Chronic exposure to imipramine induces a switch from depression-like to mania-like behavior in female serotonin transporter knockout rats: Role of BDNF signaling in the infralimbic cortex

BACKGROUND

Bipolar disorder (BD) is a highly burdensome psychiatric disorder characterized by alternating states of mania and depression. A major challenge in the clinic is the switch from depression to mania, which is often observed in female BD patients during antidepressant treatment such as imipramine. However, the underlying neural basis is unclear.

METHODS

To investigate the potential neuronal pathways, serotonin transporter knockout (SERT KO) rats, an experimental model of female BD patients, were subjected to a battery of behavioral tests under chronic treatment of the antidepressant imipramine. In addition, the expression of brain-derived neurotrophic factor (BDNF) and its downstream signaling was examined in the prefrontal cortex.

RESULTS

Chronic exposure to imipramine reduced anxiety and sociability and problem-solving capacity, and increased thigmotaxis and day/night activity in all animals, but specifically in female SERT KO rats, compared to female wild-type (WT) rats. Further, we found an activation of BDNF-TrkB-Akt pathway signaling in the infralimbic, but not prelimbic, cortex after chronic imipramine treatment in SERT KO, but not WT, rats.

LIMITATIONS

Repeated testing behaviors could potentially affect the results. Additionally, the imipramine induced changes in behavior and in the BDNF system were measured in separate animals.

CONCLUSIONS

Our study indicates that female SERT KO rats, which mirror the female BD patients with the 5-HTTLPR s-allele, are at higher risk of a switch to mania-like behaviors under imipramine treatment. Activation of the BDNF-TrkB-Akt pathway in the infralimbic cortex might contribute to this phenotype, but causal evidence remains to be provided.

Fetal brain MRI atlases and datasets: A review

Fetal brain development is a complex process involving different stages of growth and organization which are crucial for the development of brain circuits and neural connections. Fetal atlases and labeled datasets are promising tools to investigate prenatal brain development. They support the identification of atypical brain patterns, providing insights into potential early signs of clinical conditions. In a nutshell, prenatal brain imaging and post-processing via modern tools are a cutting-edge field that will significantly contribute to the advancement of our understanding of fetal development. In this work, we first provide terminological clarification for specific terms (i.e., "brain template" and "brain atlas"), highlighting potentially misleading interpretations related to inconsistent use of terms in the literature. We discuss the major structures and neurodevelopmental milestones characterizing fetal brain ontogenesis. Our main contribution is the systematic review of 18 prenatal brain atlases and 3 datasets. We also tangentially focus on clinical, research, and ethical implications of prenatal neuroimaging.

Microstructural white matter alterations associated with social anxiety disorders: A systematic review

BACKGROUND

Social anxiety disorder (SAD) is a psychiatric condition characterized by impaired social functioning that negatively impacts individuals' quality of life. Previous neuroimaging studies have revealed morphological and functional changes in various brain regions associated with SAD. Recent advances in diffusion tensor imaging (DTI) and diffusion-weighted imaging (DWI) have enabled the investigation of microstructural white matter (WM) alterations in SAD. This study aims to provide an overview of DTI/DWI studies exploring WM microstructure changes in SAD.

METHODS

A systematic search on PubMed, Scopus, Web of Science, and PsycINFO was conducted for relevant records on July 8, 2023. An exploratory meta-analysis was also performed.

RESULTS

Eight studies were reviewed. Consistent findings indicated reduced fractional anisotropy and increased diffusivity measures in different WM tracts in SAD patients compared to healthy controls. These alterations were mostly observed within regions of the fronto-limbic network, like uncinate fasciculus (UF) and superior and inferior longitudinal fasciculi (SLF and ILF). Finally, our exploratory meta-analysis on four studies utilizing a voxel-wise analytic approach yielded no significant differences between SAD patients and controls.

LIMITATIONS

Limited number of studies, small sample sizes, and heterogeneity in analysis methods.

CONCLUSIONS

Patients with SAD exhibited altered WM integrity, particularly in the UF, SLF, and ILF, compared to healthy controls. However, due to the limited number of included studies, our meta-analysis yielded no significant differences between SAD patients and controls. Therefore, future research is crucial to unravel the link between altered WM structure and the involvement of other limbic and cortical structures in SAD pathogenesis.

Quantifying pH-induced changes in plasma strong ion difference during experimental acidosis: clinical implications for base excess interpretation

It is commonly assumed that changes in plasma strong ion difference (SID) result in equal changes in whole blood base excess (BE). However, at varying pH, albumin ionic-binding and transerythrocyte shifts alter the SID of plasma without affecting that of whole blood (SIDwb), i.e., the BE. We hypothesize that, during acidosis, 1) an expected plasma SID (SIDexp) reflecting electrolytes redistribution can be predicted from albumin and hemoglobin's charges, and 2) only deviations in SID from SIDexp reflect changes in SIDwb, and therefore, BE. We equilibrated whole blood of 18 healthy subjects (albumin = 4.8 ± 0.2 g/dL, hemoglobin = 14.2 ± 0.9 g/dL), 18 septic patients with hypoalbuminemia and anemia (albumin = 3.1 ± 0.5 g/dL, hemoglobin = 10.4 ± 0.8 g/dL), and 10 healthy subjects after in vitro-induced isolated anemia (albumin = 5.0 ± 0.2 g/dL, hemoglobin = 7.0 ± 0.9 g/dL) with varying CO2 concentrations (2-20%). Plasma SID increased by 12.7 ± 2.1, 9.3 ± 1.7, and 7.8 ± 1.6 mEq/L, respectively (P < 0.01) and its agreement (bias[limits of agreement]) with SIDexp was strong: 0.5[-1.9; 2.8], 0.9[-0.9; 2.6], and 0.3[-1.4; 2.1] mEq/L, respectively. Separately, we added 7.5 or 15 mEq/L of lactic or hydrochloric acid to whole blood of 10 healthy subjects obtaining BE of -6.6 ± 1.7, -13.4 ± 2.2, -6.8 ± 1.8, and -13.6 ± 2.1 mEq/L, respectively. The agreement between ΔBE and ΔSID was weak (2.6[-1.1; 6.3] mEq/L), worsening with varying CO2 (2-20%): 6.3[-2.7; 15.2] mEq/L. Conversely, ΔSIDwb (the deviation of SID from SIDexp) agreed strongly with ΔBE at both constant and varying CO2: -0.1[-2.0; 1.7], and -0.5[-2.4; 1.5] mEq/L, respectively. We conclude that BE reflects only changes in plasma SID that are not expected from electrolytes redistribution, the latter being predictable from albumin and hemoglobin's charges.NEW & NOTEWORTHY This paper challenges the assumed equivalence between changes in plasma strong ion difference (SID) and whole blood base excess (BE) during in vitro acidosis. We highlight that redistribution of strong ions, in the form of albumin ionic-binding and transerythrocyte shifts, alters SID without affecting BE. We demonstrate that these expected SID alterations are predictable from albumin and hemoglobin's charges, or from the noncarbonic whole blood buffer value, allowing a better interpretation of SID and BE during in vitro acidosis.

Machine Learning for prediction of violent behaviors in schizophrenia spectrum disorders: a systematic review

Background

Schizophrenia spectrum disorders (SSD) can be associated with an increased risk of violent behavior (VB), which can harm patients, others, and properties. Prediction of VB could help reduce the SSD burden on patients and healthcare systems. Some recent studies have used machine learning (ML) algorithms to identify SSD patients at risk of VB. In this article, we aimed to review studies that used ML to predict VB in SSD patients and discuss the most successful ML methods and predictors of VB.

Methods

We performed a systematic search in PubMed, Web of Sciences, Embase, and PsycINFO on September 30, 2023, to identify studies on the application of ML in predicting VB in SSD patients.

Results

We included 18 studies with data from 11,733 patients diagnosed with SSD. Different ML models demonstrated mixed performance with an area under the receiver operating characteristic curve of 0.56-0.95 and an accuracy of 50.27-90.67% in predicting violence among SSD patients. Our comparative analysis demonstrated a superior performance for the gradient boosting model, compared to other ML models in predicting VB among SSD patients. Various sociodemographic, clinical, metabolic, and neuroimaging features were associated with VB, with age and olanzapine equivalent dose at the time of discharge being the most frequently identified factors.

Conclusion

ML models demonstrated varied VB prediction performance in SSD patients, with gradient boosting outperforming. Further research is warranted for clinical applications of ML methods in this field.

