Establishment of a normal control model of children's brain 18-fluorodeoxyglucose positron emission tomography and analysis of the changing pattern in patients aged 0-14 years.

Background: It is difficult to obtain 18-fluorodeoxyglucose positron emission tomography (18FDG-PET) data from normal children, and changes in brain metabolism in children due to growth and development are poorly understood. For the first time, we established a normal control model of brain 18FDG-PET in children and evaluated its feasibility. The association of PET with age in children aged 0-14 years was analyzed. This study aimed to establish a normal control model of brain 18FDG-PET in children for the first time and to verify its feasibility, and to analyze the trend of PET with age in children aged 0-14 years. Methods: In this retrospective cohort study, the 18FDG-PET imaging data of patients with no epileptiform discharge involvement contralateral to the epileptogenic zone were consecutively collected from January 2015 to June 2022 according to strictly defined screening criteria. For the normal control data, the hemisphere contralateral to the epileptogenic zone was mirrored and spliced to form an intact brain. The cohort of children aged 0-14 years was divided into 14 groups according age by year. Subsequently, patients who underwent lesionectomy with clear hypometabolism that roughly coincided with the extent of surgical resection were examined. The PET scan was compared with the control model, and the ratio of overlapping parts (hypometabolic areas ∩ surgical resection area) to hypometabolic parts (ROH) was calculated. Multiple regression analysis was performed on the normal control model for every 3- to 4-year age interval. Results: A total of 159 normal control models were established. Five patients were randomly selected to verify the reliability of each yearly model. The average ROH was 0.968. Metabolism increasing with age in the different brain regions was observed at ages 0-2~, 3-5~, and 6-10 years. No age-related metabolic increase or decrease was found in the 10- to 14-year-old group. The metabolism in the 7- to 8-year-old group was higher than that in the 13- to 14-year-old group. Conclusions: With strict screening criteria, the method of mirroring the contralateral hemisphere of the epileptic zone and splicing it into a complete brain as a means of creating a normal control group is feasible. The method offers convenience to the studies that lack healthy pediatric controls. Children under 10 years of age (especially 0-6 years old) experience considerable metabolic changes year on year. After the age of 10 years, the changes in metabolism gradually decrease, and metabolism also slowly decreases. Our findings provide guidance the clinical interpretation of areas with hypometabolism and emphasize the importance of establishing a normal control model of the child's brain, which should not be replaced by an adult model.

Practical measurements distinguishing physiological and pathological stereoelectroencephalography channels based on high-frequency oscillations in the human brain.

OBJECTIVE: The present study aimed to identify various distinguishing features for use in the accurate classification of stereoelectroencephalography (SEEG) channels based on high-frequency oscillations (HFOs) inside and outside the epileptogenic zone (EZ). METHODS: HFOs were detected in patients with focal epilepsy who underwent SEEG. Subsequently, HFOs within the seizure-onset and early spread zones were defined as pathological HFOs, whereas others were defined as physiological. Three features of HFOs were identified at the channel level, namely, morphological repetition, rhythmicity, and phase-amplitude coupling (PAC). A machine-learning (ML) classifier was then built to distinguish two HFO types at the channel level by application of the above-mentioned features, and the contributions were quantified. Further verification of the characteristics and classifier performance was performed in relation to various conscious states, imaging results, EZ location, and surgical outcomes. RESULTS: Thirty-five patients were included in this study, from whom 166 104 pathological HFOs in 255 channels and 53 374 physiological HFOs in 282 channels were entered into the analysis pipeline. The results revealed that the morphological repetitions of pathological HFOs were markedly higher than those of the physiological HFOs; this was also observed for rhythmicity and PAC. The classifier exhibited high accuracy in differentiating between the two forms of HFOs, as indicated by an area under the curve (AUC) of 0.89. Both PAC and rhythmicity contributed significantly to this distinction. The subgroup analyses supported these findings. SIGNIFICANCE: The suggested HFO features can accurately distinguish between pathological and physiological channels substantially improving its usefulness in clinical localization. PLAIN LANGUAGE SUMMARY: In this study, we computed three quantitative features associated with HFOs in each SEEG channel and then constructed a machine learning-based classifier for the classification of pathological and physiological channels. The classifier performed well in distinguishing the two channel types under different levels of consciousness as well as in terms of imaging results, EZ location, and patient surgical outcomes.

