612 results found
Suzuki H, Gao H, Bai W, et al., 2017, Hypertension and white matter microstructures in healthy participants in UK Biobank, Publisher: OXFORD UNIV PRESS, Pages: 248-249, ISSN: 0195-668X
Dong H, Supratak A, Pan W, et al., 2017, Mixed neural network approach for temporal sleep stage classification, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 26, Pages: 324-333, ISSN: 1534-4320
This paper proposes a practical approach to addressing limitations posed by using of single-channel electroencephalography (EEG) for sleep stage classification. EEG-based characterizations of sleep stage progression contribute the diagnosis and monitoring of the many pathologies of sleep. Several prior reports explored ways of automating the analysis of sleep EEG and of reducing the complexity of the data needed for reliable discrimination of sleep stages at lower cost in the home. However, these reports have involved recordings from electrodes placed on the cranial vertex or occiput, which are both uncomfortable and difficult to position. Previous studies of sleep stage scoring that used only frontal electrodes with a hierarchical decision tree motivated this paper, in which we have taken advantage of rectifier neural network for detecting hierarchical features and long short-term memory (LSTM) network for sequential data learning to optimize classification performance with single-channel recordings. After exploring alternative electrode placements, we found a comfortable configuration of a single-channel EEG on the forehead and have shown that it can be integrated with additional electrodes for simultaneous recording of the electrooculogram (EOG). Evaluation of data from 62 people (with 494 hours sleep) demonstrated better performance of our analytical algorithm than is available from existing approaches with vertex or occipital electrode placements. Use of this recording configuration with neural network deconvolution promises to make clinically indicated home sleep studies practical.
Edison P, Mayers J, Calsolaro V, et al., 2017, Dementia Platform U.K. Experimental medicine: human in vivo astroglial activation in early Alzheimer’s disease, Alzheimer's and Dementia, Vol: 13, Pages: P1073-P1074, ISSN: 1552-5260
Nie L, Yang X, Matthews PM, et al., 2017, Inferring functional connectivity in fMRI using minimum partial correlation, International Journal of Automation and Computing, Vol: 14, Pages: 371-385, ISSN: 1751-8520
Functional connectivity has emerged as a promising approach to study the functional organisation of the brain and to define features for prediction of brain state. The most widely used method for inferring functional connectivity is Pearson-s correlation, but it cannot differentiate direct and indirect effects. This disadvantage is often avoided by computing the partial correlation between two regions controlling all other regions, but this method suffers from Berkson-s paradox. Some advanced methods, such as regularised inverse covariance, have been applied. However, these methods usually depend on some parameters. Here we propose use of minimum partial correlation as a parameter-free measure for the skeleton of functional connectivity in functional magnetic resonance imaging (fMRI). The minimum partial correlation between two regions is the minimum of absolute values of partial correlations by controlling all possible subsets of other regions. Theoretically, there is a direct effect between two regions if and only if their minimum partial correlation is non-zero under faithfulness and Gaussian assumptions. The elastic PC-algorithm is designed to efficiently approximate minimum partial correlation within a computational time budget. The simulation study shows that the proposed method outperforms o thers in most cases and its application is illustrated using a resting-state fMRI dataset from the human connectome project.