Cannabis Dependence is Associated with Reduced Hippocampal Subregion Volumes Independently of Sex: Findings from an ENIGMA Addiction Working Group Multi-Country Study

Background: Males and females who consume cannabis can experience different mental health and cognitive problems. Neuroscientific theories of addiction postulate that dependence is underscored by neuroadaptations, but do not account for the contribution of distinct sexes. Further, there is little evidence for sex differences in the neurobiology of cannabis dependence as most neuroimaging studies have been conducted in largely male samples in which cannabis dependence, as opposed to use, is often not ascertained. Methods: We examined subregional hippocampus and amygdala volumetry in a sample of 206 people recruited from the ENIGMA Addiction Working Group. They included 59 people with cannabis dependence (17 females), 49 cannabis users without cannabis dependence (20 females), and 98 controls (33 females). Results: We found no group-by-sex effect on subregional volumetry. The left hippocampal cornu ammonis subfield 1 (CA1) volumes were lower in dependent cannabis users compared with non-dependent cannabis users (p<0.001, d=0.32) and with controls (p=0.022, d=0.18). Further, the left cornu ammonis subfield 3 (CA3) and left dentate gyrus volumes were lower in dependent versus non-dependent cannabis users but not versus controls (p=0.002, d=0.37, and p=0.002, d=0.31, respectively). All models controlled for age, intelligence quotient (IQ), alcohol and tobacco use, and intracranial volume. Amygdala volumetry was not affected by group or group-by-sex, but was smaller in females than males. Conclusions: Our findings suggest that the relationship between cannabis dependence and subregional volumetry was not moderated by sex. Specifically, dependent (rather than non-dependent) cannabis use may be associated with alterations in selected hippocampus subfields high in cannabinoid type 1 (CB1) receptors and implicated in addictive behavior. As these data are cross-sectional, it is plausible that differences predate cannabis dependence onset and contribute to the initiation of cannabis dependence. Longitudinal neuroimaging work is required to examine the time-course of the onset of subregional hippocampal alterations in cannabis dependence, and their progression as cannabis dependence exacerbates or recovers over time.

Distinct multimodal biological and functional profiles of symptom-based subgroups in recent-onset psychosis

Symptom heterogeneity characterizes psychotic disorders and hinders the delineation of underlying biomarkers. Here, we identify symptom-based subtypes of recent-onset psychosis (ROP) patients from the multi-center PRONIA (Personalized Prognostic Tools for Early Psychosis Management) database and explore their multimodal biological and functional signatures. We clustered N = 328 ROP patients based on their maximum factor scores in an exploratory factor analysis on the Positive and Negative Syndrome Scale items. We assessed inter-subgroup differences and compared to N = 464 healthy control (HC) individuals regarding gray matter volume (GMV), neurocognition, polygenic risk scores, and longitudinal functioning trajectories. Finally, we evaluated factor stability at 9- and 18-month follow-ups. A 4-factor solution optimally explained symptom heterogeneity, showing moderate longitudinal stability. The ROP-MOTCOG (Motor/Cognition) subgroup was characterized by GMV reductions within salience, control and default mode networks, predominantly throughout cingulate regions, relative to HC individuals, had the most impaired neurocognition and the highest genetic liability for schizophrenia. ROP-SOCWD (Social Withdrawal) patients showed GMV reductions within medial fronto-temporal regions of the control, default mode, and salience networks, and had the lowest social functioning across time points. ROP-POS (Positive) evidenced GMV decreases in salience, limbic and frontal regions of the control and default mode networks. The ROP-AFF (Affective) subgroup showed GMV reductions in the salience, limbic, and posterior default-mode and control networks, thalamus and cerebellum. GMV reductions in fronto-temporal regions of the salience and control networks were shared across subgroups. Our results highlight the existence of behavioral subgroups with distinct neurobiological and functional profiles in early psychosis, emphasizing the need for refined symptom-based diagnosis and prognosis frameworks.

Machine learning and the prediction of suicide in psychiatric populations: a systematic review

Machine learning (ML) has emerged as a promising tool to enhance suicidal prediction. However, as many large-sample studies mixed psychiatric and non-psychiatric populations, a formal psychiatric diagnosis emerged as a strong predictor of suicidal risk, overshadowing more subtle risk factors specific to distinct populations. To overcome this limitation, we conducted a systematic review of ML studies evaluating suicidal behaviors exclusively in psychiatric clinical populations. A systematic literature search was performed from inception through November 17, 2022 on PubMed, EMBASE, and Scopus following the PRISMA guidelines. Original research using ML techniques to assess the risk of suicide or predict suicide attempts in the psychiatric population were included. An assessment for bias risk was performed using the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines. About 1032 studies were retrieved, and 81 satisfied the inclusion criteria and were included for qualitative synthesis. Clinical and demographic features were the most frequently employed and random forest, support vector machine, and convolutional neural network performed better in terms of accuracy than other algorithms when directly compared. Despite heterogeneity in procedures, most studies reported an accuracy of 70% or greater based on features such as previous attempts, severity of the disorder, and pharmacological treatments. Although the evidence reported is promising, ML algorithms for suicidal prediction still present limitations, including the lack of neurobiological and imaging data and the lack of external validation samples. Overcoming these issues may lead to the development of models to adopt in clinical practice. Further research is warranted to boost a field that holds the potential to critically impact suicide mortality.

Alterations of Functional Connectivity Dynamics in Affective and Psychotic Disorders

BACKGROUND

Psychosis and depression patients exhibit widespread neurobiological abnormalities. The analysis of dynamic functional connectivity (dFC), allows for the detection of changes in complex brain activity patterns, providing insights into common and unique processes underlying these disorders.

METHODS

In the present study, we report the analysis of dFC in a large patient sample including 127 clinical high-risk patients (CHR), 142 recent-onset psychosis (ROP) patients, 134 recent-onset depression (ROD) patients, and 256 healthy controls (HC). A sliding window-based technique was used to calculate the time-dependent FC in resting-state MRI data, followed by clustering to reveal recurrent FC states in each diagnostic group.

RESULTS

We identified five unique FC states, which could be identified in all groups with high consistency (rmean = 0.889, sd = 0.116). Analysis of dynamic parameters of these states showed a characteristic increase in the lifetime and frequency of a weakly-connected FC state in ROD patients (p < 0.0005) compared to most other groups, and a common increase in the lifetime of a FC state characterised by high sensorimotor and cingulo-opercular connectivities in all patient groups compared to the HC group (p < 0.0002). Canonical correlation analysis revealed a mode which exhibited significant correlations between dFC parameters and clinical variables (r = 0.617, p < 0.0029), which was associated with positive psychosis symptom severity and several dFC parameters.

CONCLUSIONS

Our findings indicate diagnosis-specific alterations of dFC and underline the potential of dynamic analysis to characterize disorders such as depression, psychosis and clinical risk states.

Right frontal cingulate cortex mediates the effect of prenatal complications on youth internalizing behaviors

Prenatal and perinatal complications represent well-known risk factors for the future development of psychiatric disorders. Such influence might become manifested during childhood and adolescence, as key periods for brain and behavioral changes. Internalizing and externalizing behaviors in adolescence have been associated with the risk of psychiatric onset later in life. Both brain morphology and behavior seem to be affected by obstetric complications, but a clear link among these three aspects is missing. Here, we aimed at analyzing the association between prenatal and perinatal complications, behavioral issues, and brain volumes in a group of children and adolescents. Eighty-two children and adolescents with emotional-behavioral problems underwent clinical and 3 T brain magnetic resonance imaging (MRI) assessments. The former included information on behavior, through the Child Behavior Checklist/6-18 (CBCL/6-18), and on the occurrence of obstetric complications. The relationships between clinical and gray matter volume (GMV) measures were investigated through multiple generalized linear models and mediation models. We found a mutual link between prenatal complications, GMV alterations in the frontal gyrus, and withdrawn problems. Specifically, complications during pregnancy were associated with higher CBCL/6-18 withdrawn scores and GMV reductions in the right superior frontal gyrus and anterior cingulate cortex. Finally, a mediation effect of these GMV measures on the association between prenatal complications and the withdrawn dimension was identified. Our findings suggest a key role of obstetric complications in affecting brain structure and behavior. For the first time, a mediator role of frontal GMV in the relationship between prenatal complications and internalizing symptoms was suggested. Once replicated on independent cohorts, this evidence will have relevant implications for planning preventive interventions.

Case report and systematic review of cerebellar vermis alterations in psychosis

INTRODUCTION

Cerebellar alterations, including both volumetric changes in the cerebellar vermis and dysfunctions of the corticocerebellar connections, have been documented in psychotic disorders. Starting from the clinical observation of a bipolar patient with cerebellar hypoplasia, the purpose of this review is to summarize the data in the literature about the association between hypoplasia of the cerebellar vermis and psychotic disorders [schizophrenia (SCZ) and bipolar disorder (BD)].

METHODS

A bibliographic search on PubMed has been conducted, and 18 articles were finally included in the review: five used patients with BD, 12 patients with SCZ and one subject at psychotic risk.

RESULTS

For SCZ patients and subjects at psychotic risk, the results of most of the reviewed studies seem to suggest a gray matter volume reduction coupled with an increase in white matter volumes in the cerebellar vermis, compared to healthy controls. Instead, the results of the studies on BD patients are more heterogeneous with evidence showing a reduction, no difference or even an increase in cerebellar vermis volume compared to healthy controls.

CONCLUSIONS

From the results of the reviewed studies, a possible correlation emerged between cerebellar vermis hypoplasia and psychotic disorders, especially SCZ, ultimately supporting the hypothesis of psychotic disorders as neurodevelopmental disorders.

