665 research outputs found

    Computer models to inform epilepsy surgery strategies: prediction of postoperative outcome

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    This is the final version of the article. Available from OUP via the DOI in this record.M.G., M.P.R. and J.R.T. gratefully acknowledge the financial support of the EPSRC via grant EP/N014391/1. They further acknowledge funding from Epilepsy Research UK via grant number A1007 and the Medical Research Council via grant MR/K013998/1. The contribution of M.G. and J.R.T. was generously supported by a Wellcome Trust Institutional Strategic Support Award (WT105618MA). M.P.R. is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust. C.R. and A.E. were supported by the Swiss National Science Foundation (grant SPUM 140332). K.S. is grateful for support from the Swiss National Science Foundation (grants 122010 and 155950)

    Revealing epilepsy type using a computational analysis of interictal EEG

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    This is the final version. Available from Nature Research via the DOI in this record.All materials (functional networks and code) are available upon request from the corresponding author.Seizure onset in epilepsy can usually be classified as focal or generalized, based on a combination of clinical phenomenology of the seizures, EEG recordings and MRI. This classification may be challenging when seizures and interictal epileptiform discharges are infrequent or discordant, and MRI does not reveal any apparent abnormalities. To address this challenge, we introduce the concept of Ictogenic Spread (IS) as a prediction of how pathological electrical activity associated with seizures will propagate throughout a brain network. This measure is defined using a person-specific computer representation of the functional network of the brain, constructed from interictal EEG, combined with a computer model of the transition from background to seizure-like activity within nodes of a distributed network. Applying this method to a dataset comprising scalp EEG from 38 people with epilepsy (17 with genetic generalized epilepsy (GGE), 21 with mesial temporal lobe epilepsy (mTLE)), we find that people with GGE display a higher IS in comparison to those with mTLE. We propose IS as a candidate computational biomarker to classify focal and generalized epilepsy using interictal EEG.Medical Research Council (MRC)Wellcome TrustEpilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome Trus

    Revealing epilepsy type using a computational analysis of interictal EEG.

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    Seizure onset in epilepsy can usually be classified as focal or generalized, based on a combination of clinical phenomenology of the seizures, EEG recordings and MRI. This classification may be challenging when seizures and interictal epileptiform discharges are infrequent or discordant, and MRI does not reveal any apparent abnormalities. To address this challenge, we introduce the concept of Ictogenic Spread (IS) as a prediction of how pathological electrical activity associated with seizures will propagate throughout a brain network. This measure is defined using a person-specific computer representation of the functional network of the brain, constructed from interictal EEG, combined with a computer model of the transition from background to seizure-like activity within nodes of a distributed network. Applying this method to a dataset comprising scalp EEG from 38 people with epilepsy (17 with genetic generalized epilepsy (GGE), 21 with mesial temporal lobe epilepsy (mTLE)), we find that people with GGE display a higher IS in comparison to those with mTLE. We propose IS as a candidate computational biomarker to classify focal and generalized epilepsy using interictal EEG

    Computational modelling in source space from scalp EEG to inform presurgical evaluation of epilepsy

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    This is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this recordObjective: The effectiveness of intracranial electroencephalography (iEEG) to inform epilepsy surgery depends on where iEEG electrodes are implanted. This decision is informed by noninvasive recording modalities such as scalp EEG. Herein we propose a framework to interrogate scalp EEG and determine epilepsy lateralization to aid in electrode implantation. Methods: We use eLORETA to map source activities from seizure epochs recorded from scalp EEG and consider 15 regions of interest (ROIs). Functional networks are then constructed using the phase-locking value and studied using a mathematical model. By removing different ROIs from the network and simulating their impact on the network’s ability to generate seizures in silico, the framework provides predictions of epilepsy lateralization. We consider 15 individuals from the EPILEPSIAE database and study a total of 62 seizures. Results were assessed by taking into account actual intracranial implantations and surgical outcome. Results: The framework provided potentially useful information regarding epilepsy lateralization in 12 out of the 15 individuals (p=0.02, binomial test). Conclusions: Our results show promise for the use of this framework to better interrogate scalp EEG to determine epilepsy lateralization. Significance: The framework may aid clinicians in the decision process to define where to implant electrodes for intracranial monitoring.Medical Research CouncilEpilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome TrustEngineering and Physical Sciences Research Council (EPSRC)Innovate UKEuropean Union’s Horizon 2020Alzheimer's SocietyMedical Research Counci

    Elevated ictal brain network ictogenicity enables prediction of optimal seizure control