Owen DRJ, Narayan N, Wells L, et al., 2017, Pro-inflammatory activation of primary microglia and macrophages increases 18kDa Translocator Protein (TSPO) expression in rodents but not humans, Journal of Cerebral Blood Flow and Metabolism, Vol: 37, Pages: 2679-2690, ISSN: 1559-7016
The 18kDa Translocator Protein (TSPO) is the most commonly used tissue-specific marker of inflammation in positron emission tomography (PET) studies. It is expressed in myeloid cells such as microglia and macrophages, and in rodent myeloid cells expression increases with cellular activation. We assessed the effect of myeloid cell activation on TSPO gene expression in both primary human and rodent microglia and macrophages in vitro, and also measured TSPO radioligand binding with 3H-PBR28 in primary human macrophages. As observed previously, we found that TSPO expression increases (∼9-fold) in rodent-derived macrophages and microglia upon pro-inflammatory stimulation. However, TSPO expression does not increase with classical pro-inflammatory activation in primary human microglia (fold change 0.85 [95% CI 0.58–1.12], p = 0.47). In contrast, pro-inflammatory activation of human monocyte-derived macrophages is associated with a reduction of both TSPO gene expression (fold change 0.60 [95% CI 0.45–0.74], p = 0.02) and TSPO binding site abundance (fold change 0.61 [95% CI 0.49–0.73], p < 0.0001). These findings have important implications for understanding the biology of TSPO in activated macrophages and microglia in humans. They are also clinically relevant for the interpretation of PET studies using TSPO targeting radioligands, as they suggest changes in TSPO expression may reflect microglial and macrophage density rather than activation phenotype.
Wilman HR, Kelly M, Garratt S, et al., 2017, Correction: Characterisation of liver fat in the UK Biobank cohort, PLoS ONE, Vol: 12, Pages: e0176867-e0176867, ISSN: 1932-6203
[This corrects the article DOI: 10.1371/journal.pone.0172921.].
Gafson A, Craner MJ, Matthews PM, 2017, Personalised medicine for multiple sclerosis care., Multiple Sclerosis Journal, Vol: 23, Pages: 362-369, ISSN: 1477-0970
Treatments with a range of efficacy and risk of adverse events have become available for the management of multiple sclerosis (MS). However, now the heterogeneity of clinical expression and responses to treatment pose major challenges to improving patient care. Selecting and managing the drug best balancing benefit and risk demands a new focus on the individual patient. Personalised medicine for MS is based on improving the precision of diagnosis for each patient in order to capture prognosis and provide an evidence-based framework for predicting treatment response and personalising patient monitoring. It involves development of predictive models involving the integration of clinical and biological data with an understanding of the impact of disease on the lives of individual patients. Here, we provide a brief, selective review of challenges to personalisation of the management of MS and suggest an agenda for stakeholder engagement and research to address them.
Wilman HR, Kelly M, Garratt S, et al., 2017, Characterisation of liver fat in the UK Biobank cohort, PLOS ONE, Vol: 12, ISSN: 1932-6203
Non-alcoholicfattyliverdiseaseandtheriskof progressionto steatohepatitis,cirrhosisandhepatocellularcarcinomahavebeenidentifiedasmajorpublichealthconcerns.Wehavedemonstratedthefeasibilityandpotentialvalueof measuringliverfatcontentbymagneticresonanceimaging(MRI)in a largepopulationin thisstudyof 4,949participants(aged45–73years)in theUKBiobankimagingenhancement. Despiterequirementsforonlya single( 3min)scanof eachsubject,liverfatwasableto bemeasuredastheMRIprotondensityfatfraction(PDFF)withanoverallsuccessrateof 96.4%.Theoverallhepaticfatdistributionwascentredbetween1–2%,andwashighlyskewedtowardshigherfatcontent.ThemeanPDFFwas3.91%,andmedian2.11%.Analysisof PDFFin conjunctionwithotherdatafieldsavailablefromtheUKBiobankResourceshowedassociationsof increasedliverfatwithgreaterage,BMI,weightgain,highbloodpressureandType2 diabetes.SubjectswithBMIlessthan25kg/m2hada lowrisk(5%)of highliverfat(PDFF>5.5%),whereasin thehigherBMIpopulation(>30kg/m2) theprevalenceof highliverfatwasapproximately1 in 3. Thesedatasuggestthatpopulationscreeningto identifypeoplewithhighPDFFis possibleandcouldbecosteffective.MRIbasedPDFFis aneffectivemethodforthis.Finally,althoughcrosssectional,thisstudysuggeststheutilityof thePDFFmeasurement withinUKBiobank,particularlyforapplicationsto elucidatingriskfactorsthroughassociationswithprospec-tivelyacquireddataonclinicaloutcomesof liverdiseases,includingnon-alcoholicfattyliverdisease.