Longitudinal outcomes of a work inclusion program in mental health departments in the city of Milan

BACKGROUND

Work functioning impairment is a key diagnostic and prognostic criterion in patients with psychiatric disorders and work inclusion is a major goal of their therapeutic pathway. Since 2009, the Regional Innovative Program (PIR) TR106, promoted by ASST Fatebenefratelli-Sacco of Milan in collaboration with other Departments of Mental Health and Addictions (DSMDs) in the town of Milan (Italy), has been developing the employment inclusion of psychiatric patients.

AIMS

The objective of this study is to evaluate its outcomes over 8 years of observation.

METHOD

We reported the results of a retrospective epidemiologic analysis on 2,142 interventions on 1,066 patients recruited, investigating PIR TR106 outcomes per year focusing on different subgroups. We focused on 'positive', 'negative', and 'other' outcomes.

RESULTS

We preliminary calculated job maintenance interventions (5%, 107) and excluded these interventions from the overall. We observed 29 job firing (1.4%) and 15 job resignations (0.7%) as negative results (equal to 2.2% of the total) and 388 job hiring (16.6%), 647 traineeships (31.8%), and 413 work formation (20.3%) as positive outcomes (equal to 68.75%). In other outcomes (29.1%) we found 305 dismissals from PIR TR 106 (15%) and transitory outcomes (14.1%).Job hiring increased from 8.9% in 2012 to 23.8 % in 2019 (p < .001), while the dismissals diminished from 26.7% to 13.3% (p < .001). The effectiveness of traineeships in terms of job hiring increased in the ratio of annual job hiring versus job traineeship (+48.8%). The majority of hired patients (15.1%) were affected by a psychotic disorder. A significant hiring increase was observed in patients with psychotic disorders and personality disorders (p < .005).

CONCLUSIONS

PIR-TR106 represents a territorial employment inclusion program with progressively increasing effectiveness and specificity, as suggested by changes in outcomes during the 8-year observation. The adaptive capacity and sustainability of the intervention are worth further investigation.

Algorithmic fairness in precision psychiatry: analysis of prediction models in individuals at clinical high risk for psychosis

BACKGROUND

Computational models offer promising potential for personalised treatment of psychiatric diseases. For their clinical deployment, fairness must be evaluated alongside accuracy. Fairness requires predictive models to not unfairly disadvantage specific demographic groups. Failure to assess model fairness prior to use risks perpetuating healthcare inequalities. Despite its importance, empirical investigation of fairness in predictive models for psychiatry remains scarce.

AIMS

To evaluate fairness in prediction models for development of psychosis and functional outcome.

METHOD

Using data from the PRONIA study, we examined fairness in 13 published models for prediction of transition to psychosis (n = 11) and functional outcome (n = 2) in people at clinical high risk for psychosis or with recent-onset depression. Using accuracy equality, predictive parity, false-positive error rate balance and false-negative error rate balance, we evaluated relevant fairness aspects for the demographic attributes 'gender' and 'educational attainment' and compared them with the fairness of clinicians' judgements.

RESULTS

Our findings indicate systematic bias towards assigning less favourable outcomes to individuals with lower educational attainment in both prediction models and clinicians' judgements, resulting in higher false-positive rates in 7 of 11 models for transition to psychosis. Interestingly, the bias patterns observed in algorithmic predictions were not significantly more pronounced than those in clinicians' predictions.

CONCLUSIONS

Educational bias was present in algorithmic and clinicians' predictions, assuming more favourable outcomes for individuals with higher educational level (years of education). This bias might lead to increased stigma and psychosocial burden in patients with lower educational attainment and suboptimal psychosis prevention in those with higher educational attainment.

White matter integrity and medication response to antidepressants in major depressive disorder: a review of the literature

Major Depressive Disorder (MDD) is a severe psychiatric disorder characterized by selective impairments in mood regulation, cognition and behavior. Although it is well-known that antidepressants can effectively treat moderate to severe depression, the biochemical effects of these medications on white matter (WM) integrity are still unclear. Therefore, the aim of the study is to review the main scientific evidence on the differences in WM integrity in responders and non-responders to antidepressant medications. A record search was performed on three datasets (PubMed, Scopus and Web of Science) and ten records matched our inclusion criteria. Overall, the reviewed studies highlighted a good efficacy of antidepressants in MDD treatment. Furthermore, there were differences in WM integrity between responders and non-responders, mainly localized in cingulate cortices, hippocampus and corpus callosum, where the former group showed higher fractional anisotropy and lower axial diffusivity values. Modifications in WM integrity might be partially explained by branching and proliferation as well as neurogenesis of axonal fibers mediated by antidepressants, which in turn may have positively affected brain metabolism and increase the quantity of the serotonergic neurotransmitter within synaptic clefts. However, the reviewed studies suffer from some limitations, including the heterogeneity in treatment duration, antidepressant administration, medical posology, and psychiatric comorbidities. Therefore, future studies are needed to reduce confounding effects of antidepressant medications and to adopt longitudinal and multimodal approaches in order to better characterize the differences in WM integrity between responders and non-responders.

Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness

Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC. CLINICAL TRIAL REGISTRY NAME: German Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/ . Clinical trial registry number: DRKS00005042.

C-reactive protein modifies lipoprotein(a)-related risk for coronary heart disease: the BiomarCaRE project

BACKGROUND AND AIMS

Recent investigations have suggested an interdependence of lipoprotein(a) [Lp(a)]-related risk for cardiovascular disease with background inflammatory burden. The aim the present analysis was to investigate whether high-sensitive C-reactive protein (hsCRP) modulates the association between Lp(a) and coronary heart disease (CHD) in the general population.

METHODS

Data from 71 678 participants from 8 European prospective population-based cohort studies were used (65 661 without/6017 with established CHD at baseline; median follow-up 9.8/13.8 years, respectively). Fine and Gray competing risk-adjusted models were calculated according to accompanying hsCRP concentration (<2 and ≥2 mg/L).

RESULTS

Among CHD-free individuals, increased Lp(a) levels were associated with incident CHD irrespective of hsCRP concentration: fully adjusted sub-distribution hazard ratios [sHRs (95% confidence interval)] for the highest vs. lowest fifth of Lp(a) distribution were 1.45 (1.23-1.72) and 1.48 (1.23-1.78) for a hsCRP group of <2 and ≥2 mg/L, respectively, with no interaction found between these two biomarkers on CHD risk (Pinteraction = 0.82). In those with established CHD, similar associations were seen only among individuals with hsCRP ≥ 2 mg/L [1.34 (1.03-1.76)], whereas among participants with a hsCRP concentration <2 mg/L, there was no clear association between Lp(a) and future CHD events [1.29 (0.98-1.71)] (highest vs. lowest fifth, fully adjusted models; Pinteraction = 0.024).

CONCLUSIONS

While among CHD-free individuals Lp(a) was significantly associated with incident CHD regardless of hsCRP, in participants with CHD at baseline, Lp(a) was related to recurrent CHD events only in those with residual inflammatory risk. These findings might guide adequate selection of high-risk patients for forthcoming Lp(a)-targeting compounds.

Cortical alterations in relatives of patients with bipolar disorder: A review of magnetic resonance imaging studies

INTRODUCTION

Bipolar disorder (BD) is a severe mental disorder characterized by high heritability rates. Widespread brain cortical alterations have been reported in BD patients, mostly involving the frontal, temporal and parietal regions. Importantly, also unaffected relatives of BD patients (BD-RELs) present abnormalities in cortical measures, which are not influenced by disease-related factors, such as medication use and illness duration. Here, we collected all available evidence on cortical measures in BD-RELs to further our knowledge on the potential cortical alterations associated with the vulnerability and the resilience to BD.

METHODS

A search on PubMed, Web of Science and Scopus was performed to identify neuroimaging studies exploring cortical alterations in BD-RELs, including cortical thickness (CT), surface area (SA), gyrification (GI) and cortical complexity. Eleven studies were included. Of these, five assessed CT, five examined CT and SA and one explored CT, SA and GI.

RESULTS

Overall, a heterogeneous pattern of cortical alterations emerged. The areas more consistently linked with genetic liability for BD were the prefrontal and sensorimotor regions. Mixed evidence was reported in the temporal and cingulate areas.

LIMITATIONS

The small sample size and the heterogeneity in terms of methodologies and the characteristics of the participants limit the generalizability of our results.

CONCLUSIONS

Our findings suggest that the genetic liability for BD is related to reduced CT in the prefrontal cortex, which might be a marker of risk for BD, and increased CT within the sensorimotor cortex, which could represent a marker of resilience.

White matter integrity in bipolar disorder investigated with diffusion tensor magnetic resonance imaging and fractal geometry

BACKGROUND

Growing evidence suggests the presence of white matter (WM) alterations in bipolar disorder (BD). In this study we aimed to investigate the state of WM structures, in terms of tissue integrity and morphological complexity, in BD patients compared to healthy controls (HC), in an attempt to better elucidate the microstructural changes associated with BD.

METHODS

We collected a dataset of 399 Diffusion Tensor Magnetic Resonance Imaging (167 BD and 232 healthy controls) images, acquired at five different sites, which was processed with Tract-Based Spatial Statistics (TBSS) and fractal analysis.

