Long-term seizure outcome with the surgically remediable syndrome of frontal lobe epilepsy associated with superior frontal sulcus-related dysplasia.

Objective: To assess the long-term outcome of the surgically remediable syndrome of frontal lobe epilepsy (FLE) associated with superior frontal sulcus (SFS)-related dysplasia. Methods: We retrospectively reviewed the medical charts and surgical features of 31 patients with drug-resistant frontal lobe epilepsy in our centers between 2016 and 2018. All patients underwent surgical resection. According to the epileptogenic zone (EZ), localization and resection extent were classified as (1) pure SFS group (PS group), (2) associated SFS group (AS group), and (3) no SFS group (NS group). The general characteristics, neuroradiological findings, morbidity, pathology, and long-term seizure outcome after surgery were analyzed to extract the potential value of the surgery for SFS-related dysplasia. Results: Of 31 patients with FLE who underwent epilepsy surgery, 15 patients (nine men) were included PS group, five patients (five men) in the AS group, and 11 patients (eight men) in the NS group. Eleven patients detected abnormal focal signals in the presurgical MRI. Six patients in the PS group demonstrated the suspected focal cortical dysplasia (FCD) in the SFS detected with MRI. All patients demonstrated focal abnormal hypometabolism foci in the PET-MR co-registration. Twenty-five patients (80.6%) were seizure-free since surgery, including all 15 patients (100%) of the PS group, three in five patients (60%) of the AS group, and seven in 11 patients (63.6%) of the NS group. The difference in outcome between different groups was significant (p = 0.004, PS vs. AS group; p = 0.005, PS vs. NS group). As of the last follow-up (mean 66.2 ± 9.7months), 25 patients (80.6%) were seizure-free since surgery (Engel's class I). In addition, antiseizure medication was withdrawn in 19 patients (61.3%). Histologic examination of resected specimens revealed FCD in all 31 patients. The percentage of FCD II type was 100, 60, and 63.6% in the three different groups, respectively. Conclusion: SFS-related dysplasia is a neuropathologic entity with a favorable postoperative outcome. FCD II is the most common type of SFS-related dysplasia. FDG-PET co-registered with MRI should be performed in patients with suspected SFS-related dysplasia, since it may depict areas of hypometabolism suggestive of dysplasia in the absence of MRI abnormalities.

Alterations in Amygdala/Hippocampal Volume Ratios in Children with Obstructive Sleep Apnea Syndrome Caused by Adenotonsillar Hypertrophy.

BACKGROUND Intermittent hypoxemia can cause changes in certain brain structures. However, in pediatric patients with obstructive sleep apnea (OSA) caused by adenotonsillar hypertrophy (ATH), there is only limited information on the effect of ATH-induced OSA on brain structures. This study sought to investigate alterations in amygdala and hippocampal volumes in children with OSA by ATH. MATERIAL AND METHODS Magnetic resonance imaging scans were applied in children who had ATH-induced OSA (ATH/OSA) and in healthy children. Amygdala and hippocampus volumes and adenoid sizes were measured on MRI volumetric images. The ratio of adenoid size/nasopharyngeal depth was used to describe the severity of adenoid hypertrophy. The clinical variables of the involved subjects were investigated. RESULTS One hundred ATH/OSA children and 100 healthy children without ATH/OSA participated in the study. The ATH/OSA children had higher amygdala volumes and amygdala/hippocampus volume ratios but lower hippocampus volumes than healthy controls, and the amygdala/hippocampus volume ratios were correlated with disease duration and hypoxemia conditions. However, our data showed that amygdala/hippocampus volume ratios were not correlated with the ratios of adenoid size/nasopharyngeal depth in the ATH/OSA children. In addition, the ratio of adenoid size/nasopharyngeal depths in ATH/OSA children was higher than that in healthy children in each subgroup based on the age of participants. CONCLUSIONS Compared to healthy controls, amygdala/hippocampus volume ratios are increased in children with ATH/OSA.