Shenkin SD, Pernet C, Nichols TE, et al., 2017, Improving data availability for brain image biobanking in healthy subjects: Practice-based suggestions from an international multidisciplinary working group, NEUROIMAGE, Vol: 153, Pages: 399-409, ISSN: 1053-8119
Giovannoni G, Cutter G, Sormani MP, et al., 2017, Is multiple sclerosis a length-dependent central axonopathy? The case for therapeutic lag and the asynchronous progressive MS hypotheses., Mult Scler Relat Disord, Vol: 12, Pages: 70-78
Trials of anti-inflammatory therapies in non-relapsing progressive multiple sclerosis (MS) have been stubbornly negative except recently for an anti-CD20 therapy in primary progressive MS and a S1P modulator siponimod in secondary progressive MS. We argue that this might be because trials have been too short and have focused on assessing neuronal pathways, with insufficient reserve capacity, as the core component of the primary outcome. Delayed neuroaxonal degeneration primed by prior inflammation is not expected to respond to disease-modifying therapies targeting MS-specific mechanisms. However, anti-inflammatory therapies may modify these damaged pathways, but with a therapeutic lag that may take years to manifest. Based on these observations we propose that clinically apparent neurodegenerative components of progressive MS may occur in a length-dependent manner and asynchronously. If this hypothesis is confirmed it may have major implications for the future design of progressive MS trials.
Kalk NJ, Guo Q, Owen D, et al., 2017, Decreased hippocampal translocator protein (18 kDa) expression in alcohol dependence: a [(11)C]PBR28 PET study, Translational Psychiatry, Vol: 7, ISSN: 2158-3188
Repeated withdrawal from alcohol is clinically associated with progressive cognitive impairment. Microglial activation occurring during pre-clinical models of alcohol withdrawal is associated with learning deficits. We investigated whether there was microglial activation in recently detoxified alcohol-dependent patients (ADP), using [(11)C]PBR28 positron emission tomography (PET), selective for the 18kDa translocator protein (TSPO) highly expressed in activated microglia and astrocytes. We investigated the relationship between microglial activation and cognitive performance. Twenty healthy control (HC) subjects (45±13; M:F 14:6) and nine ADP (45±6, M:F 9:0) were evaluated. Dynamic PET data were acquired for 90 min following an injection of 331±15 MBq [(11)C]PBR28. Regional volumes of distribution (VT) for regions of interest (ROIs) identified a priori were estimated using a two-tissue compartmental model with metabolite-corrected arterial plasma input function. ADP had an ~20% lower [(11)C]PBR28 VT, in the hippocampus (F(1,24) 5.694; P=0.025), but no difference in VT in other ROIs. Hippocampal [(11)C]PBR28 VT was positively correlated with verbal memory performance in a combined group of HC and ADP (r=0.720, P<0.001), an effect seen in HC alone (r=0.738; P=0.001) but not in ADP. We did not find evidence for increased microglial activation in ADP, as seen pre-clinically. Instead, our findings suggest lower glial density or an altered activation state with lower TSPO expression. The correlation between verbal memory and [(11)C]PBR28 VT, raises the possibility that abnormalities of glial function may contribute to cognitive impairment in ADP.
Poldrack RA, Baker CI, Durnez J, et al., 2017, Scanning the horizon: towards transparent and reproducible neuroimaging research, Nature Reviews Neuroscience, Vol: 18, Pages: 115-126, ISSN: 1471-0048
Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, concerns have recently been raised that the conclusions that are drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors and a lack of direct replication apply to many fields, but perhaps particularly to functional MRI. Here, we discuss these problems, outline current and suggested best practices, and describe how we think the field should evolve to produce the most meaningful and reliable answers to neuroscientific questions.
