A low mortality, high morbidity Reduced Intensity Status Epilepticus (RISE) model of epilepsy and epileptogenesis in the rat

Animal models of acquired epilepsies aim to provide researchers with tools for use in understanding the processes underlying the acquisition, development and establishment of the disorder. Typically, following a systemic or local insult, vulnerable brain regions undergo a process leading to the development, over time, of spontaneous recurrent seizures. Many such models make use of a period of intense seizure activity or status epilepticus, and this may be associated with high mortality and/or global damage to large areas of the brain. These undesirable elements have driven improvements in the design of chronic epilepsy models, for example the lithium-pilocarpine epileptogenesis model. Here, we present an optimised model of chronic epilepsy that reduces mortality to 1% whilst retaining features of high epileptogenicity and development of spontaneous seizures. Using local field potential recordings from hippocampus in vitro as a probe, we show that the model does not result in significant loss of neuronal network function in area CA3 and, instead, subtle alterations in network dynamics appear during a process of epileptogenesis, which eventually leads to a chronic seizure state. The model’s features of very low mortality and high morbidity in the absence of global neuronal damage offer the chance to explore the processes underlying epileptogenesis in detail, in a population of animals not defined by their resistance to seizures, whilst acknowledging and being driven by the 3Rs (Replacement, Refinement and Reduction of animal use in scientific procedures) principles.

The tuberous sclerosis 2000 study:presentation initial assessments and implications for diagnosis and management

Aims: The Tuberous Sclerosis 2000 Study is the first comprehensive longitudinal study of tuberous sclerosis (TS) and aims to identify factors that determine prognosis. Mode of presentation and findings at initial assessments are reported here. Methods: Children aged 0-16 years newly diagnosed with TS in the UK were evaluated. Results: 125 children with TS were studied. 114 (91%) met clinical criteria for a definite diagnosis and the remaining 11 (9%) had pathogenic TSC1 or TSC2 mutations. In families with a definite clinical diagnosis, the detection rate for pathogenic mutations was 89%. 21 cases (17%) were identified prenatally, usually with abnormalities found at routine antenatal ultrasound examination. 30 cases (24%) presented before developing seizures and in 10 of these without a definite diagnosis at onset of seizures, genetic testing could have confirmed TS. 77 cases (62%) presented with seizures. Median age at recruitment assessment was 2.7 years (range:4 weeks-18 years). Dermatological features of TS were present in 81%. The detection rate of TS abnormalities was 20/107 (19%) for renal ultrasound including three cases with polycystic kidney disease, 51/88 (58%) for echocardiography, 29/35 (83%) for cranial CT and 95/104 (91%) for cranial MRI. 91% of cases had epilepsy and 65% had intellectual disability (IQ<70). Conclusions: Genetic testing can be valuable in confirming the diagnosis. Increasing numbers of cases present prenatally or in early infancy, before onset of seizures, raising important questions about whether these children should have EEG monitoring and concerning the criteria for starting anticonvulsant therapy.

Neurophysiological investigations for the diagnosis of non-epileptic attack disorder in neuropsychiatry services:from safety standards to improved effectiveness

OBJECTIVE: The discipline of clinical neuropsychiatry currently provides specialised services for a number of conditions that cross the traditional boundaries of neurology and psychiatry, including non-epileptic attack disorder. Neurophysiological investigations have an important role within neuropsychiatry services, with video-electroencephalography (EEG) telemetry being the gold standard investigation for the differential diagnosis between epileptic seizures and non-epileptic attacks. This article reviews existing evidence on best practices for neurophysiology investigations, with focus on safety measures for video-EEG telemetry. METHODS: We conducted a systematic literature review using the PubMed database in order to identify the scientific literature on the best practices when using neurophysiological investigations in patients with suspected epileptic seizures or non-epileptic attacks. RESULTS: Specific measures need to be implemented for video-EEG telemetry to be safely and effectively carried out by neuropsychiatry services. A confirmed diagnosis of non-epileptic attack disorder following video-EEG telemetry carried out within neuropsychiatry units has the inherent advantage of allowing diagnosis communication and implementation of treatment strategies in a timely fashion, potentially improving clinical outcomes and cost-effectiveness significantly. CONCLUSION: The identified recommendations set the stage for the development of standardised guidelines to enable neuropsychiatry services to implement streamlined and evidence-based care pathways.

