scholarly journals Interictal high frequency oscillations correlating with seizure outcome in patients with widespread epileptic networks in tuberous sclerosis complex

Epilepsia ◽  
2014 ◽  
Vol 55 (10) ◽  
pp. 1602-1610 ◽  
Author(s):  
Tohru Okanishi ◽  
Tomoyuki Akiyama ◽  
Shin-Ichi Tanaka ◽  
Ellen Mayo ◽  
Ayu Mitsutake ◽  
...  
2006 ◽  
Vol 37 (03) ◽  
Author(s):  
C Krahn-Peper ◽  
IEB Tuxhorn ◽  
K Ahlbory ◽  
F Behne ◽  
H Pannek

2020 ◽  
Vol 131 (4) ◽  
pp. e233
Author(s):  
E. Boran ◽  
P. Mégevand ◽  
A. Steenkamp ◽  
V. Dimakopoulos ◽  
M. Seeck ◽  
...  

Author(s):  
C Wilbur ◽  
C Sanguansermsri ◽  
H Chable ◽  
A Mihaela ◽  
P Steinbok ◽  
...  

Background: Epilepsy occurs in up to 90% of patients with Tuberous Sclerosis Complex (TSC) and is often refractory to medications. Our objective was to assess the safety and outcome of epilepsy surgery in children with TSC at our institution. Methods: We performed a systematic, retrospective chart review of children with TSC who underwent epilepsy surgery at our institution. Patients were identified through epilepsy and clinical neurophysiology databases. Results: 19 patients (out of 81 with TSC) underwent surgery between 1995-2014. Median age at surgery was 4.2 (Range 1.1-15.6) years, with patients having failed a median 4 (Range 0-10) anti-seizure medications. Surgery comprised corpus callosotomy in 2 and resection of one or more tubers in 17. 2 patients had a subsequent second resection. Minor neurologic deficits occurred after 14% of surgeries. Median follow-up was 2.4 years (Range 0.3 -13.8 years) following surgery . At last follow-up, 47% were seizure free, including 2 patients off anti-seizure medication. Conclusions: Epilepsy surgery is safe and effective in carefully selected TSC patients, with the majority having a good seizure outcome. Children with epilepsy secondary to TSC should be referred for epilepsy surgery assessment.


2020 ◽  
Author(s):  
V Dimakopoulos ◽  
P Mégevand ◽  
E Boran ◽  
S Momjian ◽  
M Seeck ◽  
...  

AbstractBackgroundInterictal high frequency oscillations (HFO) are discussed as biomarkers for epileptogenic brain tissue that should be resected in epilepsy surgery to achieve seizure freedom. The prospective classification of tissue sampled by individual electrode contacts remains a challenge. We have developed an automated, prospective definition of clinically relevant HFO in intracranial EEG (iEEG) from MNI Montreal and tested it in iEEG from Zurich. We here validate the algorithm on iEEG recorded in an independent epilepsy center so that HFO analysis was blinded to seizure outcome.MethodsWe selected consecutive patients from Geneva University Hospitals who underwent resective epilepsy surgery with postsurgical follow-up > 12 months. We analyzed long-term iEEG recordings during non-rapid eye movement (NREM) sleep that we segmented into intervals of 5 min. HFOs were defined in the ripple (80-250 Hz) and the fast ripple (FR, 250-500 Hz) frequency band. Contacts with the highest rate of ripples co-occurring with FR (FRandR) designated the HFO area. If the HFO area was not fully resected and the patient suffered from recurrent seizures (ILAE 2-6), this was classified as a true positive (TP) prediction.ResultsWe included iEEG recordings from 16 patients (median age 32 y, range [18-53]) with stereotactic depth electrodes and/or with subdural electrode grids (median follow-up 27 mo, range [12-55]). The HFO area had high test-retest reliability across intervals (median dwell time 95%). We excluded two patients with dwell time < 50% from further analysis.The HFO area was fully included in the resected volume in 2/4 patients who achieved postoperative seizure freedom (ILAE 1, specificity 50%) and was not fully included in 9/10 patients with recurrent seizures (ILAE > 1, sensitivity 90%), leading to an accuracy of 79%.ConclusionsWe validated the automated procedure to delineate the clinical relevant HFO area in individual patients of an independently recorded dataset and achieved the same good accuracy as in our previous studies.SignificanceThe reproducibility of our results across datasets is promising for a multicienter study testing the clinical application of HFO detection to guide epilepsy surgery.


2013 ◽  
Vol 45 (2) ◽  
pp. 336-353 ◽  
Author(s):  
Catherine Stamoulis ◽  
Vanessa Vogel-Farley ◽  
Geneva Degregorio ◽  
Shafali S. Jeste ◽  
Charles A. Nelson

2019 ◽  
Vol 130 (8) ◽  
pp. e133
Author(s):  
E. Boran ◽  
G. Ramantani ◽  
N. Krayenbühl ◽  
T. Fedele ◽  
J. Sarnthein

2007 ◽  
Vol 35 (9) ◽  
pp. 1573-1584 ◽  
Author(s):  
Hiram Firpi ◽  
Otis Smart ◽  
Greg Worrell ◽  
Eric Marsh ◽  
Dennis Dlugos ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Karla Burelo ◽  
Mohammadali Sharifshazileh ◽  
Niklaus Krayenbühl ◽  
Georgia Ramantani ◽  
Giacomo Indiveri ◽  
...  

AbstractTo achieve seizure freedom, epilepsy surgery requires the complete resection of the epileptogenic brain tissue. In intraoperative electrocorticography (ECoG) recordings, high frequency oscillations (HFOs) generated by epileptogenic tissue can be used to tailor the resection margin. However, automatic detection of HFOs in real-time remains an open challenge. Here we present a spiking neural network (SNN) for automatic HFO detection that is optimally suited for neuromorphic hardware implementation. We trained the SNN to detect HFO signals measured from intraoperative ECoG on-line, using an independently labeled dataset (58 min, 16 recordings). We targeted the detection of HFOs in the fast ripple frequency range (250-500 Hz) and compared the network results with the labeled HFO data. We endowed the SNN with a novel artifact rejection mechanism to suppress sharp transients and demonstrate its effectiveness on the ECoG dataset. The HFO rates (median 6.6 HFO/min in pre-resection recordings) detected by this SNN are comparable to those published in the dataset (Spearman’s $$\rho$$ ρ = 0.81). The postsurgical seizure outcome was “predicted” with 100% (CI [63 100%]) accuracy for all 8 patients. These results provide a further step towards the construction of a real-time portable battery-operated HFO detection system that can be used during epilepsy surgery to guide the resection of the epileptogenic zone.


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