He S, Yong M, Matthews PM, et al., 2016, tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles., Bioinformatics, Vol: 33, Pages: 787-788, ISSN: 1367-4803
MOTIVATION: TranSMART has a wide range of functionalities for translational research and a large user community, but it does not support imaging data. In this context, imaging data typically includes 2D or 3D sets of magnitude data and metadata information. Imaging data may summarise complex feature descriptions in a less biased fashion than user defined plain texts and numeric numbers. Imaging data also is contextualised by other data sets and may be analysed jointly with other data that can explain features or their variation. RESULTS: Here we describe the tranSMART-XNAT Connector we have developed. This connector consists of components for data capture, organisation and analysis. Data capture is responsible for imaging capture either from PACS system or directly from an MRI scanner, or from raw data files. Data are organised in a similar fashion as tranSMART and are stored in a format that allows direct analysis within tranSMART. The connector enables selection and download of DICOM images and associated resources using subjects' clinical phenotypic and genotypic criteria. AVAILABILITY AND IMPLEMENTATION: tranSMART-XNAT connector is written in Java/Groovy/Grails. It is maintained and available for download at https://github.com/sh107/transmart-xnat-connector.git
Datta G, Violante IR, Scott G, et al., 2016, Translocator positron-emission tomography and magnetic resonance spectroscopic imaging of brain glial cell activation in multiple sclerosis., Multiple Sclerosis, Vol: 23, Pages: 1469-1478, ISSN: 1352-4585
BACKGROUND: Multiple sclerosis (MS) is characterised by a diffuse inflammatory response mediated by microglia and astrocytes. Brain translocator protein (TSPO) positron-emission tomography (PET) and [myo-inositol] magnetic resonance spectroscopy (MRS) were used together to assess this. OBJECTIVE: To explore the in vivo relationships between MRS and PET [(11)C]PBR28 in MS over a range of brain inflammatory burden. METHODS: A total of 23 patients were studied. TSPO PET imaging with [(11)C]PBR28, single voxel MRS and conventional magnetic resonance imaging (MRI) sequences were undertaken. Disability was assessed by Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Functional Composite (MSFC). RESULTS: [(11)C]PBR28 uptake and [ myo-inositol] were not associated. When the whole cohort was stratified by higher [(11)C]PBR28 inflammatory burden, [ myo-inositol] was positively correlated to [(11)C]PBR28 uptake (Spearman's ρ = 0.685, p = 0.014). Moderate correlations were found between [(11)C]PBR28 uptake and both MRS creatine normalised N-acetyl aspartate (NAA) concentration and grey matter volume. MSFC was correlated with grey matter volume (ρ = 0.535, p = 0.009). There were no associations between other imaging or clinical measures. CONCLUSION: MRS [ myo-inositol] and PET [(11)C]PBR28 measure independent inflammatory processes which may be more commonly found together with more severe inflammatory disease. Microglial activation measured by [(11)C]PBR28 uptake was associated with loss of neuronal integrity and grey matter atrophy.