RESULTS

The TBSS analysis demonstrated significantly lower FA values in the BD group. Diffusion abnormalities were primarily located in the temporo-parietal network. The Fractal Dimension (FD) analysis did not reveal consistent significant differences in the morphological complexity of WM structures between the groups. When the FD values of patients were considered individually, it is possible to notice some localized significant deviations from the healthy population.

LIMITATIONS

DTI sequences have not been harmonized before acquisition, samples' sizes are heterogeneous.

CONCLUSIONS

This study, by applying both TBSS and FD analyses, allows to evaluate diffusion and structural alterations of WM at the same time. The evaluation of WM integrity from these two different perspectives could be useful to better understand the pathophysiological and morphological changes underpinning bipolar disorder.

Structural and functional brain imaging after treatment with selective-serotonin reuptake-inhibitors in obsessive-compulsive disorder: A mini review

BACKGROUND

Obsessive-compulsive disorder (OCD) is a psychiatric disorder whose etiopathogenesis, according to various neuroimaging studies, seems to be linked to selective dysfunctions in regions within the cortico-striatal-thalamo-cortical circuit. Selective Serotonin Reuptake Inhibitors (SSRIs) are the first-line therapy for OCD but their neurobiological effects on the brain is only partially understood. Therefore, the aim of this review is to highlight structural and functional brain imaging modifications induced by SSRIs treatment.

METHODS

A literature search on PubMed, Psych-Info and Embase database was performed. Studies including patients with OCD that analyzed the effect of SSRIs through structural and functional Magnetic Resonance Imaging were selected. Seven relevant studies were considered eligible for the present review.

RESULTS

Overall, the results of the reviewed studies showed that SSRIs treatment seems to normalize structural, in terms of the white matter and gray matter volumes, and functional activity alterations observed in OCD patients, especially in regions within the prefrontal cortex and striatum.

LIMITATIONS

The poor design of the studies, the small and heterogeneous samples, differences in age, gender, illness course, comorbidities, treatment protocols and the different magnetic fields used make it difficult to generalize the results.

CONCLUSIONS

From the available evidence it emerged that SSRIs treatment has proven to be effective in normalizing brain structural and functional alterations observed in OCD patients. However, future neuroimaging investigations should focus on long-term effects of drugs on brain structure and function in OCD patients through longitudinal approaches in order to identify more effective treatments for these patients.

The mental simulation of state/psychological stimuli in anxiety disorders: A 3T fMRI study

Mental imagery plays an important role in cognitive and emotional processes, therefore it might contribute to psychopathology in affective disorders. Distressive intrusive imagery is a core feature of anxiety disorders, but the underlying neurobiology remains unexplored. Here, we examined the functional brain mechanisms involved in state/psychological imagery in individuals with anxiety disorders. Functional Magnetic Resonance Imaging (fMRI) was used to assess the brain circuits involved in state/psychological (vs. action) imagery controlled by letter detection on the same stimuli in 33 individuals with anxiety disorders relative to 33 healthy controls. Patients were faster than controls in processing state/psychological stimuli and in general in the imagery task. We found that the left superior frontal gyrus was differentially activated by the state/psychological (vs. action) imagery (vs. letter detection) in the anxious individuals vs. healthy controls. We suggest that this area, which is involved in processing of state/psychological semantic information, appears deregulated during imagery in subjects with anxiety disorders. Our study provided the first evidence of both behavioral and brain functional alterations during imagery, highlighting a key role of the left superior frontal gyrus.

A multivariate cognitive approach to predict social functioning in recent onset psychosis in response to computerized cognitive training

Clinical and neuroimaging data has been increasingly used in recent years to disentangle heterogeneity of treatment response to cognitive training (CT) and predict which individuals may achieve the highest benefits. CT has small to medium effects on improving cognitive and social functioning in recent onset psychosis (ROP) patients, who show the most profound cognitive and social functioning deficits among psychiatric patients. We employed multivariate pattern analysis (MVPA) to investigate the potential of cognitive data to predict social functioning improvement in response to 10 h of CT in patients with ROP. A support vector machine (SVM) classifier was trained on the naturalistic data of the Personalized Prognostic Tools for Early Psychosis Management (PRONIA) study sample to predict functioning in an independent sample of 70 ROP patients using baseline cognitive data. PRONIA is a part of a FP7 EU grant program that involved 7 sites across 5 European countries, designed and conducted with the main aim of identifying (bio)markers associated with an enhanced risk of developing psychosis in order to improve early detection and prognosis. Social functioning was predicted with a balanced accuracy (BAC) of 66.4% (Sensitivity 78.8%; Specificity 54.1%; PPV 60.5%; NPV 74.1%; AUC 0.64; P = 0.01). The most frequently selected cognitive features (mean feature weights > ± 0.2) included the (1) correct number of symbol matchings within the Digit Symbol Substitution Test, (2) the number of distracting stimuli leading to an error within 300 and 200 trials in the Continuous Performance Test and (3) the dynamics of verbal fluency between 15 and 30 s within the Verbal Fluency Test, phonetic part. Next, the SVM classifier generated on the PRONIA sample was applied to the intervention sample, that obtained 54 ROP patients who were randomly assigned to a social cognitive training (SCT) or treatment as usual (TAU) group and dichotomized into good (GF-S ≥ 7) and poor (GF-S < 7) functioning patients based on their level of Global Functioning-Social (GF-S) score at follow-up (FU). By applying the initial PRONIA classifier, using out-of-sample cross-validation (OOCV) to the sample of ROP patients who have undergone the CT intervention, a BAC of 59.3% (Sensitivity 70.4%; Specificity 48.1%; PPV 57.6%; NPV 61.9%; AUC 0.63) was achieved at T0 and a BAC of 64.8% (Sensitivity 66.7%; Specificity 63.0%; PPV 64.3%; NPV 65.4%; AUC 0.66) at FU. After SCT intervention, a significant improvement in predicted social functioning values was observed in the SCT compared to TAU group (P ≤0.05; ES[Cohens' d] = 0.18). Due to a small sample size and modest variance of social functioning of the intervention sample it was not feasible to predict individual response to SCT in the current study. Our findings suggest that the use of baseline cognitive data could provide a robust individual estimate of future social functioning, while prediction of individual response to SCT using cognitive data that can be generated in the routine patient care remains to be addressed in large-scale cognitive training trials.

Arteriovenous fistula creation with VasQTM device: A feasibility study to reveal hemodynamic implications

BACKGROUND

Arteriovenous fistula (AVF) is the preferred vascular access (VA) for hemodialysis, but it is still affected by high non-maturation and early failure rates due to stenosis development. Increasing evidence suggests that the presence of turbulent-like flow may play a key role, therefore, to stabilize the flow in the venous segment, an external support device (VasQTM) has been designed. The aim of this study was to provide preliminary evidence of VasQTM impact on AVF hemodynamics as compared to AVFs created with conventional surgery.

METHODS

In this pilot single-center prospective randomized study six patients were enrolled, three in the VasQ group and three in the control group. Contrast-free magnetic resonance imaging (MRI) scans were acquired at 3 days, 3 months and 1 year after AVF surgery and were used to generate 3D patient-specific models. Computational fluid dynamic (CFD) simulations were performed using pimpleFoam, imposing patient-specific flow waveforms derived from ultrasound (US) examinations at the inlet of the proximal and distal artery, and a traction-free condition at the venous outflow. Morphologic and hemodynamic changes occurring over time were compared between VasQ and control AVFs.

RESULTS

Our MRI protocol provided high-quality images suitable for reliable segmentation and reconstruction of patient-specific 3D models of AVFs at all three timepoints in four out of six patients. The VasQTM device maintained the angle between the artery and the vein almost unchanged over time, with a more stable flow in the AVFs supported by the device. In contrast, one of the AVFs of the control group evolved to an extreme dilatation of the vein and highly disturbed flow, while the other developed a stenosis in the juxta-anastomotic region.

CONCLUSIONS

This study demonstrated the feasibility of characterizing the morphological and hemodynamic changes occurring over time in AVFs created using the VasQTM device and provided preliminary evidence of the potential hemodynamic benefits of its use.

An online survey among general pediatricians on melatonin use in children with chronic insomnia

OBJECTIVES

Although melatonin (MLT) is the molecule most used by pediatricians for sleep problems, scarce evidence exists on its use in healthy pediatric population. The objective of this study was to describe MLT use by Italian pediatricians in healthy children with chronic insomnia.

STUDY DESIGN

A cross-sectional open survey was administered to Italian pediatricians, between June and November 2022, collecting information about their use of MLT in healthy children: age range of patients, dosages used, time of administration, duration of treatment, association with other treatments, perceived efficacy, and side effects. Data were reported as frequencies with their respective 95% confidence intervals. Chi-square statistics assessed significant differences between pediatricians who had training in pediatric sleep and those who did not.

RESULTS

Among 428 respondents, 97.4% of pediatricians used MLT; 87.3% of them prescribed MLT in children aged 1-2 years, 62.1% in 2-5 years and 42.5% in 10-18 years. 84.9% of them suggested to take MLT 30 min before bedtime. 37.9% indicated to continue treatment for one month, 30.2% for 2-3 months. 74.1% of pediatricians usually prescribed MLT 1 mg/day. The most frequent treatment associated with MLT was sleep hygiene (85.4%). Almost all pediatricians found MLT effective in reducing difficulties falling asleep. Only 3.2% of them reported mild side effects.