Preoperative Heart Rate Variability During Sleep Predicts Vagus Nerve Stimulation Outcome Better in Patients With Drug-Resistant Epilepsy.

Objective: Vagus nerve stimulation (VNS) is an adjunctive and well-established treatment for patients with drug-resistant epilepsy (DRE). However, it is still difficult to identify patients who may benefit from VNS surgery. Our study aims to propose a VNS outcome prediction model based on machine learning with multidimensional preoperative heart rate variability (HRV) indices. Methods: The preoperative electrocardiography (ECG) of 59 patients with DRE and of 50 healthy controls were analyzed. Responders were defined as having at least 50% average monthly seizure frequency reduction at 1-year follow-up. Time domain, frequency domain, and non-linear indices of HRV were compared between 30 responders and 29 non-responders in awake and sleep states, respectively. For feature selection, univariate filter and recursive feature elimination (RFE) algorithms were performed to assess the importance of different HRV indices to VNS outcome prediction and improve the classification performance. Random forest (RF) was used to train the classifier, and leave-one-out (LOO) cross-validation was performed to evaluate the prediction model. Results: Among 52 HRV indices, 49 showed significant differences between DRE patients and healthy controls. In sleep state, 35 HRV indices of responders were significantly higher than those of non-responders, while 16 of them showed the same differences in awake state. Low-frequency power (LF) ranked first in the importance ranking results by univariate filter and RFE methods, respectively. With HRV indices in sleep state, our model achieved 74.6% accuracy, 80% precision, 70.6% recall, and 75% F1 for VNS outcome prediction, which was better than the optimal performance in awake state (65.3% accuracy, 66.4% precision, 70.5% recall, and 68.4% F1). Significance: With the ECG during sleep state and machine learning techniques, the statistical model based on preoperative HRV could achieve a better performance of VNS outcome prediction and, therefore, help patients who are not suitable for VNS to avoid the high cost of surgery and possible risks of long-term stimulation.

Quantitative assessment of structural and functional changes in temporal lobe epilepsy with hippocampal sclerosis.

BACKGROUND: Magnetic resonance imaging (MRI) changes in hippocampal sclerosis (HS) could be subtle in a significant proportion of mesial temporal lobe epilepsy (mTLE) patients. In this study, we aimed to document the structural and functional changes in the hippocampus and amygdala seen in HS patients. METHODS: Quantitative features of the hippocampus and amygdala were extracted from structural MRI data in 66 mTLE patients and 28 controls. Structural covariance analysis was undertaken using volumetric data from the amygdala and hippocampus. Functional connectivity (FC) measured using resting intracranial electroencephalography (EEG) was analyzed in 22 HS patients and 16 non-HS disease controls. RESULTS: Hippocampal atrophy was present in both MRI-positive and MRI-negative HS groups (Mann-Whitney U: 7.61, P<0.01; Mann-Whitney U: 6.51, P<0.01). Amygdala volumes were decreased in the patient group (Mann-Whitney U: 2.92, P<0.05), especially in MRI-negative HS patients (Mann-Whitney U: 2.75, P<0.05). The structural covariance analysis showed the normalized volumes of the amygdala and hippocampus were tightly coupled in both controls and HS patients (ρSpearman =0.72, P<0.01). FC analysis indicated that HS patients had significantly increased connectivity (Student's t: 2.58, P=0.03) within the hippocampus but decreased connectivity between the hippocampus and amygdala (Student's t: 3.33, P=0.01), particularly for MRI-negative HS patients. CONCLUSIONS: Quantitative structural changes, including hippocampal atrophy and temporal pole blurring, are present in both MRI-positive and MRI-negative HS patients, suggesting the potential usefulness of incorporating quantitative analyses into clinical practice. HS is characterized by increased intra-hippocampal EEG synchronization and decreased coupling between the hippocampus and amygdala.

Neuroimaging Phenotyping and Assessment of Structural-Metabolic-Electrophysiological Alterations in the Temporal Neocortex of Focal Cortical Dysplasia IIIa.

