Voxel-Based Morphometric MRI Postprocessing-Assisted Laser Interstitial Thermal Therapy for Focal Cortical Dysplasia-Suspected Lesions: Technique and Outcomes.

BACKGROUND: MRI-guided laser interstitial thermal therapy (MRgLITT) is a novel treatment modality for focal cortical dysplasia (FCD). However, identifying the location and extent of subtle FCD by visual analysis during MRgLITT remains challenging. OBJECTIVE: To introduce voxel-based morphometric MRI postprocessing into the procedure of MRgLITT for FCD-suspected lesions and assess the complementary value of the MRI postprocessing technique for the trajectory design and thermal parameter setting of MRgLITT. METHODS: Junction and normalized fluid-attenuated inversion recovery signal intensity images were used to detect the gray-white matter junction blurring and cortical fluid-attenuated inversion recovery hyperintensity, respectively. According to the 2 postprocessing images, the region of interest (ROI) for ablation was drawn. The main principle of presurgical planning is that the trajectory of the laser fiber was designed as far as possible along the long axis of the ROI while the extent of planned ablation covered the entire ROI. The subsequent intraoperative procedure was performed under the guidance of the presurgical plan. RESULTS: Nine patients with epilepsy with FCD-suspected lesions underwent MRgLITT with the assistance of MRI postprocessing images. Among them, 4 patients were junction positive, 2 patients were normalized fluid-attenuated inversion recovery signal intensity positive, and the remaining 3 patients were positive for both. Postsurgical MRI demonstrated that the ROIs were ablated entirely in 7 patients. Engel Ia, Ib, and IV scores were obtained at 1-year follow-up for 6, 1, and 2 patients, respectively. CONCLUSION: MRI postprocessing provides complementary information for designing the laser fiber trajectory and subsequent ablation for FCDs.

The effect of influenza A (H1N1) pdm09 virus infection on cytokine production and gene expression in BV2 microglial cells.

Acute influenza infection has been reported to be associated with neurological symptoms such as influenza-associated encephalopathy (IAE). Although the pathophysiology of this condition remain unclear, neuroinflammation and associated alterations in the central nervous system (CNS) are usually induced. Microglia (MGs), CNS-resident macrophages, are generally the first cells to be activated in response to brain infection or damage. We performed reverse transcriptase droplet digital PCR (RT-ddPCR) and luminex assays to investigate virus proliferation and immune reactions in BV2 MGs infected with influenza A(H1N1)pdm09 virus. Furthermore, isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics methods were used to investigate the dynamic change in the protein expression profile in BV2 MGs to gain insight into the CNS response to influenza A (H1N1) pdm09 infection. Our results showed that the influenza A(H1N1)pdm09 virus was replicative and productive in BV2 MG cells, which produced cytokines such as interleukin (IL)-1ß, IL-6, tumour necrosis factor (TNF)-α and monocyte chemoattractant protein (MCP)-1. The expression of osteopontin (OPN) in the influenza A (H1N1) pdm09-infected BV2 MGs was upregulated at 16 and 32 h post-infection (hpi) compared to that in the control group, resulting in aggravated brain damage and inflammation. Our study indicates that OPN signalling might provide new insights into the treatment of CNS injury and neurodegenerative diseases in IAE.

Synchronized Intracranial Electrical Activity and Gait Recording in Parkinson's Disease Patients With Freezing of Gait.

Background: This study aimed to describe a synchronized intracranial electroencephalogram (EEG) recording and motion capture system, which was designed to explore the neural dynamics during walking of Parkinson's disease (PD) patients with freezing of gait (FOG). Preliminary analysis was performed to test the reliability of this system. Methods: A total of 8 patients were enrolled in the study. All patients underwent bilateral STN-DBS surgery and were implanted with a right subdural electrode covering premotor and motor area. Synchronized electrophysiological and gait data were collected using the Nihon Kohden EEG amplifier and Codamotion system when subjects performed the Timed Up and Go (TUG) test. To verify the reliability of the acquisition system and data quality, we calculated and compared the FOG index between freezing and non-freezing periods during walking. For electrophysiological data, we first manually reviewed the scaled (five levels) quality during waking. Spectra comprising broadband electrocorticography (ECoG) and local field potential (LFP) were also compared between the FOG and non-FOG states. Lastly, connectivity analysis using coherence between cortical and STN electrodes were conducted. In addition, we also use machine learning approaches to classified FOG and non-FOG. Results: A total of 8 patients completed 41 walking tests, 30 of which had frozen episodes, and 21 of the 30 raw data were level 1 or 2 in quality (70%). The mean ± SD walking time for the TUG test was 85.94 ± 47.68 s (range: 38 to 190.14 s); the mean ± SD freezing duration was 12.25 ± 7.35 s (range: 1.71 to 27.50 s). The FOG index significantly increased during the manually labeled FOG period (P < 0.05). The beta power of STN LFP in the FOG period was significantly higher than that in the non-FOG period (P < 0.05), while the band power of ECoG did not exhibit a significant difference between walking states. The coherence between the ECoG and STN LFP was significantly greater in high beta and gamma bands during the FOG period compared with the shuffled surrogates (P < 0.05). Lastly, STN-LFP band power features showed above-chance performance (p < 0.01, permutation test) in identifying FOG epochs. Conclusion: In this study, we established and verified the synchronized ECoG/LFP and gait recording system in PD patients with FOG. Further neural substrates underlying FOG could be explored using the current system.

The electroclinical features and surgical outcomes of inferior perisylvian epilepsy.