Seizure detection in subdural recordings using nonlinear decision functions

This dissertation proposed a new approach to seizure detection in intracranial EEG recordings using nonlinear decision functions. It implemented well-established features that were designed to deal with complex signals such as brain recordings, and proposed a 2-D domain of analysis. Since the features considered assume both the time and frequency domains, the analysis was carried out both temporally and as a function of different frequency ranges in order to ascertain those measures that were most suitable for seizure detection. In retrospect, this study established a generalized approach to seizure detection that works across several features and across patients. ^ Clinical experiments involved 8 patients with intractable seizures that were evaluated for potential surgical interventions. A total of 35 iEEG data files collected were used in a training phase to ascertain the reliability of the formulated features. The remaining 69 iEEG data files were then used in the testing phase. ^ The testing phase revealed that the correlation sum is the feature that performed best across all patients with a sensitivity of 92% and an accuracy of 99%. The second best feature was the gamma power with a sensitivity of 92% and an accuracy of 96%. In the frequency domain, all of the 5 other spectral bands considered, revealed mixed results in terms of low sensitivity in some frequency bands and low accuracy in other frequency bands, which is expected given that the dominant frequencies in iEEG are those of the gamma band. In the time domain, other features which included mobility, complexity, and activity, all performed very well with an average a sensitivity of 80.3% and an accuracy of 95%. ^ The computational requirement needed for these nonlinear decision functions to be generated in the training phase was extremely long. It was determined that when the duration dimension was rescaled, the results improved and the convergence rates of the nonlinear decision functions were reduced dramatically by more than a 100 fold. Through this rescaling, the sensitivity of the correlation sum improved to 100% and the sensitivity of the gamma power to 97%, which meant that there were even less false negatives and false positives detected. ^

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

In vivo characterization of epileptic tissue with optical spectroscopy

For children with intractable seizures, surgical removal of epileptic foci, if identifiable and feasible, can be an effective way to reduce or eliminate seizures. The success of this type of surgery strongly hinges upon the ability to identify and demarcate those epileptic foci. The ultimate goal of this research project is to develop an effective technology for detection of unique in vivo pathophysiological characteristics of epileptic cortex and, subsequently, to use this technology to guide epilepsy surgery intraoperatively. In this PhD dissertation the feasibility of using optical spectroscopy to identify uniquein vivo pathophysiological characteristics of epileptic cortex was evaluated and proven using the data collected from children undergoing epilepsy surgery. ^ In this first in vivo human study, static diffuse reflectance and fluorescence spectra were measured from the epileptic cortex, defined by intraoperative ECoG, and its surrounding tissue from pediatric patients undergoing epilepsy surgery. When feasible, biopsy samples were taken from the investigated sites for the subsequent histological analysis. Using the histological data as the gold standard, spectral data was analyzed with statistical tools. The results of the analysis show that static diffuse reflectance spectroscopy and its combination with static fluorescence spectroscopy can be used to effectively differentiate between epileptic cortex with histopathological abnormalities and normal cortex in vivo with a high degree of accuracy. ^ To maximize the efficiency of optical spectroscopy in detecting and localizing epileptic cortex intraoperatively, the static system was upgraded to investigate histopathological abnormalities deep within the epileptic cortex, as well as to detect unique temporal pathophysiological characteristics of epileptic cortex. Detection of deep abnormalities within the epileptic cortex prompted a redesign of the fiberoptic probe. A mechanical probe holder was also designed and constructed to maintain the probe contact pressure and contact point during the time dependent measurements. The dynamic diffuse reflectance spectroscopy system was used to characterize in vivo pediatric epileptic cortex. The results of the study show that some unique wavelength dependent temporal characteristics (e.g., multiple horizontal bands in the correlation coefficient map γ(λref = 800 nm, λcomp ,t)) can be found in the time dependent recordings of diffuse reflectance spectra from epileptic cortex defined by ECoG.^

A Research Platform for Artificial Neural Networks with Applications in Pediatric Epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and non-epileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that 1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and 2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Determinantes genéticos e ambientais das doenças hipertensivas da gravidez

