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Amyloid-β accumulation starts in highly connected brain regions and is associated with functional connectivity alterations in the early stages of Alzheimer's disease. This regional vulnerability is related to the high neuronal activity and strong fluctuations typical of these regions. Recently, dynamic functional connectivity was introduced to investigate changes in functional network organization over time. High dynamic functional connectivity variations indicate increased regional flexibility to participate in multiple subnetworks, promoting functional integration. Currently, only a limited number of studies have explored the temporal dynamics of functional connectivity in the pre-dementia stages of Alzheimer's disease. We study the associations between abnormal cerebrospinal fluid amyloid and both static and dynamic properties of functional hubs, using eigenvector centrality, and their relationship with cognitive performance, in 701 non-demented participants from the European Prevention of Alzheimer's Dementia cohort. Voxel-wise eigenvector centrality was computed for the whole functional magnetic resonance imaging time series (static), and within a sliding window (dynamic). Differences in static eigenvector centrality between amyloid positive (A+) and negative (A-) participants and amyloid-tau groups were found in a general linear model. Dynamic eigenvector centrality standard deviation and range were compared between groups within clusters of significant static eigenvector centrality differences, and within 10 canonical resting-state networks. The effect of the interaction between amyloid status and cognitive performance on dynamic eigenvector centrality variability was also evaluated with linear models. Models were corrected for age, sex, and education level. Lower static centrality was found in A+ participants in posterior brain areas including a parietal and an occipital cluster; higher static centrality was found in a medio-frontal cluster. Lower eigenvector centrality variability (standard deviation) occurred in A+ participants in the frontal cluster. The default mode network and the dorsal visual networks of A+ participants had lower dynamic eigenvector centrality variability. Centrality variability in the default mode network and dorsal visual networks were associated with cognitive performance in the A- and A+ groups, with lower variability being observed in A+ participants with good cognitive scores. Our results support the role and timing of eigenvector centrality alterations in very early stages of Alzheimer's disease and show that centrality variability over time adds relevant information on the dynamic patterns that cause static eigenvector centrality alterations. We propose that dynamic eigenvector centrality is an early biomarker of the interplay between early Alzheimer's disease pathology and cognitive decline., Competing Interests: K.B. has served as a consultant, at advisory boards, or at data monitoring committees for Abcam, Axon, Biogen, JOMDD/Shimadzu. Julius Clinical, Lilly, MagQu, Novartis, Prothena, Roche Diagnostics, and Siemens Healthineers, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (all outside the work presented in this paper). JDG has received speaker’s fees from Biogen and Philips., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

In the new WHO 2021 Classification of CNS Tumors the chapter "Circumscribed astrocytic gliomas, glioneuronal and neuronal tumors" encompasses several different rare tumor entities, which occur more frequently in children, adolescents, and young adults. The Task Force has reviewed the evidence of diagnostic and therapeutic interventions, which is low particularly for adult patients, and draw recommendations accordingly. Tumor diagnosis, based on WHO 2021, is primarily performed using conventional histological techniques; however, a molecular workup is important for differential diagnosis, in particular, DNA methylation profiling for the definitive classification of histologically unresolved cases. Molecular factors are increasing of prognostic and predictive importance. MRI finding are non-specific, but for some tumors are characteristic and suggestive. Gross total resection, when feasible, is the most important treatment in terms of prolonging survival and achieving long-term seizure control. Conformal radiotherapy should be considered in grade 3 and incompletely resected grade 2 tumors. In recurrent tumors reoperation and radiotherapy, including stereotactic radiotherapy, can be useful. Targeted therapies may be used in selected patients: BRAF and MEK inhibitors in pilocytic astrocytomas, pleomorphic xanthoastrocytomas, and gangliogliomas when BRAF altered, and mTOR inhibitor everolimus in subependymal giant cells astrocytomas. Sequencing to identify molecular targets is advocated for diagnostic clarification and to direct potential targeted therapies., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: Gliomas are the most common primary tumour of the central nervous system (CNS), with an estimated annual incidence of 