602 results found
Tarroni G, Bai W, Oktay O, et al., Large-scale quality control of cardiac imaging in population studies: application to UK biobank, Scientific Reports, ISSN: 2045-2322
In large population studies such as the UK Biobank (UKBB), quality control of the acquired images by visual assessment isunfeasible. In this paper, we apply a recently developed fully-automated quality control pipeline for cardiac MR (CMR) imagesto the first 19,265 short-axis (SA) cine stacks from the UKBB. We present the results for the three estimated quality metrics(heart coverage, inter-slice motion and image contrast in the cardiac region) as well as their potential associations with factorsincluding acquisition details and subject-related phenotypes. Up to 14.2% of the analysed SA stacks had sub-optimal coverage(i.e. missing basal and/or apical slices), however most of them were limited to the first year of acquisition. Up to 16% of thestacks were affected by noticeable inter-slice motion (i.e. average inter-slice misalignment greater than 3.4 mm). Inter-slicemotion was positively correlated with weight and body surface area. Only 2.1% of the stacks had an average end-diastoliccardiac image contrast below 30% of the dynamic range. These findings will be highly valuable for both the scientists involvedin UKBB CMR acquisition and for the ones who use the dataset for research purposes.
Suzuki H, Venkataraman AV, Bai W, et al., 2019, Associations of Regional Brain Structural Differences With Aging, Modifiable Risk Factors for Dementia, and Cognitive Performance., JAMA Netw Open, Vol: 2
Importance: Identifying brain regions associated with risk factors for dementia could guide mechanistic understanding of risk factors associated with Alzheimer disease (AD). Objectives: To characterize volume changes in brain regions associated with aging and modifiable risk factors for dementia (MRFD) and to test whether volume differences in these regions are associated with cognitive performance. Design, Setting, and Participants: This cross-sectional study used data from UK Biobank participants who underwent T1-weighted structural brain imaging from August 5, 2014, to October 14, 2016. A voxelwise linear model was applied to test for regional gray matter volume differences associated with aging and MRFD (ie, hypertension, diabetes, obesity, and frequent alcohol use). The potential clinical relevance of these associations was explored by comparing their neuroanatomical distributions with the regional brain atrophy found with AD. Mediation models for risk factors, brain volume differences, and cognitive measures were tested. The primary hypothesis was that common, overlapping regions would be found. Primary analysis was conducted on April 1, 2018. Main Outcomes and Measures: Gray matter regions that showed relative atrophy associated with AD, aging, and greater numbers of MRFD. Results: Among 8312 participants (mean [SD] age, 62.4 [7.4] years; 3959 [47.1%] men), aging and 4 major MRFD (ie, hypertension, diabetes, obesity, and frequent alcohol use) had independent negative associations with specific gray matter volumes. These regions overlapped neuroanatomically with those showing lower volumes in participants with AD, including the posterior cingulate cortex, the thalamus, the hippocampus, and the orbitofrontal cortex. Associations between these MRFD and spatial memory were mediated by differences in posterior cingulate cortex volume (β = 0.0014; SE = 0.0006; P = .02). Conclusions and Relevance: This cross-sectional s
Goldman MD, LaRocca NG, Rudick RA, et al., 2019, Evaluation of multiple sclerosis disability outcome measures using pooled clinical trial data., Neurology, Vol: 93, Pages: e1921-e1931
OBJECTIVE: We report analyses of a pooled database by the Multiple Sclerosis Outcome Assessments Consortium to evaluate 4 proposed components of a multidimensional test battery. METHODS: Standardized data on 12,776 participants, comprising demographics, multiple sclerosis disease characteristics, Expanded Disability Status Scale (EDSS) score, performance measures, and Short Form-36 Physical Component Summary (SF-36 PCS), were pooled from control and treatment arms of 14 clinical trials. Analyses of Timed 25-Foot Walk (T25FW), 9-Hole Peg Test (9HPT), Low Contrast Letter Acuity (LCLA), and Symbol Digit Modalities Test (SDMT) included measurement properties; construct, convergent, and known group validity; and longitudinal performance of the measures individually and when combined into a multidimensional test battery relative to the EDSS and SF-36 to determine sensitivity and clinical meaningfulness. RESULTS: The performance measures had excellent test-retest reliability and showed expected differences between subgroups based on disease duration and EDSS level. Progression rates in detecting time to 3-month confirmed worsening were lower for T25FW and 9HPT compared to EDSS, while progression rates for LCLA and SDMT were similar to EDSS. When the 4 measures were analyzed as a multidimensional measure rather than as individual measures, progression on any one performance measure was more sensitive than the EDSS. Worsening on the performance measures analyzed individually or as a multidimensional test battery was associated with clinically meaningful SF-36 PCS score worsening, supporting clinical meaningfulness of designated performance test score worsening. CONCLUSION: These results support the use of the 4 proposed performance measures, individually or combined into a multidimensional test battery as study outcome measures.
