Hemispheric functional organization, as revealed by naturalistic neuroimaging, in pediatric epilepsy patients with cortical resections.

Functional changes in the pediatric brain following neural injuries attest to remarkable feats of plasticity. Investigations of the neurobiological mechanisms that underlie this plasticity have largely focused on activation in the penumbra of the lesion or in contralesional, homotopic regions. Here, we adopt a whole-brain approach to evaluate the plasticity of the cortex in patients with large unilateral cortical resections due to drug-resistant childhood epilepsy. We compared the functional connectivity (FC) in patients' preserved hemisphere with the corresponding hemisphere of matched controls as they viewed and listened to a movie excerpt in a functional magnetic resonance imaging (fMRI) scanner. The preserved hemisphere was segmented into 180 and 200 parcels using two different anatomical atlases. We calculated all pairwise multivariate statistical dependencies between parcels, or parcel edges, and between 22 and 7 larger-scale functional networks, or network edges, aggregated from the smaller parcel edges. Both the left and right hemisphere-preserved patient groups had widespread reductions in FC relative to matched controls, particularly for within-network edges. A case series analysis further uncovered subclusters of patients with distinctive edgewise changes relative to controls, illustrating individual postoperative connectivity profiles. The large-scale differences in networks of the preserved hemisphere potentially reflect plasticity in the service of maintained and/or retained cognitive function.

[Focal cortical dysplasia: visual assessment of MRI and MR morphometry data]. / Fokal'naya kortikal'naya displaziya: sravnitel'nyi analiz vizual'noi otsenki dannykh magnitno-rezonansnoi tomografii i magnitno-rezonansnoi morfometrii.

OBJECTIVE: Assessing the diagnostic significance of MR morphometry in determining the localization of focal cortical dysplasias (FCD). MATERIAL AND METHODS: The study included 13 children after surgery for drug-resistant epilepsy caused by FCD type II and stable postoperative remission of seizures (Engel class IA, median follow-up 56 months). We analyzed the results of independent expert assessment of native MR data by three radiologists (HARNESS protocol) and MR morphometry data regarding accuracy of FCD localization. We considered 2 indicators, i.e. local cortical thickening and gray-white matter blurring. RESULTS: FCD detection rate was higher after MR morphometry compared to visual analysis of native MR data using the HARNESS protocol. MR morphometry also makes it possible to more often identify gray-white matter blurring as a sign often missed by radiologists (p<0.05). CONCLUSION: MR morphometry is an additional non-invasive method for assessing the localization of FCD.

Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach.

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.

Connectome reorganization associated with temporal lobe pathology and its surgical resection.

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and interindividual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

A PET-based radiomics nomogram for individualized predictions of seizure outcomes after temporal lobe epilepsy surgery.

PURPOSE: To establish and validate a novel nomogram based on clinical characteristics and [18F]FDG PET radiomics for the prediction of postsurgical seizure freedom in patients with temporal lobe epilepsy (TLE). PATIENTS AND METHODS: 234 patients with drug-refractory TLE patients were included with a median follow-up time of 24 months after surgery. The correlation coefficient redundancy analysis and LASSO Cox regression were used to characterize risk factors. The Cox model was conducted to develop a Clinic-PET nomogram to predict the relapse status in the training set (n = 171). The nomogram's performance was estimated through discrimination, calibration, and clinical utility. The prognostic prediction model was validated in the test set (n = 63). RESULTS: Eight radiomics features were selected to assess the radiomics score (radscore) of the operation side (Lat_radscore) and the asymmetric index (AI) of the radiomics score (AI_radscore). AI_radscor, Lat_radscor, secondarily generalized seizures (SGS), and duration between seizure onset and surgery (Durmon) were significant predictors of seizure-free outcomes. The final model had a C-index of 0.68 (95 %CI: 0.59-0.77) for complete freedom from seizures and time-dependent AUROC was 0.65 at 12 months, 0.65 at 36 months, and 0.59 at 60 months in the test set. A web application derived from the primary predictive model was displayed for economic and efficient use. CONCLUSIONS: A PET-based radiomics nomogram is clinically promising for predicting seizure outcomes after temporal lobe epilepsy surgery.