6.6 per 100 000 individuals in the USA and around 14 deaths per day from brain tumours in the UK. The genomic and biological landscape of brain tumours has been increasingly defined and, since 2016, the WHO classification of tumours of the CNS incorporates molecular data, along with morphology, to define tumour subtypes more accurately. The Tessa Jowell BRAIN MATRIX Platform (TJBM) study aims to create a transformative clinical research infrastructure that leverages UK National Health Service resources to support research that is patient centric and attractive to both academic and commercial investors., Methods and Analysis: The TJBM study is a programme of work with the principal purpose to improve the knowledge of glioma and treatment for patients with glioma. The programme includes a platform study and subsequent interventional clinical trials (as separate protocols). The platform study described here is the backbone data-repository of disease, treatment and outcome data from clinical, imaging and pathology data being collected in patients with glioma from secondary care hospitals. The primary outcome measure of the platform is time from biopsy to integrated histological-molecular diagnosis using whole-genome sequencing and epigenomic classification. Secondary outcome measures include those that are process centred, patient centred and framework based. Target recruitment for the study is 1000 patients with interim analyses at 100 and 500 patients., Ethics and Dissemination: The study will be performed in accordance with the recommendations guiding physicians in biomedical research involving human subjects, adopted by the 18th World Medical Association General Assembly, Helsinki, Finland and stated in the respective participating countries' laws governing human research, and Good Clinical Practice. The protocol was initially approved on 18 February 2020 by West Midlands - Edgbaston Research Ethics Committee; the current protocol (v3.0) was approved on 15 June 2022. Participants will be required to provide written informed consent. A meeting will be held after the end of the study to allow discussion of the main results among the collaborators prior to publication. The results of this study will be disseminated through national and international presentations and peer-reviewed publications. Manuscripts will be prepared by the Study Management Group and authorship will be determined by mutual agreement., Trial Registration Number: NCT04274283, 18-Feb-2020; ISRCTN14218060, 03-Feb-2020., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: Multiple sclerosis (MS) is an immune-mediated, neuroinflammatory disease of the central nervous system and in industrialised countries is the most common cause of progressive neurological disability in working age persons. While treatable, there is substantial interindividual heterogeneity in disease activity and response to treatment. Currently, the ability to predict at diagnosis who will have a benign, intermediate or aggressive disease course is very limited. There is, therefore, a need for integrated predictive tools to inform individualised treatment decision making., Participants: Established with the aim of addressing this need for individualised predictive tools, FutureMS is a nationally representative, prospective observational cohort study of 440 adults with a new diagnosis of relapsing-remitting MS living in Scotland at the time of diagnosis between May 2016 and March 2019., Findings to Date: The study aims to explore the pathobiology and determinants of disease heterogeneity in MS and combines detailed clinical phenotyping with imaging, genetic and biomarker metrics of disease activity and progression. Recruitment, baseline assessment and follow-up at year 1 is complete. Here, we describe the cohort design and present a profile of the participants at baseline and 1 year of follow-up., Future Plans: A third follow-up wave for the cohort has recently begun at 5 years after first visit and a further wave of follow-up is funded for year 10. Longer-term follow-up is anticipated thereafter., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Objectives: Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remarkable potential in this area, they may perform poorly in nonoptimal conditions, such as limited training data availability. Manual whole brain segmentation is an incredibly tedious process, so minimizing the data set size required for training segmentation algorithms may be of wide interest. The purpose of this study was to compare the performance of the prototypical deep learning segmentation architecture (U-Net) with a previously published atlas-free traditional machine learning method, Classification using Derivative-based Features (C-DEF) for whole brain segmentation, in the setting of limited training data., Materials and Methods: C-DEF and U-Net models were evaluated after training on manually curated data from 5, 10, and 15 participants in 2 research cohorts: (1) people living with clinically diagnosed HIV infection and (2) relapsing-remitting multiple sclerosis, each acquired at separate