BACKGROUND: Focal cortical dysplasia IIIa (FCD IIIa) is a common histopathological finding in temporal lobe epilepsy. However, subtle alterations in the temporal neocortex of FCD IIIa renders presurgical diagnosis and definition of the resective range challenging. PURPOSE: To explore neuroimaging phenotyping and structural-metabolic-electrophysiological alterations in FCD IIIa. STUDY TYPE: Retrospective. SUBJECTS: One hundred and sixty-seven subjects aged 4-39 years, including 64 FCD IIIa patients, 89 healthy controls and 14 FCD I patients as disease controls. FIELD STRENGTH/SEQUENCE: 3 T, fast-spin-echo T2 -weighted fluid-attenuated inversion recovery (FLAIR), synthetic T1 -weighted magnetization prepared rapid acquisition gradient echo (MPRAGE). ASSESSMENT: Surface-based linear model was applied to reveal neuroimaging phenotyping in FCD IIIa and assess its relationship with clinical variables. Logistic regression was implemented to identify FCD IIIa patients. Epileptogenicity mapping (EM) was conducted to explore the structural-metabolic-electrophysiological alterations in temporal neocortex of FCD IIIa. STATISTICAL TESTS: Student's t-test was applied to determine the significance of paired differences. Calibration curves were plotted to assess the goodness-of-fit (GOF) of the models, combined with the Hosmer-Lemeshow test. RESULTS: FCD IIIa exhibited widespread hyperintensities in temporal neocortex, and these alterations correlated with disease duration (Puncorrected < 0.01). Machine learning model accurately identified 84.4% of FCD IIIa patients, 92.1% of healthy controls and 92.9% of FCD I patients. Cross-modality analysis showed a significant negative correlation between FLAIR hyperintensity and positron emission tomography hypometabolism P < 0.01). Furthermore, epileptogenic cortices were located predominantly in brain regions with FLAIR hyperintensity and hypometabolism. DATA CONCLUSION: FCD IIIa exhibited widespread temporal neocortex FLAIR hyperintensity. Automated machine learning of neuroimaging patterns is conducive for accurate identification of FCD IIIa. The degree and distribution of morphological alterations related to the extent of metabolic and epileptogenic abnormalities, lending support to its potential value for reduction of the radiative and invasive approaches during presurgical workup. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Effective connectivity among the hippocampus, amygdala, and temporal neocortex in epilepsy patients: A cortico-cortical evoked potential study.

OBJECTIVE: Mesial temporal lobe epilepsy (MTLE) is one of the most common types of intractable epilepsy. The hippocampus and amygdala are two crucial structures of the mesial temporal lobe and play important roles in the epileptogenic network of MTLE. This study aimed to explore the effective connectivity among the hippocampus, amygdala, and temporal neocortex and to determine whether differences in effective connectivity exist between MTLE patients and non-MTLE patients. METHODS: This study recruited 20 patients from a large cohort of drug-resistant epilepsy patients, of whom 14 were MTLE patients. Single-pulse electrical stimulation (SPES) was performed to acquire cortico-cortical evoked potentials (CCEPs). The root mean square (RMS) was used as the metric of the magnitude of CCEP to represent the effective connectivity. We then conducted paired and independent sample t-tests to assess the directionality of the effective connectivity. RESULTS: In both MTLE patients and non-MTLE patients, the directional connectivity from the amygdala to the hippocampus was stronger than that from the hippocampus to the amygdala (P < 0.01); the outward connectivity from the amygdala to the cortex was stronger than the inward connectivity from the cortex to the amygdala (P < 0.01); the amygdala had stronger connectivity to the neocortex than the hippocampus (P < 0.01). In MTLE patients, the neocortex had stronger connectivity to the hippocampus than to the amygdala (P < 0.01). No significant differences in directional connectivity were noted between the two groups. CONCLUSIONS: A unique effective connectivity pattern among the hippocampus, amygdala, and temporal neocortex was identified through CCEPs analysis. This study may aid in our understanding of physiological and pathological networks in the brain and inspire neurostimulation protocols for neurological and psychiatric disorders.