The 3-Dimensional Intelligent Structured Light Technique: A New Registration Method in Stereotactic Neurosurgery.

BACKGROUND AND OBJECTIVES: Surface-based facial scanning registration emerged as an essential registration method in the robot-assisted neuronavigation surgery, providing a marker-free way to align a patient's facial surface with the imaging data. The 3-dimensional (3D) structured light was developed as an advanced registration method based on surface-based facial scanning registration. We aspire to introduce the 3D structured light as a new registration method in the procedure of the robot-assisted neurosurgery and assess the accuracy, efficiency, and safety of this method by analyzing the relative operative results. METHODS: We analyzed the results of 47 patients who underwent Ommaya reservoir implantation (n = 17) and stereotactic biopsy (n = 30) assisted by 3D structured light at our hospital from January 2022 to May 2023. The accuracy and additional operative results were analyzed. RESULTS: For the Ommaya reservoir implantation, the target point error was 3.2 ± 2.2 mm and the entry point error was 3.3 ± 2.4 mm, while the operation duration was 35.8 ± 8.3 minutes. For the stereotactic biopsy, the target point error was 2.3 ± 1.3 mm and the entry point error was 2.7 ± 1.2 mm, while the operation duration was 24.5 ± 6.3 minutes. CONCLUSION: The 3D structured light technique reduces the patients' discomfort and offers the advantage of a simpler procedure, which can improve the clinical efficiency with the sufficient accuracy and safety to meet the clinical requirements of the puncture and navigation.

Hypometabolic patterns are related to post-surgical seizure outcomes in focal cortical dysplasia: A semi-quantitative study.

OBJECTIVE: Fluorine-18-fluorodeoxyglucose-positron emission tomography (FDG-PET) is routinely used for presurgical evaluation in many epilepsy centers. Hypometabolic characteristics have been extensively examined in prior studies, but the metabolic patterns associated with specific pathological types of drug-resistant epilepsy remain to be fully defined. This study was developed to explore the relationship between metabolic patterns or characteristics and surgical outcomes in type I and II focal cortical dysplasia (FCD) patients based on results from a large cohort. METHODS: Data from individuals who underwent epilepsy surgery from 2014 to 2019 with a follow-up duration of over 3 years and a pathological classification of type I or II FCD in our hospital were retrospectively analyzed. Hypometabolic patterns were quantitatively identified via statistical parametric mapping (SPM) and qualitatively analyzed via visual examination of PET-MRI co-registration images. Univariate analyses were used to explore the relationship between metabolic patterns and surgical outcomes. RESULTS: In total, this study included data from 210 patients. Following SPM calculations, four hypometabolic patterns were defined including unilobar, multi-lobar, and remote patterns as well as cases where no pattern was evident. In type II FCD patients, the unilobar pattern was associated with the best surgical outcomes (p = 0.014). In visual analysis, single gyrus (p = 0.032) and Clear-cut hypometabolism edge (p = 0.040) patterns exhibited better surgery outcomes in the type II FCD group. CONCLUSIONS: PET metabolic patterns are well-correlated with the prognosis of type II FCD patients. However, similar correlations were not observed in type I FCD, potentially owing to the complex distribution of the epileptogenic region. PLAIN LANGUAGE SUMMARY: In this study, we demonstrated that FDG-PET was a crucial examination for patients with FCD, which was a common cause of epilepsy. We compared the surgical prognosis for patients with different hypometabolism distribution patterns and found that clear and focal abnormal region in PET was correlated with good surgical outcome in type II FCD patients.

Localizing seizure onset zone by a cortico-cortical evoked potentials-based machine learning approach in focal epilepsy.

