Unraveling the relations between post-traumatic stress symptoms, neurocognitive functioning, and limbic white matter in pediatric brain tumor patients.

Background: Pediatric brain tumor patients are at risk of developing neurocognitive impairments and associated white matter alterations. In other populations, post-traumatic stress symptoms (PTSS) impact cognition and white matter. This study aims to investigate the effect of PTSS on neurocognitive functioning and limbic white matter in pediatric brain tumor patients. Methods: Sixty-six patients (6-16 years) completed neuropsychological assessment and brain MRI (1-year post-diagnosis) and parents completed PTSS proxy questionnaires (CRIES-13; 1-3 months and 1-year post-diagnosis). Mean Z-scores and percentage impaired (>1SD) for attention, processing speed, executive functioning, and memory were compared to normscores (t-tests, chi-square tests). Multi-shell diffusion MRI data were analyzed for white matter tractography (fractional anisotropy/axial diffusivity). Effects of PTSS on neurocognition and white matter were explored with linear regression models (FDR correction for multiple testing), including age at diagnosis, treatment intensity, and tumor location as covariates. Neurocognition and limbic white matter associations were explored with correlations. Results: Attention (M = -0.49, 33% impaired; P < .05) and processing speed (M = -0.57, 34% impaired; P < .05) were significantly lower than healthy peers. PTSS was associated with poorer processing speed (ß = -0.64, P < .01). Treatment intensity, age at diagnosis, and tumor location, but not PTSS, were associated with limbic white matter metrics. Neurocognition and white matter metrics were not associated. Conclusions: Higher PTSS was associated with poorer processing speed, highlighting the need for monitoring, and timely referrals to optimize psychological well-being and neurocognitive functioning. Future research should focus on longitudinal follow-up and explore the impact of PTSS interventions on neurocognitive performance.

Integration of a peer practitioner in a hospital unit for patients with psychotic disorders: an exploratory qualitative study.

Introduction: Studies on the integration of peer mental health practitioners (PMHP) in hospitals are sparse, despite significant benefits being reported for patients and professionals. The integration of PMHP requires the consideration of several parameters and a change in the culture of care. This study aims to understand the impact of the integration of a PMHP in a hospital unit caring for patients with psychiatric disorders. Methods: A qualitative content analysis of three focus groups with the interdisciplinarity team were conducted. A consulting PMHP was integrated into the entire research process. Results: Data analysis revealed five main themes: the importance of integration, benefits for patients linked to the identification process, benefits for the team and institution, potentials risks, and perspectives. Discussion: The study was conducted in a hospital setting with patients suffering from severe psychiatric disorders associated with behavioral disturbances. The benefits reported in the results outline the feasibility of PMHP integration in an acute psychiatric care setting. Nevertheless, further formalization of the PMHP role is required to minimize possible areas of tension between respective fields of activity of each professional.

Improved sensitivity and precision in multicentre diffusion MRI network analysis using thresholding and harmonization.

PURPOSE: To investigate if network thresholding and raw data harmonization improve consistency of diffusion MRI (dMRI)-based brain networks while also increasing precision and sensitivity to detect disease effects in multicentre datasets. METHODS: Brain networks were reconstructed from dMRI of five samples with cerebral small vessel disease (SVD; 629 patients, 166 controls), as a clinically relevant exemplar condition for studies on network integrity. We evaluated consistency of network architecture in age-matched controls, by calculating cross-site differences in connection probability and fractional anisotropy (FA). Subsequently we evaluated precision and sensitivity to disease effects by identifying connections with low FA in sporadic SVD patients relative to controls, using more severely affected patients with a pure form of genetically defined SVD as reference. RESULTS: In controls, thresholding and harmonization improved consistency of network architecture, minimizing cross-site differences in connection probability and FA. In patients relative to controls, thresholding improved precision to detect disrupted connections by removing false positive connections (precision, before: 0.09-0.19; after: 0.38-0.70). Before harmonization, sensitivity was low within individual sites, with few connections surviving multiple testing correction (k = 0-25 connections). Harmonization and pooling improved sensitivity (k = 38), while also achieving higher precision when combined with thresholding (0.97). CONCLUSION: We demonstrated that network consistency, precision and sensitivity to detect disease effects in SVD are improved by thresholding and harmonization. We recommend introducing these techniques to leverage large existing multicentre datasets to better understand the impact of disease on brain networks.

