Psychoradiology最新文献

Mental disorders are common health concerns and contribute to a heavy global burden on our modern society. It is challenging to identify and treat them timely. Neuroimaging evidence suggests the incidence of various psychiatric and behavioral disorders is closely related to the atypical development of brain structure and function. The identification and understanding of atypical brain development provide chances for clinicians to detect mental disorders earlier, perhaps even prior to onset, and treat them more precisely. An invaluable and necessary method in identifying and monitoring atypical brain development are growth charts of typically developing individuals in the population. The brain growth charts can offer a series of standard references on typical neurodevelopment, representing an important resource for the scientific and medical communities. In the present paper, we review the relationship between mental disorders and atypical brain development from a perspective of normative brain development by surveying the recent progress in the development of brain growth charts, including four aspects on growth chart utility: 1) cohorts, 2) measures, 3) mechanisms, and 4) clinical translations. In doing so, we seek to clarify the challenges and opportunities in charting brain growth, and to promote the application of brain growth charts in clinical practice.

Background: Distinct neuroanatomic subtypes have been identified in never-treated patients with schizophrenia based on cerebral structural abnormalities, but whether antipsychotic-treated patients would be stratified under the guidance of such previously formed classification remains unclear.

Objective: The present study aimed to investigate alterations of brain structures in antipsychotic-treated patients with schizophrenia based on a predefined morphological classification and their relationships with cognitive performance.

Methods: Cortical thickness, surface area, and subcortical volume were extracted from 147 antipsychotic-treated patients with schizophrenia using structural magnetic resonance imaging for classification. The Brief Assessment of Cognition in Schizophrenia (BACS) and Positive and Negative Syndrome Scale (PANSS) were used to assess cognition and symptoms.

Results: Antipsychotic-treated patients were categorized into three subtypes with distinct patterns of brain morphological alterations. Subtypes 1 and 2 were characterized by widespread deficits in cortical thickness but relatively limited deficits in surface area. In contrast, subtype 3 demonstrated cortical thickening mainly in parietal-occipital regions and widespread deficits in surface area. All three subgroups demonstrated cognitive deficits compared with healthy controls. Significant associations between neuroanatomic and cognitive abnormalities were only observed in subtype 1, where cortical thinning in the left lingual gyrus was conversely related to symbol coding performance.

Conclusions: Similar to drug-naïve patients, neuroanatomic heterogeneity exists in antipsychotic-treated patients, with disparate associations with cognition. These findings promote our understanding of relationships between neuroanatomic abnormalities and cognitive performance in the context of heterogeneity. Moreover, these results suggest that neurobiological heterogeneity needs to be considered in cognitive research in schizophrenia.

The epidemic of coronavirus disease 2019 (COVID-19) has broken the normal spread mode of respiratory viruses, namely, mainly spread in winter, resulting in over 230 million confirmed cases of COVID-19. Many studies have shown that severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) can affect the nervous system by varying degrees. In this review, we look at the acute neuropsychiatric impacts of COVID-19 patients, including acute ischemic stroke, encephalitis, acute necrotizing encephalopathy, dysosmia, and epilepsy, as well as the long-term neuropsychiatric sequelae of COVID-19 survivors: mental disorder and neurodegenerative diseases. In particular, this review discusses long-term changes in brain structure and function associated with COVID-19 infection. We believe that the traditional imaging sequences are important in the acute phase, while the nontraditional imaging sequences are more meaningful for the detection of long-term neuropsychiatric sequelae. These long-term follow-up changes in structure and function may also help us understand the causes of neuropsychiatric symptoms in COVID-19 survivors. Finally, we review previous studies and discuss some potential mechanisms of SARS-CoV-2 infection in the nervous system. Continuous focus on neuropsychiatric sequelae and a comprehensive understanding of the long-term impacts of the virus to the nervous system is significant for formulating effective sequelae prevention and management strategies, and may provide important clues for nervous system damage in future public health crises.

Background: Abnormalities of cortical thickness (CTh) in patients with their first episode psychosis (FEP) have been frequently reported, but findings are inconsistent.

Objective: To define the most consistent CTh changes in patients with FEP by meta-analysis of published whole-brain studies.

Methods: The meta-analysis used seed-based d mapping (SDM) software to obtain the most prominent regional CTh changes in FEP, and meta-regression analyses to explore the effects of demographics and clinical characteristics. The meta-analysis results were verified in an independent sample of 142 FEP patients and 142 age- and sex-matched healthy controls (HCs), using both a vertex-wise and a region of interest analysis, with multiple comparisons correction.

Results: The meta-analysis identified lower CTh in the right middle temporal cortex (MTC) extending to superior temporal cortex (STC), insula, and anterior cingulate cortex (ACC) in FEP compared with HCs. No significant correlations were identified between CTh alterations and demographic or clinical variables. These results were replicated in the independent dataset analysis.

Conclusion: This study identifies a robust pattern of cortical abnormalities in FEP and extends understanding of gray matter abnormalities and pathological mechanisms in FEP.

