OBJECTIVE: High-frequency oscillations (HFOs) in intracerebral EEG (stereoelectroencephalography; SEEG) are considered as better biomarkers of epileptogenic tissues than spikes. How this can be applied at the patient level remains poorly understood. We investigated how well HFOs and spikes can predict epileptogenic regions with a large spatial sampling at the patient level. METHODS: We analyzed non-REM sleep SEEG recordings sampled at 2,048Hz of 30 patients. Ripples (Rs; 80-250Hz), fast ripples (FRs; 250-500Hz), and spikes were automatically detected. Rates of these markers and several combinations-spikes co-occurring with HFOs or FRs and cross-rate (Spk⊗HFO)-were compared to a quantified measure of the seizure onset zone (SOZ) by performing a receiver operating characteristic analysis for each patient individually. We used a Wilcoxon signed-rank test corrected for false-discovery rate to assess whether a marker was better than the others for predicting the SOZ. RESULTS: A total of 2,930 channels was analyzed (median of 100 channels per patient). The HFOs or any of its variants were not statistically better than spikes. Only one feature, the cross-rate, was better than all the other markers. Moreover, fast ripples, even though very specific, were not delineating all epileptogenic tissues. INTERPRETATION: At the patient level, the performance of HFOs is weakened by the presence of strong physiological HFO generators. Fast ripples are not sensitive enough to be the unique biomarker of epileptogenicity. Nevertheless, combining HFOs and spikes using our proposed measure-the cross-rate-is a better strategy than using only one marker. Ann Neurol 2018;83:84-97.
OBJECTIVE: High-frequency oscillations (HFOs) in intracerebral EEG (stereoelectroencephalography; SEEG) are considered as better biomarkers of epileptogenic tissues than spikes. How this can be applied at the patient level remains poorly understood. We investigated how well HFOs and spikes can predict epileptogenic regions with a large spatial sampling at the patient level. METHODS: We analyzed non-REM sleep SEEG recordings sampled at 2,048Hz of 30 patients. Ripples (Rs; 80-250Hz), fast ripples (FRs; 250-500Hz), and spikes were automatically detected. Rates of these markers and several combinations-spikes co-occurring with HFOs or FRs and cross-rate (Spk⊗HFO)-were compared to a quantified measure of the seizure onset zone (SOZ) by performing a receiver operating characteristic analysis for each patient individually. We used a Wilcoxon signed-rank test corrected for false-discovery rate to assess whether a marker was better than the others for predicting the SOZ. RESULTS: A total of 2,930 channels was analyzed (median of 100 channels per patient). The HFOs or any of its variants were not statistically better than spikes. Only one feature, the cross-rate, was better than all the other markers. Moreover, fast ripples, even though very specific, were not delineating all epileptogenic tissues. INTERPRETATION: At the patient level, the performance of HFOs is weakened by the presence of strong physiological HFO generators. Fast ripples are not sensitive enough to be the unique biomarker of epileptogenicity. Nevertheless, combining HFOs and spikes using our proposed measure-the cross-rate-is a better strategy than using only one marker. Ann Neurol 2018;83:84-97.
Authors: Somin Lee; Naoum P Issa; Sandra Rose; James X Tao; Peter C Warnke; Vernon L Towle; Wim van Drongelen; Shasha Wu Journal: Seizure Date: 2019-05-03 Impact factor: 3.184
Authors: Shennan A Weiss; Zachary Waldman; Federico Raimondo; Diego Slezak; Mustafa Donmez; Gregory Worrell; Anatol Bragin; Jerome Engel; Richard Staba; Michael Sperling Journal: Biomark Med Date: 2019-05-02 Impact factor: 2.851
Authors: Mark A Kramer; Lauren M Ostrowski; Daniel Y Song; Emily L Thorn; Sally M Stoyell; McKenna Parnes; Dhinakaran Chinappen; Grace Xiao; Uri T Eden; Kevin J Staley; Steven M Stufflebeam; Catherine J Chu Journal: Brain Date: 2019-05-01 Impact factor: 13.501
Authors: Julia Jacobs; Joyce Y Wu; Piero Perucca; Rina Zelmann; Malenka Mader; Francois Dubeau; Gary W Mathern; Andreas Schulze-Bonhage; Jean Gotman Journal: Neurology Date: 2018-08-17 Impact factor: 9.910