The development of complex diseases such as preeclampsia are determined by both environmental and genetic factors, but there is also interaction among these factors. Preeclampsia is a pregnancy-specific disorder characterized by de-novo hypertension and proteinuria after 20th week of gestation. There is a broad spectrum of clinical presentations related to hypertensive disorders of pregnancy (HDP) that can range from mild preeclampsia to eclampsia (seizures) or HELLP syndrome (Hemolysis, Elevation of Liver enzymes, Low Platelets). Those clinical outcomes might be linked to different pathological mechanisms. Our work aims to identify factors (i.e. genes and environmental) associated with the HDP’s clinical spectrum. Using a case-control approach, we selected a total of 1498 pregnant women for epidemiological and genetic studies, encompassing 755 normotensive (control); 518 preeclampsia; 84 eclampsia; and 141 HELLP. Women were genotyped for 18 SNPs across 5 candidate genes (FLT1, ACVR2A, ERAP1, ERAP2 and LNPEP). For the environmental factors, we found maternal age, parity status and pre-gestational body mass index as important risk factors associated with disease. Genes were associated in a phenotype-specific manner: ACVR2A with early preeclampsia (rs1424954, p=0.002); FLT1 with HELLP syndrome (rs9513095, p=0.003); and ERAP1 with eclampsia (rs30187, p=0.03). Our results suggest that different genetic mechanisms along with specific environmental factors might determine the clinical spectrum of HDP. In addition, phenotype refinement seems to be an essential step in the search for complex disease genes

Segurança do paciente em terapia intensiva neonatal: identificação e análise de eventos adversos

The patient safety is a major concern in health services for its global dimension, as evidenced by the fragility of care processes that predispose an occurrence of adverse events. These events in a neonatal intensive care unit are considered serious and hazardous to lives of newborns. The present study aimed to identify and analyze adverse events in a neonatal intensive care unit based in Trigger Tool. It is an epidemiological, cross-sectional , exploratory, retrospective study with quantitative, descriptive and analytical approach, performed in 2015 at a school hospital. The sample was not probabilistic, involving 116 newborns who met the eligibility criteria. Data collection was performed by retrospective review of medical records, using a specific kind of "trigger" instrument, composed of sentinel events in neonatology, adapted from the American model used by the Vermont-Oxford Network. Data were analyzed using descriptive and inferential statistics. The chi-square test for linear trend was used to assess the associations between the variables of interest. The research received a favorable agreement from Ethics Committee of the Federal University of Rio Grande do Norte, under number 1055533, and Presentation Certificate for Ethics Assessment 43894515.6.0000.5537. The results show among investigated newborns, 110 experienced at least one adverse event during their stay, with a total of 391 medical records analyzed and rate of 3.37 events per patient. Prevailed the preterm newborns with low birth weight, from mother who had hypertensive diseases during pregnancy and urinary tract infection. The average hospitalization time was 25 days, associated with hospital-acquired infections events (p = 0.01). Among the identified adverse events stood out the events related to thermoregulation disorders (39.0%), with prevalence of hypothermia (26.0%), followed by health care-related infections (16.4%) and blood glucose disorders, hypoglycemia (9.00%) and hyperglycemia (6.64%). Most of these incidents were classified in categories E and F, which represents that there was damage small proportion. Due to these damages come from the care practice with newborn, 78% were classified as avoidable. There was statistically significant association between the variable birth weight with infections (p = 0.006) as well as peri/intraventricular bleeding (p = 0.02), hypoglycemia (p = 0.021), hyperglycemia (p = 0.001), hyperthermia (p = 0.39) and death (p=0,02). Gestational age was associated with seizures (p = 0.002), hyperglycemia (p=0.017) e hyperthermia (p=0.027). The security institution culture was reported by the health workers as intermediate, even though the number of adverse events found in only one unit of service indicates that there is much to be done. Thus the high rate of adverse events identified in the neonatal intensive care unit reinforces the necessity to elaborate specific preventive strategies for this risk environment.