Nutma E, Stephenson JA, Gorter RP, et al., 2019, A quantitative neuropathological assessment of translocator protein expression in multiple sclerosis, Brain, Vol: 142, Pages: 3440-3455, ISSN: 1460-2156
The 18kDa translocator protein (TSPO) is increasingly used to study brain and spinal cord inflammation in degenerative diseases of the CNS such as multiple sclerosis. The enhanced TSPO PET signal that arises during disease is widely-considered to reflect activated pathogenicmicroglia, although quantitative neuropathological data to support this interpretation has not been available. With the increasing interest in the role of chronic microglial activation in multiple sclerosis, characterising the cellular neuropathology associated with TSPO expression is of clear importance for understanding the cellular and pathological processes on which TSPO PET imaging is reporting.Here we have studied the cellular expression of TSPO and specific binding of two TSPO targeting radioligands ([3H]PK11195 and [3H]PBR28) in tissue sections from 42 multiple sclerosis cases and 12 age-matched controls. Markers of homeostatic and reactive microglia, astrocytes, and lymphocytes were used to investigate the phenotypes of cells expressing TSPO. There was an approximate 20-fold increase in cells double positive for TSPO and human leukocyte antigen -DR in active lesions and in the rim of chronic active lesion, relative to normal appearing white matter. TSPO was uniformly expressed across myeloid cells irrespective of their phenotype, rather than being preferentially associated with pro-inflammatory microglia or macrophages. TSPO+astrocytes were increased up to 7-fold compared to normal appearing white matter across all lesion sub-types and accounted for 25% of the TSPO+ cells in these lesions. To relate TSPO protein expression to ligand binding, specific binding of the TSPO ligands [3H]PK11195 and [3H]PBR28was determined in the same lesions. TSPO radioligand binding was increased up to seven times for [3H]PBR28 and up to two times for [3H]PK11195 in active lesions and the centre of chronic ac
Gorgoraptis N, Li LM, Whittington A, et al., 2019, In vivo detection of cerebral tau pathology in long-term survivors of traumatic brain injury, Science Translational Medicine, Vol: 11, Pages: 1-14, ISSN: 1946-6234
Traumatic brain injury (TBI) can trigger progressive neurodegeneration, with tau pathology seen years after a single moderate-severe TBI. Identifying this type of posttraumatic pathology in vivo might help to understand the role of tau pathology in TBI pathophysiology. We used flortaucipir positron emission tomography (PET) to investigate whether tau pathology is present many years after a single TBI in humans. We examined PET data in relation to markers of neurodegeneration in the cerebrospinal fluid (CSF), structural magnetic resonance imaging measures, and cognitive performance. Cerebral flortaucipir binding was variable, with many participants with TBI showing increases in cortical and white matter regions. At the group level, flortaucipir binding was increased in the right occipital cortex in TBI when compared to healthy controls. Flortaucipir binding was associated with increased total tau, phosphorylated tau, and ubiquitin carboxyl-terminal hydrolase L1 CSF concentrations, as well as with reduced fractional anisotropy and white matter tissue density in TBI. Apolipoprotein E (APOE) ε4 genotype affected the relationship between flortaucipir binding and time since injury, CSF β amyloid 1–42 (Aβ42) concentration, white matter tissue density, and longitudinal Mini-Mental State Examination scores in TBI. The results demonstrate that tau PET is a promising approach to investigating progressive neurodegeneration associated with tauopathy after TBI.