OBJECTIVE: We aimed to develop a new approach for identifying the localization of the seizure onset zone (SOZ) based on corticocortical evoked potentials (CCEPs) and to compare the connectivity patterns in patients with different clinical phenotypes. METHODS: Fifty patients who underwent stereoelectroencephalography and CCEP procedures were included. Logistic regression was used in the model, and six CCEP metrics were input as features: root mean square of the first peak (N1RMS) and second peak (N2RMS), peak latency, onset latency, width duration, and area. RESULTS: The area under the curve (AUC) for localizing the SOZ ranged from 0.88 to 0.93. The N1RMS values in the hippocampus sclerosis (HS) group were greater than that of the focal cortical dysplasia (FCD) IIa group (p < 0.001), independent of the distance between the recorded and stimulated sites. The sensitivity of localization was higher in the seizure-free group than in the non-seizure-free group (p = 0.036). CONCLUSIONS: This new method can be used to predict the SOZ localization in various focal epilepsy phenotypes. SIGNIFICANCE: This study proposed a machine-learning approach for localizing the SOZ. Moreover, we examined how clinical phenotypes impact large-scale abnormality of the epileptogenic networks.

Magnetic resonance-guided laser interstitial thermal therapy vs. open surgery for drug-resistant mesial temporal lobe epilepsy: a propensity score matched retrospective cohort study.

BACKGROUND: Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) and traditional open surgery (OS) are effective and safe options for patients with drug-resistant mesial temporal lobe epilepsy (DR-mTLE). However, their superiority in seizure control and preservation of functional abilities remains unclear. This study aimed to compare the surgical outcomes of MRgLITT and OS. MATERIALS AND METHODS: This multicenter retrospective cohort study included patients with DR-mTLE who underwent MRgLITT or OS at three centres between 2015 and 2023. The data on patient demographics, presurgical non-invasive evaluation, stereoelectroencephalography (SEEG) implantation, memory alteration, and seizure outcomes were collected. Propensity score matching (PSM) analysis was conducted for the comparison of seizure control and functional preservation between two surgical approaches. RESULTS: Of the 244 individuals who met the study criteria, 33 underwent MRgLITT and 211 OS. The median (interquartile range) age at seizure onset was 22.0 (13.0) and 12.3 (10.0) years in the MRgLITT and OS groups, respectively. The first PSM, based on demographic and non-invasive information, resulted in 26 matched pairs for the primary analysis. There were no significant differences in memory preservation ( P = 0.95) or surgical outcomes ( P = 0.96) between the groups. The second PSM, based on demographics and SEEG implantation, yielded 32 matched pairs for the sensitivity analysis, showing similar results. Subset analysis of early and late MRgLITT cases revealed no statistically significant differences in the proportion of patients with memory decline ( P = 0.42) or seizure control ( P = 1.00). Patients who underwent SEEG implantation were 96% less likely to achieve seizure freedom after MRgLITT ( P = 0.02). CONCLUSION: Minimally invasive MRgLITT is associated with memory preservation and seizure control, similar to traditional OS. MRgLITT is effective and safe for DR-mTLE and is relevant for future prospective randomized trials on dominant-side mTLE, providing practical implications for guiding neurosurgeons in the selection of surgical approaches.

Neural network mapping of gelastic behavior in children with hypothalamus hamartoma.