Segurança do paciente em terapia intensiva neonatal: identificação e análise de eventos adversos

The patient safety is a major concern in health services for its global dimension, as evidenced by the fragility of care processes that predispose an occurrence of adverse events. These events in a neonatal intensive care unit are considered serious and hazardous to lives of newborns. The present study aimed to identify and analyze adverse events in a neonatal intensive care unit based in Trigger Tool. It is an epidemiological, cross-sectional , exploratory, retrospective study with quantitative, descriptive and analytical approach, performed in 2015 at a school hospital. The sample was not probabilistic, involving 116 newborns who met the eligibility criteria. Data collection was performed by retrospective review of medical records, using a specific kind of "trigger" instrument, composed of sentinel events in neonatology, adapted from the American model used by the Vermont-Oxford Network. Data were analyzed using descriptive and inferential statistics. The chi-square test for linear trend was used to assess the associations between the variables of interest. The research received a favorable agreement from Ethics Committee of the Federal University of Rio Grande do Norte, under number 1055533, and Presentation Certificate for Ethics Assessment 43894515.6.0000.5537. The results show among investigated newborns, 110 experienced at least one adverse event during their stay, with a total of 391 medical records analyzed and rate of 3.37 events per patient. Prevailed the preterm newborns with low birth weight, from mother who had hypertensive diseases during pregnancy and urinary tract infection. The average hospitalization time was 25 days, associated with hospital-acquired infections events (p = 0.01). Among the identified adverse events stood out the events related to thermoregulation disorders (39.0%), with prevalence of hypothermia (26.0%), followed by health care-related infections (16.4%) and blood glucose disorders, hypoglycemia (9.00%) and hyperglycemia (6.64%). Most of these incidents were classified in categories E and F, which represents that there was damage small proportion. Due to these damages come from the care practice with newborn, 78% were classified as avoidable. There was statistically significant association between the variable birth weight with infections (p = 0.006) as well as peri/intraventricular bleeding (p = 0.02), hypoglycemia (p = 0.021), hyperglycemia (p = 0.001), hyperthermia (p = 0.39) and death (p=0,02). Gestational age was associated with seizures (p = 0.002), hyperglycemia (p=0.017) e hyperthermia (p=0.027). The security institution culture was reported by the health workers as intermediate, even though the number of adverse events found in only one unit of service indicates that there is much to be done. Thus the high rate of adverse events identified in the neonatal intensive care unit reinforces the necessity to elaborate specific preventive strategies for this risk environment.

Dynamic classifiers for neonatal brain monitoring

Brain injury due to lack of oxygen or impaired blood flow around the time of birth, may cause long term neurological dysfunction or death in severe cases. The treatments need to be initiated as soon as possible and tailored according to the nature of the injury to achieve best outcomes. The Electroencephalogram (EEG) currently provides the best insight into neurological activities. However, its interpretation presents formidable challenge for the neurophsiologists. Moreover, such expertise is not widely available particularly around the clock in a typical busy Neonatal Intensive Care Unit (NICU). Therefore, an automated computerized system for detecting and grading the severity of brain injuries could be of great help for medical staff to diagnose and then initiate on-time treatments. In this study, automated systems for detection of neonatal seizures and grading the severity of Hypoxic-Ischemic Encephalopathy (HIE) using EEG and Heart Rate (HR) signals are presented. It is well known that there is a lot of contextual and temporal information present in the EEG and HR signals if examined at longer time scale. The systems developed in the past, exploited this information either at very early stage of the system without any intelligent block or at very later stage where presence of such information is much reduced. This work has particularly focused on the development of a system that can incorporate the contextual information at the middle (classifier) level. This is achieved by using dynamic classifiers that are able to process the sequences of feature vectors rather than only one feature vector at a time.

Seizure burden and neurodevelopmental outcome in neonates with hypoxic-ischemic encephalopathy.