OBJECTIVE: To summarize the clinical and electrophysiological observations of epilepsy originating from the inferior perisylvian cortex, and analyze the potential epileptic networks underlying the semiological manifestations. METHODS: We retrospectively analyzed patients with refractory inferior perisylvian epilepsy (IPE) who had undergone resective surgery, and then reviewed the demographic, clinical, neuroelectrophysiological, neuroimaging, surgical, histopathological, and follow-up data of the patients from the respective medical records. The selected patients were then categorized in accordance with the results of semiological analysis. Quantitative 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET) analysis was performed to investigate the underlying neural network. RESULTS: Of the 18 IPE patients assessed in this study, ipsilateral frontotemporal epileptic discharges or its onsets were the dominant interictal or ictal scalp EEG observations. In addition, oroalimentary or manual automatism was the most frequently documented manifestation, followed by facial tonic or clonic movements. Moreover, the semiological analysis identified and classified the patients into 2 patterns, and the PET statistical analyses conducted on these 2 groups revealed differences in the neural network between them. CONCLUSION: Inferior perisylvian epilepsy possesses semiological manifestations similar to those of mesial temporal lobe epilepsy or rolandic opercular epilepsy, hence these conditions should be carefully differentiated. Performing lesionectomy or cortectomy, sparing the mesial temporal structures, was found to be an effective and safe treatment modality for IPE.

Focal cortical dysplasia II-related seizures originate from the bottom of the dysplastic sulcus: A stereoelectroencephalography study.

OBJECTIVES: Focal cortical dysplasia (FCD) II is a frequently observed histopathological substrate in epilepsy surgery. In the present study, we explored the spatial distribution of epileptogenic activities across FCD II lesions using stereoelectroencephalography. METHODS: Patients with histopathologically confirmed type II FCDs and who had at least one depth electrode that go through the wall of the dysplastic sulcus from the surface to the bottom were included. The dysplastic sulci were divided into the bottom and non-bottom parts manually, and contacts were defined as bottom or non-bottom contacts according to their locations. Factors (bottom location, pathological subtype, magnetic resonance imaging manifestation, and presence of bottom-of-sulcus dysplasia) potentially associated with earliest onset identified by conventional visual analysis, epileptogenicity index (EI), and standardized number of high-frequency oscillations (HFOs) were analyzed. Linear regression analyses between distance (from the location of the analyzed contact to the bottom of the sulcus) and EI value and HFO number were performed. RESULTS: Sixteen patients with 19 depth electrodes containing 112 valid contacts were included. Bottom location was the sole factor significantly associated with earliest onset (P < 0.001), EI value (P < 0.001), and HFO number (P < 0.001). Most earliest onsets were recorded by the bottom contacts, bottom contacts had higher EI value (0.81 ±â€¯0.28 vs. 0.31 ±â€¯0.24, P < 0.001) and more HFOs (0.78 ±â€¯0.28 vs. 0.35 ±â€¯0.31, P < 0.001) than non-bottom contacts. Moreover, the EI value (R = -0.72, P < 0.001) and HFO number (R = -0.64, P < 0.001) were significantly negatively correlated with distance, regardless of histopathological subtype, MRI manifestation, or absence of bottom-of-sulcus dysplasia. CONCLUSION: Seizure onsets and interictal HFOs most often arise from the bottom part of a sulcus with type II FCD. SIGNIFICANCE: The findings of the present study contribute to intracranial electrode selection, trajectory planning, and, later on, resection of this kind of malformation.

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.

Value of stereo-electroencephalogram in reoperation of patients with pharmacoresistant epilepsy: a single center, retrospective study.

PURPOSE: To systematically elucidate the value of stereo-electroencephalogram (SEEG) in the reoperation of patients with pharmacoresistant epilepsy. METHODS: Epilepsy patients who had previously undergone a failed operation and agreed to a reoperation were included in this study. The single center retrospective study evaluated the value of SEEG in epileptogenic zones (EZ) lateralization and localization as well as the complications related to the implantation. RESULTS: In total, fourteen patients met the inclusion criteria and received reoperation after implantation of SEEG. The average number of electrodes in each patient is 7.9. At the last available follow-up, nine (64.3%) patients were completely seizure-free according to the International League Against Epilepsy (ILAE) criteria. No significant complications were found in the cohort, two patients' electrodes were loosened and removed because of the seizure. No significant predictors of seizure-free status were identified in the present study, including the result of presurgical MRI, pathology and surgical strategy. CONCLUSIONS: Based on the comprehensive presurgical assessment data and careful discussion of multidisciplinary team, failed epileptic surgery deserves a second chance. Moreover, SEEG is an effective and safe methodology to determine the location of the EZ with the goal of performing reoperation.

Clinical Value of Machine Learning in the Automated Detection of Focal Cortical Dysplasia Using Quantitative Multimodal Surface-Based Features.

Objective: To automatically detect focal cortical dysplasia (FCD) lesion by combining quantitative multimodal surface-based features with machine learning and to assess its clinical value. Methods: Neuroimaging data and clinical information for 74 participants (40 with histologically proven FCD type II) was retrospectively included. The morphology, intensity and function-based features characterizing FCD lesions were calculated vertex-wise on each cortical surface and fed to an artificial neural network. The classifier performance was quantitatively and qualitatively assessed by performing statistical analysis and conventional visual analysis. Results: The accuracy, sensitivity, specificity of the neural network classifier based on multimodal surface-based features were 70.5%, 70.0%, and 69.9%, respectively, which outperformed the unimodal classifier. There was no significant difference in the detection rate of FCD subtypes (Pearson's Chi-Square = 0.001, p = 0.970). Cohen's kappa score between automated detection outcomes and post-surgical resection region was 0.385 (considered as fair). Conclusion: Automated machine learning with multimodal surface features can provide objective and intelligent detection of FCD lesion in pre-surgical evaluation and can assist the surgical strategy. Furthermore, the optimal parameters, appropriate surface features and efficient algorithm are worth exploring.