International Veterinary Epilepsy Task Force recommendations for a veterinary epilepsy-specific MRI protocol

Epilepsy is one of the most common chronic neurological diseases in veterinary practice. Magnetic resonance imaging (MRI) is regarded as an important diagnostic test to reach the diagnosis of idiopathic epilepsy. However, given that the diagnosis requires the exclusion of other differentials for seizures, the parameters for MRI examination should allow the detection of subtle lesions which may not be obvious with existing techniques. In addition, there are several differentials for idiopathic epilepsy in humans, for example some focal cortical dysplasias, which may only apparent with special sequences, imaging planes and/or particular techniques used in performing the MRI scan. As a result, there is a need to standardize MRI examination in veterinary patients with techniques that reliably diagnose subtle lesions, identify post-seizure changes, and which will allow for future identification of underlying causes of seizures not yet apparent in the veterinary literature. There is a need for a standardized veterinary epilepsy-specific MRI protocol which will facilitate more detailed examination of areas susceptible to generating and perpetuating seizures, is cost efficient, simple to perform and can be adapted for both low and high field scanners. Standardisation of imaging will improve clinical communication and uniformity of case definition between research studies. A 6–7 sequence epilepsy-specific MRI protocol for veterinary patients is proposed and further advanced MR and functional imaging is reviewed

Expression of interferon-inducible chemokines and sleep/wake changes during early encephalitis in experimental African trypanosomiasis

Background: Human African trypanosomiasis or sleeping sickness, caused by the parasite Trypanosoma brucei, leads to neuroinflammation and characteristic sleep/wake alterations. The relationship between the onset of these alterations and the development of neuroinflammation is of high translational relevance, but remains unclear. This study investigates the expression of interferon (IFN)-γ and IFN-inducible chemokine genes in the brain, and the levels of CXCL10 in the serum and cerebrospinal fluid prior to and during the encephalitic stage of trypanosome infection, and correlates these with sleep/wake changes in a rat model of the disease. Methodology/Principal findings: The expression of genes encoding IFN-γ, CXCL9, CXCL10, and CXCL11 was assessed in the brain of rats infected with Trypanosoma brucei brucei and matched controls using semi-quantitative end-point RT-PCR. Levels of CXCL10 in the serum and cerebrospinal fluid were determined using ELISA. Sleep/wake states were monitored by telemetric recording. Using immunohistochemistry, parasites were found in the brain parenchyma at 14 days post-infection (dpi), but not at 6 dpi. Ifn-γ, Cxcl9, Cxcl10 and Cxcl11 mRNA levels showed moderate upregulation by 14 dpi followed by further increase between 14 and 21 dpi. CXCL10 concentration in the cerebrospinal fluid increased between 14 and 21 dpi, preceded by a rise in the serum CXCL10 level between 6 and 14 dpi. Sleep/wake pattern fragmentation was evident at 14 dpi, especially in the phase of wake predominance, with intrusion of sleep episodes into wakefulness. Conclusions/Significance: The results show a modest increase in Cxcl9 and Cxcl11 transcripts in the brain and the emergence of sleep/wake cycle fragmentation in the initial encephalitic stage, followed by increases in Ifn-γ and IFN-dependent chemokine transcripts in the brain and of CXCL10 in the cerebrospinal fluid. The latter parameter and sleep/wake alterations could provide combined humoral and functional biomarkers of the early encephalitic stage in African trypanosomiasis

Automated diagnosis of encephalitis in pediatric patients using EEG rhythms and slow biphasic complexes

Slow biphasic complexes (SBC) have been identified in the EEG of patients suffering for inflammatory brain diseases. Their amplitude, location and frequency of appearance were found to correlate with the severity of encephalitis. Other characteristics of SBCs and of EEG traces of patients could reflect the grade of pathology. Here, EEG rhythms are investigated together with SBCs for a better characterization of encephalitis. EEGs have been acquired from pediatric patients: ten controls and ten encephalitic patients. They were split by neurologists into five classes of different severity of the pathology. The relative power of EEG rhythms was found to change significantly in EEGs labeled with different severity scores. Moreover, a significant variation was found in the last seconds before the appearance of an SBC. This information and quantitative indexes characterizing the SBCs were used to build a binary classification decision tree able to identify the classes of severity. True classification rate of the best model was 76.1% (73.5% with leave-one-out test). Moreover, the classification errors were among classes with similar severity scores (precision higher than 80% was achieved considering three instead of five classes). Our classification method may be a promising supporting tool for clinicians to diagnose, assess and make the follow-up of patients with encephalitis

Functional Connectivity of EEG in Encephalitis during Slow Biphasic Complexes

The electroencephalogram (EEG) of patients suffering from inflammatory diseases of the brain may show specific waveforms called slow biphasic complexes (SBC). Recent studies indicated a correlation between the severity of encephalitis and some features of SBCs, such as location, amplitude and frequency of appearance. Moreover, EEG rhythms were found to vary before the onset of an SBC, as if the brain was preparing to the discharge (actually with a slowing down of the EEG oscillation). Here, we investigate possible variations of EEG functional connectivity (FC) in EEGs from pediatric patients with different levels of severity of encephalitis. FC was measured by the maximal crosscorrelation of EEG rhythms in different bipolar channels. Then, the indexes of network patterns (namely strength, clustering coefficient, efficiency and characteristic path length) were estimated to characterize the global behavior when they are measured during SBCs or far from them. EEG traces showed statistical differences in the two conditions: clustering coefficient, efficiency and strength are higher close to an SBC, whereas the characteristic path length is lower. Moreover, for more severe conditions, an increase in clustering coefficient, efficiency and strength and a decrease in characteristic path length were observed in the delta–theta band. These outcomes support the hypothesis that SBCs result from the anomalous coordination of neurons in different brain areas affected by the inflammation process and indicate FC as an additional key for interpreting the EEG in encephalitis patients

Herpes Simplex Encephalitis with Two False-Negative Cerebrospinal Fluid PCR Tests and Review of Negative PCR Results in the Clinical Setting

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Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-D-Aspartate Receptor Antibody Encephalitis

PURPOSE: Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis. METHODS: A retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4-8 Hz), alpha (8 - 13 Hz), and beta (13-30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors. RESULTS: Twenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2-6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ2(1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R2) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated (P = 0.04) with an increased likelihood of poor outcome. CONCLUSIONS: In this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated