562 results found
Alfaro-Almagro F, Jenkinson M, Bangerter NK, et al., 2018, Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank, NEUROIMAGE, Vol: 166, Pages: 400-424, ISSN: 1053-8119
Bishop CA, Ricotti V, Sinclair CDJ, et al., 2018, Semi-Automated Analysis of Diaphragmatic Motion with Dynamic Magnetic Resonance Imaging in Healthy Controls and Non-Ambulant Subjects with Duchenne Muscular Dystrophy, FRONTIERS IN NEUROLOGY, Vol: 9, ISSN: 1664-2295
Dong H, Supratak A, Pan W, et al., 2018, 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
Gafson AR, Kim K, Cencioni MT, et al., 2018, Mononuclear cell transcriptome changes associated with dimethyl fumarate in MS, Neurology - Neuroimmunology Neuroinflammation, Vol: 5, Pages: e470-e470
Liu Z, Zhang J, Zhang K, et al., 2018, Distinguishable brain networks relate disease susceptibility to symptom expression in schizophrenia., Hum Brain Mapp
Disease association studies have characterized altered resting-state functional connectivities describing schizophrenia, but failed to model symptom expression well. We developed a model that could account for symptom severity and meanwhile relate this to disease-related functional pathology. We correlated BOLD signal across brain regions and tested separately for associations with disease (disease edges) and with symptom severity (symptom edges) in a prediction-based scheme. We then integrated them in an "edge bi-color" graph, and adopted mediation analysis to test for causality between the disease and symptom networks and symptom scores. For first-episode schizophrenics (FES, 161 drug-naïve patients and 150 controls), the disease network (with inferior frontal gyrus being the hub) and the symptom-network (posterior occipital-parietal cortex being the hub) were found to overlap in the temporal lobe. For chronic schizophrenis (CS, 69 medicated patients and 62 controls), disease network was dominated by thalamocortical connectivities, and overlapped with symptom network in the middle frontal gyrus. We found that symptom network mediates the relationship between disease network and symptom scores in FEP, but was unable to define a relationship between them for the smaller CS population. Our results suggest that the disease network distinguishing core functional pathology in resting-state brain may be responsible for symptom expression in FES through a wider brain network associated with core symptoms. We hypothesize that top-down control from heteromodal prefrontal cortex to posterior transmodal cortex contributes to positive symptoms of schizophrenia. Our work also suggests differences in mechanisms of symptom expression between FES and CS, highlighting a need to distinguish between these groups.
Ntusi NAB, Francis JM, Gumedze F, et al., 2018, Cardiovascular magnetic resonance characterization of myocardial and vascular function in rheumatoid arthritis patients., Hellenic J Cardiol
BACKGROUND: Rheumatoid arthritis (RA) is a multisystem, autoimmune disorder and confers one of the strongest risks for cardiovascular disease (CVD) morbidity and mortality. OBJECTIVE: To assess myocardial function and vascular stiffness in RA patients with and without cardiovascular risk factors (CVRFs) using cardiovascular magnetic resonance (CMR). METHODS: Twenty-three RA patients with no CVRFs (17 female, mean age 52 ± 13 years), 46 RA patients with CVRFs (32 female, mean age 53 ± 12), 50 normal controls (32 female, mean age 50 ± 11 years), and 13 controls with CVRFs (7 female, mean age 55 ± 7 years), underwent CMR at 1.5 Tesla, including evaluation of left ventricular (LV) ejection fraction, strain, and vascular elasticity (aortic distensibility [AD] and pulse wave velocity [PWV]). Disease activity and duration were recorded for each patient. Subjects with known symptomatic CVD were excluded. RESULTS: LV volumes, mass, and ejection fraction were similar in the four groups. RA patients with CVRFs showed the greatest abnormality in mid short-axis circumferential systolic strain, peak diastolic strain rate, and vascular indices. RA patients without CVRFs showed a similar degree of vascular dysfunction and deformational abnormality as controls with CVRFs. AD and total PWV correlated with myocardial strain and RA disease activity. On multivariate regression analysis, strain was related to age, RA disease activity, AD, and PWV. CONCLUSION: CMR demonstrates impaired myocardial deformation and vascular function in asymptomatic RA patients, worse in those with CVRFs. Subclinical cardiovascular abnormalities are frequent and appear to be incremental to those due to traditional CVRFs and likely contribute to the excess CVD in RA.
