scholarly journals Epidemic models characterize seizure propagation and the effects of epilepsy surgery in individualized brain networks based on MEG and invasive EEG recordings

2021 ◽  
Author(s):  
Ana P Millan ◽  
Elisabeth CW van Straaten ◽  
Cornelis J Stam ◽  
Ida A Nissen ◽  
Sander Idema ◽  
...  
Keyword(s):  
Epilepsy Surgery ◽  
Brain Networks ◽  
Patient Specific ◽  
Model Parameters ◽  
Seizure Freedom ◽  
Seed Region ◽  
Epidemic Spreading ◽  
Surgery Outcome ◽  
Seizure Propagation ◽  
Resection Area

Background Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients. However, seizure-freedom is currently achieved in only 2/3 of the patients after surgery. In this study we have developed an individualized computational model based on functional brain networks to explore seizure propagation and the efficacy of different virtual resections. Eventually, the goal is to obtain individualized models to optimize resection strategy and outcome. Methods We have modelled seizure propagation as an epidemic process using the susceptible-infected (SI) model on individual functional networks derived from presurgical MEG. We included 10 patients who had received epilepsy surgery and for whom the surgery outcome at least one year after surgery was known. The model parameters were tuned in order to reproduce the patient-specific seizure propagation patterns as recorded with invasive EEG. We defined a personalized search algorithm that combined structural and dynamical information to find resections that maximally decreased seizure propagation for a given resection size. The optimal resection for each patient was defined as the smallest resection leading to at least a $90\%$ reduction in seizure propagation. Results The individualized model reproduced the basic aspects of seizure propagation for 9 out of 10 patients when using the resection area as the origin of epidemic spreading, and for 10 out of 10 patients with an alternative definition of the seed region. We found that, for 7 patients, the optimal resection was smaller than the resection area, and for 4 patients we also found that a resection smaller than the resection area could lead to a 100% decrease in propagation. Moreover, for two cases these alternative resections included nodes outside the resection area. Conclusion Epidemic spreading models fitted with patient specific data can capture the fundamental aspects of clinically observed seizure propagation, and can be used to test virtual resections in silico. Combined with optimization algorithms, smaller or alternative resection strategies, that are individually targeted for each patient, can be determined with the ultimate goal to improve surgery outcome.

scholarly journals Optimization of epilepsy surgery through virtual resections on individual structural brain networks

2021 ◽  
Author(s):  
Ida A. Nissen ◽  
Cornelis J. Stam ◽  
Elisabeth C.W. Straaten ◽  
Ana P. Millán ◽  
Linda Douw ◽  
...  
Keyword(s):  
Epilepsy Surgery ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Sir Model ◽  
Correct Identification ◽  
Epileptogenic Zone ◽  
Maximal Effect ◽  
Seizure Propagation ◽  
The Impact ◽  
Structural Brain

Abstract BackgroundThe success of epilepsy surgery in patients with refractory epilepsy depends upon correct identification of the epileptogenic zone (EZ) and an optimal choice of the resection area. In this study we developed individualized computational models based upon structural brain networks to explore the impact of different virtual resections on the propagation of seizures.MethodsThe propagation of seizures was modelled as an epidemic process (susceptible-infected-recovered (SIR) model) on individual structural networks derived from presurgical diffusion tensor imaging (DTI) in 19 patients. The candidate connections for the virtual resection were all connections from the clinically hypothesized EZ, from which the seizures were modelled to start, to other brain areas. As a computationally feasible surrogate for the SIR model, we also removed the connections that maximally reduced the Eigenvector Centrality (EC) (large values indicate network hubs) of the hypothesized EZ, with a large reduction meaning a large effect. The optimal combination of connections to be removed for a maximal effect were found using simulated annealing. For comparison, the same number of connections were removed randomly, or based on measures that quantify the importance of a node or connection within the network.ResultsWe found that 90% of the effect (defined as reduction of EC of the hypothesized EZ) could already be obtained by removing substantially less than 90% of the connections. Thus, a smaller, optimized, virtual resection achieved almost the same effect as the actual surgery yet at a considerably smaller cost, sparing on average 27.49% (standard deviation: 4.65%) of the connections. Furthermore, the maximally effective connections linked the hypothesized EZ to hubs. Finally, the optimized resection was more effective than random removal of the same number of connections, and equally or more effective than removal based on structural network characteristics.ConclusionThe approach of using reduced EC as a surrogate for simulating seizure propagation can suggest more restrictive resection strategies, whilst obtaining an almost optimal effect on reducing seizure propagation, by taking into account the unique topology of individual structural brain networks of patients.

