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Cannabis use disorder (CUD) is associated with adverse mental health effects, as well as social and cognitive impairment. Given prevalence rates of CUD are increasing, there is considerable efforts, and need, to identify prognostic markers which may aid in minimising any harm associated with this condition. Previous neuroimaging studies have revealed changes in white matter (WM) organization in people with CUD, though, the findings are mixed. In this study, we applied MRI-based analysis techniques that offer complimentary mechanistic insights, i.e., a connectome approach and fixel-based analysis (FBA) to investigate properties of individual WM fibre populations and their microstructure across the entire brain, providing a highly sensitive approach to detect subtle changes and overcome limitations of previous diffusion models. We compared 56 individuals with CUD (median age 25 years) to a sample of 38 healthy individuals (median age 31.5 years). Compared to controls, those with CUD had significantly increased structural connectivity strength (FDR corrected) across 9 edges between the right parietal cortex and several cortical and subcortical regions, including left orbitofrontal, left temporal pole, and left hippocampus and putamen. Utilizing FBA, WM density was significantly higher in those with CUD (FWE-corrected) across the splenium of the corpus callosum, and lower in the bilateral cingulum and right cerebellum. We observed significant correlation between cannabis use over the past month and connectivity strength of the frontoparietal edge, and between age of regular use and WM density of the bilateral cingulum and right cerebellum. Our findings enhance the understanding of WM architecture alterations associated with CUD., (© 2024. The Author(s).)

Multiple lines of research support the dysconnectivity hypothesis of schizophrenia. However, findings on white matter (WM) alterations in patients with schizophrenia are widespread and non-specific. Confounding factors from magnetic resonance image (MRI) processing, clinical diversity, antipsychotic exposure, and substance use may underlie some of the variability. By application of refined methodology and careful sampling, we rectified common confounders investigating WM and symptom correlates in a sample of strictly antipsychotic-naïve first-episode patients with schizophrenia. Eighty-six patients and 112 matched controls underwent diffusion MRI. Using fixel-based analysis (FBA), we extracted fibre-specific measures such as fibre density and fibre-bundle cross-section. Group differences on fixel-wise measures were examined with multivariate general linear modelling. Psychopathology was assessed with the Positive and Negative Syndrome Scale. We separately tested multivariate correlations between fixel-wise measures and predefined psychosis-specific versus anxio-depressive symptoms. Results were corrected for multiple comparisons. Patients displayed reduced fibre density in the body of corpus callosum and in the middle cerebellar peduncle. Fibre density and fibre-bundle cross-section of the corticospinal tract were positively correlated with suspiciousness/persecution, and negatively correlated with delusions. Fibre-bundle cross-section of isthmus of corpus callosum and hallucinatory behaviour were negatively correlated. Fibre density and fibre-bundle cross-section of genu and splenium of corpus callosum were negative correlated with anxio-depressive symptoms. FBA revealed fibre-specific properties of WM abnormalities in patients and differentiated associations between WM and psychosis-specific versus anxio-depressive symptoms. Our findings encourage an itemised approach to investigate the relationship between WM microstructure and clinical symptoms in patients with schizophrenia., (© 2023. The Author(s).)

Background and Purpose: While brain iron dysregulation has been observed in several neurodegenerative disorders, its association with the progressive neurodegeneration in Niemann-Pick type C is unknown. Systemic iron abnormalities have been reported in patients with Niemann-Pick type C and in animal models of Niemann-Pick type C. In this study, we examined brain iron using quantitative susceptibility mapping MR imaging in individuals with Niemann-Pick type C compared with healthy controls., Materials and Methods: A cohort of 10 patients with adolescent- and adult-onset Niemann-Pick type C and 14 age- and sex-matched healthy controls underwent 7T brain MR imaging with T1 and quantitative susceptibility mapping acquisitions. A probing whole-brain voxelwise comparison of quantitative susceptibility mapping between groups was conducted. Mean quantitative susceptibility mapping in the ROIs (thalamus, hippocampus, putamen, caudate nucleus, and globus pallidus) was further compared. The correlations between regional volume, quantitative susceptibility mapping values, and clinical features, which included disease severity on the Iturriaga scale, cognitive function, and the Social and Occupational Functioning Assessment Scale, were explored as secondary analyses., Results: We observed lower volume in the thalamus and voxel clusters of higher quantitative susceptibility mapping in the pulvinar nuclei bilaterally in patients with Niemann-Pick type C compared with the control group. In patients with Niemann-Pick type C, higher quantitative susceptibility mapping in the pulvinar nucleus clusters correlated with lower volume of the thalamus on both sides. Moreover, higher quantitative susceptibility mapping in the right pulvinar cluster was associated with greater disease severity., Conclusions: Our findings suggest iron deposition in the pulvinar nucleus in Niemann-Pick type C disease, which is associated with thalamic atrophy and disease severity. This preliminary evidence supports the link between iron and neurodegeneration in Niemann-Pick type C, in line with existing literature on other neurodegenerative disorders., (© 2023 by American Journal of Neuroradiology.)

