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  • Conference paper
    Puyol-Anton E, Ruijsink B, Bai W, Langet H, De Craene M, Schnabel JA, Piro P, King AP, Sinclair Met al., 2018,

    Fully automated myocardial strain estimation from cine MRI using convolutional neural networks

    , International Symposium on Biomedical Imaging, Pages: 1139-1143, ISSN: 1945-7928

    © 2018 IEEE. Cardiovascular magnetic resonance myocardial feature tracking (CMR-FT) is a promising method for quantification of cardiac function from standard steady-state free precession (SSFP) images. However, currently available techniques require operator dependent and time-consuming manual intervention, limiting reproducibility and clinical use. In this paper, we propose a fully automated pipeline to compute left ventricular (LV) longitudinal and radial strain from 2- and 4-chamber cine acquisitions, and LV circumferential and radial strain from the short-axis imaging. The method employs a convolutional neural network to automatically segment the myocardium, followed by feature tracking and strain estimation. Experiments are performed using 40 healthy volunteers and 40 ischemic patients from the UK Biobank dataset. Results show that our method obtained strain values that were in excellent agreement with the commercially available clinical CMR-FT software CVI42(Circle Cardiovascular Imaging, Calgary, Canada).

  • Journal article
    Whittington A, Sharp DJ, Gunn RN, 2018,

    Spatiotemporal distribution of β-amyloid in Alzheimer's disease results from heterogeneous regional carrying capacities

    , Journal of Nuclear Medicine, Vol: 59, Pages: 822-827, ISSN: 1535-5667

    β-amyloid (Aβ) accumulation in the brain is one of two pathological hallmarks of Alzheimer's Disease (AD) and its spatial distribution has been studied extensively ex vivo. We apply mathematical modelling to Aβ in vivo PET imaging data in order to investigate competing theories of Aβ spread in AD. Our results provide evidence that Aβ accumulation starts in all brain regions simultaneously and that its spatiotemporal distribution is a result of heterogeneous regional carrying capacities (regional maximum possible concentration of Aβ) for the aggregated protein rather than longer term spreading from seed regions.

  • Journal article
    Sandrone S, van Gijn J, 2018,

    Macdonald Critchley (1900-1997)

    , JOURNAL OF NEUROLOGY, Vol: 265, Pages: 1244-1245, ISSN: 0340-5354
  • Journal article
    Lorenz R, Ribeiro Violante I, Monti R, Montana G, Hampshire A, Leech Ret al., 2018,

    Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization

    , Nature Communications, Vol: 9, ISSN: 2041-1723

    Understanding the unique contributions of frontoparietal networks (FPN) in cognition is challenging because they overlap spatially and are co-activated by diverse tasks. Characterizing these networks therefore involves studying their activation across many different cognitive tasks, which previously was only possible with meta-analyses. Here, we use neuroadaptive Bayesian optimization, an approach combining real-time analysis of functional neuroimaging data with machine-learning, to discover cognitive tasks that segregate ventral and dorsal FPN activity. We identify and subsequently refine two cognitive tasks, Deductive Reasoning and Tower of London, which maximally dissociate the dorsal from ventral FPN. We subsequently investigate these two FPNs in the context of a wider range of FPNs and demonstrate the importance of studying the whole activity profile across tasks to uniquely differentiate any FPN. Our findings deviate from previous meta-analyses and hypothesized functional labels for these FPNs. Taken together the results form the starting point for a neurobiologically-derived cognitive taxonomy.

  • Journal article
    Oliveira V, Kumutha JR E N, Somanna J, Benkappa N, Bandya P, Chandrasekeran M, Swamy R, Mondkar J, Dewang K, Manerkar S, Sundaram M, Chinathambi K, Bharadwaj S, Bhat V, Madhava V, Nair M, Lally PJ, Montaldo P, Atreja G, Mendoza J, Bassett P, Ramji S, Shankaran S, Thayyil Set al., 2018,

    Hypothermia for encephalopathy in low-income and middle-income countries: feasibility of whole-body cooling using a low-cost servo-controlled device

    , BMJ Paediatrics Open, Vol: 2, ISSN: 2399-9772

    Although therapeutic hypothermia (TH) is the standard of care for hypoxic ischaemic encephalopathy in high-income countries, the safety and efficacy of this therapy in low-income and middle-income countries (LMICs) is unknown. We aimed to describe the feasibility of TH using a low-cost servo-controlled cooling device and the short-term outcomes of the cooled babies in LMIC. Design: We recruited babies with moderate or severe hypoxic ischaemic encephalopathy (aged <6 hours) admitted to public sector tertiary neonatal units in India over a 28-month period. We administered whole-body cooling (set core temperature 33.5°C) using a servo-controlled device for 72 hours, followed by passive rewarming. We collected the data on short-term neonatal outcomes prior to hospital discharge. Results: Eighty-two babies were included-61 (74%) had moderate and 21 (26%) had severe encephalopathy. Mean (SD) hypothermia cooling induction time was 1.7 hour (1.5) and the effective cooling time 95% (0.08). The mean (SD) hypothermia induction time was 1.7 hour (1.5 hour), core temperature during cooling was 33.4°C (0.2), rewarming rate was 0.34°C (0.16°C) per hour and the effective cooling time was 95% (8%). Twenty-five (51%) babies had gastric bleeds, 6 (12%) had pulmonary bleeds and 21 (27%) had meconium on delivery. Fifteen (18%) babies died before discharge from hospital. Heart rate more than 120 bpm during cooling (P=0.01) and gastric bleeds (P<0.001) were associated with neonatal mortality. Conclusions: The low-cost servo-controlled cooling device maintained the core temperature well within the target range. Adequately powered clinical trials are required to establish the safety and efficacy of TH in LMICs. Clinical trial registration number: NCT01760629.

