Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes (‘sources’) and the inhibited nodes themselves (‘sinks’). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians’ predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone.

The purpose of this study was to prospectively investigate the agreement between the epileptogenic zone(s) (EZ) localization by resting-state functional magnetic resonance imaging (rs-fMRI) and the seizure onset zone(s) (SOZ) identified by intracranial electroencephalogram (ic-EEG) using novel differentiating and ranking criteria of rs-fMRI abnormal independent components (ICs) in a large consecutive heterogeneous pediatric intractable epilepsy population without an a priori alternate modality informing EZ localization or prior declaration of total SOZ number. The EZ determination criteria were developed by using independent component analysis (ICA) on rs-fMRI in an initial cohort of 350 pediatric patients evaluated for epilepsy surgery over a 3-year period. Subsequently, these rs-fMRI EZ criteria were applied prospectively to an evaluation cohort of 40 patients who underwent ic-EEG for SOZ identification. Thirty-seven of these patients had surgical resection/disconnection of the area believed to be the primary source of seizures. One-year seizure frequency rate was collected postoperatively. Among the total 40 patients evaluated, agreement between rs-fMRI EZ and ic-EEG SOZ was 90% (36/40; 95% confidence interval [CI], 0.76–0.97). Of the 37 patients who had surgical destruction of the area believed to be the primary source of seizures, 27 (73%) rs-fMRI EZ could be classified as true positives, 7 (18%) false positives, and 2 (5%) false negatives. Sensitivity of rs-fMRI EZ was 93% (95% CI 78–98%) with a positive predictive value of 79% (95% CI, 63–89%). In those with cryptogenic localization-related epilepsy, agreement between rs-fMRI EZ and ic-EEG SOZ was 89% (8/9; 95% CI, 0.52–99), with no statistically significant difference between the agreement in the cryptogenic and symptomatic localization-related epilepsy subgroups. Two children with negative ic-EEG had removal of the rs-fMRI EZ and were seizure free 1 year postoperatively. Of the 33 patients where at least 1 rs-fMRI EZ agreed with the ic-EEG SOZ, 24% had at least 1 additional rs-fMRI EZ outside the resection area. Of these patients with un-resected rs-fMRI EZ, 75% continued to have seizures 1 year later. Conversely, among 75% of patients in whom rs-fMRI agreed with ic-EEG SOZ and had no anatomically separate rs-fMRI EZ, only 24% continued to have seizures 1 year later. This relationship between extraneous rs-fMRI EZ and seizure outcome was statistically significant ( p = 0.01). rs-fMRI EZ surgical destruction showed significant association with postoperative seizure outcome. The pediatric population with intractable epilepsy studied prospectively provides evidence for use of resting-state ICA ranking criteria, to identify rs-fMRI EZ, as developed by the lead author (V.L.B.). This is a high yield test in this population, because no seizure nor particular interictal epilepiform activity needs to occur during the study. Thus, rs-fMRI EZ detected by this technique are potentially informative for epilepsy surgery evaluation and planning in this population. Independent of other brain function testing modalities, such as simultaneous EEG-fMRI or electrical source imaging, contextual ranking of abnormal ICs of rs-fMRI localized EZs correlated with the gold standard of SOZ localization, ic-EEG, across the broad range of pediatric epilepsy surgery candidates, including those with cryptogenic epilepsy.

Objective: Postoperative resting‐state functional magnetic resonance imaging (MRI) in children with intractable epilepsy has not been quantified in relation to seizure outcome. Therefore, its value as a biomarker for epileptogenic pathology is not well understood.Methods: In a sample of children with intractable epilepsy who underwent prospective resting‐state seizure onset zone (SOZ)‐targeted epilepsy surgery, postoperative resting‐state functional MRI (rs‐fMRI) was performed 6 to 12 months later. Graded normalization of the postoperative resting‐state SOZ was compared to seizure outcomes, patient, surgery, and anatomical MRI characteristics.Results: A total of 64 cases were evaluated. Network‐targeted surgery, followed by postoperative rs‐fMRI normalization was significantly (p < 0.001) correlated with seizure reduction, with a Spearman rank correlation coefficient of 0.83. Of 39 cases with postoperative rs‐fMRI SOZ normalization, 38 (97%) became completely seizure free. In contrast, of the 25 cases without complete rs‐fMRI SOZ normalization, only 3 (5%) became seizure free. The accuracy of rs‐fMRI as a biomarker predicting seizure freedom is 94%, with 96% sensitivity and 93% specificity.Interpretation: Among seizure localization techniques in pediatric epilepsy, network‐targeted surgery, followed by postoperative rs‐fMRI normalization, has high correlation with seizure freedom. This study shows that rs‐fMRI SOZ can be used as a biomarker of the epileptogenic zone, and postoperative rs‐fMRI normalization is a biomarker for SOZ quiescence. ANN NEUROL 2019;86:344–356