Verbal memory network mapping in individual patients predicts postoperative functional impairments.

Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter-individual variability in functional networks and brain function-structural dissociations pose challenges when relying solely on group-level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting-state functional MRI (rs-fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30-min rs-fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs-fMRI data for each patient. The accuracy of PVMN was assessed by comparing post-operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group-level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra-temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group-level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = -0.39, p = .038; group-level atlas: r = -0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs-fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals.

Novel Surgical Approaches in Childhood Epilepsy: Laser, Brain Stimulation, and Focused Ultrasound.

Pediatric epilepsy has a worldwide prevalence of approximately 1% (Berg et al., Handb Clin Neurol 111:391-398, 2013) and is associated with not only lower quality of life but also long-term deficits in executive function, significant psychosocial stressors, poor cognitive outcomes, and developmental delays (Schraegle and Titus, Epilepsy Behav 62:20-26, 2016; Puka and Smith, Epilepsia 56:873-881, 2015). With approximately one-third of patients resistant to medical control, surgical intervention can offer a cure or palliation to decrease the disease burden and improve neurological development. Despite its potential, epilepsy surgery is drastically underutilized. Even today only 1% of the millions of epilepsy patients are referred annually for neurosurgical evaluation, and the average delay between diagnosis of Drug Resistant Epilepsy (DRE) and surgical intervention is approximately 20 years in adults and 5 years in children (Solli et al., Epilepsia 61:1352-1364, 2020). It is still estimated that only one-third of surgical candidates undergo operative intervention (Pestana Knight et al., Epilepsia 56:375, 2015). In contrast to the stable to declining rates of adult epilepsy surgery (Englot et al., Neurology 78:1200-1206, 2012; Neligan et al., Epilepsia 54:e62-e65, 2013), rates of pediatric surgery are rising (Pestana Knight et al., Epilepsia 56:375, 2015). Innovations in surgical approaches to epilepsy not only minimize potential complications but also expand the definition of a surgical candidate. In this chapter, three alternatives to classical resection are presented. First, laser ablation provides a minimally invasive approach to focal lesions. Next, both central and peripheral nervous system stimulation can interrupt seizure networks without creating permanent lesions. Lastly, focused ultrasound is discussed as a potential new avenue not only for ablation but also modulation of small, deep foci within seizure networks. A better understanding of the potential surgical options can guide patients and providers to explore all treatment avenues.

EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes.

BACKGROUND AND OBJECTIVES: Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties. METHODS: We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time. RESULTS: Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes. DISCUSSION: Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.

Impact of Previous Surgery on Success of Magnetic Resonance-guided Laser Interstitial Thermal Therapy (MRgLITT) to Treat Pediatric Epilepsy: An Institutional Experience.

BACKGROUND: There is an emerging role for minimally invasive magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) in the treatment of pediatric epilepsy refractory to medication. To date, predictors of MRgLITT success have not been established in a sizeable singular experience. Correspondingly, the aim of this study was to elucidate if previous surgical history predicts MRgLITT success in this setting. METHODS: A retrospective review was conducted of our MRgLITT procedures for pediatric (patient age <19 years) epilepsy from 2011 to 2020 with documented seizure outcomes at 1 and 2 years after procedure. Categorical and continuous data were compared using χ2 and Student's t test, respectively. RESULTS: A total of 41 patients satisfied all criteria with 16 (39%) female and 25 (61%) male patients. Following MRgLITT, seizure-freedom at 1-year was achieved in 15 (37%) patients. In the cohort, there were 14 (34%) patients who had undergone previous open surgery for epilepsy at mean age of 9.4 ± 5.5 years. Patients with a previous open surgery history were found to statistically experience longer length of hospitalization after MRgLITT (P = 0.04) with a statistically lower proportion of seizure-freedom at 1-year after MRgLITT (14% vs. 48%, P = 0.03). However, there was no difference in the rate of seizure-freedom at 2 years (29% vs. 41%, P = 0.44), as well as no difference in subsequent surgical interventions for seizure management between groups. CONCLUSIONS: Based on our institutional experience, patients with previous open surgery history may experience longer length of hospitalization after MRgLITT for pediatric epilepsy and lesser response in seizure-freedom within the first year but with non-inferior seizure freedom by the second year.