institutions, and between 5 and 295 participants' data using a large, publicly available, and annotated data set of glioblastoma and lower grade glioma (brain tumor segmentation). Statistics was performed on the Dice similarity coefficient using repeated-measures analysis of variance and Dunnett-Hsu pairwise comparison., Results: C-DEF produced better segmentation than U-Net in lesion (29.2%-38.9%) and cerebrospinal fluid (5.3%-11.9%) classes when trained with data from 15 or fewer participants. Unlike C-DEF, U-Net showed significant improvement when increasing the size of the training data (24%-30% higher than baseline). In the brain tumor segmentation data set, C-DEF produced equivalent or better segmentations than U-Net for enhancing tumor and peritumoral edema regions across all training data sizes explored. However, U-Net was more effective than C-DEF for segmentation of necrotic/non-enhancing tumor when trained on 10 or more participants, probably because of the inconsistent signal intensity of the tissue class., Conclusions: These results demonstrate that classical machine learning methods can produce more accurate brain segmentation than the far more complex deep learning methods when only small or moderate amounts of training data are available (n ≤ 15). The magnitude of this advantage varies by tissue and cohort, while U-Net may be preferable for deep gray matter and necrotic/non-enhancing tumor segmentation, particularly with larger training data sets (n ≥ 20). Given that segmentation models often need to be retrained for application to novel imaging protocols or pathology, the bottleneck associated with large-scale manual annotation could be avoided with classical machine learning algorithms, such as C-DEF., (Copyright © 2022 Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

Myelin-sensitive MRI such as magnetization transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetization transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetization transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including 'magnetization transfer' and 'brain' for systematic review, according to a pre-defined protocol. Only studies that used human in vivo quantitative magnetization transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesized. Where possible, effect sizes were calculated for meta-analyses to determine magnetization transfer (i) differences between patients and healthy controls; (ii) longitudinal change and (iii) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetization transfer ratio in white matter, but magnetization transfer metrics, brain regions examined and results were heterogeneous. The analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetization transfer ratio was 1.17 per cent units (95% CI -1.42 to -0.91) lower in relapsing-remitting multiple sclerosis than healthy controls ( z -value: -8.99, P < 0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetization transfer ratio across all brain regions [ β = 0.12 (-0.56 to 0.80), t -value = 0.35, P = 0.724, 14 studies] or normal-appearing white matter alone [ β = 0.037 (-0.14 to 0.22), t -value = 0.41, P = 0.68, eight studies]. There was a significant negative association between the magnetization transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale [ r = -0.32 (95% CI -0.46 to -0.17); z -value = -4.33, P < 0.001, 13 studies]. Evidence suggests that magnetization transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonized magnetization transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetization transfer saturation or inhomogeneous magnetization transfer ratio., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Introduction: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination. Magnetic resonance imaging (MRI) can detect disease activity and underlying damage non-invasively in vivo at the micro and macrostructural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study, which focuses on deeply phenotyping patients with recently diagnosed relapsing-remitting MS (RRMS). Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. This paper provides an overview of MRI data acquisition, management and processing in FutureMS. FutureMS is registered with the Integrated Research Application System (IRAS, UK) under reference number 169955. Methods and analysis: MRI is performed at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, FLAIR and proton density images. Primary imaging outcome measures are new/enlarging white matter lesions (WML) and reduction in brain volume over one year. Secondary imaging outcome measures comprise WML volume as an additional quantitative structural MRI measure, rim lesions on susceptibility-weighted imaging, and microstructural MRI measures, including diffusion tensor imaging and neurite orientation dispersion and density imaging metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures. Conclusions: FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression in a large population of RRMS patients in Scotland., Competing Interests: No competing interests were disclosed., (Copyright: © 2022 Meijboom R et al.)

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer's Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features - i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features - Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) - were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Introduction: Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS., Methods: Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained. 3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated. Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values., Results: In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and -0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF., Discussion: G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility., Conclusion: MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: FutureMS, hosted by Precision Medicine Scotland Innovation Centre (PMS-IC) reports financial support was provided by Biogen UK Ltd., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Myelin loss is associated with axonal damage in established multiple sclerosis. This relationship is challenging to study in vivo in early disease. Here, we ask whether myelin loss is associated with axonal damage at diagnosis by combining non-invasive neuroimaging and blood biomarkers. We performed quantitative microstructural MRI and single-molecule ELISA plasma neurofilament measurement in 73 patients with newly diagnosed, immunotherapy naïve relapsing-remitting multiple sclerosis. Myelin integrity was evaluated using aggregate g-ratios, derived from magnetization transfer saturation and neurite orientation dispersion and density imaging diffusion data. We found significantly higher g-ratios within cerebral white matter lesions (suggesting myelin loss) compared with normal-appearing white matter (0.61 versus 0.57, difference 0.036, 95% CI: 0.029-0.043, P < 0.001). Lesion volume (Spearman's rho r s = 0.38, P < 0.001) and g-ratio (r s = 0.24, P < 0.05) correlated independently with plasma neurofilament. In patients with substantial lesion load ( n = 38), those with higher g-ratio (defined as greater than median) were more likely to have abnormally elevated plasma neurofilament than those with normal g-ratio (defined as less than median) [11/23 (48%) versus 2/15 (13%), P < 0.05]. These data suggest that, even at multiple sclerosis diagnosis, reduced myelin integrity is associated with axonal damage. MRI-derived g-ratio may provide useful additional information regarding lesion severity and help to identify individuals with a high degree of axonal damage at disease onset., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: We classified non-demented European Prevention of Alzheimer's Dementia (EPAD) participants through the amyloid/tau/neurodegeneration (ATN) scheme and assessed their neuropsychological and imaging profiles., Materials and Methods: From 1500 EPAD participants, 312 were excluded. Cerebrospinal fluid cut-offs of 1000 pg/mL for amyloid beta (Aß)1-42 and 27 pg/mL for p-tau181 were validated using Gaussian mixture models. Given strong correlation of p-tau and t-tau (R 2  = 0.98, P < 0.001), neurodegeneration was defined by age-adjusted hippocampal volume. Multinomial regressions were used to test whether neuropsychological tests and regional brain volumes could distinguish ATN stages., Results: Age was 65 ± 7 years, with 58% females and 38% apolipoprotein E (APOE) ε4 carriers; 57.1% were A-T-N-, 32.5% were in the Alzheimer's disease (AD) continuum, and 10.4% suspected non-Alzheimer's pathology. Age and cerebrovascular burden progressed with biomarker positivity (P < 0.001). Cognitive dysfunction appeared with T+. Paradoxically higher regional gray matter volumes were observed in A+T-N- compared to A-T-N- (P < 0.001)., Discussion: In non-demented individuals along the AD continuum, p-tau drives cognitive dysfunction. Memory and language domains are affected in the earliest stages., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Objectiv E: To summarise current evidence for the utility of interval imaging in monitoring disease in adult brain tumours, and to develop a position for future evidence gathering while incorporating the application of data science and health economics., Methods: Experts in 'interval imaging' (imaging at pre-planned time-points to assess tumour status); data science; health economics, trial management of adult brain tumours, and patient representatives convened in London, UK. The current evidence on the use of interval imaging for monitoring brain tumours was reviewed. To improve the evidence that interval imaging has a role in disease management, we discussed specific themes of data science, health economics, statistical considerations, patient and carer perspectives, and multi-centre study design. Suggestions for future studies aimed at filling knowledge gaps were discussed., Results: Meningioma and glioma were identified as priorities for interval imaging utility analysis. The "monitoring biomarkers" most commonly used in adult brain tumour patients were standard structural MRI features. Interval imaging was commonly scheduled to provide reported imaging prior to