Dichgans M, Wardlaw J, Smith E, et al., 2016, METACOHORTS for the study of vascular disease and its contribution to cognitive decline and neurodegeneration: An initiative of the Joint Programme for Neurodegenerative Disease Research, Alzheimers & Dementia, Vol: 12, Pages: 1235-1249, ISSN: 1552-5260
Dementia is a global problem and major target for health care providers. Although up to 45% of cases are primarily or partly due to cerebrovascular disease, little is known of these mechanisms or treatments because most dementia research still focuses on pure Alzheimer's disease. An improved understanding of the vascular contributions to neurodegeneration and dementia, particularly by small vessel disease, is hampered by imprecise data, including the incidence and prevalence of symptomatic and clinically “silent” cerebrovascular disease, long-term outcomes (cognitive, stroke, or functional), and risk factors. New large collaborative studies with long follow-up are expensive and time consuming, yet substantial data to advance the field are available. In an initiative funded by the Joint Programme for Neurodegenerative Disease Research, 55 international experts surveyed and assessed available data, starting with European cohorts, to promote data sharing to advance understanding of how vascular disease affects brain structure and function, optimize methods for cerebrovascular disease in neurodegeneration research, and focus future research on gaps in knowledge. Here, we summarize the results and recommendations from this initiative. We identified data from over 90 studies, including over 660,000 participants, many being additional to neurodegeneration data initiatives. The enthusiastic response means that cohorts from North America, Australasia, and the Asia Pacific Region are included, creating a truly global, collaborative, data sharing platform, linked to major national dementia initiatives. Furthermore, the revised World Health Organization International Classification of Diseases version 11 should facilitate recognition of vascular-related brain damage by creating one category for all cerebrovascular disease presentations and thus accelerate identification of targets for dementia prevention.
Newbould R, Muraro P, Bishop C, et al., 2016, Analysis of ageing-associated grey matter volume in patients with multiple sclerosis shows excess atrophy in subcortical regions, NeuroImage-Clinical, Vol: 13, Pages: 9-15, ISSN: 2213-1582
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.
Dong H, Matthews P, Guo Y, 2016, A new soft material based in-the-ear EEG recording technique, The 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16), Publisher: IEEE
Long-term electroencephalogram (EEG) is important for seizure detection, sleep monitoring and etc. In-the- ear EEG device makes such recording robust to noise and privacy protected (invisible to other people). However, the state-of-art techniques suffer from various drawbacks such as customization for specific users, manufacturing difficulties and short life cycle. To address these issues, we proposed silvered glass silicone based in-the-ear electrode which can be manufactured using conventional compression moulding. The material and in-the-ear EEG are evaluated separately, showing that the proposed method is durable, low-cost and easy-to-make.
Russo E, Khan S, Janisch R, et al., 2016, Role of 18F-fluorodeoxyglucose Positron Emission Tomography in the Monitoring of Inflammatory Activity in Crohn's Disease., Inflammatory Bowel Diseases, ISSN: 1536-4844
Background: 18Fluorine-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has recently attracted interest for the measurement ofdisease activity in Crohn’s disease (CD). The aim of this study was to assess the utility of FDG-PET as a marker of progression of inflammatory activityand its response to treatment in patients with CD.Methods: Twenty-two patients with active CD were recruited prospectively to undergo FDG-PET scanning at 2 time points. All 22 index scans were used toassess sensitivity and specificity against a reference standard magnetic resonance imaging measure. Correlations with clinicopathological markers of severity(Harvey-Bradshaw Index, C-reactive protein, and calprotectin) were also performed. Of note, 17/22 patients participated in the longitudinal component andunderwent scanning before and 12 weeks after the initiation of anti–tumor necrosis factor alpha therapy. Patients were subcategorized on the basis ofa clinically significant response, and responsiveness of the PET measures was assessed using previously described indices. Of note, 5/22 patients took partin the test–retest component of the study and underwent scanning twice within a target interval of 1 week, to assess the reproducibility of the PET measures.Results: The sensitivity and specificity of 18F-FDG PET were 88% and 70%, respectively. Standardized uptake value (SUV)-related PET measurescorrelated significantly both with C-reactive protein and Harvey-Bradshaw Index in cross-sectional and longitudinal analyses. (G)SUVMAX and (G)SUVMEANdemonstrated favorable responsiveness and reliability characteristics (responsiveness ratio of Guyatt .0.80 and % variability ,20%) compared with volumedependentFDG-PET measures. A proportion of the FDG signal (10%–30%) was found to originate from the lumen of diseased segments.Conclusions: 18F-FDG PET may be useful for longitudinal monitoring of inflammatory activity in CD.
