracy.

Conclusion

Disruption of brain networks may account for the progression of cognitive dysfunction in ESRD patients. Implementation of prediction models based on neuroimaging metrics may provide more objective information to promote early diagnosis and intervention.

Decoding transcriptional signatures of the association between free water and macroscale organizations in healthy adolescents

We leveraged a novel index of diffusion MRI to investigate the relationships among cortical free water, macro-organizations and gene expression in healthy adults. Few research has been conducted to investigate the role of free water in the healthy adults due to it can easily be affected also by aging diseases. High quality data of 350 subjects from Human Connectome Project were used in our study. Cortical free water was estimated by using a bi-tensor model. The free water was high in the limbic, insular and somatosensory cortex, while being lower in motor and association cortex. The negative correlation between the free water and cortical thickness has been consistently identified in almost all the cortical regions. Negative correlation between the cortical free water and structural covariance (rho=-0.38, p_spin=0.005) revealed the free water was sensitive to cortical heterogeneity. Using human gene expression dataset, we found the gene expression pattern of the relationship between the free water and cortical thickness spatially coupled with primary gradient of structural covariance network (rho=0.40, p_spin=0.004). Our findings indicated the free water was sensitive to the cortical cellular status. The relationship between free water and macroscale organization also reflected hierarchal structures of cerebral cortex.

Transdiagnostic In Vivo Magnetic Resonance Imaging Markers of Neuroinflammation

Accumulating evidence suggests that inflammation is not limited to archetypal inflammatory diseases such as multiple sclerosis, but instead represents an intrinsic feature of many psychiatric and neurological disorders not typically classified as neuroinflammatory. A growing body of research suggests that neuroinflammation can be observed in early and prodromal stages of these disorders and, under certain circumstances, may lead to tissue damage. Traditional methods to assess neuroinflammation include serum or cerebrospinal fluid markers and positron emission tomography. These methods require invasive procedures or radiation exposure and lack the exquisite spatial resolution of magnetic resonance imaging (MRI). There is, therefore, an increasing interest in noninvasive neuroimaging tools to evaluate neuroinflammation reliably and with high specificity. While MRI does not provide information at a cellular level, it facilitates the characterization of several biophysical tissue properties that are closely linked to neuroinflammatory processes. The purpose of this review is to evaluate the potential of MRI as a noninvasive, accessible, and cost-effective technology to image neuroinflammation across neurological and psychiatric disorders. We provide an overview of current and developing MRI methods used to study different aspects of neuroinflammation and weigh their strengths and shortcomings. Novel MRI contrast agents are increasingly able to target inflammatory processes directly, therefore offering a high degree of specificity, particularly if used in conjunction with multitissue, biophysical diffusion MRI compartment models. The capability of these methods to characterize several aspects of the neuroinflammatory milieu will likely push MRI to the forefront of neuroimaging modalities used to characterize neuroinflammation transdiagnostically.

Altered Cerebral Microstructure in Adults With Atrial Septal Defect and Ventricular Septal Defect Repaired in Childhood

Background

Delayed brain development, brain injury, and neurodevelopmental disabilities are commonly observed in infants operated for complex congenital heart defect. Our previous findings of poorer neurodevelopmental outcomes in individuals operated for simple congenital heart defects calls for further etiological clarification. Hence, we examined the microstructural tissue composition in cerebral cortex and subcortical structures in comparison to healthy controls and whether differences were associated with neurodevelopmental outcomes.

Methods and Results

Adults (n=62) who underwent surgical closure of an atrial septal defect (n=33) or a ventricular septal defect (n=29) in childhood and a group of healthy, matched controls (n=38) were enrolled. Brain diffusional kurtosis imaging and neuropsychological assessment were performed. Cortical and subcortical tissue microstructure were assessed using mean kurtosis tensor and mean diffusivity and compared between groups and tested for associations with neuropsychological outcomes. Alterations in microstructural tissue composition were found in the parietal, temporal, and occipital lobes in the congenital heart defects, with distinct mean kurtosis tensor cluster‐specific changes in the right visual cortex (pericalcarine gyrus, P=0.002; occipital part of fusiform and lingual gyri, P=0.019). Altered microstructural tissue composition in the subcortical structures was uncovered in atrial septal defects but not in ventricular septal defects. Associations were found between altered cerebral microstructure and social recognition and executive function.

Conclusions

Children operated for simple congenital heart defects demonstrated altered microstructural tissue composition in the cerebral cortex and subcortical structures during adulthood when compared with healthy peers. Alterations in cerebral microstructural tissue composition were associated with poorer neuropsychological performance.

Registration

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03871881.