Aim: To examine the relationship between electrographic seizures and long-term outcome in neonates with hypoxic-ischemic encephalopathy (HIE). Method: Full-term neonates with HIE born in Cork University Maternity Hospital from 2003 to 2006 (pre-hypothermia era) and 2009 to 2012 (hypothermia era) were included in this observational study. All had early continuous electroencephalography monitoring. All electrographic seizures were annotated. The total seizure burden and hourly seizure burden were calculated. Outcome (normal/abnormal) was assessed at 24 to 48 months in surviving neonates using either the Bayley Scales of Infant and Toddler Development, Third Edition or the Griffiths Mental Development Scales; a diagnosis of cerebral palsy or epilepsy was also considered an abnormal outcome. Results: Continuous electroencephalography was recorded for a median of 57.1 hours (interquartile range 33.5-80.5h) in 47 neonates (31 males, 16 females); 29 out of 47 (62%) had electrographic seizures and 25 out of 47 (53%) had an abnormal outcome. The presence of seizures per se was not associated with abnormal outcome (p=0.126); however, the odds of an abnormal outcome increased over ninefold (odds ratio [OR] 9.56; 95% confidence interval [95% CI] 2.43-37.67) if a neonate had a total seizure burden of more than 40 minutes (p=0.001), and eightfold (OR: 8.00; 95% CI: 2.06-31.07) if a neonate had a maximum hourly seizure burden of more than 13 minutes per hour (p=0.003). Controlling for electrographic HIE grade or treatment with hypothermia did not change the direction of the relationship between seizure burden and outcome. Interpretation: In HIE, a high electrographic seizure burden is significantly associated with abnormal outcome, independent of HIE severity or treatment with hypothermia.

Meningeal alveolar soft part sarcoma confirmed by characteristic ASPCR1-TFE3 fusion

Sarcoma metastatic to the brain is uncommon and rarely occurs as the initial manifestation of tumor. Alveolar soft part sarcoma (ASPS) is a rare but well-studied subtype of sarcoma. A 39-year-old man presented with seizures due to a left temporal meningeal-enhancing lesion with striking brain edema on MRI. The patient underwent neurosurgical resection for suspected meningioma. Histology showed large tumor cells clustering and forming small nests, in places with pseudoalveolar pattern. Diastase-resistant periodic acid-Schiff revealed very rare granular and rod-like cytoplasmic inclusions. Immunohistochemistry showed convincing positivity only with vimentin and smooth muscle actin. The histological features were strongly suggestive of ASPS. At the molecular level RT-PCR and sequencing analysis demonstrated ASPCR1-TFE3 fusion confirming the histological diagnosis of ASPS. There was no evidence of primary extracranial tumor by physical examination and on chest and abdominal CT scan 11 months after presentation. ASPS typically arise from the soft tissues of the extremities and develop multiple metastatic deposits usually with a long clinical course. This case may represent primary meningeal ASPS although metastatic deposit from an undiscovered primary site cannot be entirely excluded.

Electrophysiological effects of guanosine and MK-801 in a quinolinic acid-induced seizure model

TORRES, F ; FILHO, M.S. ; ANTUNES, C. ; KALININE, E. ; ANTONIOLLI, E. ; PORTELA, Luis Valmor ; SOUZA, Diogo Onofre ; TORT, A. B. L. . Electrophysiological effects of guanosine and MK-801 in a quinolinic acid-induced seizure model. Experimental Neurology , v. 221, p. 296-306, 2010

Parental reports of the oral health-related quality of life of children with cerebral palsy

BACKGROUND The severity of physical and mental impairments and oral problems, as well as socioeconomic factors, may have an impact on quality of life of children with cerebral palsy (CP). The aim of this research was to assess the impact of impairments and oral health conditions, adjusted by socioeconomic factors, on the Oral Health-Related Quality of Life (OHRQoL) of children with CP using their parents as proxies. METHODS Sixty children, between 6-14 years of age were selected. Their parents answered a children's OHRQoL instrument (5 domains) which combines the Parental-Caregivers Perception Questionnaire (P-CPQ) and Family Impact Scale (FIS). The severity of dental caries, type of CP, communication ability, gross motor function, seizures and socioeconomic conditions were assessed. RESULTS Considering the total score of the OHRQoL instrument, only the reduction of communication ability and dental caries severity had a negative impact on the OHRQoL (p < 0.05). Considering each domain of the instrument, the severity of the type of CP and its reduction of communication ability showed a negative impact on oral symptoms and functional limitations domains (p < 0.05). Seizures have a negative impact on oral symptoms domain (p = 0.006). The multivariate fitted model showed that the severity of dental caries, communication ability and low family income were negatively associated with the impact on OHRQoL (p = 0.001). CONCLUSIONS The severity of dental caries, communication ability, and family income are conditions strongly associated with a negative impact on OHRQoL of children with CP.