Fancy NN, Srivastava P, Matthews PM, et al., 2019, A bioinformatics approach to understand the regulation of TSPO gene expression in myeloid cells, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 222-222, ISSN: 1352-4585
Longbrake EE, Matthews PM, Mao-Draayer Y, et al., 2019, Change in absolute lymphocyte count is not a biomarker of clinical response and does not correlate with change in serum neurofilament light for patients treated with delayed-release dimethyl fumarate, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 552-553, ISSN: 1352-4585
Smith AM, Khozoie C, Fancy N, et al., 2019, Single nucleus RNA sequencing of post-mortem multiple sclerosis cortical grey matter, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 233-233, ISSN: 1352-4585
Weinert M, Cowley SA, Alavian KN, et al., 2019, Exploring the mitochondrial TSPO protein as a possible immunometabolic modulatory target for treatment of multiple sclerosis, 35th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS) / 24th Annual Conference of Rehabilitation in MS, Publisher: SAGE PUBLICATIONS LTD, Pages: 515-515, ISSN: 1352-4585
Evangelou E, Gao H, Blakeley P, et al., 2019, New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders, Nature Human Behaviour, Vol: 3, Pages: 950-961, ISSN: 2397-3374
Excessive alcohol consumption is one of the main causes of death and disability worldwide. Alcohol consumption is a heritable complex trait. Here we conducted a meta-analysis of genome-wide association studies of alcohol consumption (g d−1) from the UK Biobank, the Alcohol Genome-Wide Consortium and the Cohorts for Heart and Aging Research in Genomic Epidemiology Plus consortia, collecting data from 480,842 people of European descent to decipher the genetic architecture of alcohol intake. We identified 46 new common loci and investigated their potential functional importance using magnetic resonance imaging data and gene expression studies. We identify genetic pathways associated with alcohol consumption and suggest genetic mechanisms that are shared with neuropsychiatric disorders such as schizophrenia.
Matthews P, 2019, Chronic inflammation in multiple sclerosis — seeing what was always there, Nature Reviews Neurology, Vol: 15, Pages: 582-593, ISSN: 1759-4758
Activation of innate immune cells and other brain compartmentalized inflammatory cellsin the brains and spinal cords of people with relapsing–remitting multiple sclerosis (MS) and progressive MS have been well described histopathologically. However, conventional clinical MRI is largely insensitive to this inflammatory activity. The past two decades have seen the introduction of quantitative dynamic MRI scanning with contrast agents that are sensitive to the reduction in blood–brain barrier integrity associated with inflammation and to the trafficking of inflammatory myeloid cells. New MRI imaging sequences provide improved contrast for better detection of grey matter lesions. Quantitative lesion volume measures and magnetic resonance susceptibility imaging are sensitive to the activity of macrophages in the rims of white matter lesions. PET and magnetic resonance spectroscopy methods also can be used to detect contributions from innate immune activation in the brain and spinal cord. Some of these advanced research imaging methods for visualization of chronic inflammation are practical for relatively routine clinical applications. Observations using these techniques suggest ways of stratifying patients with MS to improve their care. The imaging methods also provide new tools to support the development of therapies for chronic inflammation in MS.
Bai W, Chen C, Tarroni G, et al., 2019, Self-supervised learning for cardiac MR image segmentation by anatomicalposition prediction, Publisher: arXiv
In the recent years, convolutional neural networks have transformed the fieldof medical image analysis due to their capacity to learn discriminative imagefeatures for a variety of classification and regression tasks. However,successfully learning these features requires a large amount of manuallyannotated data, which is expensive to acquire and limited by the availableresources of expert image analysts. Therefore, unsupervised, weakly-supervisedand self-supervised feature learning techniques receive a lot of attention,which aim to utilise the vast amount of available data, while at the same timeavoid or substantially reduce the effort of manual annotation. In this paper,we propose a novel way for training a cardiac MR image segmentation network, inwhich features are learnt in a self-supervised manner by predicting anatomicalpositions. The anatomical positions serve as a supervisory signal and do notrequire extra manual annotation. We demonstrate that this seemingly simple taskprovides a strong signal for feature learning and with self-supervisedlearning, we achieve a high segmentation accuracy that is better than orcomparable to a U-net trained from scratch, especially at a small data setting.When only five annotated subjects are available, the proposed method improvesthe mean Dice metric from 0.811 to 0.852 for short-axis image segmentation,compared to the baseline U-net.