CONCLUSIONS

MLT is widely prescribed by Italian pediatricians, but no consensus exists about its use in typically developing children. There is a need for clear guidelines to optimize the use of MLT in healthy children.

Chest X-ray at Emergency Admission and Potential Association with Barotrauma in Mechanically Ventilated Patients: Experience from the Italian Core of the First Pandemic Peak

Barotrauma occurs in a significant number of patients with COVID-19 interstitial pneumonia undergoing mechanical ventilation. The aim of the current study was to investigate whether the Brixia score (BS) calculated on chest-X-rays acquired at the Emergency Room was associated with barotrauma. We retrospectively evaluated 117 SARS-CoV-2 patients presented to the Emergency Department (ED) and then admitted to the intensive care unit (ICU) for mechanical ventilation between February and April 2020. Subjects were divided into two groups according to the occurrence of barotrauma during their hospitalization. CXRs performed at ED admittance were assessed using the Brixia score. Distribution of barotrauma (pneumomediastinum, pneumothorax, subcutaneous emphysema) was identified in chest CT scans. Thirty-eight subjects (32.5%) developed barotrauma (25 pneumomediastinum, 24 pneumothorax, 24 subcutaneous emphysema). In the barotrauma group we observed higher Brixia score values compared to the non-barotrauma group (mean value 12.18 vs. 9.28), and logistic regression analysis confirmed that Brixia score is associated with the risk of barotrauma. In this work, we also evaluated the relationship between barotrauma and clinical and ventilatory parameters: SOFA score calculated at ICU admittance and number of days of non-invasive ventilation (NIV) prior to intubation emerged as other potential predictors of barotrauma.

Structural and Functional Brain Patterns Predict Formal Thought Disorder's Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study

BACKGROUND

Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level.

METHODS

Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up.

RESULTS

Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%.

CONCLUSIONS

We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.

Machine learning applied to functional magnetic resonance imaging in anxiety disorders

BACKGROUND

Brain functional abnormalities have been commonly reported in anxiety disorders, including generalized anxiety disorder, social anxiety disorder, panic disorder, agoraphobia, and specific phobias. The role of functional abnormalities in the discrimination of these disorders can be tested with machine learning (ML) techniques. Here, we aim to provide a comprehensive overview of ML studies exploring the potential discriminating role of functional brain alterations identified by functional magnetic resonance imaging (fMRI) in anxiety disorders.

METHODS

We conducted a search on PubMed, Web of Science, and Scopus of ML investigations using fMRI as features in patients with anxiety disorders. A total of 12 studies (resting-state fMRI n = 5, task-based fMRI n = 6, resting-state and task-based fMRI n=1) met our inclusion criteria.

RESULTS

Overall, the studies showed that, regardless of the classifiers, alterations in functional connectivity and aberrant neural activation involving the amygdala, anterior cingulate cortex, hippocampus, insula, orbitofrontal cortex, temporal pole, cerebellum, default mode network, dorsal attention network, sensory network, and affective network were able to discriminate patients with anxiety from controls, with accuracies spanning from 36 % to 94 %.

LIMITATIONS

The small sample size, different ML approaches and heterogeneity in the selection of regions included in the multivariate pattern analyses limit the conclusions of the present review.

CONCLUSIONS

ML methods using fMRI as features can distinguish patients with anxiety disorders from healthy controls, indicating that these techniques could be used as a helpful tool for the diagnosis and the development of more targeted treatments for these disorders.

Functional Magnetic Resonance Imaging to Monitor Disease Progression: a prospective study in Patients with Primary Membranoproliferative Glomerulonephritis

INTRODUCTION

Primary membranoproliferative glomerulonephritis (MPGN) is a rare kidney disease with poor prognosis and no specific therapies. The disease heterogeneity and the difficulty of performing repeated kidney biopsies poses big challenges. This study investigates the correlation between non-contrast enhanced magnetic resonance imaging (MRI) and histologic and clinical findings in patients with primary MPGN.

METHODS

Patients with primary MPGN underwent baseline and 1-year kidney MRI in addition to biopsy and laboratory testing as part of a prospective MRI subproject of a clinical trial (ClinicalTrials.gov identifier NCT03723512). Diffusion-weighted and phase-contrast MRI were used to investigate kidney diffusivity and perfusion. Peritubular interstitial volume and fibrosis were quantified on kidney biopsies.

RESULTS

Seven patients with primary MPGN (18[17-21] years, 43% females) were included. Kidney biopsies showed variable degree of global and segmental glomerular sclerosis ([5-30]% and [10-60]%), mild interstitial fibrosis (<10%), and increased peritubular interstitial volume ([19-40]%). MRI and laboratory parameters changed very differently from patient to patient over 1 year. Peritubular interstitial volume and glomerular sclerosis negatively associated with renal blood flow (RBF)(rho = -0.81 and -0.77), and positively with renal vascular resistance (RVR)(rho = 0.65 and 0.73). Urinary albumin to creatinine ratio (uACR) negatively associated with RBF and filtration fraction (FF)(rho = -0.86 and -0.6), while positively with RVR (rho = 0.88). uACR decrease was associated with kidney diffusivity increase (rho = -0.5). Measured glomerular filtration rate (GFR) positively associated with kidney diffusivity, RBF, and FF (rho = 0.87, 0.85 and 0.59), while negatively with RVR (rho = -0.89); GFR increase was associated with kidney diffusivity, RBF, and FF increase (rho = 0.77, 0.7, and 0.7) and RVR decrease (rho = -0.7).

DISCUSSION/CONCLUSION

The strong correlation found between MRI and histologic and clinical findings, despite the rather limited number of patients, highlights MRI potential to monitor disease progression in patients with rare kidney disease.

Classification of suicidality by training supervised machine learning models with brain MRI findings: A systematic review

BACKGROUND

Suicide is a global public health issue causing around 700,000 deaths worldwide each year. Therefore, identifying suicidal thoughts and behaviors in patients can help lower the suicide-related mortality rate. This review aimed to investigate the feasibility of suicidality identification by applying supervised Machine Learning (ML) methods to Magnetic Resonance Imaging (MRI) data.

METHODS

We conducted a systematic search on PubMed, Scopus, and Web of Science to identify studies examining suicidality by applying ML methods to MRI features. Also, the Prediction Model Risk of Bias Assessment Tool (PROBAST) was employed for the quality assessment.

RESULTS

23 studies met the inclusion criteria. Of these, 20 developed prediction models without external validation and 3 developed prediction models with external validation. The performance of ML models varied among the reviewed studies, with the highest reported values of accuracies and Area Under the Curve (AUC) ranging from 51.7 % to 100 % and 0.52 to 1, respectively. Over half of the studies that reported accuracy (12/21) or AUC (13/16) achieved values of ≥0.8. Our comparative analysis indicated that deep learning exhibited the highest predictive performance compared to other ML models. The most commonly identified discriminative imaging features were resting-state functional connectivity and grey matter volume within prefrontal-limbic structures.

LIMITATIONS

Small sample sizes, lack of external validation, heterogeneous study designs, and ML model development.

CONCLUSIONS

Most of the studies developed ML models capable of ML-based suicide identification, although ML models' predictive performance varied across the reviewed studies. Thus, further well-designed is necessary to uncover the true potential of different ML models in this field.

Intermediate dose enoxaparin in hospitalized patients with moderate-severe COVID-19: a pilot phase II single-arm study, INHIXACOVID19

BACKGROUND

Randomized clinical trials in non-critically ill COVID-19 patients showed that therapeutic-dose heparin increased survival with reduced organ support as compared with usual-care thromboprophylaxis, albeit with increased bleeding risk. The purpose of the study is to assess the safety of intermediate dose enoxaparin in hospitalized patients with moderate to severe COVID-19.

METHODS

A phase II single-arm interventional prospective study including patients receiving intermediate dose enoxaparin once daily according to body weight: 60 mg for 45-60 kg, 80 mg for 61-100 kg or 100 mg for > 100 kg for 14 days, with dose adjustment according to anti-factor Xa activity (target range: 0.4-0.6 UI/ml); an observational cohort (OC) included patients receiving enoxaparin 40 mg day for comparison. Follow-up was 90 days. Primary outcome was major bleeding within 30 and 90 days after treatment onset. Secondary outcome was the composite of all-cause 30 and 90-day mortality rates, disease severity at the end of treatment, intensive care unit (ICU) admission and length of ICU stay, length of hospitalization. All outcomes were adjudicated by an independent committee and analyzed before and after propensity score matching (PSm).

RESULTS

Major bleeding was similar in IC (1/98 1.02%) and in the OC (none), with only one event observed in a patient receiving concomitantly anti-platelet therapy. The composite outcome was observed in 53/98 patients (54%) in the IC and 132/203 (65%) patients in the OC (p = 0.07) before PSm, while it was observed in 50/90 patients (55.6%) in the IC and in 56/90 patients (62.2%) in the OC after PSm (p = 0.45). Length of hospitalization was lower in the IC than in OC [median 13 (IQR 8-16) vs 14 (11-21) days, p = 0.001], however it lost statistical significance after PSm (p = 0.08). At 30 days, two patients had venous thrombosis and two pulmonary embolism in the OC. Time to first negative RT-PCR were similar in the two groups.