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    This is the final version of the article. Available from Frontiers Media via the DOI in this record.Recent studies have shown that mathematical models can be used to analyze brain networks by quantifying how likely they are to generate seizures. In particular, we have introduced the quantity termed brain network ictogenicity (BNI), which was demonstrated to have the capability of differentiating between functional connectivity (FC) of healthy individuals and those with epilepsy. Furthermore, BNI has also been used to quantify and predict the outcome of epilepsy surgery based on FC extracted from pre-operative ictal intracranial electroencephalography (iEEG). This modeling framework is based on the assumption that the inferred FC provides an appropriate representation of an ictogenic network, i.e., a brain network responsible for the generation of seizures. However, FC networks have been shown to change their topology depending on the state of the brain. For example, topologies during seizure are different to those pre- and post-seizure. We therefore sought to understand how these changes affect BNI. We studied peri-ictal iEEG recordings from a cohort of 16 epilepsy patients who underwent surgery and found that, on average, ictal FC yield higher BNI relative to pre- and post-ictal FC. However, elevated ictal BNI was not observed in every individual, rather it was typically observed in those who had good post-operative seizure control. We therefore hypothesize that elevated ictal BNI is indicative of an ictogenic network being appropriately represented in the FC. We evidence this by demonstrating superior model predictions for post-operative seizure control in patients with elevated ictal BNI.ML, MG, MR, and JT gratefully acknowledge funding from the Medical Research Council via grant MR/K013998/1. MG, MR, and JT further acknowledge the financial support of the EPSRC via grant EP/N014391/1. The contribution of MG and JT was further generously supported by a Wellcome Trust Institutional Strategic Support Award (WT105618MA). MR and EA are supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust. KS gratefully acknowledges support by the Swiss National Science Foundation (SNF 32003B_155950)

    Background EEG connectivity captures the time-course of epileptogenesis in a mouse model of epilepsy

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    This is the author accepted manuscript. The final version is available from Society for Neuroscience via the DOI in this recordLarge-scale brain networks are increasingly recognized as important for the generation of seizures in epilepsy. However, how a network evolves from a healthy state through the process of epileptogenesis remains unclear. To address this question, here, we study longitudinal epicranial background EEG recordings (30 electrodes, EEG free from epileptiform activity) of a mouse model of mesial temporal lobe epilepsy. We analyse functional connectivity networks and observe that over the time-course of epileptogenesis the networks become increasingly asymmetric. Furthermore, computational modelling reveals that a set of nodes, located outside of the region of initial insult, emerges as particularly important for the network dynamics. These findings are consistent with experimental observations, thus demonstrating that ictogenic mechanisms can be revealed on the EEG, that computational models can be used to monitor unfolding epileptogenesis and that both the primary focus and epileptic network play a role in epileptogenesis.Epilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome Trus

    A study of general practitioners' perspectives on electronic medical records systems in NHS Scotland

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    <b>Background</b> Primary care doctors in NHSScotland have been using electronic medical records within their practices routinely for many years. The Scottish Health Executive eHealth strategy (2008-2011) has recently brought radical changes to the primary care computing landscape in Scotland: an information system (GPASS) which was provided free-of-charge by NHSScotland to a majority of GP practices has now been replaced by systems provided by two approved commercial providers. The transition to new electronic medical records had to be completed nationally across all health-boards by March 2012. <p></p><b> Methods</b> We carried out 25 in-depth semi-structured interviews with primary care doctors to elucidate GPs' perspectives on their practice information systems and collect more general information on management processes in the patient surgical pathway in NHSScotland. We undertook a thematic analysis of interviewees' responses, using Normalisation Process Theory as the underpinning conceptual framework. <p></p> <b>Results</b> The majority of GPs' interviewed considered that electronic medical records are an integral and essential element of their work during the consultation, playing a key role in facilitating integrated and continuity of care for patients and making clinical information more accessible. However, GPs expressed a number of reservations about various system functionalities - for example: in relation to usability, system navigation and information visualisation. <b>Conclusion </b>Our study highlights that while electronic information systems are perceived as having important benefits, there remains substantial scope to improve GPs' interaction and overall satisfaction with these systems. Iterative user-centred improvements combined with additional training in the use of technology would promote an increased understanding, familiarity and command of the range of functionalities of electronic medical records among primary care doctors

    Arterial oxygen content is precisely maintained by graded erythrocytotic responses in settings of high/normal serum iron levels, and predicts exercise capacity: an observational study of hypoxaemic patients with pulmonary arteriovenous malformations.