BACKGROUND: Hypothalamus hamartomas (HHs) are rare, congenital, tumor-like, and nonprogressive malformations resulting in drug-resistant epilepsy, mainly affecting children. Gelastic seizures (GS) are an early hallmark of epilepsy with HH. The aim of this study was to explore the disease progression and the underlying physiopathological mechanisms of pathological laughter in HH. METHODS: We obtained clinical information and metabolic images of 56 HH patients and utilized ictal semiology evaluation to stratify the specimens into GS-only, GS-plus, and no-GS subgroups and then applied contrasted trajectories inference (cTI) to calculate the pseudotime value and evaluate GS progression. Ordinal logistic regression was performed to identify neuroimaging-clinical predictors of GS, and then voxelwise lesion network-symptom mapping (LNSM) was applied to explore GS-associated brain regions. RESULTS: cTI inferred the specific metabolism trajectories of GS progression and revealed increased complexity from GS to other seizure types. This was further validated via actual disease duration (Pearson R = 0.532, P = 0.028). Male sex [odds ratio (OR) = 2.611, P = 0.013], low age at seizure onset (OR = 0.361, P = 0.005), high normalized HH metabolism (OR = - 1.971, P = 0.037) and severe seizure burden (OR = - 0.006, P = 0.032) were significant neuroimaging clinical predictors. LNSM revealed that the dysfunctional cortico-subcortico-cerebellar network of GS and the somatosensory cortex (S1) represented a negative correlation. CONCLUSIONS: This study sheds light on the clinical characteristics and progression of GS in children with HH. We identified distinct subtypes of GS and demonstrated the involvement of specific brain regions at the cortical-subcortical-cerebellar level. These valuable results contribute to our understanding of the neural correlates of GS.

Multimodal imaging-based diagnostic approach for MRI-negative posterior cortex epilepsy.

Background: Posterior cortex epilepsy (PCE) primarily comprises seizures originating from the occipital, parietal, and/or posterior edge of the temporal lobe. Electroclinical dissociation and subtle imaging representation render the diagnosis of PCE challenging. Improved methods for accurately identifying patients with PCE are necessary. Objectives: To develop a novel voxel-based image postprocessing method for better visual identification of the neuroimaging abnormalities associated with PCE. Design: Multicenter, retrospective study. Methods: Clinical and imaging features of 165 patients with PCE were retrospectively reviewed and collected from five epilepsy centers. A total of 37 patients (32.4% female, 20.2 ± 8.9 years old) with magnetic resonance imaging (MRI)-negative PCE were finally included for analysis. Image postprocessing features were calculated over a neighborhood for each voxel in the multimodality data. The postprocessed maps comprised structural deformation, hyperintense signal, and hypometabolism. Five raters from three different centers were blinded to the clinical diagnosis and determined the neuroimaging abnormalities in the postprocessed maps. Results: The average accuracy of correct identification was 55.7% (range from 43.2 to 62.2%) and correct lateralization was 74.1% (range from 64.9 to 81.1%). The Cronbach's alpha was 0.766 for the correct identification and 0.683 for the correct lateralization with similar results of the interclass correlation coefficient, thus indicating reliable agreement between the raters. Conclusion: The image postprocessing method developed in this study can potentially improve the visual detection of MRI-negative PCE. The technique could lead to an increase in the number of patients with PCE who could benefit from the surgery.

Associated factors with stimulation induced seizures and the relevance with surgical outcomes.

OBJECTIVE: To analyze the associated factors with stimulation-induced seizures (SIS) and the relevant factors in predicting surgical outcomes. METHODS: We analyzed 80 consecutive epilepsy patients explored by stereo-electroencephalography with routine electrical stimulation mapping (ESM). If seizures induced by ESM, patients were classified as SIS-positive (SIS-P); otherwise, SIS-negative (SIS-N). Patients received radical surgery were further classified as favorable (Engel I) and unfavorable (Engel II-IV) groups. RESULTS: Of the 80 patients included, we identified 44 (55.0%) and 36(45.0%) patients in the SIS-P and SIS-N groups, respectively. Multivariate analysis revealed that the seizure onset pattern (SOP) of preceding repetitive epileptiform discharges following LVFA (PRED→LVFA) (OR 3.319, 95% CI 1.200-9.183, P = 0.021) and pathology of focal cortical dysplasia (FCD) type II (OR 3.943, 95% CI 1.093-14.226, P = 0.036) were independent factors influencing whether the electrical stimulation can induce a seizure. Among the patients received radical surgery, there were 55 and 15 patients in the favorable and unfavorable groups separately. Multivariate analysis revealed that the SOP of PRED→LVFA induced seizures by stimulation (OR 11.409, 95% CI 1.182-110.161, P = 0.035) and bilateral implantation (OR 0.048, 95% CI 0.005-0.497, P = 0.011) were independent factors affecting surgical outcomes. The previous epilepsy surgery had a trend to be a negative factor with SIS (OR 0.156, 95% CI 0.028-0.880, P = 0.035) and surgical outcomes (OR 0.253, 95% CI 0.053-1.219, P = 0.087). CONCLUSION: ESM is a highly valuable method for localizing the seizure onset zone. The SOP of PRED→LVFA and FCD type II were associated with elicitation of SIS by ESM, whereas a previous epilepsy surgery showed a negative association. Furthermore, the SOP of PRED→LVFA together with SIS in the same patient predicted favorable surgical outcomes, whereas bilateral electrode implantation predicted unfavorable outcomes.