Preclinical studies of remote degeneration have largely focused on brain changes over the first few days or weeks after stroke. Accumulating evidence suggests that neurodegeneration occurs in other brain regions remote to the site of infarction for months and even years following ischaemic stroke. Brain atrophy appears to be driven by both axonal degeneration and widespread brain inflammation. The evolution and duration of these changes are increasingly being described in human studies, using advanced brain imaging techniques. Here, we sought to investigate long-term structural brain changes in a model of mild focal ischaemic stroke following injection of endothlin-1 in adult Long-Evans rats ( n  = 14) compared with sham animals ( n  = 10), over a clinically relevant time-frame of 48 weeks. Serial structural and diffusion-weighted MRI data were used to assess dynamic volume and white matter trajectories. We observed dynamic regional brain volume changes over the 48 weeks, reflecting both normal changes with age in sham animals and neurodegeneration in regions connected to the infarct following ischaemia. Ipsilesional cortical volume loss peaked at 24 weeks but was less prominent at 36 and 48 weeks. We found significantly reduced fractional anisotropy in both ipsi- and contralesional motor cortex and cingulum bundle regions of infarcted rats ( P  < 0.05) from 4 to 36 weeks, suggesting ongoing white matter degeneration in tracts connected to but distant from the stroke. We conclude that there is evidence of significant cortical atrophy and white matter degeneration up to 48 weeks following infarct, consistent with enduring, pervasive stroke-related degeneration., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: Validated clinical prediction models of short-term remission in psychosis are lacking. Our aim was to develop a clinical prediction model aimed at predicting 4-6-week remission following a first episode of psychosis., Method: Baseline clinical data from the Athens First Episode Research Study was used to develop a Support Vector Machine prediction model of 4-week symptom remission in first-episode psychosis patients using repeated nested cross-validation. This model was further tested to predict 6-week remission in a sample of two independent, consecutive Danish first-episode cohorts., Results: Of the 179 participants in Athens, 120 were male with an average age of 25.8 years and average duration of untreated psychosis of 32.8 weeks. 62.9% were antipsychotic-naïve. Fifty-seven percent attained remission after 4 weeks. In the Danish cohort, 31% attained remission. Eleven clinical scale items were selected in the Athens 4-week remission cohort. These included the Duration of Untreated Psychosis, Personal and Social Performance Scale, Global Assessment of Functioning and eight items from the Positive and Negative Syndrome Scale. This model significantly predicted 4-week remission status (area under the receiver operator characteristic curve (ROC-AUC) = 71.45, P < .0001). It also predicted 6-week remission status in the Danish cohort (ROC-AUC = 67.74, P < .0001), demonstrating reliability., Conclusions: Using items from common and validated clinical scales, our model significantly predicted early remission in patients with first-episode psychosis. Although replicated in an independent cohort, forward testing between machine learning models and clinicians' assessment should be undertaken to evaluate the possible utility as a routine clinical tool., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: Psychosis spectrum disorders are associated with cerebral changes, but the prognostic value and clinical utility of these findings are unclear. Here, we applied a multivariate statistical model to examine the predictive accuracy of global white matter fractional anisotropy (FA) for transition to psychosis in individuals at ultra-high risk for psychosis (UHR)., Methods: 110 UHR individuals underwent 3 Tesla diffusion-weighted imaging and clinical assessments at baseline, and after 6 and 12 months. Using logistic regression, we examined the reliability of global FA at baseline as a predictor for psychosis transition after 12 months. We tested the predictive accuracy, sensitivity and specificity of global FA in a multivariate prediction model accounting for potential confounders to FA (head motion in scanner, age, gender, antipsychotic medication, parental socioeconomic status and activity level). In secondary analyses, we tested FA as a predictor of clinical symptoms and functional level using multivariate linear regression., Results: Ten UHR individuals had transitioned to psychosis after 12 months (9%). The model reliably predicted transition at 12 months (χ 2  = 17.595, p = 0.040), accounted for 15-33% of the variance in transition outcome with a sensitivity of 0.70, a specificity of 0.88 and AUC of 0.87. Global FA predicted level of UHR symptoms (R 2  = 0.055, F = 6.084, p = 0.016) and functional level (R 2  = 0.040, F = 4.57, p = 0.036) at 6 months, but not at 12 months., Conclusion: Global FA provided prognostic information on clinical outcome and symptom course of UHR individuals. Our findings suggest that the application of prediction models including neuroimaging data can inform clinical management on risk for psychosis transition., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Aim: Growing evidence