Temporo-Parieto-Occipital Disconnection by Robot-Assisted Magnetic Resonance Imaging-Guided Laser Interstitial Thermal Therapy for Refractory Epilepsy in a Pediatric Patient: Proof-of-Principle Case Report and Surgical Nuances.

OBJECTIVE: Magnetic resonance imaging-guided laser interstitial thermal therapy (MRIgLITT) has been proven safe and effective for the treatment of focal epilepsy of different etiologies. It has also been used to disconnect brain tissue in more extensive or diffuse epilepsy, such as corpus callosotomy and hemispherotomy. METHODS: In this study, we report a case of temporo-parieto-occipital disconnection surgery performed using MRIgLITT assisted by a robotic arm for refractory epilepsy of the posterior quadrant. A highly realistic cadaver simulation was performed before the actual surgery. RESULTS: The patient was a 14-year-old boy whose seizures began at the age of 8. The epilepsy was a result of a left perinatal ischemic event that caused a porencephalic cyst, and despite receiving multiple antiepileptic drugs, the patient continued to experience daily seizures which led to the recommendation of surgery. CONCLUSIONS: A Wada test lateralized language in the right hemisphere. Motor and sensory function was confirmed in the left hemisphere through magnetic resonance imaging functional studies and NexStim. The left MRIgLITT temporo-parieto-occipital disconnection disconnection was achieved using 5 laser fibers. The patient followed an excellent postoperative course and was seizure-free, with no additional neurological deficits 24 months after the surgery.

Monopolar stereoelectroencephalography-guided radiofrequency thermocoagulation.

OBJECTIVE: Stereoelectroencephalography (SEEG)-guided radiofrequency thermocoagulation (RFTC) has the advantage of producing a lesion in the epileptogenic zone (EZ) at the end of SEEG. The majority of published SEEG-guided RFTCs have been bipolar and usually performed between contiguous contacts of the same electrode. In the present study, the authors evaluate the safety, efficacy, and benefits of monopolar RFTC at the end of SEEG. METHODS: This study included a series of 31 consecutive patients who had undergone RFTC at the end of SEEG for drug-resistant focal epilepsy in the period of January 2013-December 2019. Post-RFTC seizure control was assessed after 2 months and at the last follow-up visit. Twenty-one patients underwent resective epilepsy surgery after the SEEG-guided RFTC, and the postoperative seizure outcome among these patients was compared with the post-RFTC seizure outcome. RESULTS: Four hundred forty-six monopolar RFTCs were done in the 31 patients. Monopolar RFTCs were performed in all cortical areas, including the insular cortex in 11 patients (56 insular RFTCs). There were 31 noncontiguous lesions (7.0%) because of vascular constraints. The volume of one monopolar RFTC, as measured on T2-weighted MRI immediately after the procedure, was between 44 and 56 mm3 (mean 50 mm3). The 2-month post-RFTC seizure outcomes were as follows: seizure freedom in 13 patients (41.9%), ≥ 50% reduced seizure frequency in 11 (35.5%), and no significant change in 7 (22.6%). Seizure outcome at the last follow-up visit (mean 18 months, range 2-54 months) showed seizure freedom in 2 patients (6.5%) and ≥ 50% reduced seizure frequency in 20 patients (64.5%). Seizure freedom after monopolar RFTC was not significantly associated with the number or location of coagulated contacts. Seizure response after monopolar RFTC had a high positive predictive value (93.8%) but a low negative predictive value (40%) for seizure outcome after subsequent resective surgery. In this series, the only complication (3.2%) was a limited intraventricular hematoma following RFTC performed in the hippocampal head, with spontaneous resolution and no sequelae. CONCLUSIONS: The use of monopolar SEEG-guided RFTC provides more freedom in terms of choosing the SEEG contacts for thermocoagulation and a larger thermolesion volume. Monopolar thermocoagulation seems particularly beneficial in cases with an insular EZ, in which vascular constraints could be partially avoided by making noncontiguous lesions within the EZ.