CONCLUSIONS

Weight adjusted intermediate dose heparin with anti-FXa monitoring is safe with potential positive impact on clinical course in COVID-19 non-critically ill patients.

TRIAL REGISTRATION

The study INHIXACOVID19 was registred on ClinicalTrials.gov with the trial registration number (TRN) NCT04427098 on 11/06/2020.

How does feeling pain look like in depression: A review of functional neuroimaging studies

INTRODUCTION

Major Depression Disorder (MDD) and pain appear to be reciprocal risk factors and sharing common neuroanatomical pathways and biological substrates. However, the role of MDD on pain processing remains still unclear. Therefore, this review aims to focus on the effect of depression on pain anticipation, and perception, before and after treatment, through functional magnetic resonance imaging (fMRI).

METHODS

A bibliographic search was conducted on PubMed, Scopus and Web of Science, looking for fMRI studies exploring pain processing in MDD patients.

RESULTS

Amongst the 602 studies retrieved, 12 met the inclusion criteria. In terms of pain perception, studies evidenced that MDD patients generally presented increased activation in brain regions within the prefrontal cortex, insula and in the limbic system (such as amygdala, hippocampus) and occipital cortex. The studies investigating the effect of antidepressant treatment evidenced a reduced activation in areas such as insula, anterior cingulate, and prefrontal cortices. In terms of pain anticipation, contrasting results were evidenced in MDD patients, which presented both increased and decreased activity in the prefrontal cortex, the insula and the temporal lobe, alongside with increased activity in the anterior cingulate cortex, the frontal gyrus and occipital lobes.

LIMITATIONS

The small number of included studies, the heterogeneous approaches of the studies might limit the conclusions of this review.

CONCLUSIONS

Acute pain processing in MDD patients seems to involve numerous and different brain areas. However, more specific fMRI studies with a more homogeneous population and rigorous approach should be conducted to better highlight the effect of depression on pain processing.

Neuroimaging alterations associated with medication use in early-onset bipolar disorder: An updated review

BACKGROUND

Pediatric bipolar disorder (PBD) is a severe disorder characterized by mood fluctuations starting at a young age. Several neuroimaging studies revealed a specific biological signature of PBD involving alterations in the amygdala and prefrontal regions. Considering the growing concerns regarding the effects of PBD treatments on developing brains, this review aims to provide an overview of the studies investigating the effect of mood stabilizers, antipsychotics, and anticonvulsants on neuroimaging findings in PBD.

METHODS

We searched PubMed, Scopus, and Web of Science to identify all structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), and diffusion tensor imaging (DTI) studies exploring the effects of medications on neuroimaging findings in PBD. A total of 18 studies met our inclusion criteria (fMRI n = 11, sMRI n = 6, DTI n = 1).

RESULTS

Although the findings varied highly across the studies, some investigations consistently indicated that medications primarily affect the prefrontal cortex and the amygdala. Moreover, despite some exceptions, the reported medication effects predominantly lean towards structural and functional normalization.

LIMITATIONS

The reviewed studies differ in methods, medications, and fMRI paradigms. Furthermore, most studies used observational approaches with small sample sizes, minimizing the statistical power.

CONCLUSIONS

Evidence suggests the potential of antipsychotics and mood stabilizers to modulate the neuroimaging findings in PBD patients, mostly normalizing brain structure and function in key mood-regulating regions.

Neuropsychological instruments for bipolar disorders: A systematic review on psychometric properties

BACKGROUND

Cognitive deficits are a core feature of bipolar disorder (BD) that persist during the euthymic phase and affect global functioning. However, nowadays, there is no consensus on the optimal tool to capture cognitive deficits in BD. Therefore, this review aims to examine the psychometric properties of tools commonly used to assess cognitive functioning in BD.

METHODS

Literature search was conducted on PubMed and Web of Science databases on August 1, 2022 and on April 20, 2023, yielding 1758 de-duplicated records. Thirteen studies fulfilled the inclusion criteria and were included in the review.

RESULTS

All tools examined showed acceptable-to-good psychometric properties suggesting that both brief cognitive screeners and comprehensive batteries may be appropriate for detecting or monitoring cognitive changes in BD.

LIMITATIONS

Methodological differences between the included studies precluded a direct comparison of the results. Further research is needed to investigate the psychometric properties of cognitive tools that assess also affective and social cognition.

CONCLUSIONS

The tools examined appear sensitive enough to distinguish between BD patients with versus without cognitive deficits, however, an optimal tool has not yet been identified. The applicability and clinical utility of the tools may depend on multiple factors such as available resources. That said, web-based instruments are expected to become the first-choice instrument for cognitive screening as they can be applied on a large scale and at an affordable cost. As for second-level assessment instruments, the BACA shows robust psychometric properties and tests both affective and non-affective cognition.

The association between anger rumination and emotional dysregulation in borderline personality disorder: A review

INTRODUCTION

Borderline Personality Disorder (BPD) is characterized by impulsiveness, interpersonal difficulties, emotional instability and dysfunctional cognitive processes. In addition to these symptoms, anger rumination is a cognitive mechanism often prominent in BPD patients and it has been found to be associated with maladaptive outcomes, such as increasing anger feelings, aggressive and impulsive behaviors. In this context, the aim of our review is to synthesize results on the relationship between emotional dysregulation and anger rumination in BPD with the final goal to get more information about possible psychotherapeutic methods in the treatment of BPD.

METHODS

A comprehensive search on BPD and anger rumination was performed on PubMed, Embase and Scopus. The search identified 8 articles meeting our inclusion criteria.

RESULTS

Most of the studies reported a correlation between BPD emotional instability and dyscontrolled behaviors, anger and depressive rumination. Specifically, from the reviewed studies, it emerged that the tendency to use dysfunctional cognitive strategies, such as anger rumination, predicted aggressive behavior above and beyond emotion dysregulation, ultimately suggesting that anger rumination mediates the relationship between emotional dysregulation and aggression proneness.

LIMITATIONS

The cross-sectional design and the inclusion of subjects without a definite diagnosis of BPD (e.g., university students), may have decreased the generalizability of the results to the clinical populations and limited the possibility to explore the effect of anger rumination over time in BPD.

CONCLUSIONS

From the reviewed studies emerged that the identification of anger rumination as a proximal process with respect to BPD may have the potential to expand and support psychotherapeutic treatment.

Hemodynamics in AVF over time: A protective role of vascular remodeling toward flow stabilization

The mechanisms underlying vascular stenosis formation in the arteriovenous fistula (AVF) for hemodialysis (HD) remain mostly unknown. Several computational fluid dynamics (CFD) studies have suggested a potential role for unsteady flow in inducing intimal hyperplasia and AVF stenosis, but the majority of these observations have been limited to a single time point after surgical creation. The aim of the present study was to investigate the relation between hemodynamic conditions and AVF vascular remodeling through a CFD longitudinal study. Non contrast-enhanced MR images and Doppler Ultrasound (US) examinations were acquired at 3 days, 40 days, 6 months, 1 year, and 1.5 years after surgery in a 72-year male referred for native radio-cephalic AVF. Three-dimensional AVF models were generated and high fidelity CFD simulations were performed using pimpleFoam, setting patient-specific boundary conditions derived from US. Morphological and hemodynamic changes over time were then analyzed. Analysis of vessel morphology and hemodynamics during follow-up showed that the AVF had a successful maturation process, characterized by a massive arterial and venous dilatation within the 6 months after surgery, a corresponding increase in blood flow volume and important flow instabilities. Between 6 months and 1 year, a stenosis developed in the juxta-anastomotic vein and caused AVF failure at 1.5 years. The development of stenosis was paralleled by the regularization of blood flow velocity pattern and consequent decrease in the near-wall disturbed flow metrics. These results suggest that development of intimal hyperplasia and vessel stenosis, triggered by unsteady flow, could be the result of vascular inward remodeling toward regularization of turbulent-like flow.

Prevalence of cognitive impairments and strengths in the early course of psychosis and depression

BACKGROUND

Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression.

METHODS

A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15-41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1-2 s.d. below or above HC, respectively) for each cognitive test.

RESULTS

Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP.

CONCLUSIONS

These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

White matter modifications of corpus callosum in bipolar disorder: A DTI tractography review

BACKGROUND

The recent widespread use of diffusion tensor imaging (DTI) tractography allowed researchers to investigate the diffusivity modifications and neuroanatomical changes of white matter (WM) fascicles in major psychiatric disorders, including bipolar disorder (BD). In BD, corpus callosum (CC) seems to have a crucial role in explaining the pathophysiology and cognitive impairment of this psychiatric disorder. This review aims to provide an overview on the latest results emerging from studies that investigated neuroanatomical changes of CC in BD using DTI tractography.

METHODS

Bibliographic research was conducted on PubMed, Scopus and Web of Science datasets until March 2022. Ten studies fulfilled our inclusion criteria.