Paley C, Hull H, Ji Y, et al., 2016, Body fat differences by self-reported race/ethnicity in healthy term newborns., Pediatr Obes, Vol: 11, Pages: 361-368
BACKGROUND: Ethnic differences in total body fat (fat mass [FM]) have been reported in adults and children, but the timing of when these differences manifest and whether they are present at birth are unknown. OBJECTIVES: This study aimed to assess whether ethnic differences in body fat are present at birth in healthy infants born at term, where body fat is measured using air displacement plethysmography and fat distribution by skin-fold thickness. METHODS: Data were from a multiracial cross-sectional convenience sample of 332 term infants from four racial or ethnic groups based on maternal self-report (A, Asian; AA, non-Hispanic Black [African-American]; C, non-Hispanic White; and H, Hispanic). The main outcome measure was infant body fat at 1-3 days after birth, with age, birth weight, gestational age and maternal pre-pregnancy weight as covariates. RESULTS: Significant effects for race (P = 0.0011), sex (P = 0.0051) and a race by sex interaction (P = 0.0236) were found. C females had higher FM than C males (P = 0.0001), and AA females had higher FM than AA males (P = 0.0205). C males had less FM than A males (P = 0.0353) and H males (P = 0.0001). CONCLUSION: Race/ethnic and sex differences in FM are present in healthy term newborns. Although the implications of these differences are unclear, studies beginning in utero and birth set the stage for a life course approach to understanding disease later in life.
Ricotti V, Evans MR, Sinclair CD, et al., 2016, Upper Limb Evaluation in Duchenne Muscular Dystrophy: Fat-Water Quantification by MRI, Muscle Force and Function Define Endpoints for Clinical Trials., PLOS One, Vol: 11, ISSN: 1932-6203
OBJECTIVE: A number of promising experimental therapies for Duchenne muscular dystrophy (DMD) are emerging. Clinical trials currently rely on invasive biopsies or motivation-dependent functional tests to assess outcome. Quantitative muscle magnetic resonance imaging (MRI) could offer a valuable alternative and permit inclusion of non-ambulant DMD subjects. The aims of our study were to explore the responsiveness of upper-limb MRI muscle-fat measurement as a non-invasive objective endpoint for clinical trials in non-ambulant DMD, and to investigate the relationship of these MRI measures to those of muscle force and function. METHODS: 15 non-ambulant DMD boys (mean age 13.3 y) and 10 age-gender matched healthy controls (mean age 14.6 y) were recruited. 3-Tesla MRI fat-water quantification was used to measure forearm muscle fat transformation in non-ambulant DMD boys compared with healthy controls. DMD boys were assessed at 4 time-points over 12 months, using 3-point Dixon MRI to measure muscle fat-fraction (f.f.). Images from ten forearm muscles were segmented and mean f.f. and cross-sectional area recorded. DMD subjects also underwent comprehensive upper limb function and force evaluation. RESULTS: Overall mean baseline forearm f.f. was higher in DMD than in healthy controls (p<0.001). A progressive f.f. increase was observed in DMD over 12 months, reaching significance from 6 months (p<0.001, n = 7), accompanied by a significant loss in pinch strength at 6 months (p<0.001, n = 9) and a loss of upper limb function and grip force observed over 12 months (p<0.001, n = 8). CONCLUSIONS: These results support the use of MRI muscle f.f. as a biomarker to monitor disease progression in the upper limb in non-ambulant DMD, with sensitivity adequate to detect group-level change over time intervals practical for use in clinical trials. Clinical validity is supported by the association of the progressive fat transformation of muscle with loss of muscle force and func
Miller KL, Alfaro-Almagro F, Bangerter NK, et al., 2016, Multimodal population brain imaging in the UK Biobank prospective epidemiological study, Nature Neuroscience, Vol: 19, Pages: 1523-1536, ISSN: 1546-1726
Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank.