Epileptogenic network of focal epilepsies mapped with cortico-cortical evoked potentials.

OBJECTIVE: The goal of this study was to investigate the spatial extent and functional organization of the epileptogenic network through cortico-cortical evoked potentials (CCEPs) in patients being evaluated with intracranial stereoelectroencephalography. METHODS: We retrospectively included 25 patients. We divided the recorded sites into three regions: epileptogenic zone (EZ); propagation zone (PZ); and noninvolved zone (NIZ). The root mean square of the amplitudes was calculated to reconstruct effective connectivity network. We also analyzed the N1/N2 amplitudes to explore the responsiveness influenced by epileptogenicity. Prognostic analysis was performed by comparing intra-region and inter-region connectivity between seizure-free and non-seizure-free groups. RESULTS: Our results confirmed that stimulation of the EZ caused the strongest responses on other sites within and outside the EZ. Moreover, we found a hierarchical connectivity pattern showing the highest connectivity strength within EZ, and decreasing connectivity gradient from EZ, PZ to NIZ. Prognostic analysis indicated a stronger intra-EZ connection in the seizure-free group. CONCLUSION: The EZ showed highest excitability and dominantly influenced other regions. Quantitative CCEPs can be useful in mapping epileptic networks and predicting surgical outcome. SIGNIFICANCE: The generated computational connectivity model may enhance our understanding of epileptogenic networks and provide useful information for surgical planning and prognosis prediction.

Integrated Automatic Detection, Classification and Imaging of High Frequency Oscillations With Stereoelectroencephalography.

OBJECTIVE: During presurgical evaluation for focal epilepsy patients, the evidence supporting the use of high frequency oscillations (HFOs) for delineating the epileptogenic zone (EZ) increased over the past decade. This study aims to develop and validate an integrated automatic detection, classification and imaging pipeline of HFOs with stereoelectroencephalography (SEEG) to narrow the gap between HFOs quantitative analysis and clinical application. METHODS: The proposed pipeline includes stages of channel inclusion, candidate HFOs detection and automatic labeling with four trained convolutional neural network (CNN) classifiers and HFOs sorting based on occurrence rate and imaging. We first evaluated the initial detector using an open simulated dataset. After that, we validated our full algorithm in a 20-patient cohort against three assumptions based on previous studies. Classified HFOs results were compared with seizure onset zone (SOZ) channels for their concordance. The receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) were calculated representing the prediction ability of the labeled HFOs outputs for SOZ. RESULTS: The initial detector demonstrated satisfactory performance on the simulated dataset. The four CNN classifiers converged quickly during training, and the accuracies on the validation dataset were above 95%. The localization value of HFOs was significantly improved by HFOs classification. The AUC values of the 20 testing patients increased after HFO classification, indicating a satisfactory prediction value of the proposed algorithm for EZ identification. CONCLUSION: Our detector can provide robust HFOs analysis results revealing EZ at the individual level, which may ultimately push forward the transitioning of HFOs analysis into a meaningful part of the presurgical evaluation and surgical planning.

Automated detection of hippocampal sclerosis using clinically empirical and radiomics features.

OBJECTIVE: Temporal lobe epilepsy is a common form of epilepsy that might be amenable to surgery. However, magnetic resonance imaging (MRI)-negative hippocampal sclerosis (HS) can hamper early diagnosis and surgical intervention for patients in clinical practice, resulting in disease progression. Our aim was to automatically detect and evaluate the structural alterations of HS. METHODS: Eighty patients with pharmacoresistant epilepsy and histologically proven HS and 80 healthy controls were included in the study. Two automated classifiers relying on clinically empirical and radiomics features were developed to detect HS. Cross-validation was implemented on all participants, and specificity was assessed in the 80 controls. The performance, robustness, and clinical utility of the model were also evaluated. Structural analysis was performed to investigate the morphological abnormalities of HS. RESULTS: The computational model based on clinical empirical features showed excellent performance, with an area under the curve (AUC) of 0.981 in the primary cohort and 0.993 in the validation cohort. One of the features, gray-white matter boundary blurring in the temporal pole, exhibited the highest weight in model performance. Another model based on radiomics features also showed satisfactory performance, with AUC of 0.997 in the primary cohort and 0.978 in the validation cohort. In particular, the model improved the detection rate of MRI-negative HS to 96.0%. The novel feature of cortical folding complexity of the temporal pole not only played a crucial role in the classifier but also had significant correlation with disease duration. SIGNIFICANCE: Machine learning with quantitative clinical and radiomics features is shown to improve HS detection. HS-related structural alterations were similar in the MRI-positive and MRI-negative HS patient groups, indicating that misdiagnosis originates mainly from empirical interpretation. The cortical folding complexity of the temporal pole is a potentially valuable feature for exploring the nature of HS.