  • Journal article
    Mason SL, Daws RE, Soreq E, Johnson EB, Scahill RI, Tabrizi SJ, Barker RA, Hampshire Aet al., 2018,

    Predicting clinical diagnosis in Huntington's disease: An imaging polymarker

    , ANNALS OF NEUROLOGY, Vol: 83, Pages: 532-543, ISSN: 0364-5134

    ObjectiveHuntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real‐life clinical diagnosis in HD.MethodA multivariate machine learning approach was applied to resting‐state and structural magnetic resonance imaging scans from 19 premanifest HD gene carriers (preHD, 8 of whom developed clinical disease in the 5 years postscanning) and 21 healthy controls. A classification model was developed using cross‐group comparisons between preHD and controls, and within the preHD group in relation to “estimated” and “actual” proximity to disease onset. Imaging measures were modeled individually, and combined, and permutation modeling robustly tested classification accuracy.ResultsClassification performance for preHDs versus controls was greatest when all measures were combined. The resulting polymarker predicted converters with high accuracy, including those who were not expected to manifest in that time scale based on the currently adopted statistical models.InterpretationWe propose that a holistic multivariate machine learning treatment of brain abnormalities in the premanifest phase can be used to accurately identify those patients within 5 years of developing motor features of HD, with implications for prognostication and preclinical trials.

  • Journal article
    Sandrone S, Cambiaghi M, 2018,

    Ugo Cerletti (1877-1963)

    , JOURNAL OF NEUROLOGY, Vol: 265, Pages: 731-732, ISSN: 0340-5354
  • Journal article
    Huntley J, Corbett A, Wesnes K, Brooker H, Stenton R, Hampshire A, Ballard Cet al., 2018,

    Online assessment of risk factors for dementia and cognitive function in healthy adults.

    , Int J Geriatr Psychiatry, Vol: 33, Pages: e286-e293

    OBJECTIVE: Several potentially modifiable risk factors for cognitive decline and dementia have been identified, including low educational attainment, smoking, diabetes, physical inactivity, hypertension, midlife obesity, depression, and perceived social isolation. Managing these risk factors in late midlife and older age may help reduce the risk of dementia; however, it is unclear whether these factors also relate to cognitive performance in older individuals without dementia. METHOD: Data from 14 201 non-demented individuals aged >50 years who enrolled in the online PROTECT study were used to examine the relationship between cognitive function and known modifiable risk factors for dementia. Multivariate regression analyses were conducted on 4 cognitive outcomes assessing verbal and spatial working memory, visual episodic memory, and verbal reasoning. RESULTS: Increasing age was associated with reduced performance across all tasks. Higher educational achievement, the presence of a close confiding relationship, and moderate alcohol intake were associated with benefits across all 4 cognitive tasks, and exercise was associated with better performance on verbal reasoning and verbal working memory tasks. A diagnosis of depression was negatively associated with performance on visual episodic memory and working memory tasks, whereas being underweight negatively affected performance on all tasks apart from verbal working memory. A history of stroke was negatively associated with verbal reasoning and working memory performance. CONCLUSION: Known modifiable risk factors for dementia are associated with cognitive performance in non-demented individuals in late midlife and older age. This provides further support for public health interventions that seek to manage these risk factors across the lifespan.

  • Journal article
    Zanin E, Moro A, Sandrone S, 2018,

    Eric Heinz Lenneberg (1921-1975)

    , JOURNAL OF NEUROLOGY, Vol: 265, Pages: 449-450, ISSN: 0340-5354
  • Journal article
    Jenkins PO, De Simoni S, Bourke N, Fleminger J, Scott G, Towey D, Svensson W, Khan S, Patel M, Greenwood R, Cole J, Sharp DJet al., 2018,

    Dopaminergic abnormalities following traumatic brain injury

    , Brain, Vol: 141, Pages: 797-810, ISSN: 1460-2156

    Traumatic brain injury can reduce striatal dopamine levels. The cause of this is uncertain, but is likely to be related to damage to the nigrostriatal system. We investigated the pattern of striatal dopamine abnormalities using 123I-Ioflupane single-photon emission computed tomography (SPECT) scans and their relationship to nigrostriatal damage and clinical features. We studied 42 moderate–severe traumatic brain injury patients with cognitive impairments but no motor parkinsonism signs and 20 healthy controls. 123I-Ioflupane scanning was used to assess dopamine transporter levels. Clinical scan reports were compared to quantitative dopamine transporter results. Advanced MRI methods were used to assess the nigrostriatal system, including the area through which the nigrostriatal projections pass as defined from high-resolution Human Connectome data. Detailed clinical and neuropsychological assessments were performed. Around 20% of our moderate–severe patients had clear evidence of reduced specific binding ratios for the dopamine transporter in the striatum measured using 123I-Ioflupane SPECT. The caudate was affected more consistently than other striatal regions. Dopamine transporter abnormalities were associated with reduced substantia nigra volume. In addition, diffusion MRI provided evidence of damage to the regions through which the nigrostriatal tract passes, particularly the area traversed by dopaminergic projections to the caudate. Only a small percentage of patients had evidence of macroscopic lesions in the striatum and there was no relationship between presence of lesions and dopamine transporter specific binding ratio abnormalities. There was also no relationship between reduced volume in the striatal subregions and reduced dopamine transporter specific binding ratios. Patients with low caudate dopamine transporter specific binding ratios show impaired processing speed and executive dysfunction compared to patients with normal levels. Taken toge

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