Martin Pail

An optimized voxel-based morphometric study of gray matter changes in patients with left-sided and right-sided mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE/HS)

Purpose:  To determine whether changes in gray matter volume (GMV) differ according to the affected side in mesial temporal lobe epilepsy/hippocampal sclerosis (MTLE/HS) syndrome, and moreover to test the hypothesis of more pronounced structural changes in right‐sided MTLE/HS. This hypothesis (especially that the contralateral thalamus is more affected in right‐sided MTLE/HS) arose from the results of our recent study, wherein more expressed structural and functional changes were observed in a small sample of patients with right‐sided MTLE/HS ( Brázdil et al., 2009 ).

The role of voxel‐based morphometry in the detection of cortical dysplasia within the temporal pole in patients with intractable mesial temporal lobe epilepsy

Purpose:  To determine whether voxel‐based morphometry (VBM) might contribute to the detection of cortical dysplasia within the temporal pole in patients with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE/HS).

Very High-Frequency Oscillations: Novel Biomarkers of the Epileptogenic Zone

In the present study, we aimed to investigate depth electroencephalographic (EEG) recordings in a large cohort of patients with drug‐resistant epilepsy and to focus on interictal very high‐frequency oscillations (VHFOs) between 500Hz and 2kHz. We hypothesized that interictal VHFOs are more specific biomarkers for epileptogenic zone compared to traditional HFOs.

Frequency-independent characteristics of high-frequency oscillations in epileptic and non-epileptic regions.

OBJECTIVE The purpose of the presented study is to determine whether there are frequency-independent high-frequency oscillation (HFO) parameters which may differ in epileptic and non-epileptic regions. METHODS We studied 31 consecutive patients with medically intractable focal (temporal and extratemporal) epilepsies who were examined by either intracerebral or subdural electrodes. Automated detection was used to detect HFO. The characteristics (rate, amplitude, and duration) of HFO were statistically compared within three groups: the seizure onset zone (SOZ), the irritative zone (IZ), and areas outside the IZ and SOZ (nonSOZ/nonIZ). RESULTS In all patients, fast ripples (FR) and ripples (R) were significantly more frequent and shorter in the SOZ than in the nonSOZ/nonIZ region. In the group of patients with favorable surgical outcomes, the relative amplitude of FR was higher in the SOZ than in the IZ and nonIZ/nonSOZ regions; in patients with poor outcomes, the results were reversed. The relative amplitude of R was significantly higher in the SOZ, with no difference between patients with poor and favorable surgical outcomes. CONCLUSIONS FR are more frequent, shorter, and have higher relative amplitudes in the SOZ area than in other regions. The study suggests a worse prognosis in patients with higher amplitudes of FR outside the SOZ. SIGNIFICANCE Various HFO parameters, especially of FR, differ in epileptic and non-epileptic regions. The amplitude and duration may be as important as the frequency band and rate of HFO in marking the seizure onset region or the epileptogenic area and may provide additional information on epileptogenicity.

Morphological changes of cerebellar substructures in temporal lobe epilepsy: A complex phenomenon, not mere atrophy

PURPOSE To evaluate cerebellar volume changes in temporal lobe epilepsy (TLE) patients in greater detail. We aimed to determine which discrete substructures significantly differ in patients with TLE compared to controls and the nature of this difference. Correlations with age at epilepsy onset, epilepsy duration, seizure frequency, and total number of antiepileptic drugs (AED) in the patients history were studied. We analyzed the potential association between cerebellar atrophy and epilepsy surgery outcome. METHODS Study participants were 36 TLE patients; 22 hippocampal sclerosis (HS) only and 38 healthy controls. All patients later underwent temporal lobe resection. All subjects were examined using 1.5T MRI. Cerebellar volume was adjusted for total intracranial volume, age, and gender, and measured using voxel-based morphometry. Cerebellar substructures were defined using the AAL atlas. Data processing was performed automatically. Separate analyses for HS only subset were performed. RESULTS Total cerebellar gray matter volume (GMV) appeared non-significantly smaller in epilepsy patients. Within the substructures, the GMV of the selected vermian segments were significantly larger in patients. The GMV of the whole cerebellum and of all individual cerebellar substructures non-significantly decreased with increasing complex partial seizure frequency and total number of AEDs in the patients history. Total cerebellar GMV was significantly smaller in patients with persistent seizures after epilepsy surgery than in seizure-free patients. CONCLUSION Cerebellar atrophy is a complex phenomenon, the character of changes differs significantly within the cerebellar substructures. Total cerebellar GMV reduction is associated with worse outcome of temporal lobe resection.

MicroRNA and mesial temporal lobe epilepsy with hippocampal sclerosis: Whole miRNome profiling of human hippocampus.