planned, regular clinic visits. There is limited evidence relating interval imaging in the absence of clinical deterioration to management change that alters morbidity, mortality, quality of life, or resource use. Progression-free survival is confounded as an outcome measure when using structural MRI in glioma. Uncertainty from imaging causes distress for some patients and their caregivers, while for others it provides an important indicator of disease activity. Any study design that changes imaging regimens should consider the potential for influencing current or planned therapeutic trials, ensure that opportunity costs are measured, and capture indirect benefits and added value., Conclusion: Evidence for the value, and therefore utility, of regular interval imaging is currently lacking. Ongoing collaborative efforts will improve trial design and generate the evidence to optimise monitoring imaging biomarkers in standard of care brain tumour management., Competing Interests: TB, speaker’s bureau for AbbVie and Siemens Healthineers. Craig Buckley, Head of Research and Innovation – Siemens Healthineers GB&I. JC, BrainMiner Founder. Involved in machine learning enterprise and business. JK, involved in enterprise and business. MM, BrainMiner Founder. Involved in machine learning enterprise and business. SO, BrainMiner Founder. Involved in machine learning enterprise and business. MP, received payment for consultancy work from Merck not related to cancer. AW, unrestricted educational grant, Bayer Schering, consultancy work and honoraria not related to cancer. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Booth, Thompson, Bulbeck, Boele, Buckley, Cardoso, Dos Santos Canas, Jenkinson, Ashkan, Kreindler, Huskens, Luis, McBain, Mills, Modat, Morley, Murphy, Ourselin, Pennington, Powell, Summers, Waldman, Watts, Williams, Grant and Jenkinson.)

Management of symptoms and prevention of life-threatening hemorrhage in immune thrombocytopenia (ITP) must be balanced against adverse effects of therapies. Because current treatment guidelines based on platelet count are confounded by variable bleeding phenotypes, there is a need to identify new objective markers of disease severity for treatment stratification. In this cross-sectional prospective study of 49 patients with ITP and nadir platelet counts <30 × 109/L and 18 aged-matched healthy controls, we used susceptibility-weighted magnetic resonance imaging to detect cerebral microbleeds (CMBs) as a marker of occult hemorrhage. CMBs were detected using a semiautomated method and correlated with clinical metadata using multivariate regression analysis. No CMBs were detected in health controls. In contrast, lobar CMBs were identified in 43% (21 of 49) of patients with ITP; prevalence increased with decreasing nadir platelet count (0/4, ≥15 × 109/L; 2/9, 10-14 × 109/L; 4/11, 5-9 × 109/L; 15/25 <5 × 109/L) and was associated with longer disease duration (P = 7 × 10-6), lower nadir platelet count (P = .005), lower platelet count at time of neuroimaging (P = .029), and higher organ bleeding scores (P = .028). Mucosal and skin bleeding scores, number of previous treatments, age, and sex were not associated with CMBs. Occult cerebral microhemorrhage is common in patients with moderate to severe ITP. Strong associations with ITP duration may reflect CMB accrual over time or more refractory disease. Further longitudinal studies in children and adults will allow greater understanding of the natural history and clinical and prognostic significance of CMBs., (© 2020 by The American Society of Hematology.)

Addiction has been proposed as a 'reward deficient' state, which is compensated for with substance use. There is growing evidence of dysregulation in the opioid system, which plays a key role in reward, underpinning addiction. Low levels of endogenous opioids are implicated in vulnerability for developing alcohol dependence (AD) and high mu-opioid receptor (MOR) availability in early abstinence is associated with greater craving. This high MOR availability is proposed to be the target of opioid antagonist medication to prevent relapse. However, changes in endogenous opioid tone in AD are poorly characterised and are important to understand as opioid antagonists do not help everyone with AD. We used [ 11 C]carfentanil, a selective MOR agonist positron emission tomography (PET) radioligand, to investigate endogenous opioid tone in AD for the first time. We recruited 13 abstinent male AD and 15 control participants who underwent two [ 11 C]carfentanil PET scans, one before and one 3 h following a 0.5 mg/kg oral dose of dexamphetamine to measure baseline MOR availability and endogenous opioid release. We found significantly blunted dexamphetamine-induced opioid release in 5 out of 10 regions-of-interest including insula, frontal lobe and putamen in AD compared with controls, but no significantly higher MOR availability AD participants compared with HC in any region. This study is comparable to our previous results of blunted dexamphetamine-induced opioid release in gambling disorder, suggesting that this dysregulation in opioid tone is common to both behavioural and substance addictions.