Efficient volume-based localization and automatic labeling of intracranial depth electrodes.

Background: The accurate localization and anatomical labeling of intracranial depth electrodes are crucial for stereoelectroencephalography (SEEG) recordings and the interpretation of results in patients with epilepsy. The laborious electrode localization procedure requires an efficient and easy-to-use pipeline. Thus, we developed a useful tool, which we called the depth electrode localizer (DELLO), to automatically identify and label depth electrode contacts with ease. Methods: The DELLO is an open-source package developed in MATLAB (MathWorks). It was specifically fine-tuned to expedite the localization of depth electrodes. The basic procedures include preoperative magnetic resonance imaging (MRI) and postoperative computed tomography coregistration, intensity threshold electrode spatial sampling, the hierarchical clustering of electrode samples, and gray-matter and automatic anatomical labeling (AAL). The DELLO also has a graphical user interface (GUI) that can be used to review the results. The only manual intervention procedures are the identification of the target (tip) and entry point of each electrode and the naming of the clustered electrode contact groups, which generally take ~5 min per case. The coordinates of each contact were recorded in individual spaces and were also transformed in standard space by applying a volume-based deformation field. To validate the performance of the current method, 7 patients with epilepsy were retrospectively included in the analysis. Results: A total of 80 depth electrodes, including 1,030 contacts from the 7 patients with epilepsy, were localized. All the procedures functioned well, and the entire process was robust and intuitive. Among the 1,030 contacts, 746 (72.43%) were labeled as inside the gray matter. The gray-matter and AAL accuracy rates were 95.83% and 90.78%, respectively, over all contacts. Conclusions: The DELLO is an integrated tool that was designed to semi-automatically localize and label intracranial depth electrodes. It is open source and freely available. Given its high accuracy and efficiency, the DELLO could facilitate SEEG interpretation and be used in SEEG-based cognitive neuroscience studies.

Interictal HFO and FDG-PET correlation predicts surgical outcome following SEEG.

OBJECTIVE: This study aimed to investigate the quantitative relationship between interictal 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) and interictal high-frequency oscillations (HFOs) from stereo-electroencephalography (SEEG) recordings in patients with refractory epilepsy. METHODS: We retrospectively included 32 patients. FDG-PET data were quantified through statistical parametric mapping (SPM) t test modeling with normal controls. Interictal SEEG segments with four, 10-min segments were selected randomly. HFO detection and classification procedures were automatically performed. Channel-based HFOs separating ripple (80-250 Hz) and fast ripple (FR; 250-500 Hz) counts were correlated with the surrounding metabolism T score at the individual and group level, respectively. The association was further validated across anatomic seizure origins and sleep vs wake states. We built a joint feature FR × T reflecting the FR and hypometabolism concordance to predict surgical outcomes in 28 patients who underwent surgery. RESULTS: We found a negative correlation between interictal FDG-PET and HFOs through the linear mixed-effects model (R2  = .346 and .457 for ripples and FRs, respectively, p < .001); these correlations were generalizable to different epileptogenic-zone lobar localizations and vigilance states. The FR × T inside the resection volume could be used as a predictor for surgical outcomes with an area under the curve of 0.81. SIGNIFICANCE: The degree of hypometabolism is associated with HFO generation rate, especially for FRs. This relationship would be meaningful for selection of SEEG candidates and for optimizing SEEG scheme planning. The concordance between FRs and hypometabolism inside the resection volume could provide prognostic information regarding surgical outcome.