RESULTS

From the reviewed DTI tractography studies a significant decrease of fractional anisotropy emerged in the genu, body and splenium of CC of BD patients compared to controls. This finding is coupled with reduction of fiber density and modification in fiber tract length. Finally, an increase of radial and mean diffusivity in forceps minor and in the entire CC was also reported.

LIMITATIONS

Small sample size, heterogeneity in terms of methodological (diffusion gradient) and clinical (lifetime comorbidity, BD status, pharmacological treatments) characteristics.

CONCLUSIONS

Overall, these findings suggest the presence of structural modifications in CC in BD patients, which may in turn explain the cognitive impairments often observed in this psychiatric disorder, especially in executive processing, motor control and visual memory. Finally, structural modifications may suggest an impairment in the amount of functional information and a morphological impact within those brain regions connected by CC.

Neurocognitive skills and vulnerability for psychosis in depression and across the psychotic spectrum: findings from the PRONIA Consortium

BACKGROUND

Neurocognitive deficits are a core feature of psychosis and depression. Despite commonalities in cognitive alterations, it remains unclear if and how the cognitive deficits in patients at clinical high risk for psychosis (CHR) and those with recent-onset psychosis (ROP) are distinct from those seen in recent-onset depression (ROD).

AIMS

This study was carried out within the European project 'Personalized Prognostic Tools for Early Psychosis Management', and aimed to characterise the cognitive profiles of patients with psychosis or depression.

METHOD

We examined cognitive profiles for patients with ROP (n = 105), patients with ROD (n = 123), patients at CHR (n = 116) and healthy controls (n = 372) across seven sites in five European countries. Confirmatory factor analysis identified four cognitive factors independent of gender, education and site: speed of processing, attention and working memory, verbal learning and spatial learning.

RESULTS

Patients with ROP performed worse than healthy controls in all four domains (P < 0.001), whereas performance of patients with ROD was not affected (P > 0.05). Patients at CHR performed worse than healthy controls in speed of processing (P = 0.001) and spatial learning (P = 0.003), but better than patients with ROP across all cognitive domains (all P ≤ 0.01). CHR and ROD groups did not significantly differ in any cognitive domain. These findings were independent of comorbid depressive symptoms, substance consumption and illness duration.

CONCLUSIONS

These results show that neurocognitive abilities are affected in CHR and ROP, whereas ROD seems spared. Although our findings may support the notion that those at CHR have a specific vulnerability to psychosis, future studies investigating broader transdiagnostic risk cohorts in longitudinal designs are needed.

Association between cannabis use and symptom dimensions in schizophrenia spectrum disorders: an individual participant data meta-analysis on 3053 individuals

Background

The association between cannabis use and positive symptoms in schizophrenia spectrum disorders is well documented, especially via meta-analyses. Yet, findings are inconsistent regarding negative symptoms, while other dimensions such as disorganization, depression, and excitement, have not been investigated. In addition, meta-analyses use aggregated data discarding important confounding variables which is a source of bias.

Methods

PubMed, ScienceDirect and PsycINFO were used to search for publications from inception to September 27, 2022. We contacted the authors of relevant studies to extract raw datasets and perform an Individual Participant Data meta-analysis (IPDMA). Inclusion criteria were: psychopathology of individuals with schizophrenia spectrum disorders assessed by the Positive and Negative Syndrome Scale (PANSS); cannabis-users had to either have a diagnosis of cannabis use disorder or use cannabis at least twice a week. The main outcomes were the PANSS subscores extracted via the 3-factor (positive, negative and general) and 5-factor (positive, negative, disorganization, depression, excitement) structures. Preregistration is accessible via Prospero: ID CRD42022329172.

Findings

Among the 1149 identified studies, 65 were eligible and 21 datasets were shared, totaling 3677 IPD and 3053 complete cases. The adjusted multivariate analysis revealed that relative to non-use, cannabis use was associated with higher severity of positive dimension (3-factor: Adjusted Mean Difference, aMD = 0.34, 95% Confidence Interval, CI = [0.03; 0.66]; 5-factor: aMD = 0.38, 95% CI = [0.08; 0.63]), lower severity of negative dimension (3-factor: aMD = -0.49, 95% CI [-0.90; -0.09]; 5-factor: aMD = -0.50, 95% CI = [-0.91; -0.08]), higher severity of excitement dimension (aMD = 0.16, 95% CI = [0.03; 0.28]). No association was found between cannabis use and disorganization (aMD = -0.13, 95% CI = [-0.42; 0.17]) or depression (aMD = -0.14, 95% CI = [-0.34; 0.06]).

Interpretation

No causal relationship can be inferred from the current results. The findings could be in favor of both a detrimental and beneficial effect of cannabis on positive and negative symptoms, respectively. Longitudinal designs are needed to understand the role of cannabis is this association. The reported effect sizes are small and CIs are wide, the interpretation of findings should be taken with caution.

Funding

This research did not receive any specific grant or funding. Primary financial support for authors was provided by Le Vinatier Psychiatric Hospital.

Improved estimation of the risk of manic relapse by combining clinical and brain scan data

INTRODUCTION

Estimating the risk of manic relapse could help the psychiatrist individually adjust the treatment to the risk. Some authors have attempted to estimate this risk from baseline clinical data. Still, no studies have assessed whether the estimation could improve by adding structural magnetic resonance imaging (MRI) data. We aimed to evaluate it.

MATERIAL AND METHODS

We followed a cohort of 78 patients with a manic episode without mixed symptoms (bipolar type I or schizoaffective disorder) at 2-4-6-9-12-15-18 months and up to 10 years. Within a cross-validation scheme, we created and evaluated a Cox lasso model to estimate the risk of manic relapse using both clinical and MRI data.

RESULTS

The model successfully estimated the risk of manic relapse (Cox regression of the time to relapse as a function of the estimated risk: hazard ratio (HR)=2.35, p=0.027; area under the curve (AUC)=0.65, expected calibration error (ECE)<0.2). The most relevant variables included in the model were the diagnosis of schizoaffective disorder, poor impulse control, unusual thought content, and cerebellum volume decrease. The estimations were poorer when we used clinical or MRI data separately.

CONCLUSION

Combining clinical and MRI data may improve the risk of manic relapse estimation after a manic episode. We provide a website that estimates the risk according to the model to facilitate replication by independent groups before translation to clinical settings.

Review on deep learning fetal brain segmentation from Magnetic Resonance images

Brain segmentation is often the first and most critical step in quantitative analysis of the brain for many clinical applications, including fetal imaging. Different aspects challenge the segmentation of the fetal brain in magnetic resonance imaging (MRI), such as the non-standard position of the fetus owing to his/her movements during the examination, rapid brain development, and the limited availability of imaging data. In recent years, several segmentation methods have been proposed for automatically partitioning the fetal brain from MR images. These algorithms aim to define regions of interest with different shapes and intensities, encompassing the entire brain, or isolating specific structures. Deep learning techniques, particularly convolutional neural networks (CNNs), have become a state-of-the-art approach in the field because they can provide reliable segmentation results over heterogeneous datasets. Here, we review the deep learning algorithms developed in the field of fetal brain segmentation and categorize them according to their target structures. Finally, we discuss the perceived research gaps in the literature of the fetal domain, suggesting possible future research directions that could impact the management of fetal MR images.

Diffusion magnetic resonance imaging for kidney cyst volume quantification and non-cystic tissue characterisation in ADPKD

OBJECTIVES

Beyond total kidney and cyst volume (TCV), non-cystic tissue plays an important role in autosomal dominant polycystic kidney disease (ADPKD) progression. This study aims at presenting and preliminarily validating a diffusion MRI (DWI)-based TCV quantification method and providing evidence of DWI potential in characterising non-cystic tissue microstructure.

METHODS

T2-weighted MRI and DWI scans (b = 0, 15, 50, 100, 200, 350, 500, 700, 1000; 3 directions) were acquired from 35 ADPKD patients with CKD stage 1 to 3a and 15 healthy volunteers on a 1.5 T scanner. ADPKD classification was performed using the Mayo model. DWI scans were processed by mono- and segmented bi-exponential models. TCV was quantified on T2-weighted MRI by the reference semi-automatic method and automatically computed by thresholding the pure diffusivity (D) histogram. The agreement between reference and DWI-based TCV values and the differences in DWI-based parameters between healthy and ADPKD tissue components were assessed.

RESULTS

There was strong correlation between DWI-based and reference TCV (rho = 0.994, p < 0.001). Non-cystic ADPKD tissue had significantly higher D, and lower pseudo-diffusion and flowing fraction than healthy tissue (p < 0.001). Moreover, apparent diffusion coefficient and D values significantly differed by Mayo imaging class, both in the whole kidney (Wilcoxon p = 0.007 and p = 0.004) and non-cystic tissue (p = 0.024 and p = 0.007).

CONCLUSIONS

DWI shows potential in ADPKD to quantify TCV and characterise non-cystic kidney tissue microstructure, indicating the presence of microcysts and peritubular interstitial fibrosis. DWI could complement existing biomarkers for non-invasively staging, monitoring, and predicting ADPKD progression and evaluating the impact of novel therapies, possibly targeting damaged non-cystic tissue besides cyst expansion.