suggests that subtle white matter (WM) alterations are associated with psychopathology in individuals at ultra-high risk for psychosis (UHR). However, the longitudinal relationship between symptom progression and WM changes over time remains under-explored. Here, we examine associations between changes in clinical symptoms and changes in WM over six months in a large UHR-cohort., Methods: 110 UHR-individuals and 59 healthy controls underwent diffusion weighted imaging at baseline and after six months. Group × time effects on fractional anisotropy (FA) were tested globally and in four predefined regions of interest (ROIs) bilaterally using linear modelling with repeated measures. Correlations between the changes in clinical symptoms and FA changes in the ROIs were examined with Pearson's correlation. A partial least squares correlation-technique (PLS-C) explored multivariate associations between patterns of changes in psychopathology, regional FA and additional WM indices., Results: At baseline, UHR-individuals displayed significantly lower FA globally (p = 0.018; F = 12.274), in right superior longitudinal fasciculus (p = 0.02; Adj R 2  = 0.07) and in left uncinate fasciculus (p = 0.048; Adj R 2  = 0.058) compared to controls (corrected). We identified a group × time interaction in global FA and right superior longitudinal fasciculus, but the finding did not survive multiple comparisons. However, an increase of negative symptoms in UHR-individuals correlated with FA increase in right superior longitudinal fasciculus (p = 0.048, corrected, r = 0.357), and this finding was supported by the multivariate PLS-C., Conclusion: We found a positive correlation with a moderate effect between change in negative symptoms and FA change over 6 months in right superior longitudinal fasciculus. This link appeared mainly to reflect a subgroup of UHR-individuals, which already at baseline presented as vulnerable., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

23 Na provides the second strongest MR-observable signal in biological tissue and exhibits bi-exponential T 2 ∗ relaxation in micro-environments such as the brain. There is significant interest in developing 23 Na biomarkers for neurological diseases that are associated with sodium channel dysfunction such as multiple sclerosis and epilepsy. We have previously reported methods for acquisition of multi-echo sodium MRI and continuous distribution modelling of sodium relaxation properties as surrogate markers of brain microstructure. This study aimed to compare 23 Na T 2 ∗ relaxation times to more established measures of tissue microstructure derived from advanced diffusion MRI at 7 ​T. Six healthy volunteers were scanned using a 3D multi-echo radial ultra-short TE sequence using a dual-tuned 1 H/ 23 Na birdcage coil, and a high-resolution multi-shell, high angular resolution diffusion imaging sequence using a 32-channel 1 H receive coil. 23 Na T 2 ∗ relaxation parameters [mean T 2 ∗ (T 2 ∗ mean ) and fast relaxation fraction (T 2 ∗ ff )] were calculated from a voxel-wise continuous gamma distribution signal model. White matter (restricted anisotropic diffusion) and grey matter (restricted isotropic diffusion) density were calculated from multi-shell multi-tissue constrained spherical deconvolution. Sodium parameters were compared with white and grey matter diffusion properties. Sodium T 2 ∗ mean and T 2 ∗ ff showed little variation across a range of white matter axonal fibre and grey matter densities. We conclude that sodium T 2 ∗ relaxation parameters are not greatly influenced by relative differences in intra- and extracellular partial volumes. We suggest that care be taken when interpreting sodium relaxation changes in terms of tissue microstructure in healthy tissue., Competing Interests: Declaration of competing interest The authors report no conflicts of interest relating to this work., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: Parameter mapping in sodium MRI data is challenging due to inherently low SNR and spatial resolution, prompting the need to employ robust models and estimation techniques. This work aims to develop a continuum model of sodium T 2 * -decay to overcome the limitations of the commonly employed bi-exponential models. Estimates of mean T 2 * -decay and fast component fraction in tissue are emergent from the inferred continuum model., Methods: A closed-form continuum model was derived assuming a gamma distribution of T 2 * components. Sodium MRI was performed on four healthy human subjects and a phantom consisting of closely packed vials filled with an aqueous solution of varying sodium and agarose concentrations. The continuum model was applied to the phantom and in vivo human multi-echo 7T data. Parameter maps by voxelwise model-fitting were obtained., Results: The continuum model demonstrated comparable estimation performance to the bi-exponential model. The parameter maps provided improved contrast between tissue structures. The fast component fraction, an indicator of the heterogeneity of localised sodium motion regimes in tissue, was zero in CSF and high in WM structures., Conclusions: The continuum distribution model provides high quality, high contrast parameter maps, and informative voxelwise estimates of the relative weighting between fast and slow decay components., (© 2019 International Society for Magnetic Resonance in Medicine.)