Magnetic Resonance-Guided Laser Interstitial Thermal Therapy for Hypothalamic Hamartoma: Surgical Approach and Treatment Outcomes.

Hypothalamic hamartoma (HH) is a rare lesion consisting of normal neurons and neuroglia arranged in an abnormal pattern which usually causes gelastic seizures (GS). Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) has been developed as a minimally invasive approach to treat HH and gradually become a first-line treatment. In total, this study enrolled 47 consecutive HH patients that underwent one round of ablation. Patients were followed for at least one year. Patients' medical records and surgical information were carefully reviewed, and univariate analyses were performed. Of the treated patients, 72.3% remained GS-free in this study, with an overall Engel class I rate of 68.1%. Long-term postoperative complications occurred in six patients. Factors associated with GS prognosis included Delalande classification (p = 0.033), HH volume (p = 0.01), and the ablation rate of the HH body (p = 0.035). The disconnection rate was 0.73 ± 0.14 in the Engel class Ia group as compared to 0.62 ± 0.13 in the Engel Ib-Engel IV group (p = 0.046). MRgLITT represents a safe and effective surgical procedure. Patients with larger or Delalande type IV HH may require multiple rounds of ablation. In addition to assessing the degree of disconnection, ablation volume should also be carefully considered for patients undergoing this procedure.

Is intracranial electroencephalography mandatory for MRI-negative neocortical epilepsy surgery?

OBJECTIVE: MRI-negative focal epilepsy is one of the most challenging cases in surgical epilepsy treatment. Many epilepsy centers recommend intracranial electroencephalography (EEG) for MRI-negative cases, especially neocortical epilepsy. This retrospective study aimed to explore whether intracranial monitoring is mandatory in MRI-negative neocortical epilepsy surgery and the factors that significantly influence the decision on whether to perform intracranial recording. METHODS: In this study, consecutive surgical patients with focal MRI-negative neocortical epilepsy were recruited. All patients underwent routine preoperative evaluation according to the dedicated protocol of the authors' epilepsy center to determine the treatment strategy. Patients were divided into two groups according to the surgical strategy, i.e., a direct group and a stereo-EEG (SEEG)-guided group. History of epilepsy, seizure frequency, interictal and ictal EEG data, PET data, PET/MRI coregistration data, neuropathological findings, and surgical outcomes were compared between the two groups. Multivariate analysis was performed to identify factors influencing the decision to perform SEEG monitoring. RESULTS: Sixty-four patients were included in this study, 19 and 45 of whom underwent direct and SEEG-guided cortical resection, respectively. At an average follow-up of 3.9 years postoperatively, 56 patients (87.5%) had Engel class I results without permanent neurological deficits. Surgical outcomes were not significantly different between the direct and SEEG-guided groups (94.7% vs 84.4%). PET hypometabolic abnormalities were detected in all patients. There were significant differences between the two groups in the extent of hypometabolism (focal vs nonfocal, p < 0.01) and pathological subtype (focal cortical dysplasia type II vs others, p = 0.03). Multivariate analysis revealed that the extent of hypometabolism (OR 0.01, 95% CI 0.00-0.15; p = 0.001) was the only independent factor affecting the treatment strategy. CONCLUSIONS: Careful selection of patients with MRI-negative neocortical epilepsy may yield favorable outcomes after direct cortical resection without intracranial monitoring. PET/MRI coregistration plays an essential role in the preoperative evaluation and subsequent resection of these patients. Intracranial monitoring is not a mandatory requirement for surgery if the focal hypometabolic areas are consistent with the findings of semiology and scalp EEG.

Anatomical features decide the atypical seizure manifestation of parahypothalamic hamartomas.