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    Oxygen, haemoglobin and cardiac output are integrated components of oxygen transport: each gram of haemoglobin transports 1.34 mls of oxygen in the blood. Low arterial partial pressure of oxygen (PaO2), and haemoglobin saturation (SaO2), are the indices used in clinical assessments, and usually result from low inspired oxygen concentrations, or alveolar/airways disease. Our objective was to examine low blood oxygen/haemoglobin relationships in chronically compensated states without concurrent hypoxic pulmonary vasoreactivity.165 consecutive unselected patients with pulmonary arteriovenous malformations were studied, in 98 cases, pre/post embolisation treatment. 159 (96%) had hereditary haemorrhagic telangiectasia. Arterial oxygen content was calculated by SaO2 x haemoglobin x 1.34/100.There was wide variation in SaO2 on air (78.5-99, median 95)% but due to secondary erythrocytosis and resultant polycythaemia, SaO2 explained only 0.1% of the variance in arterial oxygen content per unit blood volume. Secondary erythrocytosis was achievable with low iron stores, but only if serum iron was high-normal: Low serum iron levels were associated with reduced haemoglobin per erythrocyte, and overall arterial oxygen content was lower in iron deficient patients (median 16.0 [IQR 14.9, 17.4]mls/dL compared to 18.8 [IQR 17.4, 20.1]mls/dL, p<0.0001). Exercise tolerance appeared unrelated to SaO2 but was significantly worse in patients with lower oxygen content (p<0.0001). A pre-defined athletic group had higher Hb:SaO2 and serum iron:ferritin ratios than non-athletes with normal exercise capacity. PAVM embolisation increased SaO2, but arterial oxygen content was precisely restored by a subsequent fall in haemoglobin: 86 (87.8%) patients reported no change in exercise tolerance at post-embolisation follow-up.Haemoglobin and oxygen measurements in isolation do not indicate the more physiologically relevant oxygen content per unit blood volume. This can be maintained for SaO2 ≥78.5%, and resets to the same arterial oxygen content after correction of hypoxaemia. Serum iron concentrations, not ferritin, seem to predict more successful polycythaemic responses

    Comparison of SPECT bone scintigraphy with MRI for diagnosis of meniscal tears

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    BACKGROUND: Scintigraphy has been considered as competitive to MRI, but limited data are available on the accuracy of single photon emission tomography (SPECT) compared with MRI for the assessment of meniscal tears. Our objective was to assess the value of SPECT in comparison to MRI. METHODS: Between January 2003 and March 2004, sixteen patients were studied with both modalities and the accuracy rates of SPECT scan results, and MRI findings in the diagnosis of meniscal tears were compared. Arthroscopy was the gold standard. RESULTS: The respective sensitivity rate, specificity rate, and positive and negative predictive accuracies of MRI were 89%, 94%, 93%, and 79% and for SPECT those were 78%, 94%, 94%, and 88%. There was good agreement on the presence or absence of tears between two modalities (κ statistic = 0.699). CONCLUSION: SPECT and MRI are both valuable imaging techniques. SPECT is a useful alternative when MRI is unavailable or unsuitable and it is beneficial when more possible accuracy is desired (such as when MRI results are either inconclusive or conflict with other clinical data)

    Cigarettes and alcohol in relation to colorectal cancer: the Singapore Chinese Health Study

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    The relations were examined between colorectal cancer and cigarette smoking and alcohol consumption within the Singapore Chinese Health Study, a population-based, prospective cohort of 63 257 middle-aged and older Chinese men and women enrolled between 1993 and 1998, from whom baseline data on cigarette smoking and alcohol consumption were collected through in-person interviews. By 31 December 2004, 845 cohort participants had developed colorectal cancer (516 colon cancer, 329 rectal cancer). Compared with nondrinkers, subjects who drank seven or more alcoholic drinks per week had a statistically significant, 72% increase in risk of colorectal cancer hazard ratio (HR)=1.72; 95% confidence interval (CI)=1.33–2.22). Cigarette smoking was associated with an increased risk of rectal cancer only. Compared with nonsmokers, HRs (95% CIs) for rectal cancer were 1.43 (1.10–1.87) for light smokers and 2.64 (1.77–3.96) for heavy smokers. Our data indicate that cigarette smoking and alcohol use interact in the Chinese population in an additive manner in affecting risk of rectal cancer, thus suggesting that these two exposures may share a common etiologic pathway in rectal carcinogenesis
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