scholarly journals Optimization of epilepsy surgery through virtual resections on individual structural brain networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ida A. Nissen ◽  
Ana P. Millán ◽  
Cornelis J. Stam ◽  
Elisabeth C. W. van Straaten ◽  
Linda Douw ◽  
...  
Keyword(s):  
Epilepsy Surgery ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Sir Model ◽  
Correct Identification ◽  
Epileptogenic Zone ◽  
Maximal Effect ◽  
Seizure Propagation ◽  
The Impact ◽  
Structural Brain

AbstractThe success of epilepsy surgery in patients with refractory epilepsy depends upon correct identification of the epileptogenic zone (EZ) and an optimal choice of the resection area. In this study we developed individualized computational models based upon structural brain networks to explore the impact of different virtual resections on the propagation of seizures. The propagation of seizures was modelled as an epidemic process [susceptible-infected-recovered (SIR) model] on individual structural networks derived from presurgical diffusion tensor imaging in 19 patients. The candidate connections for the virtual resection were all connections from the clinically hypothesized EZ, from which the seizures were modelled to start, to other brain areas. As a computationally feasible surrogate for the SIR model, we also removed the connections that maximally reduced the eigenvector centrality (EC) (large values indicate network hubs) of the hypothesized EZ, with a large reduction meaning a large effect. The optimal combination of connections to be removed for a maximal effect were found using simulated annealing. For comparison, the same number of connections were removed randomly, or based on measures that quantify the importance of a node or connection within the network. We found that 90% of the effect (defined as reduction of EC of the hypothesized EZ) could already be obtained by removing substantially less than 90% of the connections. Thus, a smaller, optimized, virtual resection achieved almost the same effect as the actual surgery yet at a considerably smaller cost, sparing on average 27.49% (standard deviation: 4.65%) of the connections. Furthermore, the maximally effective connections linked the hypothesized EZ to hubs. Finally, the optimized resection was equally or more effective than removal based on structural network characteristics both regarding reducing the EC of the hypothesized EZ and seizure spreading. The approach of using reduced EC as a surrogate for simulating seizure propagation can suggest more restrictive resection strategies, whilst obtaining an almost optimal effect on reducing seizure propagation, by taking into account the unique topology of individual structural brain networks of patients.

Preoperative Epilepsy Network Distribution Correlates With Seizure Recurrence Following Epilepsy Surgery

Neurosurgery ◽  
2019 ◽  
Vol 66 (Supplement_1) ◽  
Author(s):  
Long Di ◽  
Elliot G Neal ◽  
Stephanie Maciver ◽  
Fernando L Vale
Keyword(s):  
Temporal Lobe ◽  
Epilepsy Surgery ◽  
Surgical Outcome ◽  
Demographic Data ◽  
Brain Network ◽  
Patient Specific ◽  
Seizure Freedom ◽  
Seizure Recurrence ◽  
Postoperative Seizure ◽  
Epileptic Networks

Abstract INTRODUCTION Surgery remains an essential option for the treatment of medically intractable temporal lobe epilepsy. However, only 66% of patients achieve postoperative seizure freedom, perhaps attributable to an incomplete understanding of brain network alterations in surgical candidates. Here, we present a novel network modeling algorithm that may be used to identify key characteristics of epileptic networks correlated with improved surgical outcome. METHODS Twenty-nine patients were prospectively included, and relevant demographic information was attained. Resting-state functional magnetic resonance imaging (MRI) and electroencephalography (EEG) data were recorded and preprocessed. Using our novel algorithm, patient-specific epileptic networks were mapped preoperatively and geographic spread was quantified. Global functional connectivity was also determined using a volumetric functional atlas. Key demographic data and features of epileptic networks were then correlated with surgical outcome using Pearson's product-moment correlation. RESULTS At an average follow-up of 19 mo, 20/29 (69%) patients were seizure-free. Higher rates of seizure recurrence correlated with the localization of the epilepsy network to either temporal lobe (R = –0.415, P = .039), with the stronger correlation found with the localization to the contralateral temporal lobe (R = –0.566, P = .003). When the volumetric functional atlas connectivity was measured, increased connectivity globally was correlated with seizure recurrence (R = –0.541, P = .006). Seizure recurrence also correlated with greater atlas-based connectivity within the contralateral hemisphere (R = –0.390, P = .049). CONCLUSION Network localization to the temporal lobes, in particular the contralateral temporal lobe, and increased atlas-defined connectivity contralateral to the surgery side are associated with seizure recurrence. These findings may reflect network-level disruption that has infiltrated the contralateral temporal lobe contributing to relatively worse surgical outcomes. Further identification of network parameters that predict patient outcomes may aid in patient selection, resection planning, and ultimately the efficacy of epilepsy surgery.

scholarly journals Secondary generalization of focal-onset seizures: examining the relationship between seizure propagation and epilepsy surgery outcome