Background: The intrahypothalamic phenotype of hypothalamic hamartomas (HH) is associated with epilepsy, and the parahypothalamic phenotype usually leads to central precocious puberty but not neurological comorbidities or seizures. No study has confirmed the pathological role of parahypothalamic hamartomas in epileptogenesis, and the underlying mechanism is yet to be elucidated. Objective: We aimed to investigate whether parahypothalamic hamartomas are intrinsically epileptogenic and elucidate the underlying pathway of epileptogenesis. Methods: We reviewed 92 patients with HH-related epilepsy, categorized them by the classification system of Delalande and Fohlen, and further classified Type I (corresponding to parahypothalamic HH) into the following three groups based on the relationship between the lesion and mammillary bodies (MB): entirely invaded (Group 1), partially connected (Group 2), and not connected at all (Group 3). We examined different anatomical features with their relationship to clinical manifestations. Stereoelectroencephalography (SEEG) was implanted in both HH and extra-HH cortices in different groups to identify the epileptogenic zone. Corticocortical evoked potentials (CCEPs) were also used to determine the pathological correlation among different regions to determine the related epileptogenic network. Results: A total of 13 patients presented with parahypothalamic HH and 10 (76.9%) presented with non-GS only, with late-onset age and normal cognitive development, which is different from classical clinical features. SEEG showed that HH is intrinsically epileptogenic in MB-involved parahypothalamic groups. No statistical difference was found in onset age (p = 0.213), and lesions horizontally oriented from the tuber cinereum without connection to MB were not involved in seizure genesis. CCEP indicated a pathological connection among HH, middle cingulate cortex, and insular cortex. Conclusion: The parahypothalamic HH can also cause epilepsy and is different from classic HH-related seizures, by non-GS only with the late-onset age and normal cognitive development. MB is proven to be related to non-GS by the mamillo-cingulate-cortex pathway.

Metabolism and Intracranial Epileptogenicity in Temporal Lobe Long-Term Epilepsy-Associated Tumor.

Brain tumors are common in epilepsy surgery and frequently occur in the temporal lobe, but the optimal surgical strategies to remove the tumor and epileptogenic zone remain controversial. We aim at illustrating the positron emission tomography (PET) metabolism and the stereoelectroencephalography (SEEG) epileptogenicity of temporal lobe long-term epilepsy-associated tumors (LEAT). In this study, 70 patients and 25 healthy controls were included. Our analysis leveraged group-level analysis to reveal the whole-brain metabolic pattern of temporal lobe LEATs. The SEEG-based epileptogenicity mapping was performed to verify the PET findings in the epileptic network. Compared to controls, patients with a temporal lobe LEAT showed a more widespread epileptic network based on 18FDG-PET in patients with a mesial temporal lobe LEAT than in those with a lateral temporal lobe LEAT. The significant brain clusters mainly involved the paracentral lobule (ANOVA F = 9.731, p < 0.001), caudate nucleus (ANOVA F = 20.749, p < 0.001), putamen (Kruskal−Wallis H = 19.258, p < 0.001), and thalamus (ANOVA F = 4.754, p = 0.011). Subgroup analysis and SEEG-based epileptogenicity mapping are similar to the metabolic pattern. Our findings demonstrate the metabolic and electrophysiological organization of the temporal lobe LEAT epileptic network, which may assist in a patient-specific surgical strategy.

Automated Detection and Surgical Planning for Focal Cortical Dysplasia with Multicenter Validation.

BACKGROUND: In patients with surgically amenable focal cortical dysplasia (FCD), subtle neuroimaging representation and the risk of open surgery lead to gaps in surgical treatment and delays in surgery. OBJECTIVE: To construct an integrated platform that can accurately detect FCD and automatically establish trajectory planning for magnetic resonance-guided laser interstitial thermal therapy. METHODS: This multicenter study included retrospective patients to train the automated detection model, prospective patients for model evaluation, and an additional cohort for construction of the automated trajectory planning algorithm. For automated detection, we evaluated the performance and generalization of the conventional neural network in different multicenter cohorts. For automated trajectory planning, feasibility/noninferiority and safety score were calculated to evaluate the clinical value. RESULTS: Of the 260 patients screened for eligibility, 202 were finally included. Eighty-eight patients were selected for conventional neural network training, 88 for generalizability testing, and 26 for the establishment of an automated trajectory planning algorithm. The model trained using preprocessed and multimodal neuroimaging displayed the best performance in diagnosing FCD (figure of merit = 0.827 and accuracy range = 75.0%-91.7% across centers). None of the clinical variables had a significant effect on prediction performance. Moreover, the automated trajectory was feasible and noninferior to the manual trajectory ( χ2 = 3.540, P = .060) and significantly safer (overall: test statistic = 30.423, P < .001). CONCLUSION: The integrated platform validated based on multicenter, prospective cohorts exhibited advantages of easy implementation, high performance, and generalizability, thereby indicating its potential in the diagnosis and minimally invasive treatment of FCD.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