Scott G, Zetterberg H, Jolly A, et al., 2018, Minocycline reduces chronic microglial activation after brain trauma but increases neurodegeneration, BRAIN, Vol: 141, Pages: 459-471, ISSN: 0006-8950
Bai W, Oktay O, Sinclair M, et al., 2017, Semi-supervised learning for network-based cardiac MR image segmentation, Pages: 253-260, ISSN: 0302-9743
© Springer International Publishing AG 2017. Training a fully convolutional network for pixel-wise (or voxel-wise) image segmentation normally requires a large number of training images with corresponding ground truth label maps. However, it is a challenge to obtain such a large training set in the medical imaging domain, where expert annotations are time-consuming and difficult to obtain. In this paper, we propose a semi-supervised learning approach, in which a segmentation network is trained from both labelled and unlabelled data. The network parameters and the segmentations for the unlabelled data are alternately updated. We evaluate the method for short-axis cardiac MR image segmentation and it has demonstrated a high performance, outperforming a baseline supervised method. The mean Dice overlap metric is 0.92 for the left ventricular cavity, 0.85 for the myocardium and 0.89 for the right ventricular cavity. It also outperforms a state-of-the-art multi-atlas segmentation method by a large margin and the speed is substantially faster.
Bishop CA, Newbould RD, Lee JSZ, et al., 2017, 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
Coffey S, Lewandowski AJ, Garratt S, et al., 2017, Protocol and quality assurance for carotid imaging in 100,000 participants of UK Biobank: development and assessment, EUROPEAN JOURNAL OF PREVENTIVE CARDIOLOGY, Vol: 24, Pages: 1799-1806, ISSN: 2047-4873
Datta G, Colasanti A, Kalk N, et al., 2017, C-11-PBR28 and F-18-PBR111 Detect White Matter Inflammatory Heterogeneity in Multiple Sclerosis, JOURNAL OF NUCLEAR MEDICINE, Vol: 58, Pages: 1477-1482, ISSN: 0161-5505
Datta G, Colasanti A, Rabiner EA, et al., 2017, Neuroinflammation and its relationship to changes in brain volume and white matter lesions in multiple sclerosis, BRAIN, Vol: 140, Pages: 2927-2938, ISSN: 0006-8950
Datta G, Violante IR, Scott G, et al., 2017, Translocator positron-emission tomography and magnetic resonance spectroscopic imaging of brain glial cell activation in multiple sclerosis, MULTIPLE SCLEROSIS JOURNAL, Vol: 23, Pages: 1469-1478, ISSN: 1352-4585
Gafson A, Craner MJ, Matthews PM, 2017, Personalised medicine for multiple sclerosis care, MULTIPLE SCLEROSIS JOURNAL, Vol: 23, Pages: 362-369, ISSN: 1352-4585
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.