Impact of thresholding on the consistency and sensitivity of diffusion MRI-based brain networks in patients with cerebral small vessel disease.

INTRODUCTION: Thresholding of low-weight connections of diffusion MRI-based brain networks has been proposed to remove false-positive connections. It has been previously established that this yields more reproducible scan-rescan network architecture in healthy subjects. In patients with brain disease, network measures are applied to assess inter-individual variation and changes over time. Our aim was to investigate whether thresholding also achieves improved consistency in network architecture in patients, while maintaining sensitivity to disease effects for these applications. METHODS: We applied fixed-density and absolute thresholding on brain networks in patients with cerebral small vessel disease (SVD, n = 86; ≈24 months follow-up), as a clinically relevant exemplar condition. In parallel, we applied the same methods in healthy young subjects (n = 44; scan-rescan interval ≈4 months) as a frame of reference. Consistency of network architecture was assessed with dice similarity of edges and intraclass correlation coefficient (ICC) of edge-weights and hub-scores. Sensitivity to disease effects in patients was assessed by evaluating interindividual variation, changes over time, and differences between those with high and low white matter hyperintensity burden, using correlation analyses and mixed ANOVA. RESULTS: Compared to unthresholded networks, both thresholding methods generated more consistent architecture over time in patients (unthresholded: dice = .70; ICC: .70-.78; thresholded: dice = .77; ICC: .73-.83). However, absolute thresholding created fragmented nodes. Similar observations were made in the reference group. Regarding sensitivity to disease effects in patients, fixed-density thresholds that were optimal in terms of consistency (densities: .10-.30) preserved interindividual variation in global efficiency and node strength as well as the sensitivity to detect effects of time and group. Absolute thresholding produced larger fluctuations of interindividual variation. CONCLUSIONS: Our results indicate that thresholding of low-weight connections, particularly when using fixed-density thresholding, results in more consistent network architecture in patients with longer rescan intervals, while preserving sensitivity to disease effects.

Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease.

OBJECTIVES: Acquisition-related differences in diffusion magnetic resonance imaging (dMRI) hamper pooling of multicentre data to achieve large sample sizes. A promising solution is to harmonize the raw diffusion signal using rotation invariant spherical harmonic (RISH) features, but this has not been tested in elderly subjects. Here we aimed to establish if RISH harmonization effectively removes acquisition-related differences in multicentre dMRI of elderly subjects with cerebral small vessel disease (SVD), while preserving sensitivity to disease effects. METHODS: Five cohorts of patients with SVD (N = 397) and elderly controls (N = 175) with 3 Tesla MRI on different systems were included. First, to establish effectiveness of harmonization, the RISH method was trained with data of 13 to 15 age and sex-matched controls from each site. Fractional anisotropy (FA) and mean diffusivity (MD) were compared in matched controls between sites using tract-based spatial statistics (TBSS) and voxel-wise analysis, before and after harmonization. Second, to assess sensitivity to disease effects, we examined whether the contrast (effect sizes of FA, MD and peak width of skeletonized MD - PSMD) between patients and controls within each site remained unaffected by harmonization. Finally, we evaluated the association between white matter hyperintensity (WMH) burden, FA, MD and PSMD using linear regression analyses both within individual cohorts as well as with pooled scans from multiple sites, before and after harmonization. RESULTS: Before harmonization, significant differences in FA and MD were observed between matched controls of different sites (p < 0.05). After harmonization these site-differences were removed. Within each site, RISH harmonization did not alter the effect sizes of FA, MD and PSMD between patients and controls (relative change in Cohen's d = 4 %) nor the strength of association with WMH volume (relative change in R2 = 2.8 %). After harmonization, patient data of all sites could be aggregated in a single analysis to infer the association between WMH volume and FA (R2 = 0.62), MD (R2 = 0.64), and PSMD (R2 = 0.60). CONCLUSIONS: We showed that RISH harmonization effectively removes acquisition-related differences in dMRI of elderly subjects while preserving sensitivity to SVD-related effects. This study provides proof of concept for future multicentre SVD studies with pooled datasets.

[Rapid tranquilisation in adults†: algorithm proposed for psychopharmacological treatment]. / Agitation aiguë chez l'adulte†: proposition d'un algorithme de traitement psychopharmacologique.