James A, Joyce E, Lunn D, et al., 2016, Corrigendum to “Abnormal frontostriatal connectivity in adolescent-onset schizophrenia and its relationship to cognitive functioning” [Eur. Psychiatry 35C (2016) 32–38], European Psychiatry, Vol: 38, Pages: 22-22, ISSN: 1778-3585
Gafson AR, Nicholas R, Giovannoni G, et al., 2016, Plasma cytokine concentration changes in multiple sclerosis patients after treatment with dimethyl fumarate, 32nd Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Publisher: SAGE PUBLICATIONS LTD, Pages: 670-671, ISSN: 1352-4585
Matthews PM, 2016, Pharmacological applications of fMRI, Neuromethods, Pages: 817-831
© Springer Science+Business Media New York 2016. Increasing societal expectations for new drugs, lack of confidence in short-term endpoints related to long- term outcomes for chronic neurological and psychiatric diseases and rising costs of development in an increasing cost-constrained market all have created a sense of crisis in CNS drug development. New approaches are needed. For some time, the potential of clinical functional imaging for more confident progression from preclinical to clinical development stages has been recognized. Pharmacological functional MRI (fMRI), which refers specifically to applications of fMRI to questions in drug development, provides one set of these tools. With related structural MRI measures, relatively high resolution data concerning target, disease-relevant pathophysiology and effects of therapeutic interventions can be related to brain functional anatomy. In this chapter, current and potential applications of pharmacological fMRI for target validation, patient stratification and characterization of therapeutic molecule pharmacokinetics and pharmacodynamics are reviewed. Challenges to better realizing the promise of pharmacological fMRI will be discussed. The review concludes that there is a strong rationale for greater use of pharmacological fMRI particularly for early phase studies, but also outlines the need for preclinical and early clinical development to be more seamlessly integrated, for greater harmonization of clinical imaging methodologies and for sharing of data to facilitate these goals.
Datta G, Colasanti A, Kalk NJ, et al., 2016, In vivo translocator protein positron emission tomography imaging detects a heterogeneity of lesion inflammatory activity in multiple sclerosis not evident by MRI., 32nd Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Publisher: SAGE PUBLICATIONS LTD, Pages: 36-37, ISSN: 1352-4585
Lema A, Bishop C, Malik O, et al., 2016, A compararison of magnetization transfer methods to assess brain and cervical cord microstructure in multiple sclerosis, Journal of Neuroimaging, Vol: 27, Pages: 221-226, ISSN: 1552-6569
BACKGROUND: Demyelination is a core pathological feature of multiple sclerosis (MS) and spontaneous remyelination appears to be an important mechanism for repair in the disease. Magnetization transfer ratio imaging (MTR) has been used extensively to evaluate demyelination, although limitations to its specificity are recognized. MT saturation imaging (MTsat) removes some of the T1 dependence of MTR. We have performed a comparative evaluation of MTR and MTsat imaging in a mixed group of subjects with active MS, to explore their relative sensitivity to pathology relevant to explaining clinical outcomes. METHODS: A total of 134 subjects underwent MRI of their brain and cervical spinal cord. Isotropic 3-dimensional pre- and postcontrast T1-weighted and T2-weighted fluid-attenuated inversion recovery (FLAIR) volumes were segmented into brain normal appearing white matter (NAWM), brain WM lesions (WML), normal appearing spinal cord (NASC), and spinal cord lesions. Volumes and metrics for MTR and MTsat histograms were calculated for each region. RESULTS: Significant Spearman correlations were found with the Expanded Disability Status Scale and timed 25-foot walk for the whole brain and WML MTR, but not in that from the NAWM or any cervical spinal cord region. By contrast, the MTsat was correlated with both disability metrics in all these regions in both the brain and spine. CONCLUSIONS: This study extends prior work relating atrophy and lesion load with disability, by characterization of MTsat parameters. MTsat is practical in routine clinical applications and may be more sensitive to tissue damage than MTR for both brain and cervical spinal cord.
