RESUMEN

OBJECTIVE: Stereoelectroencephalography (SEEG) is increasingly utilized worldwide in epilepsy surgery planning. International guidelines for SEEG terminology and interpretation are yet to be proposed. There are worldwide differences in SEEG definitions, application of features in epilepsy surgery planning, and interpretation of surgical outcomes. This hinders the clinical interpretation of SEEG findings and collaborative research. We aimed to assess the global perspectives on SEEG terminology, differences in the application of presurgical features, and variability in the interpretation of surgery outcome scores, and analyze how clinical expert demographics influenced these opinions. METHODS: We assessed the practices and opinions of epileptologists with specialized training in SEEG using a survey. Data were qualitatively analyzed, and subgroups were examined based on geographical regions and years of experience. Primary outcomes included opinions on SEEG terminology, features used for epilepsy surgery, and interpretation of outcome scores. Additionally, we conducted a multilevel regression and poststratification analysis to characterize the nonresponders. RESULTS: A total of 321 expert responses from 39 countries were analyzed. We observed substantial differences in terminology, practices, and use of presurgical features across geographical regions and SEEG expertise levels. The majority of experts (220, 68.5%) favored the Lüders epileptogenic zone definition. Experts were divided regarding the seizure onset zone definition, with 179 (55.8%) favoring onset alone and 135 (42.1%) supporting onset and early propagation. In terms of presurgical SEEG features, a clear preference was found for ictal features over interictal features. Seizure onset patterns were identified as the most important features by 265 experts (82.5%). We found similar trends after correcting for nonresponders using regression analysis. SIGNIFICANCE: This study underscores the need for standardized terminology, interpretation, and outcome assessment in SEEG-informed epilepsy surgery. By highlighting the diverse perspectives and practices in SEEG, this research lays a solid foundation for developing globally accepted terminology and guidelines, advancing the field toward improved communication and standardization in epilepsy surgery.

RESUMEN

Neurosurgical intervention is the best available treatment for selected patients with drug resistant epilepsy. For these patients, surgical planning requires biomarkers that delineate the epileptogenic zone, the brain area that is indispensable for the generation of seizures. Interictal spikes recorded with electrophysiological techniques are considered key biomarkers of epilepsy. Yet, they lack specificity, mostly because they propagate across brain areas forming networks. Understanding the relationship between interictal spike propagation and functional connections among the involved brain areas may help develop novel biomarkers that can delineate the epileptogenic zone with high precision. Here, we reveal the relationship between spike propagation and effective connectivity among onset and areas of spread and assess the prognostic value of resecting these areas. We analysed intracranial EEG data from 43 children with drug resistant epilepsy who underwent invasive monitoring for neurosurgical planning. Using electric source imaging, we mapped spike propagation in the source domain and identified three zones: onset, early-spread and late-spread. For each zone, we calculated the overlap and distance from surgical resection. We then estimated a virtual sensor for each zone and the direction of information flow among them via Granger causality. Finally, we compared the prognostic value of resecting these zones, the clinically-defined seizure onset zone and the spike onset on intracranial EEG channels by estimating their overlap with resection. We observed a spike propagation in source space for 37 patients with a median duration of 95 ms (interquartile range: 34-206), a spatial displacement of 14 cm (7.5-22 cm) and a velocity of 0.5 m/s (0.3-0.8 m/s). In patients with good surgical outcome (25 patients, Engel I), the onset had higher overlap with resection [96% (40-100%)] than early-spread [86% (34-100%), P = 0.01] and late-spread [59% (12-100%), P = 0.002], and it was also closer to resection than late-spread [5 mm versus 9 mm, P = 0.007]. We found an information flow from onset to early-spread in 66% of patients with good outcomes, and from early-spread to onset in 50% of patients with poor outcome. Finally, resection of spike onset, but not area of spike spread or the seizure onset zone, predicted outcome with positive predictive value of 79% and negative predictive value of 56% (P = 0.04). Spatiotemporal mapping of spike propagation reveals information flow from onset to areas of spread in epilepsy brain. Surgical resection of the spike onset disrupts the epileptogenic network and may render patients with drug resistant epilepsy seizure-free without having to wait for a seizure to occur during intracranial monitoring.

Asunto(s)

RESUMEN

Epigenetic changes such as DNA methylation were observed in drug-resistant temporal lobe epilepsy (DR-TLE), a disease that affects 25-30% of epilepsy patients. The main objective is to simultaneously describe DNA methylation patterns associated with DR-TLE in hippocampus, amygdala, surrounding cortex to the epileptogenic zone (SCEZ), and peripheral blood. An Illumina Infinium MethylationEPIC BeadChip array was performed in 19 DR-TLE patients and 10 postmortem non-epileptic controls. Overall, 32, 59, and 3210 differentially methylated probes (DMPs) were associated with DR-TLE in the hippocampus, amygdala, and SCEZ, respectively. These DMP-affected genes were involved in neurotrophic and calcium signaling in the hippocampus and voltage-gated channels in SCEZ, among others. One of the hippocampus DMPs (cg26834418 (CHORDC1)) showed a strong blood-brain correlation with BECon and IMAGE-CpG, suggesting that it could be a potential surrogate peripheral biomarker of DR-TLE. Moreover, in three of the top SCEZ's DMPs (SHANK3, SBF1, and MCF2L), methylation status was verified with methylation-specific qPCR. The differentially methylated CpGs were classified in DMRs: 2 in the hippocampus, 12 in the amygdala, and 531 in the SCEZ. We identified genes that had not been associated to DR-TLE so far such as TBX5, EXOC7, and WRHN. The area with more DMPs associated with DR-TLE was the SCEZ, some of them related to voltage-gated channels. The DMPs found in the amygdala were involved in inflammatory processes. We also found a potential surrogate peripheral biomarker of DR-TLE. Thus, these results provide new insights into epigenetic modifications involved in DR-TLE.

Asunto(s)

RESUMEN

OBJECTIVE: To perform a side-by-side comparison of two epileptogenicity biomarkers, high frequency oscillations (HFOs) and delayed responses (DRs), as a result of single-pulse electrical stimulation. METHODS: We have recorded stimulation-evoked HFOs and DRs in 16 epileptic patients undergoing presurgical evaluation using the stereoelectroencephalographic method. To evaluate converging and complementary information provided by the biomarkers, we analyzed them individually and for logical "and"/"or" combinations between them. 3D maps of the biomarkers' distributions by recording location (inbound maps) and by stimulation location (outbound maps) were created to analyze their relationship with the epileptogenic structures. RESULTS: HFOs occur less frequently than DRs, by 18.7%, when counting by recording contacts, and more frequently, by 7.4%, when counting by stimulation contacts. 40.6% of the contacts exhibiting HFOs also exhibit DRs, and 44.1% of the contacts exhibiting DRs also exhibit HFOs. When combining biomarkers, there was a tradeoff between increased seizure onset zone (SOZ) sensitivity, from 21.3% to 73%, and decreased specificity, from 87.2% to 34.3%. CONCLUSIONS: There is a moderate similarity in the information provided by the DRs and HFOs. SIGNIFICANCE: The biomarkers complement each other, but there is a tradeoff between different metrics for SOZ localization.

Asunto(s)