Acute treatment of agitation in psychiatry is one of the urgent situations for which management recommendations are needed. Various existing international recommendations have been evaluated and adapted to our clinical practice and to the drugs available in Switzerland in order to propose a uniform management strategy in our hospital. This strategy includes a treatment choice algorithm with different options depending on the clinical situation and the possible route of administration. Dose recommendations for the oral and intramuscular routes, certain pharmacokinetic parameters, as well as risks of interactions and important warnings are also included in this clinical recommendation.

Le traitement aigu de l'agitation en psychiatrie fait partie des situations urgentes pour lesquelles des recommandations de prise en charge sont nécessaires. Diverses recommandations internationales existantes ont été évaluées et adaptées à notre pratique clinique ainsi qu'aux médicaments disponibles en Suisse afin de proposer une stratégie de prise en charge uniformisée au sein de notre hôpital. Cette stratégie inclut un algorithme de choix de traitement avec différentes options selon la situation clinique et la voie d'administration possible. Des recommandations de doses pour les voies orale et intramusculaire, certains paramètres pharmacocinétiques, ainsi que les risques d'interactions et des mises en garde importantes figurent également dans cette recommandation clinique.

Effect of Fixed-Density Thresholding on Structural Brain Networks: A Demonstration in Cerebral Small Vessel Disease.

A popular solution to control for edge density variability in structural brain network analysis is to threshold the networks to a fixed density across all subjects. However, it remains unclear how this type of thresholding affects the basic network architecture in terms of edge weights, hub location, and hub connectivity and, especially, how it affects the sensitivity to detect disease-related abnormalities. We investigated these two questions in a cohort of patients with cerebral small vessel disease and age-matched controls. Brain networks were reconstructed from diffusion magnetic resonance imaging data using deterministic fiber tractography. Networks were thresholded to a fixed density by removing edges with the lowest number of streamlines. We compared edge length (mm), fractional anisotropy (FA), proportion of hub connections, and hub location between the unthresholded and the thresholded networks of each subject. Moreover, we compared weighted graph measures of global and local connectivity obtained from the (un)thresholded networks between patients and controls. We performed these analyses over a range of densities (2-20%). Results indicate that fixed-density thresholding disproportionally removes edges composed of long streamlines, but is independent of FA. The edges removed were not preferentially connected to hub or nonhub nodes. Over half of the original hubs were reproducible when networks were thresholded to a density ≥10%. Furthermore, the between-group differences in graph measures observed in the unthresholded network remained present after thresholding, irrespective of the chosen density. We therefore conclude that moderate fixed-density thresholds can successfully be applied to control for the effects of density in structural brain network analysis.

Cortical Microinfarcts and White Matter Connectivity in Memory Clinic Patients.

Background and purpose: Cerebral microinfarcts (CMIs) are associated with cognitive impairment and dementia. CMIs might affect cognitive performance through disruption of cerebral networks. We investigated in memory clinic patients whether cortical CMIs are clustered in specific brain regions and if presence of cortical CMIs is associated with reduced white matter (WM) connectivity in tracts projecting to these regions. Methods:164 memory clinic patients with vascular brain injury with a mean age of 72 ± 11 years (54% male) were included. All underwent 3 tesla MRI, including a diffusion MRI and cognitive testing. Cortical CMIs were rated according to established criteria and their spatial location was marked. Diffusion imaging-based tractography was used to reconstruct WM connections and voxel based analysis (VBA) to assess integrity of WM directly below the cortex. WM connectivity and integrity were compared between patients with and without cortical CMIs for the whole brain and regions with a high CMI burden. Results:30 patients (18%) had at least 1 cortical CMI [range 1-46]. More than 70% of the cortical CMIs were located in the superior frontal, middle frontal, and pre- and postcentral brain regions (covering 16% of the cortical surface). In these high CMI burden regions, presence of cortical CMIs was not associated with WM connectivity after correction for conventional neuroimaging markers of vascular injury. WM connectivity in the whole brain and WM voxels directly underneath the cortical surface did not differ between patients with and without cortical CMIs. Conclusion:Cortical CMIs displayed a strong local clustering in highly interconnected frontal, pre- and postcentral brain regions. Nevertheless, WM connections projecting to these regions were not disproportionally impaired in patients with compared to patients without cortical CMIs. Alternative mechanisms, such as focal disturbances in cortical structure and functioning, may better explain CMI associated cognitive impairment.