Non-lesional epilepsy does not necessarily convey poor outcomes after invasive monitoring followed by resection or thermal ablation.

OBJECTIVE: We aimed to compare outcomes including seizure-free status at the last follow-up in adult patients with medically refractory focal epilepsy identified as lesional vs. non-lesional based on their magnetic resonance imaging (MRI) findings who underwent invasive evaluation followed by subsequent resection or thermal ablation (LiTT). METHODS: We identified 88 adult patients who underwent intracranial monitoring between 2014 and 2021. Of those, 40 received resection or LiTT, and they were dichotomized based on MRI findings, as lesional (N = 28) and non-lesional (N = 12). Patient demographics, seizure characteristics, non-invasive interventions, intracranial monitoring, and surgical variables were compared between the groups. Postsurgical seizure outcome at the last follow-up was rated according to the Engel classification, and postoperative seizure freedom was determined by Kaplan-Meyer survival analysis. Statistical analyses employed Fisher's exact test to compare categorical variables, while a t-test was used for continuous variables. RESULTS: There were no differences in baseline characteristics between groups except for more often noted PET abnormality in the lesional group (p = 0.0003). 64% of the lesional group and 57% of the non-lesional group received surgical resection or LiTT (p = 0.78). At the last follow-up, 78.5% of the patients with lesional MRI findings achieved Engel I outcomes compared to 66.7% of non-lesional patients (p = 0.45). Kaplan-Meier curves did not show a significant difference in seizure-free duration between both groups after surgical intervention (p = 0.49). SIGNIFICANCE: In our sample, the absence of lesion on brain MRI was not associated with worse seizure outcomes in adult patients who underwent invasive intracranial monitoring followed by resection or thermal ablation.

Development and prospective clinical validation of a convolutional neural network for automated detection and segmentation of focal cortical dysplasias.

PURPOSE: Focal cortical dysplasias (FCDs) are a leading cause of drug-resistant epilepsy. Early detection and resection of FCDs have favorable prognostic implications for postoperative seizure freedom. Despite advancements in imaging methods, FCD detection remains challenging. House et al. (2021) introduced a convolutional neural network (CNN) for automated FCD detection and segmentation, achieving a sensitivity of 77.8%. However, its clinical applicability was limited due to a low specificity of 5.5%. The objective of this study was to improve the CNN's performance through data-driven training and algorithm optimization, followed by a prospective validation on daily-routine MRIs. MATERIAL AND METHODS: A dataset of 300 3 T MRIs from daily clinical practice, including 3D T1 and FLAIR sequences, was prospectively compiled. The MRIs were visually evaluated by two neuroradiologists and underwent morphometric assessment by two epileptologists. The dataset included 30 FCD cases (11 female, mean age: 28.1 ± 10.1 years) and a control group of 150 normal cases (97 female, mean age: 32.8 ± 14.9 years), along with 120 non-FCD pathological cases (64 female, mean age: 38.4 ± 18.4 years). The dataset was divided into three subsets, each analyzed by the CNN. Subsequently, the CNN underwent a two-phase-training process, incorporating subset MRIs and expert-labeled FCD maps. This training employed both classical and continual learning techniques. The CNN's performance was validated by comparing the baseline model with the trained models at two training levels. RESULTS: In prospective validation, the best model trained using continual learning achieved a sensitivity of 90.0%, specificity of 70.0%, and accuracy of 72.0%, with an average of 0.41 false positive clusters detected per MRI. For FCD segmentation, an average Dice coefficient of 0.56 was attained. The model's performance improved in each training phase while maintaining a high level of sensitivity. Continual learning outperformed classical learning in this regard. CONCLUSIONS: Our study presents a promising CNN for FCD detection and segmentation, exhibiting both high sensitivity and specificity. Furthermore, the model demonstrates continuous improvement with the inclusion of more clinical MRI data. We consider our CNN a valuable tool for automated, examiner-independent FCD detection in daily clinical practice, potentially addressing the underutilization of epilepsy surgery in drug-resistant focal epilepsy and thereby improving patient outcomes.

An automated algorithm for stereoelectroencephalography electrode localization and labelling.