2017 ◽  
Vol 117 (4) ◽  
pp. 1426-1430 ◽  
Author(s):  
Samuel B. Tomlinson ◽  
Arun Venkataraman
Keyword(s):  
Epilepsy Surgery ◽  
Surgical Outcomes ◽  
Surgical Intervention ◽  
Intractable Epilepsy ◽  
Surgery Outcome ◽  
Seizure Propagation ◽  
The Relationship ◽  
Secondary Generalization

Surgical intervention often fails to achieve seizure-free results in patients with intractable epilepsy. Identifying features of the epileptic brain that dispose certain patients to unfavorable outcomes is critical for improving surgical candidacy assessments. Recent research by Martinet, Ahmad, Lepage, Cash, and Kramer ( J Neurosci 35: 9477–9490, 2015) suggests that pathways of secondary seizure generalization distinguish patients with favorable (i.e., seizure free) vs. unfavorable (i.e., seizure persistent) surgical outcomes, lending insights into the network mechanisms of epilepsy surgery failure.

scholarly journals Identifying spatio-temporal seizure propagation patterns in epilepsy using Bayesian inference

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Anirudh N. Vattikonda ◽  
Meysam Hashemi ◽  
Viktor Sip ◽  
Marmaduke M. Woodman ◽  
Fabrice Bartolomei ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Synthetic Data ◽  
Patient Specific ◽  
Seizure Freedom ◽  
Epileptogenic Zone ◽  
Model Predictions ◽  
Seizure Propagation ◽  
Spatio Temporal ◽  
Eeg Recordings ◽  
Drug Resistant Epilepsy

AbstractFocal drug resistant epilepsy is a neurological disorder characterized by seizures caused by abnormal activity originating in one or more regions together called as epileptogenic zone. Treatment for such patients involves surgical resection of affected regions. Epileptogenic zone is typically identified using stereotactic EEG recordings from the electrodes implanted into the patient’s brain. Identifying the epileptogenic zone is a challenging problem due to the spatial sparsity of electrode implantation. We propose a probabilistic hierarchical model of seizure propagation patterns, based on a phenomenological model of seizure dynamics called Epileptor. Using Bayesian inference, the Epileptor model is optimized to build patient specific virtual models that best fit to the log power of intracranial recordings. First, accuracy of the model predictions and identifiability of the model are investigated using synthetic data. Then, model predictions are evaluated against a retrospective patient cohort of 25 patients with varying surgical outcomes. In the patients who are seizure free after surgery, model predictions showed good match with the clinical hypothesis. In patients where surgery failed to achieve seizure freedom model predictions showed a strong mismatch. Our results demonstrate that proposed probabilistic model could be a valuable tool to aid the clinicians in identifying the seizure focus.

A historical cohort of temporal lobe surgery for medically refractory epilepsy: a systematic review and meta-analysis to guide future nonrandomized controlled trial studies

2020 ◽  
Vol 133 (1) ◽  
pp. 71-78 ◽  
Author(s):  
Anthony T. Lee ◽  
John F. Burke ◽  
Pranathi Chunduru ◽  
Annette M. Molinaro ◽  
Robert Knowlton ◽  
...  
Keyword(s):  
Systematic Review ◽  
Temporal Lobe ◽  
Epilepsy Surgery ◽  
Refractory Epilepsy ◽  
Meta Analysis ◽  
Small Sample ◽  
Seizure Freedom ◽  
Level I ◽  
Study Designs ◽  
Medically Refractory Epilepsy

OBJECTIVERecent trials for temporal lobe epilepsy (TLE) highlight the challenges of investigating surgical outcomes using randomized controlled trials (RCTs). Although several reviews have examined seizure-freedom outcomes from existing data, there is a need for an overall seizure-freedom rate estimated from level I data as investigators consider other methods besides RCTs to study outcomes related to new surgical interventions.METHODSThe authors performed a systematic review and meta-analysis of the 3 RCTs of TLE in adults and report an overall surgical seizure-freedom rate (Engel class I) composed of level I data. An overall seizure-freedom rate was also collected from level II data (prospective cohort studies) for validation. Eligible studies were identified by filtering a published Cochrane meta-analysis of epilepsy surgery for RCTs and prospective studies, and supplemented by searching indexed terms in MEDLINE (January 1, 2012–April 1, 2018). Retrospective studies were excluded to minimize heterogeneity in patient selection and reporting bias. Data extraction was independently reverified and pooled using a fixed-effects model. The primary outcome was overall seizure freedom following surgery. The historical benchmark was applied in a noninferiority study design to compare its power to a single-study cohort.RESULTSThe overall rate of seizure freedom from level I data was 72.4% (55/76 patients, 3 RCTs), which was nearly identical to the overall seizure-freedom rate of 71.7% (1325/1849 patients, 18 studies) from prospective cohorts (z = 0.134, p = 0.89; z-test). Seizure-freedom rates from level I and II studies were consistent over the years of publication (R2< 0.01, p = 0.73). Surgery resulted in markedly improved seizure-free outcomes compared to medical management (RR 10.82, 95% CI 3.93–29.84, p < 0.01; 2 RCTs). Noninferiority study designs in which the historical benchmark was used had significantly higher power at all difference margins compared to using a single cohort alone (p < 0.001, Bonferroni’s multiple comparison test).CONCLUSIONSThe overall rate of seizure freedom for temporal lobe surgery is approximately 70% for medically refractory epilepsy. The small sample size of the RCT cohort underscores the need to move beyond standard RCTs for epilepsy surgery. This historical seizure-freedom rate may serve as a useful benchmark to guide future study designs for new surgical treatments for refractory TLE.