Summary: Objective: The purpose of this study is to investigate the outcomes of epilepsy surgery targeting the subcentimeter‐sized resting state functional magnetic resonance imaging (rs‐fMRI) epileptogenic onset zone (EZ) in hypothalamic hamartoma (HH).Methods: Fifty‐one children with HH‐related intractable epilepsy received anatomical MRI‐guided stereotactic laser ablation (SLA) procedures. Fifteen of these children were control subjects (CS) not guided by rs‐fMRI. Thirty‐six had been preoperatively guided by rs‐fMRI (RS) to determine EZs, which were subsequently targeted by SLA. The primary outcome measure for the study was a predetermined goal of 30% reduction in seizure frequency and improvement in class I Engel outcomes 1 year postoperatively. Quantitative and qualitative volumetric analyses of total HH and ablated tissue were also assessed.Results: In the RS group, the EZ target within the HH was ablated with high accuracy (>87.5% of target ablated in 83% of subjects). There was no difference between the groups in percentage of ablated hamartoma volume (P = 0.137). Overall seizure reduction was higher in the rs‐fMRI group: 85% RS versus 49% CS (P = 0.0006, adjusted). The Engel Epilepsy Surgery Outcome Scale demonstrated significant differences in those with freedom from disabling seizures (class I), 92% RS versus 47% CS, a 45% improvement (P = 0.001). Compared to prior studies, there was improvement in class I outcomes (92% vs 76%‐81%). No postoperative morbidity or mortality occurred.Significance: For the first time, surgical SLA targeting of subcentimeter‐sized EZs, located by rs‐fMRI, guided surgery for intractable epilepsy. Our outcomes demonstrated the highest seizure freedom rate without surgical complications and are a significant improvement over prior reports. The approach improved freedom from seizures by 45% compared to conventional ablation, regardless of hamartoma size or anatomical classification. This technique showed the same or reduced morbidity (0%) compared to recent non–rs‐fMRI‐guided SLA studies with as high as 20% permanent significant morbidity.

OBJECTIVE: The authors’ goal was to prospectively quantify the impact of resting-state functional MRI (rs-fMRI) on pediatric epilepsy surgery planning.METHODS: Fifty-one consecutive patients (3 months to 20 years old) with intractable epilepsy underwent rs-fMRI for presurgical evaluation. The team reviewed the following available diagnostic data: video-electroencephalography (n = 51), structural MRI (n = 51), FDG-PET (n = 42), magnetoencephalography (n = 5), and neuropsychological testing (n = 51) results to formulate an initial surgery plan blinded to the rs-fMRI findings. Subsequent to this discussion, the connectivity results were revealed and final recommendations were established. Changes between pre– and post–rs-fMRI treatment plans were determined, and changes in surgery recommendation were compared using McNemar’s test.RESULTS: Resting-state fMRI was successfully performed in 50 (98%) of 51 cases and changed the seizure onset zone localization in 44 (88%) of 50 patients. The connectivity results prompted 6 additional studies, eliminated the ordering of 11 further diagnostic studies, and changed the intracranial monitoring plan in 10 cases. The connectivity results significantly altered surgery planning with the addition of 13 surgeries, but it did not eliminate planned surgeries (p = 0.003). Among the 38 epilepsy surgeries performed, the final surgical approach changed due to rs-fMRI findings in 22 cases (58%), including 8 (28%) of 29 in which extraoperative direct electrical stimulation mapping was averted.CONCLUSIONS: This study demonstrates the impact of rs-fMRI connectivity results on the decision-making for pediatric epilepsy surgery by providing new information about the location of eloquent cortex and the seizure onset zone. Additionally, connectivity results may increase the proportion of patients considered eligible for surgery while optimizing the need for further testing.

An accurate and comprehensive test of integrated brain network function is needed for neonates during the acute brain injury period to inform on morbidity. This retrospective cohort study assessed whether integrated brain network function acquired by resting state functional MRI during the acute period in neonates with brain injury, is associated with acute exam, neonatal mortality, and 6-month outcomes. Study subjects included 40 consecutive neonates with resting state functional MRI acquired within 31 days after suspected brain insult from March 2018 to July 2019 at Phoenix Children’s Hospital. Acute-period exam and test results were assigned ordinal scores based on severity as documented by respective treating specialists. Analyses (Fisher exact, Wilcoxon-rank sum test, ordinal/multinomial logistic regression) examined association of resting state networks with demographics, presentation, neurological exam, electroencephalogram, anatomical MRI, magnetic resonance spectroscopy, passive task functional MRI, and outcomes of discharge condition, outpatient development, motor tone, seizure, and mortality. Subjects had a mean (standard deviation) gestational age of 37.8 (2.6) weeks, a majority were male (63%), with a diagnosis of hypoxic ischemic encephalopathy (68%). Findings at birth included mild distress (48%), moderately abnormal neurological exam (33%), and consciousness characterized as awake but irritable (40%). Significant associations after multiple testing corrections were detected for resting state networks: basal ganglia with outpatient developmental delay (odds ratio [OR], 14.5; 99.4% confidence interval [CI], 2.00–105; P < .001) and motor tone/weakness (OR, 9.98; 99.4% CI, 1.72–57.9; P < .001); language/frontoparietal network with discharge condition (OR, 5.13; 99.4% CI, 1.22–21.5; P = .002) and outpatient developmental delay (OR, 4.77; 99.4% CI, 1.21–18.7; P=.002); default mode network with discharge condition (OR, 3.72; 99.4% CI, 1.01–13.78; P=.006) and neurological exam (P = .002 (FE); OR, 11.8; 99.4% CI, 0.73–191; P = .01 (OLR)); and seizure onset zone with motor tone/weakness (OR, 3.31; 99.4% CI, 1.08–10.1; P=.003). Resting state networks were not detected in three neonates, who died prior to discharge. This study provides level 3 evidence (OCEBM Levels of Evidence Working Group) demonstrating that in neonatal acute brain injury, the degree of abnormality of resting state networks is associated with acute exam and outcomes. Total lack of brain network detection was only found in patients who did not survive.