Venkataraman A, Mansur A, Lewis Y, et al., Evaluation of mitochondrial and synaptic function in Alzheimer’s disease (AD): a [18F]BCPP-EF, [11C]SA4503 and [11C]UCB-J PET study, Journal of Cerebral Blood Flow and Metabolism, Vol: 39, Pages: 121-122, ISSN: 1559-7016
ObjectivesMitochondrial deficits leading to synaptic dysfunction have been hypothesised in the pathophysiology of neurodegenerative disease, with Aβ/tau impairing mitochondrial function in AD. To date a combined evaluation of human mitochondrial and synaptic function has not been performed directly in vivo. We describe the pilot results of MINDMAPS-AD, a study within the MINDMAPS1 programme aiming to evaluate mitochondrial and synaptic function in the brain of patients with MCI/AD. MINDMAPS-AD uses the novel radioligands [18F]BCPP-EF, [11C]SA4503 and [11C]UCB-J, to compare the regional density of mitochondrial complex I (MC1), the sigma 1 receptor (s1R) and synaptic vesicular protein 2A (SV2A) respectively.MethodsSix participants with a range of AD related pathologies, EMCI (n = 2), LMCI (n = 2), and AD (n = 2), were enrolled into the study. Participants fulfilled NIA-AA criteria and were amyloid-beta +ve confirmed by [18F]Florbetaben PET. All participants underwent three PET scans with [18F]BCPP-EF, [11C]SA4503 and [11C]UCB-J. Arterial blood samples were collected and a metabolite corrected arterial plasma input function was estimated to derive regional volumes of distribution (VT). These data were compared to six age/sex matched cognitively normal (CN) healthy subjects recruited for ongoing studies within the MINDMAPS programme. Regions of interest (ROIs) were defined on individual subject MR images using an anatomical atlas and included: frontal cortex, hippocampus, amygdala, anterior cingulate, posterior cingulate, thalamus, temporal cortex, parietal cortex, caudate, putamen, and occipital lobe. Regional target density was evaluated using the VT, as well as VT corrected for the plasma free fraction of the radioligand (fP; VT/fp), and the regional VT ratio versus the VT in the centrum semiovale, a white matter region expected to have low levels of the targets evaluated (DVR). Comparison of regional target density and
Venkataraman AV, Mansur A, Huiban M, et al., 2019, Evaluation of mitochondrial and synaptic function in Alzheimer's disease (AD): a [F-18]BCPP-EF, [C-11]SA4503 and [C-11]UCB-J PET study, 29th International Symposium on Cerebral Blood Flow, Metabolism and Function / 14th International Conference on Quantification of Brain Function with PET (BRAIN and BRAIN Pet), Publisher: SAGE PUBLICATIONS INC, Pages: 121-122, ISSN: 0271-678X
Schmierer K, Campion T, Sinclair A, et al., Towards a standard MRI protocol for multiple sclerosis across the UK., Br J Radiol, Pages: 20180926-20180926
Multiple sclerosis is a chronic inflammatory demyelinating and degenerative disease of the central nervous system. It is the most common non-traumatic cause of chronic disability in young adults. An early and accurate diagnosis, and effective disease modifying treatment are key elements of optimum care for people with MS (pwMS). MRI has become a critical tool to confirm the presence of dissemination in space and time of lesions characteristic of inflammatory demyelination, a cornerstone of MS diagnosis, over and above exclusion of numerous differential diagnoses. In the modern era of early and highly effective DMT, follow-up of pwMS also relies heavily on MRI, to both confirm efficacy and for pharmacovigilance. Since criteria for MS rely heavily on MRI, an agreed standardized acquisition and reporting protocol enabling efficient and equitable application across the UK is desirable. Following a recent meeting of MS experts in London (UK), we make recommendations for a standardized UK MRI protocol that captures the diagnostic phase as well as monitoring for safety and treatment efficacy once the diagnosis is established. Our views take into account issues arising from the (repeated) use of contrast agents as well as the advent of (semi-) automated tools to further optimize disease monitoring in pwMS.