Multimodal Magnetic Resonance Imaging Reveals Aberrant Brain Age Trajectory During Youth in Schizophrenia Patients

Accelerated brain aging had been widely reported in patients with schizophrenia (SZ). However, brain aging trajectories in SZ patients have not been well-documented using three-modal magnetic resonance imaging (MRI) data. In this study, 138 schizophrenia patients and 205 normal controls aged 20–60 were included and multimodal MRI data were acquired for each individual, including structural MRI, resting state-functional MRI and diffusion tensor imaging. The brain age of each participant was estimated by features extracted from multimodal MRI data using linear multiple regression. The correlation between the brain age gap and chronological age in SZ patients was best fitted by a positive quadratic curve with a peak chronological age of 47.33 years. We used the peak to divide the subjects into a youth group and a middle age group. In the normal controls, brain age matched chronological age well for both the youth and middle age groups, but this was not the case for schizophrenia patients. More importantly, schizophrenia patients exhibited increased brain age in the youth group but not in the middle age group. In this study, we aimed to investigate brain aging trajectories in SZ patients using multimodal MRI data and revealed an aberrant brain age trajectory in young schizophrenia patients, providing new insights into the pathophysiological mechanisms of schizophrenia.

Altered Microstructure of Cerebral Gray Matter in Neuromyelitis Optica Spectrum Disorder-Optic Neuritis: A DKI Study

The purpose of this study was to analyze microstructural alterations in cerebral gray matter using non-Gaussian diffusion kurtosis imaging (DKI) in neuromyelitis optica spectrum disorder (NMOSD) patients with optic neuritis (NMOSD-ON). DKI was performed in 14 NMOSD-ON patients and 22 normal controls (NCs). DKI-derived metrics, including mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK), fractional anisotropy (FA), and mean diffusivity (MD), were voxel-wisely compared by two-sample t-tests with gaussian random field (GRF) correction between the two groups. The correlations between altered DKI metrics and clinical features were analyzed. Compared with NCs, NMOSD-ON patients showed significantly decreased MK and RK both in the left inferior temporal gyrus (ITG), and decreased AK in the bilateral calcarine (CAL). While increased MD in the left fusiform gyrus (FFG), right CAL, and right hippocampus (HIP)/parahippocampal gyrus (PHG) were found. Furthermore, correlation analysis showed that mean deviation was negatively correlated with AK values of bilateral CAL and positively correlated with MD values of right CAL (q < 0.05, false discovery rate (FDR) corrected). For NMOSD-ON patients, microstructural abnormalities in the occipital visual cortex are correlated with clinical disability. These findings may provide complementary information to understand the neuropathological mechanisms underlying the impairments of cerebral gray matter in NMOSD-ON.

Grey and white matter microstructure is associated with polygenic risk for schizophrenia

Recent discovery of approximately 270 common genetic variants associated with schizophrenia has enabled polygenic risk scores (PRS) to be measured in the population. We hypothesized that normal variation in PRS would be associated with magnetic resonance imaging (MRI) phenotypes of brain morphometry and tissue composition. We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (N_max = 29,878) who had multiple micro- and macrostructural MRI metrics measured at each of 180 cortical areas, seven subcortical structures, and 15 major white matter tracts. Linear mixed-effect models were used to investigate associations between PRS and brain structure at global and regional scales, controlled for multiple comparisons. Polygenic risk was significantly associated with reduced neurite density index (NDI) at global brain scale, at 149 cortical regions, five subcortical structures, and 14 white matter tracts. Other microstructural parameters, e.g., fractional anisotropy, that were correlated with NDI were also significantly associated with PRS. Genetic effects on multiple MRI phenotypes were co-located in temporal, cingulate, and prefrontal cortical areas, insula, and hippocampus. Post-hoc bidirectional Mendelian randomization analyses provided preliminary evidence in support of a causal relationship between (reduced) thalamic NDI and (increased) risk of schizophrenia. Risk-related reduction in NDI is plausibly indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks. Cortical, subcortical, and white matter microstructure may be linked to the genetic mechanisms of schizophrenia.

Brain microstructural abnormalities in 22q11.2 deletion syndrome: A systematic review of diffusion tensor imaging studies

22q11.2 deletion syndrome (22q11DS) is a severe genetic syndrome characterized by cognitive deficits and neuropsychiatric disorders, particularly schizophrenia. Neuroimaging alterations have been extensively reported in 22q11DS, both in gray and white matter structures. However, a considerable variability among the results affects the generalizability of the findings to date. Herein, we reviewed diffusion tensor imaging (DTI) findings in 22q11DS, their association with psychosis and cognition, and the implications of DTI studies on neurodevelopment in 22q11DS. We also investigated differences between 22q11DS and schizophrenic patients without 22q11DS. Using an online search of PubMed and Embase, we identified studies investigating DTI findings in 22q11DS. After selecting eligible studies in accordance with the preferred reporting items for systematic reviews and meta-analyses guideline, we included thirty-one studies. Overall, 22q11DS patients show altered structural connectivity and disrupted microstructural organization of most cortical and subcortical structures and white matter tracts. Moreover, despite a significant heterogeneity in the results, reduced diffusivity measures and elevated fractional anisotropy were observed. However controversial, compared to typically developing children, 22q11DS patients reached the peak of fractional anisotropy (FA) and the trough of radial diffusivity (RD) at an older age, which shows neurodevelopmental delay. DTI measures were also associated with psychotic symptoms and cognitive deficits. In conclusion, this study provides a comprehensive review of microstructural alterations in 22q11DS. Future larger investigations on this syndrome could potentially lead to the detection of early diagnostic imaging markers for genetically induced schizophrenia, thus improving the treatment and, ultimately, the outcome.