Age of onset in multiple sclerosis (MS) exerts an influence on the course of disease. This study examined whether global and regional brain volumes differed between "younger" and "older" onset MS subjects who were matched for short disease duration, mean 1.9 years and burden as measured by the MS Severity Score and relapses. 21 younger-onset MS subjects (age 30.4 ± 3.2 years) were compared with 17 older-onset (age 48.7 ± 3.3 years) as well as age-matched controls ( n  = 31, 31.9 ± 3.5 years and n  = 21, 47.3 ± 4.0 years). All subjects underwent 3D volumetric T1 and T2-FLAIR imaging. White matter (WM) and grey matter (GM) lesions were outlined manually. Lesions were filled prior to tissue and structural segmentation to reduce classification errors. Volume loss versus control was predominantly in the subcortical GM, at > 13% loss. Younger and older-onset MS subjects had similar, strong excess loss in the putamen, thalamus, and nucleus accumbens. No excess loss was detected in the amygdala or pallidum. The hippocampus and caudate showed significant excess loss in the younger group ( p  < 0.001) and a strong trend in the older-onset group. These results provide a potential imaging correlate of published neuropsychological studies that reported the association of younger age at disease onset with impaired cognitive performance, including decreased working memory.

Drug and alcohol dependence are global problems with substantial societal costs. There are few treatments for relapse prevention and therefore a pressing need for further study of brain mechanisms underpinning relapse circuitry. The Imperial College Cambridge Manchester (ICCAM) platform study is an experimental medicine approach to this problem: using functional magnetic resonance imaging (fMRI) techniques and selective pharmacological tools, it aims to explore the neuropharmacology of putative relapse pathways in cocaine, alcohol, opiate dependent, and healthy individuals to inform future drug development. Addiction studies typically involve small samples because of recruitment difficulties and attrition. We established the platform in three centres to assess the feasibility of a multisite approach to address these issues. Pharmacological modulation of reward, impulsivity and emotional reactivity were investigated in a monetary incentive delay task, an inhibitory control task, and an evocative images task, using selective antagonists for µ-opioid, dopamine D3 receptor (DRD3) and neurokinin 1 (NK1) receptors (naltrexone, GSK598809, vofopitant/aprepitant), in a placebo-controlled, randomised, crossover design. In two years, 609 scans were performed, with 155 individuals scanned at baseline. Attrition was low and the majority of individuals were sufficiently motivated to complete all five sessions (n=87). We describe herein the study design, main aims, recruitment numbers, sample characteristics, and explain the test hypotheses and anticipated study outputs., (© The Author(s) 2015.)

Objective: The objectives of this study were to define the range of apparent diffusion coefficients (ADCs) from whole-body DWI in normal abdominal organs and bone marrow, to identify ADC differences between sexes and changes occurring with age, and to evaluate the effect of the fat fraction (FF) on the ADC of normal liver parenchyma and bone marrow., Materials and Methods: Fifty-one healthy volunteers (mean age = 38 years; age range = 23-68 years) underwent whole-body DWI using single-shot echo-planar imaging (b = 0, 150, 400, 750, and 1000 s/mm(2)). A two-point Dixon technique was used to evaluate the FF. Perfusion-sensitive ADCs, which we refer to as "ADCALL," and perfusion-insensitive ADCs, which we refer to as "ADCHIGH," of the liver and renal parenchyma, spleen, pancreatic tail, and red and yellow bone marrow were calculated. The relationships between ADC and sex, age, and FF were examined., Results: ADCALL and ADCHIGH were significantly higher in female volunteers for the pancreatic tail (p = 0.046 and 0.008, respectively), red bone marrow (p = 0.029 and 0.001), and yellow bone marrow (p < 0.001 for both) but with considerable overlap. There were significant negative correlations between ADCALL and ADCHIGH and age in the liver parenchyma (p = 0.008 and 0.01, respectively) and in the yellow bone marrow (p = 0.013 and 0.039) for all subjects. ADCALL and ADCHIGH were also negatively correlated with FF in the liver parenchyma (p = 0.006 and 0.008, respectively) and in yellow bone marrow (p < 0.001 and p = 0.001) in all subjects., Conclusion: The ADCs of normal liver parenchyma and bone marrow change significantly with age. The ADCs of bone marrow in women are significantly higher than those of men and correlate strongly with FF. These effects may have an impact on image interpretation when using whole-body DWI to assess disease burden and treatment response.