Tarroni G, Oktay O, Bai W, et al., 2019, Learning-based quality control for cardiac MR images, IEEE Transactions on Medical Imaging, Vol: 38, Pages: 1127-1138, ISSN: 0278-0062
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned and on the potential occurrence of imaging artefacts such as cardiac and respiratory motion. In the clinical practice, a quality control step is performed by visual assessment of the acquired images: however, this procedure is strongly operatordependent, cumbersome and sometimes incompatible with the time constraints in clinical settings and large-scale studies. We propose a fast, fully-automated, learning-based quality control pipeline for CMR images, specifically for short-axis image stacks. Our pipeline performs three important quality checks: 1) heart coverage estimation, 2) inter-slice motion detection, 3) image contrast estimation in the cardiac region. The pipeline uses a hybrid decision forest method - integrating both regression and structured classification models - to extract landmarks as well as probabilistic segmentation maps from both long- and short-axis images as a basis to perform the quality checks. The technique was tested on up to 3000 cases from the UK Biobank as well as on 100 cases from the UK Digital Heart Project, and validated against manual annotations and visual inspections performed by expert interpreters. The results show the capability of the proposed pipeline to correctly detect incomplete or corrupted scans (e.g. on UK Biobank, sensitivity and specificity respectively 88% and 99% for heart coverage estimation, 85% and 95% for motion detection), allowing their exclusion from the analysed dataset or the triggering of a new acquisition.
Gafson AR, Savva C, Thorne T, et al., 2019, Breaking the cycle: reversal of flux in the tricarboxylic acid cycle by dimethyl fumarate, Neurology, Neuroimmunology and Neuroinflammation, Vol: 6, ISSN: 2332-7812
ObjectiveTo infer possible molecular effectors of therapeutic effects and adverse events for the pro-drug dimethyl fumarate (DMF, Tecfidera) in the plasma of relapsing-remitting MS patients (RRMS) based on untargeted blood plasma metabolomics. MethodsBlood samples were collected from 27 RRMS patients at baseline and six weeks after initiation of treatment with DMF (BG-12; Tecfidera). Patients were separated into a discovery (n=15) and a validation cohort (n=12). Ten healthy controls were also recruited and blood samples were collected over the same time intervals. Untargeted metabolomic profiling using ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS) was performed on plasma samples from the discovery cohort and healthy controls at Metabolon Inc. (Durham, NC). UPLC-MS was then performed on samples from the validation cohort at the National Phenome Centre (Imperial College, UK). Plasma neurofilament concentration (NfL) was also assayed for all subjects using the Simoa platform (Quanterix, Lexington, MA). Time course and cross-sectional statistical analyses were performed to identify pharmacodynamic changes in the metabolome secondary to DMF and relate these to adverse events. Results In the discovery cohort, tricarboxylic acid (TCA) cycle intermediates fumarate and succinate and TCA cycle metabolites succinyl-carnitine and methyl succinyl-carnitine were increased 6-weeks after the start of treatment (q < 0.05). We confirmed that methyl succinyl carnitine was also increased in the validation cohort 6-weeks after the start of treatment (q < 0.05). Changes in concentrations of these metabolites were not seen over a similar time period in blood from the untreated healthy control population. Increased succinyl-carnitine and methyl succinyl-carnitine were associated with adverse events from DMF (flushing, abdominal symptoms. The mean plasma NfL concentration before treatment was higher in the RRMS patients than in the healthy contro
Robinson R, Valindria VV, Bai W, et al., 2019, Automated quality control in image segmentation: application to the UK Biobank cardiac MR imaging study, Journal of Cardiovascular Magnetic Resonance, Vol: 21, ISSN: 1097-6647
Background: 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, e.g. image segmentation methods, are employed to derive quantitative measures or biomarkers for later analyses. Manual inspection and visual QC of each segmentation isn't feasible at large scale. However, it's important to be able to automatically detect when a segmentation method fails so as to avoid inclusion of wrong measurements into subsequent analyses which could lead to incorrect conclusions. Methods: 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 segmentations on a per-cases basis. We validate this approach on a new, large-scale manually-annotated set of 4,800 cardiac magnetic resonance scans. We then apply our method to a large cohort of 7,250 cardiac MRI on which we have performed manual QC. Results: We report results used for predicting segmentation quality metrics including Dice Similarity Coefficient (DSC) and surface-distance measures. As initial validation, we present data for 400 scans demonstrating 99% accuracy for classifying low and high quality segmentations using predicted DSC scores. As further validation we show high correlation between real and predicted scores and 95% classification accuracy on 4,800 scans for which manual segmentations were available. We mimic real-world application of the method on 7,250 cardiac MRI where we show good agreement between predicted quality metrics and manual visual QC scores. Conclusions: We show that RCA has the potential for accurate and fully automatic segmentation QC on a per-case basis in the context of large-scale population imaging as in the UK Biobank Imaging Study.