PURPOSE: Stereoelectroencephalography (sEEG) is increasingly utilized for localization of seizure foci, functional mapping, and neurocognitive research due to its ability to target deep and difficult to reach anatomical locations and to study in vivo brain function with a high signal-to-noise ratio. The research potential of sEEG is constrained by the need for accurate localization of the implanted electrodes in a common template space for group analyses. METHODS: We present an algorithm to automate the grouping of sEEG electrodes by trajectories, labelled by target and insertion point. This algorithm forms the core of a pipeline that fully automates the entire process of electrode localization in standard space, using raw CT and MRI images to produce atlas labelled MNI coordinates. RESULTS: Across 196 trajectories from 20 patients, the pipeline successfully processed 190 trajectories with localizations within 0.25±0.55 mm of the manual annotation by two reviewers. Six electrode trajectories were not directly identified due to metal artifacts and locations were interpolated based on the first and last contact location and the number of contacts in that electrode as listed in the surgical record. CONCLUSION: We introduce our algorithm and pipeline for automatically localizing, grouping, and classifying sEEG electrodes from raw CT and MRI. Our algorithm adds to existing pipelines and toolboxes for electrode localization by automating the manual step of marking and grouping electrodes, thereby expedites the analyses of sEEG data, particularly in large datasets.

Amygdala enlargement in temporal lobe epilepsy: Histopathology and surgical outcomes.

OBJECTIVES: Amygdala enlargement is detected on magnetic resonance imaging (MRI) in some patients with drug-resistant temporal lobe epilepsy (TLE), but its clinical significance remains uncertain We aimed to assess if the presence of amygdala enlargement (1) predicted seizure outcome following anterior temporal lobectomy with amygdalohippocampectomy (ATL-AH) and (2) was associated with specific histopathological changes. METHODS: This was a case-control study. We included patients with drug-resistant TLE who underwent ATL-AH with and without amygdala enlargement detected on pre-operative MRI. Amygdala volumetry was done using FreeSurfer for patients who had high-resolution T1-weighted images. Mann-Whitney U test was used to compare pre-operative clinical characteristics between the two groups. The amygdala volume on the epileptogenic side was compared to the amygdala volume on the contralateral side among cases and controls. Then, we used a two-sample, independent t test to compare the means of amygdala volume differences between cases and controls. The chi-square test was used to assess the correlation of amygdala enlargement with (1) post-surgical seizure outcomes and (2) histopathological changes. RESULTS: Nineteen patients with and 19 patients without amygdala enlargement were studied. Their median age at surgery was 38 years for cases and 39 years for controls, and 52.6% were male. There were no statistically significant differences between the two groups in their pre-operative clinical characteristics. There were significant differences in the means of volume difference between cases and controls (Diff = 457.2 mm3, 95% confidence interval [CI] 289.6-624.8; p < .001) and in the means of percentage difference (p < .001). However, there was no significant association between amygdala enlargement and surgical outcome (p = .72) or histopathological changes (p = .63). SIGNIFICANCE: The presence of amygdala enlargement on the pre-operative brain MRI in patients with TLE does not affect the surgical outcome following ATL-AH, and it does not necessarily suggest abnormal histopathology. These findings suggest that amygdala enlargement might reflect a secondary reactive process to seizures in the epileptogenic temporal lobe.

Combining magnetic resonance fingerprinting with voxel-based morphometric analysis to reduce false positives for focal cortical dysplasia detection.