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.

Whole-brain metabolic pattern analysis in patients with anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis.

BACKGROUND AND PURPOSE: Faciobrachial dystonic seizures (FBDS) and hyponatremia are the distinct clinical features of autoimmune encephalitis (AE) caused by antibodies against leucine-rich glioma-inactivated 1 (LGI1). The present study aims to explore the pathophysiological patterns and neural mechanisms underlying these symptoms. METHODS: We included 30 patients with anti-LGI1 AE and 30 controls from a retrospective observational cohort. Whole-brain metabolic pattern analysis was performed to assess the pathological network of anti-LGI1 AE, as well as the symptom networks associated with FBDS. Logistic regression was applied to explore independent predictors of FBDS. Finally, we used a multiple regression model to investigate the hyponatremia-associated brain network and its effect on serum sodium levels. RESULTS: The pathological network of anti-LGI1 AE involved hypermetabolism in the cerebellum, subcortical structures and Rolandic area, as well as hypometabolism in the medial prefrontal cortex. The symptom network of FBDS included hypometabolism in the cerebellum and Rolandic area (pFDR <0.05). Hypometabolism in the cerebellum was an independent predictor of FBDS (p < 0.001). Hyponatremia-associated network highlighted a negative effect on the caudate nucleus, frontal and temporal white matter. The metabolism of the hypothalamus was negatively associated with (Pearson's R = -0.180, p = 0.342), while not the independent predictor for serum sodium level (path c' = -7.238, 95% confidence interval = -30.947 to 16.472). CONCLUSIONS: Our results provide insights into the whole-brain metabolic patterns of patients with anti-LGI1 AE, including the symptom network associated with FBDS and the hyponatremia-associated brain network. The findings help us to understand the neural mechanisms underlying anti-LGI1 AE and to evaluate the progress of this disease.

Neuroimaging gradient alterations and epileptogenic prediction in focal cortical dysplasia IIIa.

Objective.Focal cortical dysplasia type IIIa (FCD IIIa) is a highly prevalent temporal lobe epilepsy but the seizure outcomes are not satisfactory after epilepsy surgery. Hence, quantitative neuroimaging, epileptogenic alterations, as well as their values in guiding surgery are worth exploring.Approach.We examined 69 patients with pathologically verified FCD IIIa using multimodal neuroimaging and stereoelectroencephalography (SEEG). Among them, 18 received postoperative imaging which showed the extent of surgical resection and 9 underwent SEEG implantation. We also explored neuroimaging gradient alterations along with the distance to the temporal pole. Subsequently, the machine learning regression model was employed to predict whole-brain epileptogenicity. Lastly, the correlation between neuroimaging or epileptogenicity and surgical cavities was assessed.Main results.FCD IIIa displayed neuroimaging gradient alterations on the temporal neocortex, morphology-signal intensity decoupling, low similarity of intra-morphological features and high similarity of intra-signal intensity features. The support vector regression model was successfully applied at the whole-brain level to calculate the continuous epileptogenic value at each vertex (mean-squared error = 13.8 ± 9.8).Significance.Our study investigated the neuroimaging gradient alterations and epileptogenicity of FCD IIIa, along with their potential values in guiding suitable resection range and in predicting postoperative seizure outcomes. The conclusions from this study may facilitate an accurate presurgical examination of FCD IIIa. However, further investigation including a larger cohort is necessary to confirm the results.