Matthews PM, Hampshire A, 2016, Clinical concepts emerging from fMRI functional connectomics, Neuron, Vol: 91, Pages: 511-528, ISSN: 0896-6273
Recent advances in connectomics have led to a synthesis of perspectives regarding the brain's functional organization that reconciles classical concepts of localized specialization with an appreciation for properties that emerge from interactions across distributed functional networks. This provides a more comprehensive framework for understanding neural mechanisms of normal cognition and disease. Although fMRI has not become a routine clinical tool, research has already had important influences on clinical concepts guiding diagnosis and patient management. Here we review illustrative examples. Studies demonstrating the network plasticity possible in adults and the global consequences of even focal brain injuries or disease both have had substantial impact on modern concepts of disease evolution and expression. Applications of functional connectomics in studies of clinical populations are challenging traditional disease classifications and helping to clarify biological relationships between clinical syndromes (and thus also ways of extending indications for, or "re-purposing," current treatments). Large datasets from prospective, longitudinal studies promise to enable the discovery and validation of functional connectomic biomarkers with the potential to identify people at high risk of disease before clinical onset, at a time when treatments may be most effective. Studies of pain and consciousness have catalyzed reconsiderations of approaches to clinical management, but also have stimulated debate about the clinical meaningfulness of differences in internal perceptual or cognitive states inferred from functional connectomics or other physiological correlates. By way of a closing summary, we offer a personal view of immediate challenges and potential opportunities for clinically relevant applications of fMRI-based functional connectomics.
Poldrack RA, Baker CI, Durnez J, et al., 2016, Scanning the Horizon: Towards transparent and reproducible neuroimaging research, Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:p>Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, concerns have recently been raised that the conclusions drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors, and lack of direct replication apply to many fields, but perhaps particularly to fMRI. Here we discuss these problems, outline current and suggested best practices, and describe how we think the field should evolve to produce the most meaningful answers to neuroscientific questions.</jats:p>
Maron E, Near J, Wallis G, et al., 2016, A pilot study of the effect of short-term escitalopram treatment on brain metabolites and gamma-oscillations in healthy subjects, Journal of Psychopharmacology, Vol: 30, Pages: 579-580, ISSN: 1461-7285
Nie L, Matthews PM, Guo Y, 2016, Inferring individual-level variations in the functional parcellation of the cerebral cortex, IEEE Transactions on Biomedical Engineering, Vol: 63, Pages: 2505-2517, ISSN: 0018-9294
Objective: Functional parcellation of the cerebral cortex is variable across different subjects or between cognitive states. Ignoring individual - or state - dependent variations in the functional parcellation may lead to inaccurate representations of individual functional connectivity, limiting the precision of interpretations of differences in individual connectivity profiles. However, it is difficult to infer the individual-level variations due to the relatively low robustness of methods for parcellation of individual subjects. Methods: We propose a method called “joint K-means” to robustly parcellate the cerebral cortex using fMRI data for contrasts between two states or subjects that intended to characterize variance in individual functional parcellations. The key idea of the proposed method is to jointly infer parcellations in contrasted datasets by iterative descent, while constraining the similarity of the two pathways in searches for local minima to reduce spurious variations. Results: Parcellations of resting-state fMRI datasets from the Human Connectome Project show that the similarity of parcellations for an individual subject studied on two sessions is greater than that between different subjects. Differences in parcellations between subjects are non-uniformly distributed across the cerebral cortex, with clusters of higher variance in the prefrontal, lateral temporal and occipito-parietal cortices. This pattern is reproducible across sessions, between groups and using different numbers of parcels. Conclusion: The individual-level variations inferred by the proposed method are plausible and consistent with the previously reported functional connectivity variability. Significance: The proposed method is a promising tool for investigating relationships between the cerebral functional organization and behavioral differences.
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