CLINICAL RELEVANCE STATEMENT

This study shows diffusion-weighted MRI (DWI) potential to quantify total cyst volume and characterise non-cystic kidney tissue microstructure in ADPKD. DWI could complement existing biomarkers for non-invasively staging, monitoring, and predicting ADPKD progression and evaluating the impact of novel therapies, possibly targeting damaged non-cystic tissue besides cyst expansion.

KEY POINTS

• Diffusion magnetic resonance imaging shows potential to quantify total cyst volume in ADPKD. • Diffusion magnetic resonance imaging might allow to non-invasively characterise non-cystic kidney tissue microstructure. • Diffusion magnetic resonance imaging-based biomarkers significantly differ by Mayo imaging class, suggesting their possible prognostic value.

Brain volumes in alcohol use disorder: Do females and males differ? A whole-brain magnetic resonance imaging mega-analysis

Emerging evidence suggests distinct neurobiological correlates of alcohol use disorder (AUD) between sexes, which however remain largely unexplored. This work from ENIGMA Addiction Working Group aimed to characterize the sex differences in gray matter (GM) and white matter (WM) correlates of AUD using a whole-brain, voxel-based, multi-tissue mega-analytic approach, thereby extending our recent surface-based region of interest findings on a nearly matching sample using a complementary methodological approach. T1-weighted magnetic resonance imaging (MRI) data from 653 people with AUD and 326 controls was analyzed using voxel-based morphometry. The effects of group, sex, group-by-sex, and substance use severity in AUD on brain volumes were assessed using General Linear Models. Individuals with AUD relative to controls had lower GM volume in striatal, thalamic, cerebellar, and widespread cortical clusters. Group-by-sex effects were found in cerebellar GM and WM volumes, which were more affected by AUD in females than males. Smaller group-by-sex effects were also found in frontotemporal WM tracts, which were more affected in AUD females, and in temporo-occipital and midcingulate GM volumes, which were more affected in AUD males. AUD females but not males showed a negative association between monthly drinks and precentral GM volume. Our results suggest that AUD is associated with both shared and distinct widespread effects on GM and WM volumes in females and males. This evidence advances our previous region of interest knowledge, supporting the usefulness of adopting an exploratory perspective and the need to include sex as a relevant moderator variable in AUD.

Safety intervention for improving functioning in suicidal attempters (STRONG): A secondary prevention study. Study rationale and research protocol

BACKGROUND

Suicide is one of the most largely preventable causes of death worldwide. The aim of the STRONG study is to assess the effectiveness of a specific intervention (an extended Safety Planning Intervention) called iFightDepression-SURVIVE (iFD-S) in suicidal attempters by changes in psychosocial functioning. As secondary outcomes, quality of life, cognitive performance, clinical state and neuroimaging correlates will be considered.

OBJECTIVE

To describe the rationale and design of the STRONG study, an extension of the SURVIVE study, a national multicenter cohort about on prevention in suicidal attempters.

METHODS

The STRONG study is a two-year clinical trial. A total sample of 60 patients will be randomly allocated to two arms: a group will receive a iFD-S and treatment as usual (TAU) (n=30 treatment group), while another group will exclusively receive TAU (n=30 control group). There will be three study points: baseline; 3-month; and 6-month follow-up assessments, all of which will include rater-blinded evaluation of psychosocial functioning, quality of life, clinical state, cognitive performance and neuroimaging acquisition.

RESULTS

It is expected to obtain data on the efficacy of iFD-S in patients who have committed a suicide attempt.

CONCLUSION

Results will provide insight into the effectiveness of IFD-S in suicidal attempters with respect to improvements in psychosocial functioning, quality of life, cognition, and neuroimaging correlates.

CLINICAL TRIALS ID

NCT05655390.

Psychophysiological responses to psychological stress exposure and neural correlates in adults with mental disorders: a scoping review

Introduction

The dysregulation of psychophysiological responses to mental stressors is a common issue addressed in individuals with psychiatric conditions, while brain circuit abnormalities are often associated with psychiatric conditions and their manifestations. However, to our knowledge, there is no systematic overview that would comprehensively synthesize the literature on psychophysiological responses during laboratory-induced psychosocial stressor and neural correlates in people with mental disorders. Thus, we aimed to systematically review the existing research on psychophysiological response during laboratory-induced stress and its relationship with neural correlates as measured by magnetic resonance imaging techniques in mental disorders.

Methods

The systematic search was performed on PubMed/Medline, EBSCOhost/PsycArticles, Web of Science, and The Cochrane Library databases during November 2021 following the PRISMA guidelines. Risk of bias was evaluated by employing the checklists for cross-sectional and case-control studies from Joanna Briggs Institute (JBI) Reviewers Manual.

Results

Out of 353 de-duplicated publications identified, six studies were included in this review. These studies were identified as representing two research themes: (1) brain anatomy and psychophysiological response to mental stress in individuals with mental disorders, and (2) brain activity and psychophysiological response to mental stress in individuals with mental disorders.

Conclusions

Overall, the evidence from studies exploring the interplay between stress psychophysiology and neural correlates in mental disorders is limited and heterogeneous. Further studies are warranted to better understand the mechanisms of how psychophysiological stress markers interplay with neural correlates in manifestation and progression of psychiatric illnesses.

The heterogeneity of attenuated and brief limited psychotic symptoms: association of contents with age, sex, country, religion, comorbidities, and functioning

Introduction

The Attenuated Psychosis Symptoms (APS) syndrome mostly represents the ultra-high-risk state of psychosis but, as does the Brief Intermittent Psychotic Symptoms (BIPS) syndrome, shows a large variance in conversion rates. This may be due to the heterogeneity of APS/BIPS that may be related to the effects of culture, sex, age, and other psychiatric morbidities. Thus, we investigated the different thematic contents of APS and their association with sex, age, country, religion, comorbidity, and functioning to gain a better understanding of the psychosis-risk syndrome.

Method

A sample of 232 clinical high-risk subjects according to the ultra-high risk and basic symptom criteria was recruited as part of a European study conducted in Germany, Italy, Switzerland, and Finland. Case vignettes, originally used for supervision of inclusion criteria, were investigated for APS/BIPS contents, which were compared for sex, age, country, religion, functioning, and comorbidities using chi-squared tests and regression analyses.

Result

We extracted 109 different contents, mainly of APS (96.8%): 63 delusional, 29 hallucinatory, and 17 speech-disorganized contents. Only 20 contents (18.3%) were present in at least 5% of the sample, with paranoid and referential ideas being the most frequent. Thirty-one (28.5%) contents, in particular, bizarre ideas and perceptual abnormalities, demonstrated an association with age, country, comorbidity, or functioning, with regression models of country and obsessive-compulsive disorders explaining most of the variance: 55.8 and 38.3%, respectively. Contents did not differ between religious groups.

Conclusion

Psychosis-risk patients report a wide range of different contents of APS/BIPS, underlining the psychopathological heterogeneity of this group but also revealing a potential core set of contents. Compared to earlier reports on North-American samples, our maximum prevalence rates of contents were considerably lower; this likely being related to a stricter rating of APS/BIPS and cultural influences, in particular, higher schizotypy reported in North-America. The various associations of some APS/BIPS contents with country, age, comorbidities, and functioning might moderate their clinical severity and, consequently, the related risk for psychosis and/or persistent functional disability.

Geometric Reliability of Super-Resolution Reconstructed Images from Clinical Fetal MRI in the Second Trimester

Fetal Magnetic Resonance Imaging (MRI) is an important noninvasive diagnostic tool to characterize the central nervous system (CNS) development, significantly contributing to pregnancy management. In clinical practice, fetal MRI of the brain includes the acquisition of fast anatomical sequences over different planes on which several biometric measurements are manually extracted. Recently, modern toolkits use the acquired two-dimensional (2D) images to reconstruct a Super-Resolution (SR) isotropic volume of the brain, enabling three-dimensional (3D) analysis of the fetal CNS.We analyzed 17 fetal MR exams performed in the second trimester, including orthogonal T2-weighted (T2w) Turbo Spin Echo (TSE) and balanced Fast Field Echo (b-FFE) sequences. For each subject and type of sequence, three distinct high-resolution volumes were reconstructed via NiftyMIC, MIALSRTK, and SVRTK toolkits. Fifteen biometric measurements were assessed both on the acquired 2D images and SR reconstructed volumes, and compared using Passing-Bablok regression, Bland-Altman plot analysis, and statistical tests.Results indicate that NiftyMIC and MIALSRTK provide reliable SR reconstructed volumes, suitable for biometric assessments. NiftyMIC also improves the operator intraclass correlation coefficient on the quantitative biometric measures with respect to the acquired 2D images. In addition, TSE sequences lead to more robust fetal brain reconstructions against intensity artifacts compared to b-FFE sequences, despite the latter exhibiting more defined anatomical details.Our findings strengthen the adoption of automatic toolkits for fetal brain reconstructions to perform biometry evaluations of fetal brain development over common clinical MR at an early pregnancy stage.