Superior Frontal Sulcus Focal Cortical Dysplasia Type II: An MRI, PET, and Quantified SEEG Study.

Purpose: The superior frontal sulcus (SFS), located in the prefrontal and premotor cortex, is considered as one of the common locations of focal cortical dysplasia (FCD). However, the characteristics of seizures arising from this area are incompletely known. The primary purpose of this study was to investigate the clinical features and the epileptic networks of seizures originating from the SFS. Methods: We included seventeen patients with type II FCD within the SFS. SFS was identified both visually and automatically. Semiological features were evaluated and grouped. Interictal 18FDG-PET imaging in all patients was compared to controls using statistical parametric mapping (SPM-PET). In those subjects with stereoelectroencephalography (SEEG), two different quantitative intracranial electroencephalography analyses were applied. Finally, the locations of the SFS-related hypometabolic regions and epileptogenic zones (EZs) were transformed into standard space for group analysis. Results: We identified two semiological groups. Group 1 (9/17) showed elementary motor signs (head version and tonic posturing), while group 2 (8/17) exhibited complex motor behavior (fear, hypermotor, and ictal pouting). Based on SPM-PET, an SFS-supplementary motor area (SMA) epileptic propagation network was found in group 1, and an SFS-middle cingulate cortex (MCC)-pregenual anterior cingulate cortex (pACC) propagation network was discovered in group 2. Intracranial EEG analysis suggested similar affected structures with high epileptogenicity. The SFS-related hypometabolic regions and EZs in these groups showed a posterior-anterior spatial relationship. Conclusions: Even though originating from the spatially restricted cortex, SFS seizures can be divided into two groups based on semiological features. The SFS-SMA and SFS-MCC-pACC epileptic propagation networks may play pivotal roles in the generation of different semiologies. The posterior-anterior spatial relationship of both hypometabolic regions and EZs provides potentially useful information for distinguishing different types of SFS seizures and surgical evaluation.

Deceleration and acceleration capacities of heart rate in patients with drug-resistant epilepsy.

OBJECTIVE: Epilepsy and seizures can have dramatic effects on cardiac function. The aim of the present study was to investigate deceleration capacity, acceleration capacity and their 24-h fluctuations of heart rate variability in patients with drug-resistant epilepsy. METHODS: Deceleration capacity, acceleration capacity of heart rate and their 24-h dynamics derived from the phase rectified signal averaging method as well as traditional measures were analyzed in 39 patients with drug-resistant epilepsy and 33 healthy control subjects using 24-h electrocardiogram recordings. The discriminatory power of heart rate variability measures were validated by assessment of the area under the receiver operating characteristic curve. Net reclassification improvement and integrated discrimination improvement models were also estimated. RESULTS: Both deceleration capacity and absolute values of acceleration capacity were significantly lower in patients with drug-resistant epilepsy. The abnormal suppression of absolute deceleration capacity and acceleration capacity values were observed throughout the 24-h recording time (peaked at about 3 to 5 A.M.). Deceleration capacity had the greatest discriminatory power to differentiate the patients from the healthy controls. Moreover, in both net reclassification improvement and integrated discrimination improvement models, the combination of acceleration capacity or deceleration capacity with traditional heart rate variability measures has greater discriminatory power than any of the single heart rate variability features. INTERPRETATION: Drug-resistant epilepsy was associated with a significant inhibition of vagal modulation of heart rate, which was more pronounced during the night than during the day. These findings indicate that phase rectified signal averaging method may serve as a complementary approach for characterizing and understanding the neuro-pathophysiology in epilepsy, and may provide a new clue to sudden unexpected death in epilepsy.

Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis.

Purpose: Magnetic resonance imaging (MRI) and positron emission tomography (PET) with 18F-fluorodeoxyglucose (18FDG) are valuable tools for evaluating hippocampal sclerosis (HS); however, bias may arise during visual analyses. The aim of this study was to evaluate and compare MRI and PET post-processing techniques, automated quantitative hippocampal volume (Q-volume), and fluid-attenuated inversion-recovery (FLAIR) signal (Q-FLAIR) and glucose metabolism (Q-PET) analyses in patients with HS. Methods: We collected MRI and 18FDG-PET images from 54 patients with HS and 22 healthy controls and independently performed conventional visual analyses (CVA) of PET (CVA-PET) and MRI (CVA-MRI) images. During the subsequent quantitative analyses, the hippocampus was segmented from the 3D T1 image, and the mean volumetric, FLAIR intensity and standardized uptake value ratio (SUVR) values of the left and right hippocampus were assessed in each subject. Threshold confidence levels calculated from the mean volumetric, FLAIR intensity and SUVR values of the controls were used to identify healthy subjects or subjects with HS. The performance of the three methods was assessed using receiver operating characteristic (ROC) curves, and the detection rates of CVA-MRI, CVA-PET, Q-volume, Q-FLAIR, and Q-PET were statistically compared. Results: The areas under the curves (AUCs) for the Q-volume, Q-FLAIR, and Q-PET ROC analyses were 0.88, 0.41, and 0.98, which suggested a diagnostic method with moderate, poor, and high accuracy, respectively. Although Q-PET had the highest detection rate among the two CVA methods and three quantitative methods, the difference between Q-volume and Q-PET did not reach statistical significance. Regarding the HS subtypes, CVA-MRI, CVA-PET, Q-volume, and Q-PET had similar detection rates for type 1 HS, and Q-PET was the most sensitive method for detecting types 2 and 3 HS. Conclusions: In MRI or 18FDG-PET images that have been visually assessed by experts, the quantification of hippocampal volume or glucose uptake can increase the detection of HS and appear to be additional valuable diagnostic tools for evaluating patients with epilepsy who are suspected of having HS.

Multimodality Image Post-processing in Detection of Extratemporal MRI-Negative Cortical Dysplasia.

Purpose: To determine the diagnostic value of individual image post-processing techniques in a series of patients who underwent extratemporal operations for histologically proven, MRI-negative focal cortical dysplasia (FCD). Methods: The morphometric analysis program (MAP), PET/MRI co-registration and statistical parametric mapping (SPM) analysis of PET (SPM-PET) techniques were analyzed in 33 consecutive patients. The epileptogenic zone (EZ) assumed by MAP, PET/MRI, and SPM-PET was compared with the location of the FCD lesions determined by stereoelectroencephalography (SEEG) and histopathological study. The detection rate of each modality was statistically compared. Results: Three lesions were simultaneously detected by the three post-processing methods, while two lesions were only MAP positive, and 8 were only PET/MRI positive. The detection rate of MAP, PET/MRI, SPM-PET and the combination of the three modalities was 24.2, 90.9, 57.6, and 97.0%, respectively. Taking the pathological subtype into account, no type I lesions were detected by MAP, and PET/MRI was the most sensitive method for detecting FCD types II and IIA. During a mean follow-up period of 22.94 months, seizure freedom was attained in 26/33 patients (78.8%) after focal corticectomy. Conclusions: MAP, PET/MRI, and SPM-PET provide complementary information for FCD detection, intracranial electrode design, and lesion resection. PET/MRI was particularly useful, with the highest detection rate of extratemporal MRI-negative FCD.