The most accurate predictor of the subsequent development of multiple sclerosis in clinically isolated syndrome is the presence of lesions at magnetic resonance imaging. We used in vivo positron emission tomography with (11)C-(R)-PK11195, a biomarker of activated microglia, to investigate the normal-appearing white matter and grey matter of subjects with clinically isolated syndrome to explore its role in the development of multiple sclerosis. Eighteen clinically isolated syndrome and eight healthy control subjects were recruited. Baseline assessment included: history, neurological examination, expanded disability status scale, magnetic resonance imaging and PK11195-positron emission tomography scans. All assessments except the PK11195-positron emission tomography scan were repeated over 2 years. SUPERPK methodology was used to measure the binding potential relative to the non-specific volume, BPND. We show a global increase of normal-appearing white matter PK11195 BPND in clinically isolated syndrome subjects compared with healthy controls (P = 0.014). Clinically isolated syndrome subjects with T2 magnetic resonance imaging lesions had higher PK11195 BPND in normal-appearing white matter (P = 0.009) and their normal-appearing white matter PK11195 BPND correlated with the Expanded Disability Status Scale (P = 0.007; r = 0.672). At 2 years those who developed dissemination in space or multiple sclerosis, had higher PK11195 BPND in normal-appearing white matter at baseline (P = 0.007 and P = 0.048, respectively). Central grey matter PK11195 BPND was increased in subjects with clinically isolated syndrome compared to healthy controls but no difference was found in cortical grey matter PK11195 BPND. Microglial activation in clinically isolated syndrome normal-appearing white matter is diffusely increased compared with healthy control subjects and is further increased in those who have magnetic resonance imaging lesions. Furthermore microglial activation in clinically isolated syndrome normal-appearing white matter is also higher in those subjects who developed multiple sclerosis at 2 years. Our finding, if replicated in a larger study, could be of prognostic value and aid early treatment decisions in clinically isolated syndrome., (© The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

This study aimed to replicate a previous study which showed that endogenous opioid release, following an oral dose of amphetamine, can be detected in the living human brain using [11C]carfentanil positron emission tomography (PET) imaging. Nine healthy volunteers underwent two [11C]carfentanil PET scans, one before and one 3 h following oral amphetamine administration (0.5 mg/kg). Regional changes in [11C]carfentanil BPND from pre- to post-amphetamine were assessed. The amphetamine challenge led to significant reductions in [11C]carfentanil BPND in the putamen, thalamus, frontal lobe, nucleus accumbens, anterior cingulate, cerebellum and insula cortices, replicating our earlier findings. None of the participants experienced significant euphoria/'high', supporting the use of oral amphetamine to characterize in vivo endogenous opioid release following a pharmacological challenge. [11C]carfentanil PET is able to detect changes in binding following an oral amphetamine challenge that reflects endogenous opioid release and is suitable to characterize the opioid system in neuropsychiatric disorders.