Meyer HV, Dawes TJW, Serrani M, et al., 2019, Genomic analysis reveals a functional role for myocardial trabeculae in adults, Publisher: Cold Spring Harbor Laboratory
<jats:title>ABSTRACT</jats:title><jats:p>Since being first described by Leonardo da Vinci in 1513 it has remained an enigma why the endocardial surfaces of the adult heart retain a complex network of muscular trabeculae – with their persistence thought to be a vestige of embryonic development. For causative physiological inference we harness population genomics, image-based intermediate phenotyping and <jats:italic>in silico</jats:italic> modelling to determine the effect of this complex cardiovascular trait on function. Using deep learning-based image analysis we identified genetic associations with trabecular complexity in 18,097 UK Biobank participants which were replicated in an independently measured cohort of 1,129 healthy adults. Genes in these associated regions are enriched for expression in the fetal heart or vasculature and implicate loci associated with haemodynamic phenotypes and developmental pathways. A causal relationship between increasing trabecular complexity and both ventricular performance and electrical activity are supported by complementary biomechanical simulations and Mendelian randomisation studies. These findings show that myocardial trabeculae are a previously-unrecognised determinant of cardiovascular physiology in adult humans.</jats:p>
Ntusi NAB, Francis JM, Gumedze F, et al., 2019, Cardiovascular magnetic resonance characterization of myocardial and vascular function in rheumatoid arthritis patients, Hellenic Journal of Cardiology, Vol: 60, Pages: 28-35, ISSN: 1109-9666
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.
Nalbantian S, Matthews PM, 2019, Secrets of Creativity What Neuroscience, the Arts, and Our Minds Reveal, Publisher: Oxford University Press, USA, ISBN: 9780190462321
Authors in this volume take on the challenge of showing how creativity can be characterized behaviorally, cognitively, and neurophysiologically. The complementary perspectives of the authors add to the richness of these findings.
Gafson AR, Thorne T, McKechnie CIJ, et al., 2018, Lipoprotein markers associated with disability from multiple sclerosis, Scientific Reports, Vol: 8, ISSN: 2045-2322
Altered lipid metabolism is a feature of chronic infammatory disorders. Increased plasma lipids andlipoproteins have been associated with multiple sclerosis (MS) disease activity. Our objective was tocharacterise the specifc lipids and associated plasma lipoproteins increased in MS and to test for anassociation with disability. Plasma samples were collected from 27 RRMS patients (median EDSS,1.5, range 1–7) and 31 healthy controls. Concentrations of lipids within lipoprotein sub-classes weredetermined from NMR spectra. Plasma cytokines were measured using the MesoScale DiscoveryV-PLEX kit. Associations were tested using multivariate linear regression. Diferences between thepatient and volunteer groups were found for lipids within VLDL and HDL lipoprotein sub-fractions(p<0.05). Multivariate regression demonstrated a high correlation between lipids within VLDLsub-classes and the Expanded Disability Status Scale (EDSS) (p<0.05). An optimal model for EDSSincluded free cholesterol carried by VLDL-2, gender and age (R2=0.38, p<0.05). Free cholesterolcarried by VLDL-2 was highly correlated with plasma cytokines CCL-17 and IL-7 (R2=0.78, p<0.0001).These results highlight relationships between disability, infammatory responses and systemic lipidmetabolism in RRMS. Altered lipid metabolism with systemic infammation may contribute to immuneactivation.