Quantitative Macromolecular Proton Fraction Mapping Reveals Altered Cortical Myelin Profile in Schizophrenia Spectrum Disorders

Myelin abnormalities have been reported in schizophrenia spectrum disorders (SSD) in white matter. However, in vivo examinations of cortical myeloarchitecture in SSD, especially those using quantitative measures, are limited. Here, we employed macromolecular proton fraction (MPF) obtained from quantitative magnetization transfer imaging to characterize intracortical myelin organization in 30 SSD patients versus 34 healthy control (HC) participants. We constructed cortical myelin profiles by extracting MPF values at various cortical depths and quantified their shape using a nonlinearity index (NLI). To delineate the association of illness duration with myelin changes, SSD patients were further divided into 3 duration groups. Between-group comparisons revealed reduced NLI in the SSD group with the longest illness duration (>5.5 years) compared with HC predominantly in bilateral prefrontal areas. Within the SSD group, cortical NLI decreased with disease duration and was positively associated with a measure of spatial working memory capacity as well as with cortical thickness (CT). Layer-specific analyses suggested that NLI decreases in the long-duration SSD group may arise in part from significantly increased MPF values in the midcortical layers. The current study reveals cortical myelin profile changes in SSD with illness progression, which may reflect an abnormal compensatory mechanism of the disorder.

MK-Curve improves sensitivity to identify white matter alterations in clinical high risk for psychosis

Diffusion kurtosis imaging (DKI) is a diffusion MRI approach that enables the measurement of brain microstructural properties, reflecting molecular restrictions and tissue heterogeneity. DKI parameters such as mean kurtosis (MK) provide additional subtle information to that provided by popular diffusion tensor imaging (DTI) parameters, and thus have been considered useful to detect white matter abnormalities, especially in populations that are not expected to show severe brain pathologies. However, DKI parameters often yield artifactual output values that are outside of the biologically plausible range, which diminish sensitivity to identify true microstructural changes. Recently we have proposed the mean-kurtosis-curve (MK-Curve) method to correct voxels with implausible DKI parameters, and demonstrated its improved performance against other approaches that correct artifacts in DKI. In this work, we aimed to evaluate the utility of the MK-Curve method to improve the identification of white matter abnormalities in group comparisons. To do so, we compared group differences, with and without the MK-Curve correction, between 115 individuals at clinical high risk for psychosis (CHR) and 93 healthy controls (HCs). We also compared the correlation of the corrected and uncorrected DKI parameters with clinical characteristics. Following the MK-curve correction, the group differences had larger effect sizes and higher statistical significance (i.e., lower p-values), demonstrating increased sensitivity to detect group differences, in particular in MK. Furthermore, the MK-curve-corrected DKI parameters displayed stronger correlations with clinical variables in CHR individuals, demonstrating the clinical relevance of the corrected parameters. Overall, following the MK-curve correction our analyses found widespread lower MK in CHR that overlapped with lower fractional anisotropy (FA), and both measures were significantly correlated with a decline in functioning and with more severe symptoms. These observations further characterize white matter alterations in the CHR stage, demonstrating that MK and FA abnormalities are widespread, and mostly overlap. The improvement in group differences and stronger correlation with clinical variables suggest that applying MK-curve would be beneficial for the detection and characterization of subtle group differences in other experiments as well.

Diffusion kurtosis imaging of gray matter in young adults with autism spectrum disorder

Prior ex vivo histological postmortem studies of autism spectrum disorder (ASD) have shown gray matter microstructural abnormalities, however, in vivo examination of gray matter microstructure in ASD has remained scarce due to the relative lack of non-invasive methods to assess it. The aim of this work was to evaluate the feasibility of employing diffusional kurtosis imaging (DKI) to describe gray matter abnormalities in ASD in vivo. DKI data were examined for 16 male participants with a diagnosis of ASD and IQ>80 and 17 age- and IQ-matched male typically developing (TD) young adults 18-25 years old. Mean (MK), axial (AK), radial (RK) kurtosis and mean diffusivity (MD) metrics were calculated for lobar and sub-lobar regions of interest. Significantly decreased MK, RK, and MD were found in ASD compared to TD participants in the frontal and temporal lobes and several sub-lobar regions previously associated with ASD pathology. In ASD participants, decreased kurtosis in gray matter ROIs correlated with increased repetitive and restricted behaviors and poor social interaction symptoms. Decreased kurtosis in ASD may reflect a pathology associated with a less restrictive microstructural environment such as decreased neuronal density and size, atypically sized cortical columns, or limited dendritic arborizations.