A hypometabolic gradient is identified in TLE, which covaries with cytoarchitectonic organization, microstructural changes, and hippocampal-neocortical interactions and provides a biologically grounded framework for precise surgical planning, emphasizing that targeting severe hypometabolism may optimize prognosis.
Abstract
Abstract Anterior temporal lobectomy (ATL) remains the standard surgical treatment for pharmacoresistant temporal lobe epilepsy (TLE), yet long-term seizure freedom remains suboptimal. Neuroimaging studies show neocortical metabolic abnormalities beyond the mesiotemporal epicentre, but how such patterns inform resection extent remains unclear. We hypothesized that neocortical hypometabolism in TLE follows a quantifiable spatial gradient that can be translated into personalized surgical strategies. Our multicentre study included 358 participants across discovery, validation, and sensitivity analyses. Multimodal MRI and FDG-PET data were processed to derive vertex-wise structural, intensity, and metabolic features. Individual metabolic abnormalities were quantified using a normative asymmetry modelling approach. In the discovery cohort (227 patients undergoing ATL and 37 healthy controls), we characterized the topography of neocortical hypometabolism, and evaluated its correspondence to cytoarchitectural profiles, multimodal MRI features, and hippocampal measures. Three gradient-informed surgical metrics were evaluated in relation to seizure outcomes, with replication in an independent prospective validation cohort of 38 patients undergoing ATL. An additional sensitivity cohort comprising 56 surgical candidates, whose procedure spared the temporal neocortex was included to assess the robustness. Neocortical hypometabolism in TLE followed a spatially organized gradient, with the most severe hypometabolism at the hippocampal-neocortical interface that diminished with increasing geodesic distance (r = 0.955, Pperm < 0.001). Regions closer to the interface exhibited lower cytoarchitectonic differentiation and stronger FLAIR-related alterations. Hippocampal abnormalities also showed distance-dependent coupling with neocortical metabolism (r = 0.871, Pperm < 0.001). Among surgical metrics, greater resection of severe hypometabolism was associated with seizure freedom (OR = 1.448, P = 0.022). The association was replicated in the validation cohort. The present study identified a hypometabolic gradient in TLE, which covaries with cytoarchitectonic organization, microstructural changes, and hippocampal-neocortical interactions. The gradient provides a biologically grounded framework for precise surgical planning, emphasizing that targeting severe hypometabolism may optimize prognosis.
Multi-site findings demonstrate marked thalamic circuit fragmentation in TLE, and robustly showed subdivision-specific effects, which point to both mesiotemporal co-lateralization as well as broader system-level involvement.
Rui Ding, K. Xie, Judy Chen et al.· bioRxiv· 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.
Yuming Li, Fang Li, Danyang Cao et al.· Human Brain Mapping· 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
Introduction
Approximately 20-30% of temporal lobe epilepsy (TLE) cases present with no visible abnormalities on conventional magnetic resonance imaging (MRI). When interictal electroencephalography (EEG) recordings are also persistently normal, the diagnosis and lateralization become major clinical challenges. We aimed to investigate whether automated hippocampal subfield volumetry could detect subtle structural alterations in these "electro-clinically silent" MRI-negative cases and to correlate these findings with seizure semiology.
Methods
We analyzed 24 patients with clinically diagnosed MRI-negative/EEG-negative TLE and 26 age-matched healthy controls. Despite normal visual inspection on 1.5-T MRI, hippocampal subfield volumes were extracted using an automated segmentation pipeline (volBrain). Seizure semiology was systematically categorized to provide clinical-anatomical correlation.
Results
TLE patients exhibited a significant and selective volume reduction in the right CA4-dentate gyrus (CA4-DG) subfield compared to healthy controls (p=0.003), even after adjusting for age, sex, and total intracranial volume (p=0.002). No statistically significant differences were observed in other hippocampal subfields (CA1, CA2/3, or subiculum), indicating a highly localized pattern of structural alteration.
Conclusion
These results imply that selective CA4-DG atrophy is a defining characteristic of the MRI-negative TLE phenotype, thereby corroborating the "dentate gate" failure hypothesis. Quantitative volumetry provides a crucial diagnostic tool in settings with limited resources, where advanced techniques like 3-T MRI or invasive monitoring are not accessible. This objective structural marker, when integrated with comprehensive semiological analysis, improves diagnostic accuracy and facilitates early clinical intervention in difficult non-lesional TLE cases.
C. Sayman, Elif Özdemir, Sena Güneş et al.· Nöropsikiyatri arşivi· 0 citations
These findings provide robust evidence that multiscale MRI profiling can identify FCD signatures and contribute to in-vivo subtyping and the novel use of myeloarchitecture profiling and contextualization with macro-scale brain gradients provides new avenues to understand intracortical alterations and the embedding of FCD lesions into broader organizational patterns.
E. Sahlas, Judy Chen, Arielle Dascal et al.· bioRxiv· 0 citations