Functional brain imaging technology has developed rapidly in recent years. On the one hand, high-field 7-Tesla magnetic resonance imaging (MRI) has excelled the limited spatial resolution of 3-Tesla MRI, allowing us to enter a new world of mesoscopic imaging from the macroscopic imaging of human brain functions. On the other hand, novel optical pumping magnetometer-magnetoencephalography (OPM-MEG) has broken down the technical barriers of traditional superconducting MEG, which brings imaging of neuronal electromagnetic signals from cortical imaging to whole-brain imaging. This article aims to present a brief introduction regarding the development of conventional MRI and MEG technology, and, more importantly, to delineate that high-field MRI and OPM-MEG complement each other and together will lead us into a new era of functional brain imaging.

One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness, prediction of prognosis before treatment, and guidance for selection of effective treatments that target patient-relevant pathophysiological features. This is the primary aim of the field of Psychoradiology. Using databases collected from large samples at multiple centers, sophisticated artificial intelligence (AI) algorithms may be used to develop clinically useful image analysis pipelines that can help physicians diagnose, predict, and make treatment decisions. In this review, we selectively summarize psychoradiological research using magnetic resonance imaging of the brain to explore the neural mechanism of psychiatric disorders, and outline progress and the path forward for the combination of psychoradiology and AI for complementing clinical examinations in patients with psychiatric disorders, as well as limitations in the application of AI that should be considered in future translational research.

Background: A long-haul flight across more than five time zones may produce a circadian rhythm sleep disorder known as jet lag. Little is known about the effect of jet lag on white matter (WM) functional connectivity (FC).

Objective: The present study is to investigate changes in WM FC in subjects due to recovery from jet lag after flying across six time zones.

Methods: Here, resting-state functional magnetic resonance imaging was performed in 23 participants within 24 hours of flying and again 50 days later. Gray matter (GM) and WM networks were identified by k-means clustering. WM FC and functional covariance connectivity (FCC) were analyzed. Next, a sliding window method was used to establish dynamic WM FC. WM static and dynamic FC and FCC were compared between when participants had initially completed their journey and 50 days later. Emotion was assessed using the Positive and Negative Affect Schedule and the State Anxiety Inventory.

Results: All participants were confirmed to have jet lag symptoms by the Columbian Jet Lag Scale. The static FC strengthes of cingulate network (WM7)- sensorimotor network and ventral frontal network- visual network were lower after the long-haul flight compared with recovery. Corresponding results were obtained for the dynamic FC analysis. The analysis of FCC revealed weakened connections between the WM7 and several other brain networks, especially the precentral/postcentral network. Moreover, a negative correlation was found between emotion scores and the FC between the WM7 and sensorimotor related regions.

Conclusions: The results of this study provide further evidence for the existence of WM networks and show that jet lag is associated with alterations in static and dynamic WM FC and FCC, especially in sensorimotor networks. Jet lag is a complex problem that not only is related to sleep rhythm but also influences emotion.

Background: Amphetamine-type stimulants (ATS) have become a critical public health issue. Animal models have indicated a clear neurotoxic potential of ATSs. In humans, chronic use has been associated with cognitive deficits and structural brain abnormalities. However, cross-sectional retrospective designs in chronic users cannot truly determine the causal direction of the effects.

Objective: To prospectively determine effects of occasional ATS use on cognitive functioning and brain structure.

Methods: In a prospective longitudinal study design, cognitive functioning and brain structure were assessed at baseline and at 12-month follow-up in occasional ATS users (cumulative lifetime use <10 units at baseline).

Results: Examination of change scores between the initial examination and follow-up revealed declined verbal memory performance and putamen volume in users with high relative to low interim ATS exposure. In the entire sample, interim ATS use, memory decline, and putamen volume reductions were strongly associated.

Conclusions: The present findings support the hypothesis that ATS use is associated with deficient dorsal striatal morphology that might reflect alterations in dopaminergic pathways. More importantly, these findings strongly suggest that even occasional, low-dose ATS use disrupts striatal integrity and cognitive functioning.

Background: Major depressive disorder (MDD) is associated with high risk of suicide, but the biological underpinnings of suicidality in MDD patients are far from conclusive. Previous neuroimaging studies using voxel-based morphometry (VBM) demonstrated that depressed individuals with suicidal thoughts or behaviors exhibit specific cortical structure alterations. To complement VBM findings, surface-based morphometry (SBM) can provide more details into gray matter structure, including the cortical complexity, cortical thickness and sulcal depth for brain images.

Objective: This study aims to use SBM to investigate cortical morphology alterations to obtain evidence for neuroanatomical alterations in depressed patients with suicidality.

Methods: Here, 3D T1-weighted MR images of brain from 39 healthy controls, 40 depressed patients without suicidality (patient controls), and 39 with suicidality (suicidal groups) were analyzed based on SBM to estimate the fractal dimension, gyrification index, sulcal depth, and cortical thickness using the Computational Anatomy Toolbox. Correlation analyses were performed between clinical data and cortical surface measurements from patients.

Results: Surface-based morphometry showed decreased sulcal depth in the parietal, frontal, limbic, occipital and temporal regions and decreased fractal dimension in the frontal regions in depressed patients with suicidality compared to both healthy and patient controls. Additionally, in patients with depression, the sulcal depth of the left caudal anterior cingulate cortex was negatively correlated with Hamilton Depression Rating Scale scores.

Conclusions: Depressed patients with suicidality had abnormal cortical morphology in some brain regions within the default mode network, frontolimbic circuitry and temporal regions. These structural deficits may be associated with the dysfunction of emotional processing and impulsivity control. This study provides insights into the underlying neurobiology of the suicidal brain.