Mesial temporal lobe epilepsy (mTLE) is a severe neurological disorder characterized by recurrent seizures. mTLE is frequently accompanied by neurodegeneration in the hippocampus resulting in hippocampal sclerosis (HS), the most common morphological correlate of drug resistance in mTLE patients. Incomplete knowledge of pathological changes in mTLE+HS complicates its therapy. The pathological mechanism underlying mTLE+HS may involve abnormal gene expression regulation, including posttranscriptional networks involving microRNAs (miRNAs). miRNA expression deregulation has been reported in various disorders, including epilepsy. However, the miRNA profile of mTLE+HS is not completely known and needs to be addressed.

Generalized myoclonus as a prominent symptom in a patient with FTLD-TDP

We report on a patient who developed generalized asymmetric myoclonus associated with frontotemporal lobar degeneration with TDP-43 positive inclusions (FTLD-TDP).

Single-center long-term results of vagus nerve stimulation for epilepsy: A 10–17 year follow-up study

PURPOSE The paper presents a long-term follow-up study of VNS patients, analyzing seizure outcome, medication changes, and surgical problems. METHOD 74 adults with VNS for 10 to 17 years were evaluated yearly as: non-responder - NR (seizure frequency reduction <50%), responder - R (reduction ≥ 50% and <90%), and 90% responder - 90R (reduction ≥ 90%). Delayed R or 90R (≥ 4 years after surgery), patients with antiepileptic medication changes and battery or complete system replacement were identified. Statistical analysis of potential outcome predictors (age, seizure duration, MRI, seizure type) was performed. RESULTS The rates of R and 90R related to the patients with outcome data available for the study years 1, 2, 10, and 17 were for R 38.4%, 51.4%, 63.6%, and 77.8%, and for 90R 1.4%, 5.6%, 15.1%, and 11.1%. The absolute numbers of R and 90R increased until years 2 and 6. Antiepileptic therapy was changed in 62 patients (87.9%). There were 11 delayed R and four delayed 90R, with medication changes in the majority. At least one battery replacement was performed in 51 patients (68.9%), 49 of whom R or 90R. VNS system was completely replaced in 7 patients (9.5%) and explanted in 7 NR (9.5%). No significant predictor of VNS outcome was found. CONCLUSIONS After an initial increase, the rate of R and 90R remains stable in long-term follow-up. The changes of antiepileptic treatment in most patients potentially influence the outcome. Battery replacements or malfunctioning system exchange reflect the patients satisfaction and correlate with good outcomes.

Intracerebral EEG Artifact Identification Using Convolutional Neural Networks

Manual and semi-automatic identification of artifacts and unwanted physiological signals in large intracerebral electroencephalographic (iEEG) recordings is time consuming and inaccurate. To date, unsupervised methods to accurately detect iEEG artifacts are not available. This study introduces a novel machine-learning approach for detection of artifacts in iEEG signals in clinically controlled conditions using convolutional neural networks (CNN) and benchmarks the method’s performance against expert annotations. The method was trained and tested on data obtained from St Anne’s University Hospital (Brno, Czech Republic) and validated on data from Mayo Clinic (Rochester, Minnesota, U.S.A). We show that the proposed technique can be used as a generalized model for iEEG artifact detection. Moreover, a transfer learning process might be used for retraining of the generalized version to form a data-specific model. The generalized model can be efficiently retrained for use with different EEG acquisition systems and noise environments. The generalized and specialized model F1 scores on the testing dataset were 0.81 and 0.96, respectively. The CNN model provides faster, more objective, and more reproducible iEEG artifact detection compared to manual approaches.

03-Falls in temporal lobe epilepsy

Objective Falls are not supposed to be common signs of temporal lobe epilepsy (TLE). The main aim of this study was to identify a group of patients with known history of unexpected falls which could not be explained by presence of ictal asystole or concomitant heart disesase. Methods We retrospectively evaluated the data of all patient who underwent pre-surgical evaluation in Brno Epilepsy Center since 2002. We identified 49 patients with TLE who reported unexpected falls. Thirteen (33%) out of 49 patients (TLE-falls group) underwent surgery which led to disappearance of both seizures and falls. In the next step, the control group of age- and gender- matched patients with TLE (TLE-control group) was formed. We identified RR intervals and following parameters were analyzed duration of RR intervals and heart rate variability (HRV). Results There were no statistically significant differences between TLE-falls group and TLE-surgery group regarding age of epilepsy onset, duration of epilepsy, age at surgery. Both the duration of RR intervals and HRV were statistically significantly different between TLE-falls group and TLE-control group (p = 0.025, respectively p = 0.025). Conclusion It seems that unexpected falls could be a novel rare signs in TLE epilepsy. Their presence could be conditioned by heart rhythms.