He S, Yong M, Matthews PM, et al., 2017, tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles, BIOINFORMATICS, Vol: 33, Pages: 787-788, ISSN: 1367-4803
Kalk NJ, Guo Q, Owen D, et al., 2017, Decreased hippocampal translocator protein (18kDa) expression in alcohol dependence: a [C-11] PBR28 PET study, TRANSLATIONAL PSYCHIATRY, Vol: 7, ISSN: 2158-3188
LaRocca NG, Hudson LD, Rudick R, et al., 2017, The MSOAC approach to developing performance outcomes to measure and monitor multiple sclerosis disability., Mult Scler
BACKGROUND: The Multiple Sclerosis Outcome Assessments Consortium (MSOAC) was formed by the National MS Society to develop improved measures of multiple sclerosis (MS)-related disability. OBJECTIVES: (1) To assess the current literature and available data on functional performance outcome measures (PerfOs) and (2) to determine suitability of using PerfOs to quantify MS disability in MS clinical trials. METHODS: (1) Identify disability dimensions common in MS; (2) conduct a comprehensive literature review of measures for those dimensions; (3) develop an MS Clinical Data Interchange Standards Consortium (CDISC) data standard; (4) create a database of standardized, pooled clinical trial data; (5) analyze the pooled data to assess psychometric properties of candidate measures; and (6) work with regulatory agencies to use the measures as primary or secondary outcomes in MS clinical trials. CONCLUSION: Considerable data exist supporting measures of the functional domains ambulation, manual dexterity, vision, and cognition. A CDISC standard for MS ( http://www.cdisc.org/therapeutic#MS ) was published, allowing pooling of clinical trial data. MSOAC member organizations contributed clinical data from 16 trials, including 14,370 subjects. Data from placebo-arm subjects are available to qualified researchers. This integrated, standardized dataset is being analyzed to support qualification of disability endpoints by regulatory agencies.
Lema A, Bishop C, Malik O, et al., 2017, A Comparison of Magnetization Transfer Methods to Assess Brain and Cervical Cord Microstructure in Multiple Sclerosis, JOURNAL OF NEUROIMAGING, Vol: 27, Pages: 221-226, ISSN: 1051-2284
Matthews PM, 2017, Advanced MRI measures like DTI or fMRI should be outcome measures in future clinical trials - NO, MULTIPLE SCLEROSIS JOURNAL, Vol: 23, Pages: 1456-1458, ISSN: 1352-4585
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: 1476-8186
Owen DR, Fan J, Campioli E, et al., 2017, TSPO mutations in rats and a human polymorphism impair the rate of steroid synthesis, BIOCHEMICAL JOURNAL, Vol: 474, Pages: 3985-3999, ISSN: 0264-6021
Owen DR, Narayan N, Wells L, et al., 2017, Pro-inflammatory activation of primary microglia and macrophages increases 18 kDa translocator protein expression in rodents but not humans, JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, Vol: 37, Pages: 2679-2690, ISSN: 0271-678X
Peeters LM, Lamers I, Valkenborg D, et al., 2017, Towards personalized therapy through extensive longitudinal follow-up using a multidisciplinary data infrastructure for people with MS: a-proof-of-concept study, 7th Joint European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS)-Americas-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ACTRIMS), Publisher: SAGE PUBLICATIONS LTD, Pages: 934-935, ISSN: 1352-4585
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: 1471-003X
Robinson R, Valindria VV, Bai W, et al., 2017, Automatic quality control of cardiac MRI segmentation in large-scale population imaging, Pages: 720-727, ISSN: 0302-9743
© 2017, Springer International Publishing AG. The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic processing tools such as image segmentation methods are employed to derive quantitative measures or biomarkers for further analyses. Manual inspection and visual QC of each segmentation result is not feasible at large scale. However, it is important to be able to detect when an automatic method fails to avoid inclusion of wrong measurements into subsequent analyses which could otherwise lead to incorrect conclusions. To overcome this challenge, we explore an approach for predicting segmentation quality based on reverse classification accuracy, which enables us to discriminate between successful and failed cases. We validate this approach on a large cohort of cardiac MRI for which manual QC scores were available. Our results on 7,425 cases demonstrate the potential for fully automatic QC in the context of large-scale population imaging such as the UK Biobank Imaging Study.
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
Stangel M, Kuhlmann T, Matthews PM, et al., 2017, Achievements and obstacles of remyelinating therapies in multiple sclerosis, NATURE REVIEWS NEUROLOGY, Vol: 13, Pages: 742-754, ISSN: 1759-4758
Suzuki H, Gao H, Bai W, et al., 2017, Abnormal brain white matter microstructure is associated with both pre-hypertension and hypertension, PLOS ONE, Vol: 12, ISSN: 1932-6203
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
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