The Anatomo-Electrical Network Underlying Hypermotor Seizures.

PURPOSE: Hypermotor seizures (HMS) can be triggered by different epileptogenic foci and thus common symptomatic networks generating HMS may exist among these patients. The goal of the present study was to investigate the specialized networks underlying HMS by analyzing interictal 18FDG-PET imaging and ictal stereo-electroencephalography (SEEG) recordings. METHODS: Fourteen patients with HMS were retrospectively analyzed. HMS were classified into HMS1 and HMS2 according to the speed and intensity of the motor seizure behavior. Then, the interictal PET data of patients was compared with those of 18 healthy controls using statistical parametric mapping to identify regions with significant hypometabolism. Ictal SEEG recordings were reviewed to identify the spreading areas at the beginning of HMS occurrence. RESULTS: Compared to controls, patients with HMS presented significant hypometabolism in the bilateral anterosuperior insular lobes, mesial premotor cortex (MPMC), middle cingulate cortex (MCC), as well as in the bilateral caudate nuclei. When comparing patients in the two HMS subgroups with controls, more extensive hypometabolic areas were seen in HMS1 patients than in HMS2 patients, including the orbitofrontal cortex (OFC), the temporal pole, and the anterior cingulate cortex (ACC). OFC and ventromedial prefrontal cortex was also found significantly hypometabolic in patients with HMS1 when compared with HMS2 directly. SEEG recordings further suggested that insula, MCC, and MPMC were commonly recruited at the beginning of HMS. CONCLUSION: We have identified a specialized interictal hypometabolic pattern in patients with HMS. A network involving the anterosuperior insula, mesiofrontal cortex (MCC-MPMC), and caudate nucleus may contribute to the generation of HMS. ACC, OFC, and temporal pole are possibly associated with the affective components of HMS. Our findings provide further insight into understanding the network basis of HMS semiology.

Preoperative Heart Rate Variability as Predictors of Vagus Nerve Stimulation Outcome in Patients with Drug-resistant Epilepsy.

Vagus nerve stimulation (VNS) is an adjunctive treatment for drug-resistant epilepsy (DRE). However, it is still difficult to predict which patients will respond to VNS treatment and to what extent. We aim to explore the relationship between preoperative heart rate variability (HRV) and VNS outcome. 50 healthy control subjects and 63 DRE patients who had received VNS implants and had at least one year of follow up were included. The preoperative HRV were analyzed by traditional linear methods and heart rhythm complexity analyses with multiscale entropy (MSE). DRE patients had significantly lower complexity indices (CI) as well as traditional linear HRV measurements than healthy controls. We also found that non-responders0 had significantly lower preoperative CI including Area 1-5, Area 6-15 and Area 6-20 than those in the responders0 while those of the non-responders50 had significantly lower RMSSD, pNN50, VLF, LF, HF, TP and LF/HF than the responders50. In receiver operating characteristic (ROC) curve analysis, Area 6-20 and RMSSD had the greatest discriminatory power for the responders0 and non-responders0, responders50 and non-responders50, respectively. Our results suggest that preoperative assessment of HRV by linear and MSE analysis can help in predicting VNS outcomes in patients with DRE.

Impairment of heart rhythm complexity in patients with drug-resistant epilepsy: An assessment with multiscale entropy analysis.