Ntusi NAB, Francis JM, Sever E, et al., 2018, Anti-TNF modulation reduces myocardial inflammation and improves cardiovascular function in systemic rheumatic diseases, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 270, Pages: 253-259, ISSN: 0167-5273
Inkster B, Simmons A, Cole JH, et al., 2018, Unravelling the GSK3 beta-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder, Psychiatric Genetics, Vol: 28, Pages: 77-84, ISSN: 0955-8829
Objective Glycogen synthase kinase 3β (GSK3β) has been implicated in mood disorders. We previously reported associations between a GSK3β polymorphism and hippocampal volume in major depressive disorder (MDD). We then reported similar associations for a subset of GSK3β-regulated genes. We now investigate an algorithm-derived comprehensive list of genes encoding proteins that directly interact with GSK3β to identify a genotypic network influencing hippocampal volume in MDD.Participants and methods We used discovery (N=141) and replication (N=77) recurrent MDD samples. Our gene list was generated from the NetworKIN database. Hippocampal measures were derived using an optimized Freesurfer protocol. We identified interacting single nucleotide polymorphisms using the machine learning algorithm Random Forest and verified interactions using likelihood ratio tests between nested linear regression models.Results The discovery sample showed multiple two-single nucleotide polymorphism interactions with hippocampal volume. The replication sample showed a replicable interaction (likelihood ratio test: P=0.0088, replication sample; P=0.017, discovery sample; Stouffer’s combined P=0.0007) between genes associated previously with endoplasmic reticulum stress, calcium regulation and histone modifications.Conclusion Our results provide genetic evidence supporting associations between hippocampal volume and MDD, which may reflect underlying cellular stress responses. Our study provides evidence of biological mechanisms that should be further explored in the search for disease-modifying therapeutic targets for depression.
LaRocca NG, Hudson LD, Rudick R, et al., 2018, The MSOAC approach to developing performance outcomes to measure and monitor multiple sclerosis disability, Multiple Sclerosis Journal, Vol: 24, Pages: 1469-1484, ISSN: 1352-4585
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.
Bai W, Suzuki H, Qin C, et al., 2018, Recurrent neural networks for aortic image sequence segmentation with sparse annotations, International Conference On Medical Image Computing & Computer Assisted Intervention, Publisher: Springer Nature Switzerland AG, Pages: 586-594, ISSN: 0302-9743
Segmentation of image sequences is an important task in medical image analysis, which enables clinicians to assess the anatomy and function of moving organs. However, direct application of a segmentation algorithm to each time frame of a sequence may ignore the temporal continuity inherent in the sequence. In this work, we propose an image sequence segmentation algorithm by combining a fully convolutional network with a recurrent neural network, which incorporates both spatial and temporal information into the segmentation task. A key challenge in training this network is that the available manual annotations are temporally sparse, which forbids end-to-end training. We address this challenge by performing non-rigid label propagation on the annotations and introducing an exponentially weighted loss function for training. Experiments on aortic MR image sequences demonstrate that the proposed method significantly improves both accuracy and temporal smoothness of segmentation, compared to a baseline method that utilises spatial information only. It achieves an average Dice metric of 0.960 for the ascending aorta and 0.953 for the descending aorta.