scholarly journals Does etiology really matter for epilepsy surgery outcome?

2021 ◽  
Vol 31 (4) ◽  
Author(s):  
Lara Jehi ◽  
Kees Braun
Keyword(s):  
Epilepsy Surgery ◽  
Surgery Outcome

scholarly journals A flexible framework for sequential estimation of model parameters in computational hemodynamics

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Christopher J. Arthurs ◽  
Nan Xiao ◽  
Philippe Moireau ◽  
Tobias Schaeffter ◽  
C. Alberto Figueroa
Keyword(s):  
Unscented Kalman Filter ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Sequential Estimation ◽  
Wall Material ◽  
Patient Specific ◽  
Model Parameters ◽  
Computational Framework ◽  
Lumped Parameter ◽  
Estimation Of Model Parameters

AbstractA major challenge in constructing three dimensional patient specific hemodynamic models is the calibration of model parameters to match patient data on flow, pressure, wall motion, etc. acquired in the clinic. Current workflows are manual and time-consuming. This work presents a flexible computational framework for model parameter estimation in cardiovascular flows that relies on the following fundamental contributions. (i) A Reduced-Order Unscented Kalman Filter (ROUKF) model for data assimilation for wall material and simple lumped parameter network (LPN) boundary condition model parameters. (ii) A constrained least squares augmentation (ROUKF-CLS) for more complex LPNs. (iii) A “Netlist” implementation, supporting easy filtering of parameters in such complex LPNs. The ROUKF algorithm is demonstrated using non-invasive patient-specific data on anatomy, flow and pressure from a healthy volunteer. The ROUKF-CLS algorithm is demonstrated using synthetic data on a coronary LPN. The methods described in this paper have been implemented as part of the CRIMSON hemodynamics software package.

scholarly journals The Role of KRAS Mutations in Cortical Malformation and Epilepsy Surgery: A Novel Report of Nevus Sebaceous Syndrome and Review of the Literature

2021 ◽  
Vol 11 (6) ◽  
pp. 793
Author(s):  
Chiara Pepi ◽  
Luca de Palma ◽  
Marina Trivisano ◽  
Nicola Pietrafusa ◽  
Francesca Romana Lepri ◽  
...  
Keyword(s):  
Epilepsy Surgery ◽  
Focal Cortical Dysplasia ◽  
Hippocampal Sclerosis ◽  
Brain Mri ◽  
Seizure Freedom ◽  
Histopathological Diagnosis ◽  
Cortical Malformation ◽  
Cognitive Improvement ◽  
Cortical Malformations ◽  
Nevus Sebaceous

The rare nevus sebaceous (NS) syndrome (NSS) includes cortical malformations and drug-resistant epilepsy. Somatic RAS-pathway genetic variants are pathogenetic in NS, but not yet described within the brain of patients with NSS. We report on a 5-year-old boy with mild psychomotor delay. A brown-yellow linear skin lesion suggestive of NS in the left temporo-occipital area was evident at birth. Epileptic spasms presented at aged six months. EEG showed continuous left temporo-occipital epileptiform abnormalities. Brain MRI revealed a similarly located diffuse cortical malformation with temporal pole volume reduction and a small hippocampus. We performed a left temporo-occipital resection with histopathological diagnosis of focal cortical dysplasia type Ia in the occipital region and hippocampal sclerosis type 1. Three years after surgery, he is seizure-and drug-free (Engel class Ia) and showed cognitive improvement. Genetic examination of brain and skin specimens revealed the c.35G > T (p.Gly12Val) KRAS somatic missense mutation. Literature review suggests epilepsy surgery in patients with NSS is highly efficacious, with 73% probability of seizure freedom. The few histological analyses reported evidenced disorganized cortex, occasionally with cytomegalic neurons. This is the first reported association of a KRAS genetic variant with cortical malformations associated with epilepsy, and suggests a possible genetic substrate for hippocampal sclerosis.

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