Following bilateral vestibular loss (BVL) patients gradually adapt to the loss of vestibular input and rely more on other sensory inputs. Here we examine changes in the way proprioceptive and visual inputs interact. We used functional magnetic resonance imaging (fMRI) to investigate visual responses in the context of varying levels of proprioceptive input in 12 BVL subjects and 15 normal controls. A novel metal-free vibrator was developed to allow vibrotactile neck proprioceptive input to be delivered in the MRI system. A high level (100 Hz) and low level (30 Hz) control stimulus was applied over the left splenius capitis; only the high frequency stimulus generates a significant proprioceptive stimulus. The neck stimulus was applied in combination with static and moving (optokinetic) visual stimuli, in a factorial fMRI experimental design. We found that high level neck proprioceptive input had more cortical effect on brain activity in the BVL patients. This included a reduction in visual motion responses during high levels of proprioceptive input and differential activation in the midline cerebellum. In early visual cortical areas, the effect of high proprioceptive input was present for both visual conditions but in lateral visual areas, including V5/MT, the effect was only seen in the context of visual motion stimulation. The finding of a cortical visuo-proprioceptive interaction in BVL patients is consistent with behavioural data indicating that, in BVL patients, neck afferents partly replace vestibular input during the CNS-mediated compensatory process. An fMRI cervico-visual interaction may thus substitute the known visuo-vestibular interaction reported in normal subject fMRI studies. The results provide evidence for a cortical mechanism of adaptation to vestibular failure, in the form of an enhanced proprioceptive influence on visual processing. The results may provide the basis for a cortical mechanism involved in proprioceptive substitution of vestibular function in BVL patients.

Magnetic resonance imaging (MRI) provides essential information on anatomical location and morphology for diagnosis, therapy planning, and treatment evaluation in brain tumors, but lacks biological specificity. "Advanced" quantitative MRI methods yield additional metabolic and physiological indices relevant to tumor growth, vasculature, and ultrastructure; these improve lesion characterization and delineation, and provide potential biomarkers of treatment susceptibility and response. Validation and standardization of relevant parameters is required for use across multiple centers for large scale clinical trials of novel therapeutic regimens and to guide clinical management of individual patients.

Purpose: To prospectively perform longitudinal magnetic resonance (MR) perfusion imaging of conservatively treated low-grade gliomas to determine whether relative cerebral blood volume (rCBV) changes precede malignant transformation as defined by conventional MR imaging and clinical criteria., Materials and Methods: All patients gave written informed consent for this institutional ethics committee-approved study. Thirteen patients (seven men, six women; age range, 29-69 years) with biopsy-proved low-grade glioma treated only with antiepileptic drugs were examined longitudinally with susceptibility-weighted perfusion, T2-weighted, fluid-attenuated inversion recovery, and high-dose contrast material-enhanced T1-weighted MR imaging at 6-month intervals to date or until malignant transformation was diagnosed. Student t tests were used to determine differences in rCBV values between "transformers" and "nontransformers" at defined time points throughout study follow-up., Results: Seven patients showed progression to high-grade tumors between 6 and 36 months (mean, 22.3 months), and disease in six patients remained stable over a period of 12-36 months (mean, 23 months). Transformers had a slightly (but not statistically significantly) higher group mean rCBV than nontransformers at the point of study entry (1.93 vs 1.31). In nontransformers, the rCBV remained relatively stable and increased to only 1.52 over a mean follow-up of 23 months. In contrast, transformers showed a continuous increase in rCBV up to the point of transformation, when contrast enhancement became apparent on T1-weighted images. The group mean rCBV was 5.36 at transformation but also showed a significant increase from the initial study at 12 months (3.14, P = .022) and at 6 months (3.65, P = .049) before transformation. Rates of rCBV change between two successive time points were also significantly higher in transformers than in nontransformers., Conclusion: In transforming low-grade glioma, susceptibility-weighted MR perfusion imaging can demonstrate significant increases in rCBV up to 12 months before contrast enhancement is apparent on T1-weighted MR images.

We report the case of malignant oligodendroglioma in a 36-year-old man who underwent diffusion-weighted, perfusion-weighted, and volumetric MR imaging before and after PCV (procarbazine, CCNU, vincristine) chemotherapy. The tumor regions exhibiting a low apparent diffusion coefficient and increased relative cerebral blood volume showed a marked response to chemotherapy and dramatic decrease in volume, whereas the remaining tumor regions showed little change. Diffusion-weighted and perfusion-weighted MR imaging may be helpful in predicting chemosensitivity of glial tumors.