OBJECTIVE: Epilepsy and seizures can have dramatic effects on the cardiac function. The aim of this study was to investigate the heart rhythm complexity in patients with drug-resistant epilepsy (DRE). METHODS: Ambulatory 24-h electrocardiograms (ECG) from 70 DRE patients and 50 healthy control subjects were analyzed using conventional heart rate variability (HRV) and multiscale entropy (MSE) methods The variation of complexity indices (CI), which was calculated from MSE profile, was determined. RESULTS: DRE patients had significantly lower time domain (Mean RR, SDNN, RMSSD, pNN50) and frequency domain (VLF, LF, HF, TP) HRV measurements than healthy controls. Of the MSE analysis, MSE profile, CI including Slope 5, Area 1-5, Area 6-15 and Area 6-20 were significantly lower than those in the healthy control group. In receiver operating characteristic (ROC) curve analysis, VLF had the greatest discriminatory power for the two groups. In both net reclassification improvement (NRI) model and integrated discrimination improvement (IDI) models, CI derived from MSE profiles significantly improved the discriminatory power of Mean RR, SDNN, RMSSD, pNN50, VLF, LF, HF and TP. SIGNIFICANCE: The heart rate complexity is impaired for DRE patients. CI are useful to discriminate DRE patients from subjects with normal cardiac complexity. These findings indicate that MSE method may serve as a complementary approach for characterizing and understanding abnormal heart rate dynamics in epilepsy. Furthermore, the CI may potentially be used as a biomarker in monitoring epilepsy.

Vagus Nerve Stimulation for Pediatric and Adult Patients with Pharmaco-resistant Epilepsy.

BACKGROUND: Over past two decades, vagus nerve stimulation (VNS) has been widely used and reported to alleviate seizure frequency worldwide, however, so far, only hundreds of patients with pharmaco-resistant epilepsy (PRE) have been treated with VNS in mainland China. The study aimed to evaluate the effectiveness of VNS for Chinese patients with PRE and compare its relationship with age cohort and gender. METHODS: We retrospectively assessed the clinical outcome of 94 patients with PRE, who were treated with VNS at Beijing Fengtai Hospital and Beijing Tiantan Hospital between November 2008 and April 2014 from our database of 106 consecutive patients. The clinical data analysis was retrospectively examined. RESULTS: Seizure frequency significantly decreased with VNS therapy after intermittent stimulation of the vagus nerve. At last follow-up, we found McHugh classifications of Class I in 33 patients (35.1%), Class II in 27 patients (28.7%), Class III in 20 patients (21.3%), Class IV in 3 patients (3.2%), and Class V in 11 patients (11.7%). Notably, 8 (8.5%) patients were seizure-free while ≥50% seizure frequency reduction occurred in as many as 60 patients (63.8%). Furthermore, with regard to the modified Engel classification, 12 patients (12.8%) were classified as Class I, 11 patients (11.7%) were classified as Class II, 37 patients (39.4%) were classified as Class III, 34 patients (36.2%) were classified as Class IV. We also found that the factors of gender or age are not associated with clinical outcome. CONCLUSIONS: This comparative study confirmed that VNS is a safe, well-tolerated, and effective treatment for Chinese PRE patients. VNS reduced the seizure frequency regardless of age or gender of studied patients.

Melatonin as an effective protector against doxorubicin-induced cardiotoxicity.

The present study was designed to explore the protective effects of melatonin and its analogs, 6-hydroxymelatonin and 8-methoxy-2-propionamidotetralin, on the survival of doxorubicin-treated mice and on doxorubicin-induced cardiac dysfunction, ultrastructural alterations, and apoptosis in mouse hearts. Whereas 60% of the mice treated with doxorubicin (25 mg/kg ip) died in 5 days, almost all the doxorubicin-treated mice survived when melatonin or 6-hydroxymelatonin (10 mg/l) was administered in their drinking water. Perfusion of mouse hearts with 5 microM doxorubicin for 60 min led to a 50% suppression of heart rate x left ventricular developed pressure and a 50% reduction of coronary flow. Exposure of hearts to 1 microM melatonin or 6-hydroxymelatonin reversed doxorubicin-induced cardiac dysfunction. 8-Methoxy-2-propionamidotetralin had no protective effects on animal survival and on in vitro cardiac function. Infusion of melatonin or 6-hydroxymelatonin (2.5 microg/h) significantly attenuated doxorubicin-induced cardiac dysfunction, ultrastructural alterations, and apoptosis in mouse hearts. Neither melatonin nor 6-hydroxymelatonin compromised the antitumor activity of doxorubicin in cultured PC-3 cells. These results suggest that melatonin protect against doxorubicin-induced cardiotoxicity without interfering with its antitumor effect.