Correlating Resting-State Functional Magnetic Resonance Imaging Connectivity by Independent Component Analysis-Based Epileptogenic Zones with Intracranial Electroencephalogram Localized Seizure Onset Zones and Surgical Outcomes in Prospective Pediatric Intractable Epilepsy Study

Abstract

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 populatio...

Network‐targeted approach and postoperative resting‐state functional magnetic resonance imaging are associated with seizure outcome

“…8 In this study, we demonstrated that 75% of Engel I seizure outcomes at 2-year follow-up were achieved in those with rs-fMRI SOZ-targeted destruction. 8 In this study, we demonstrated that 75% of Engel I seizure outcomes at 2-year follow-up were achieved in those with rs-fMRI SOZ-targeted destruction.…”

“…The baseline and postoperative MRIs were obtained under standard clinical conditions as described in Boerwinkle et al 8 Baseline data were collected on patient demographics, treating neurologist's examination, developmental history as reported by family, and epileptologist's reported patient epilepsy characteristics.…”

“…8,23 Each brain network oscillates in its oxygen concentration independently from the other brain networks, which makes major brain networks distinguishable from each other. Independent component analysis (ICA) is a mathematical process that analyzes the raw rs-fMRI signal and separates it into detected oscillating subsignals.…”

“…Independent component analysis (ICA) is a mathematical process that analyzes the raw rs-fMRI signal and separates it into detected oscillating subsignals. 8 The preprocessed BOLD sequences underwent multisession temporal concatenation. Sources of noise derive from the MRI scanner, respiration, cardiovascular pulsation, and cerebrospinal fluid (CSF) movement.…”

“…Remove signal due to noise. 8 Normal RSNs have slow frequency (<0.073Hz 25,26 ) and regular oscillation rate (lack interruption from spikes such that change in period is no greater than one-half the period value between cycles). 23 2.…”