Long-term outcomes in temporal lobe epilepsy depend not only on accurate localization and removal of epileptogenic tissue but also on how its connectivity is distributed across brain networks before surgery, which may represent a biomarker of late relapse.
Abstract
Objective
Although many patients with temporal lobe epilepsy achieve seizure freedom in the first post-operative year, the likelihood of long-term seizure freedom declines substantially over time. Late seizure relapse may reflect ongoing epileptogenicity, potentially driven by persistent epileptic activity arising from the epileptogenic zone. We hypothesized that its more distributed connectivity profile across brain networks would distinguish patients experiencing late relapse.
Methods
We prospectively enrolled 209 patients with drug-resistant temporal lobe epilepsy across six centers who underwent destructive surgery, pre-operative diffusion-weighted magnetic resonance imaging (MRI), and/or resting-state functional MRI. To isolate network mechanisms related to late relapse rather than early surgical failure, we focused on patients who achieved seizure freedom after the first post-operative year. After two post-operative years, these patients were stratified into long-term seizure freedom (SF-SF) and late relapse (SF-NSF). We delineated post-operative resections to localize epileptogenic zones and quantified their network properties using graph-theory metrics-betweenness centrality and participation coefficient. Patient graph-theory metrics were standardized relative to normative connectomes derived from 362 healthy controls. We evaluated associations between patient graph-theory metrics and long-term outcomes using Firth's bias-reduced regressions and permutation testing.
Results
Fifty-four patients with diffusion-weighted MRI (SF-SF = 37, SF-NSF = 17) and 30 patients with functional MRI (SF-SF = 19, SF-NSF = 11) met the inclusion criteria. Greater functional MRI-derived participation coefficient of resections was associated with late relapse, reflecting a more distributed connectivity profile across networks. In a post hoc analysis, lower diffusion-weighted MRI-derived betweenness centrality of the epileptogenic hippocampus was associated with late relapse. Effects were confirmed by patient-level and anatomy-preserving permutations.
Significance
Long-term outcomes in temporal lobe epilepsy depend not only on accurate localization and removal of epileptogenic tissue but also on how its connectivity is distributed across brain networks before surgery. Pre-operative cross-network connectivity of the epileptogenic zone may represent a biomarker of late relapse.
The model achieved high specificity in predicting long-term seizure recurrence, which supports its potential clinical utility for postoperative risk stratification and counseling rather than surgical exclusion and underscores the translational potential of network-level biomarkers to complement conventional predictors.
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Successful TLE surgery is associated with partial restoration of cholinergic arousal network connectivity, supporting the idea that seizure cessation enables recovery of brain networks disrupted by recurrent seizures.
Addison C Cavender, Derek J. Doss, Ghassan S Makhoul et al.· Epilepsia· 0 citations
Surgical failure in temporal lobe epilepsy with hippocampal sclerosis (TLE‐HS) may reflect insufficient disruption of epileptogenic networks. We investigated whether integrating quantitative spatial patterns of regional atrophy and hypometabolism, along with clinical features, could provide complementary prognostic information for postoperative seizure freedom. T1‐weighted MRI, 18F‐FDG‐PET, and postoperative CT scans of patients with TLE‐HS were retrospectively analyzed against a validated healthy control cohort to compute age‐ and gender‐adjusted W‐score maps. Regional relationships of atrophy and hypometabolism were assessed using bivariate correlations and multiple regression analyses. Machine learning models integrating laterality of seizure onset, preoperative (extra‐)temporal atrophy/hypometabolism extent, seizure frequency, focal to bilateral tonic–clonic seizures during the preceding year, and resection volume were developed to predict seizure freedom 1 year after surgery. Model interpretability was assessed via permutation‐based variable importance analysis. The cohort comprised 101 patients with TLE‐HS (48 left, LHS; 53 right, RHS), including 72 patients who underwent anterior temporal lobectomy. Distinct modality‐specific patterns emerged: hypometabolism was significantly greater than local atrophy in left temporo‐limbic cortex in TLE‐LHS, while atrophy exceeded hypometabolism in bilateral occipital regions in TLE‐RHS. Positive correlations between local atrophy and hypometabolism were more robust in ipsilateral temporo‐limbic cortex in TLE‐LHS. The combined model integrating preoperative atrophy and hypometabolism features (AUC: 0.56–0.64) significantly outperformed single‐modality models (pfdr < 0.05). Notably, incorporating clinical factors further enhanced predictive performance (AUC: 0.63–0.70) and model calibration. This comprehensive preoperative clinical‐imaging model achieved robust prognostic efficacy that was not significantly improved by the addition of actual postoperative resection volumes. Structural MRI and 18F‐FDG‐PET reveal complementary facets of the epileptogenic network in TLE‐HS. While integrating multimodal imaging with clinical metrics demonstrates significant synergistic potential for predicting surgical outcomes, our models remain exploratory. External validation in independent multi‐center cohorts is required before translating these findings into precise clinical tools for surgical planning.
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High-frequency IEDs on early postoperative EEG may identify patients at increased risk of long-term deterioration after surgery for HS-related TLE, and prospective studies are needed before modifying routine follow-up strategies.
Kate Durbano, Q. Calonge, Valerio Frazzini et al.· Seizure· 0 citations
Initial evidence is provided that intra-thalamic functional connectivity, particularly within the bilateral VA complex, is associated with FBTCS history in TLE and varies with lateralization of seizureonset, and may represent a biomarker for FBTCS.
Stacy N. Hudgins, Michael R Sperling, Hasan Ayaz et al.· Epilepsia· 0 citations
Thalamo-cortical synchrony shapes seizure expression in human temporal lobe epilepsy Aung T, Li J, Tumnark T, Belly C, Thomas J, Jaber K, Parikh P, Zafar M, Southwell D, Chauvel P, Frauscher B, Gonzalez-Martinez J. Nat Commun. Published online May 25, 2026. doi:10.1038/s41467-026-73053-9 In drug-resistant temporal lobe epilepsy (DR-TLE), some seizures are clinically symptomatic while others remain electrographic despite arising from the same seizure-onset zone (SOZ), suggesting that clinical expression reflects network dynamics beyond seizure origin. We examined whether thalamo-cortical network engagement differs between clinical seizure (CS) and non-CS (NCS). We analyzed 286 seizures from 62 DR-TLE patients recorded using stereoelectroencephalography with pulvinar and/or anterior thalamic group coverage. Thalamo-cortical synchrony during the first 20 s of seizure onset was quantified as correlation between stereoelectroencephalography-derived time-frequency patterns in thalamic nuclei and the cortical SOZ. Synchrony was significantly stronger during CS than NCS (P < .0001, δ > 0.6), including within-subject analyses, and was independent of other clinical variables, including postsurgical outcome. Linear mixed-effects modeling identified seizure type as the sole independent predictor of synchrony (P = .0069). These findings identify thalamo-cortical synchrony as a network-level feature associated with CS expression in DR-TLE.
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