OBJECTIVE: We aim to improve focal cortical dysplasia (FCD) detection by combining high-resolution, three-dimensional (3D) magnetic resonance fingerprinting (MRF) with voxel-based morphometric magnetic resonance imaging (MRI) analysis. METHODS: We included 37 patients with pharmacoresistant focal epilepsy and FCD (10 IIa, 15 IIb, 10 mild Malformation of Cortical Development [mMCD], and 2 mMCD with oligodendroglial hyperplasia and epilepsy [MOGHE]). Fifty-nine healthy controls (HCs) were also included. 3D lesion labels were manually created. Whole-brain MRF scans were obtained with 1 mm3 isotropic resolution, from which quantitative T1 and T2 maps were reconstructed. Voxel-based MRI postprocessing, implemented with the morphometric analysis program (MAP18), was performed for FCD detection using clinical T1w images, outputting clusters with voxel-wise lesion probabilities. Average MRF T1 and T2 were calculated in each cluster from MAP18 output for gray matter (GM) and white matter (WM) separately. Normalized MRF T1 and T2 were calculated by z-scores using HCs. Clusters that overlapped with the lesion labels were considered true positives (TPs); clusters with no overlap were considered false positives (FPs). Two-sample t-tests were performed to compare MRF measures between TP/FP clusters. A neural network model was trained using MRF values and cluster volume to distinguish TP/FP clusters. Ten-fold cross-validation was used to evaluate model performance at the cluster level. Leave-one-patient-out cross-validation was used to evaluate performance at the patient level. RESULTS: MRF metrics were significantly higher in TP than FP clusters, including GM T1, normalized WM T1, and normalized WM T2. The neural network model with normalized MRF measures and cluster volume as input achieved mean area under the curve (AUC) of .83, sensitivity of 82.1%, and specificity of 71.7%. This model showed superior performance over direct thresholding of MAP18 FCD probability map at both the cluster and patient levels, eliminating ≥75% FP clusters in 30% of patients and ≥50% of FP clusters in 91% of patients. SIGNIFICANCE: This pilot study suggests the efficacy of MRF for reducing FPs in FCD detection, due to its quantitative values reflecting in vivo pathological changes. © 2024 International League Against Epilepsy.

Optimized microburst VNS elicits fMRI responses beyond thalamic-specific response from standard VNS.

OBJECTIVE: In parallel to standard vagus nerve stimulation (VNS), microburst stimulation delivery has been developed. We evaluated the fMRI-related signal changes associated with standard and optimized microburst stimulation in a proof-of-concept study (NCT03446664). METHODS: Twenty-nine drug-resistant epilepsy patients were prospectively implanted with VNS. Three 3T fMRI scans were collected 2 weeks postimplantation. The maximum tolerated VNS intensity was determined prior to each scan starting at 0.125 mA with 0.125 mA increments. FMRI scans were block-design with alternating 30 sec stimulation [ON] and 30 sec no stimulation [OFF]: Scan 1 utilized standard VNS and Scan 3 optimized microburst parameters to determine target settings. Semi-automated on-site fMRI data processing utilized ON-OFF block modeling to determine VNS-related fMRI activation per stimulation setting. Anatomical thalamic mask was used to derive highest mean thalamic t-value for determination of microburst stimulation parameters. Paired t-tests corrected at P < 0.05 examined differences in fMRI responses to each stimulation type. RESULTS: Standard and microburst stimulation intensities at Scans 1 and 3 were similar (P = 0.16). Thalamic fMRI responses were obtained in 28 participants (19 with focal; 9 with generalized seizures). Group activation maps showed standard VNS elicited thalamic activation while optimized microburst VNS showed widespread activation patterns including thalamus. Comparison of stimulation types revealed significantly greater cerebellar, midbrain, and parietal fMRI signal changes in microburst compared to standard VNS. These differences were not associated with seizure responses. INTERPRETATION: While standard and optimized microburst VNS elicited thalamic activation, microburst also engaged other brain regions. Relationship between these fMRI activation patterns and clinical response warrants further investigation. CLINICAL TRIAL REGISTRATION: The study was registered with clinicaltrials.gov (NCT03446664).

Measurable transitions during seizures in intracranial EEG: A stereoelectroencephalography and SPECT study.