Bai W, Sinclair M, Tarroni G, et al., 2018, Automated cardiovascular magnetic resonance image analysis with fully convolutional networks., Journal of Cardiovascular Magnetic Resonance, Vol: 20, ISSN: 1097-6647
Background: Cardiovascular magnetic resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing information for diagnosis and monitoring of CVDs. However, for years, clinicians have been relying on manual approaches for CMR imageanalysis, which is time consuming and prone to subjective errors. It is a major clinical challenge to automatically derive quantitative and clinically relevant information from CMR images.Methods: Deep neural networks have shown a great potential in image pattern recognition and segmentation for a variety of tasks. Here we demonstrate an automated analysis method for CMR images, which is based on a fully convolutional network (FCN). The network is trained and evaluated on a large-scale dataset from the UK Biobank, consisting of 4,875 subjects with 93,500 pixelwise annotated images. The performance of the method has been evaluated using a number of technical metrics, including the Dice metric, mean contour distance and Hausdorff distance, as well as clinically relevant measures, including left ventricle (LV)end-diastolic volume (LVEDV) and end-systolic volume (LVESV), LV mass (LVM); right ventricle (RV) end-diastolic volume (RVEDV) and end-systolic volume (RVESV).Results: By combining FCN with a large-scale annotated dataset, the proposed automated method achieves a high performance in segmenting the LV and RV on short-axis CMR images and the left atrium (LA) and right atrium (RA) on long-axis CMR images. On a short-axis image test set of 600 subjects, it achieves an average Dice metric of 0.94 for the LV cavity, 0.88 for the LV myocardium and 0.90 for the RV cavity. The meanabsolute difference between automated measurement and manual measurement was 6.1 mL for LVEDV, 5.3 mL for LVESV, 6.9 gram for LVM, 8.5 mL for RVEDV and 7.2 mL for RVESV. On long-ax
Liu Z, Zhang J, Zhang K, et al., 2018, Distinguishable brain networks relate disease susceptibility to symptom expression in schizophrenia, Human Brain Mapping, Vol: 39, Pages: 3503-3515, ISSN: 1065-9471
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.
Gibson LM, Littlejohns TJ, Adamska L, et al., 2018, Impact of detecting potentially serious incidental findings during multi-modal imaging, Publisher: F1000 Research Ltd
<ns4:p><ns4:bold>Background</ns4:bold>: There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images.</ns4:p><ns4:p> <ns4:bold>Methods</ns4:bold>: Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts.</ns4:p><ns4:p> <ns4:bold>Results</ns4:bold>: Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%).</ns4:p><ns4:p> <ns4:bold>Conclusions</ns4:bold>: Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoi
Gibson L, Littlejohns T, Adamska L, et al., 2018, Impact of detecting potentially serious incidental findings during multi-modal imaging, Wellcome Open Research
Background : There are limited data on the impact of feedback of incidental findings (IFs) from research imaging. We evaluated the impact of UK Biobank’s protocol for handling potentially serious IFs in a multi-modal imaging study of 100,000 participants (radiographer ‘flagging’ with radiologist confirmation of potentially serious IFs) compared with systematic radiologist review of all images. Methods : Brain, cardiac and body magnetic resonance, and dual-energy x-ray absorptiometry scans from the first 1000 imaged UK Biobank participants were independently assessed for potentially serious IFs using both protocols. We surveyed participants with potentially serious IFs and their GPs up to six months after imaging to determine subsequent clinical assessments, final diagnoses, emotional, financial and work or activity impacts. Results : Compared to systematic radiologist review, radiographer flagging resulted in substantially fewer participants with potentially serious IFs (179/1000 [17.9%] versus 18/1000 [1.8%]) and a higher proportion with serious final diagnoses (21/179 [11.7%] versus 5/18 [27.8%]). Radiographer flagging missed 16/21 serious final diagnoses (i.e., false negatives), while systematic radiologist review generated large numbers of non-serious final diagnoses (158/179) (i.e., false positives). Almost all (90%) participants had further clinical assessment (including invasive procedures in similar numbers with serious and non-serious final diagnoses [11 and 12 respectively]), with additional impact on emotional wellbeing (16.9%), finances (8.9%), and work or activities (5.6%). Conclusions : Compared with systematic radiologist review, radiographer flagging missed some serious diagnoses, but avoided adverse impacts for many participants with non-serious diagnoses. While systematic radiologist review may benefit some participants, UK Biobank’s responsibility to avoid both unnecessary harm to larger numbers of
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