OBJECTIVE: Ictal Single Photon Emission Computed Tomography (SPECT) and stereo-electroencephalography (SEEG) are diagnostic techniques used for the management of patients with drug-resistant focal epilepsies. While hyperperfusion patterns in ictal SPECT studies reveal seizure onset and propagation pathways, the role of ictal hypoperfusion remains poorly understood. The goal of this study was to systematically characterize the spatio-temporal information flow dynamics between differently perfused brain regions using stereo-EEG recordings. METHODS: We identified seizure-free patients after resective epilepsy surgery who had prior ictal SPECT and SEEG investigations. We estimated directional connectivity between the epileptogenic-zone (EZ), non-resected areas of hyperperfusion, hypoperfusion, and baseline perfusion during the interictal, preictal, ictal, and postictal periods. RESULTS: Compared to the background, we noted significant information flow (1) during the preictal period from the EZ to the baseline and hyperperfused regions, (2) during the ictal onset from the EZ to all three regions, and (3) during the period of seizure evolution from the area of hypoperfusion to all three regions. CONCLUSIONS: Hypoperfused brain regions were found to indirectly interact with the EZ during the ictal period. SIGNIFICANCE: Our unique study, combining intracranial electrophysiology and perfusion imaging, presents compelling evidence of dynamic changes in directional connectivity between brain regions during the transition from interictal to ictal states.

Distributed source modeling of stereoencephalographic measurements of ictal activity.

OBJECTIVES: Stereoelectroencephalography (SEEG) can define the epileptogenic zone (EZ). However, SEEG is susceptible to the sampling bias, where no SEEG recording is taken within a circumscribed EZ. METHODS: Nine patients with medically refractory epilepsy underwent SEEG recording, and brain resection got positive outcomes. Ictal neuronal currents were estimated by distributed source modeling using the SEEG data and individual's anatomical magnetic resonance imaging. Using a retrospective leave-one-out data sub-sampling, we evaluated the sensitivity and specificity of the current estimates using MRI after surgical resection or radio-frequency ablation. RESULTS: The sensitivity and specificity in detecting the EZ were indistinguishable from either the data from all electrodes or the sub-sampled data (rank sum test: rank sum = 23719, p = 0.13) when at least one remaining electrode contact was no more than 20 mm away. CONCLUSIONS: The distributed neuronal current estimates of ictal SEEG data can mitigate the challenge of delineating the boundary of the EZ in cases of missing an electrode implanted within the EZ and a required second SEEG exploration. SIGNIFICANCE: Distributed source modeling can be a tool for clinicians to infer the EZ by allowing for more flexible planning of the electrode implantation route and minimizing the number of electrodes.

Evidence for interictal blood-brain barrier dysfunction in people with epilepsy.

OBJECTIVE: Interictal blood-brain barrier dysfunction in chronic epilepsy has been demonstrated in animal models and pathological specimens. Ictal blood-brain barrier dysfunction has been shown in humans in vivo using an experimental quantitative magnetic resonance imaging (MRI) protocol. Here, we hypothesized that interictal blood-brain barrier dysfunction is also present in people with drug-resistant epilepsy. METHODS: Thirty-nine people (21 females, mean age at MRI ± SD = 30 ± 8 years) with drug-resistant epilepsy were prospectively recruited and underwent interictal T1-relaxometry before and after administration of a paramagnetic contrast agent. Likewise, quantitative T1 was acquired in 29 people without epilepsy (12 females, age at MRI = 48 ± 18 years). Quantitative T1 difference maps were calculated and served as a surrogate imaging marker for blood-brain barrier dysfunction. Values of quantitative T1 difference maps inside hemispheres ipsilateral to the presumed seizure onset zone were then compared, on a voxelwise level and within presumed seizure onset zones, to the contralateral side of people with epilepsy and to people without epilepsy. RESULTS: Compared to the contralateral side, ipsilateral T1 difference values were significantly higher in white matter (corrected p < .05), gray matter (uncorrected p < .05), and presumed seizure onset zones (p = .04) in people with epilepsy. Compared to people without epilepsy, significantly higher T1 difference values were found in the anatomical vicinity of presumed seizure onset zones (p = .004). A subgroup of people with hippocampal sclerosis demonstrated significantly higher T1 difference values in the ipsilateral hippocampus and in regions strongly interconnected with the hippocampus compared to people without epilepsy (corrected p < .01). Finally, z-scores reflecting the deviation of T1 difference values within the presumed seizure onset zone were associated with verbal memory performance (p = .02) in people with temporal lobe epilepsy. SIGNIFICANCE: Our results indicate a blood-brain barrier dysfunction in drug-resistant epilepsy that is detectable interictally in vivo, anatomically related to the presumed seizure onset zone, and associated with cognitive deficits.