Exploring Cortico-cortical Evoked Potentials as a Marker of the Seizure Onset Zone
Abstract number :
2.056
Submission category :
3. Neurophysiology / 3E. Brain Stimulation
Year :
2023
Submission ID :
476
Source :
www.aesnet.org
Presentation date :
12/3/2023 12:00:00 AM
Published date :
Authors :
Presenting Author: Joshua LaRocque, MD, PhD – University of Pennsylvania
Doris Xu, undergraduate student – Undergraduate, University of Pennsylvania; Marissa Mojena, B.S. – Research coordinator, Neurology, University of Pennsylvania; Alfredo Lucas, B.S. – Graduate student, University of Pennsylvania; William Ojemann, B.S. – Graduate student, University of Pennsylvania; Nishant Sinha, PhD – Post-doctoral fellow, University of Pennsylvania; Kathryn Davis, M.D. – University of Pennsylvania; Erin Conrad, M.D. – University of Pennsylvania
Rationale:
For some patients with drug-resistant epilepsy, surgical removal of brain regions causing their seizures can be a highly effective treatment option. Accurately identifying the seizure onset zone (SOZ) is critical to the success of such surgery. To more accurately identify the SOZ, we performed low-frequency electrical stimulation in order to measure cortico-cortical evoked potentials (CCEPs). We hypothesized that quantitative parameters obtained from CCEPs measured within vs. outside the SOZ would have higher amplitudes due to hyperexcitability within the SOZ.
Methods:
We analyzed data from low frequency stimulation (bipolar/biphasic stimulation, 3 mA current, 300-500 µs pulse width, 1 Hz frequency) performed in 26 patients (16 female, age 21-53) who underwent intracranial EEG monitoring for epilepsy surgery planning at the University of Pennsylvania. After an initial artifact rejection step, the ~30 trials for each stimulation site were time-locked to the stimulation onset and averaged for each response site. We then extracted the largest peak in the 15-50 ms post-stimulation time window (the “N1”) and the largest peak in the 50-300 ms time window (the “N2”). In order to characterize the dynamic signal in these waveforms, we also calculated the root mean square (RMS) of the 25-300 ms time window. Finally, in order to measure the consistency of the CCEPs at a single response site, we calculated the correlation between all the waveforms obtained from a given response site then averaged them. This procedure generated an average R2 for each response site reflecting the similarity of the waveforms measured there. We then averaged each of these measures separately for response sites within and outside the SOZ prior to making across-subject comparisons using Wilcoxon signed-rank tests.
Results:
Neither N1 nor N2 significantly differed between SOZ and non-SOZ (all p’s > 0.09). The RMS was significantly higher inside the SOZ compared with outside it (z = -2.29, p = 0.02). The correlation between the waveforms for each response site was higher outside the SOZ than inside it (z = 2.57, p = 0.01); i.e., the evoked waveforms were more similar to each other at response sites outside the SOZ.
Conclusions:
Contrary to our expectations and to a prior study examining N1 amplitudes [1], we found no significant differences in the N1 or N2 amplitudes between SOZ and non-SOZ; yet, the RMS value was significantly larger inside the SOZ. This discrepancy may be because the N1 and N2 measures reflect a peak amplitude in a time window and are insensitive to the dynamics of the signal as compared to RMS. Finally, the wave forms within the SOZ were less consistent than those outside the SOZ. Although more work is needed to clarify the physiologic basis of these findings, this work suggests that CCEPs may differentiate SOZ from healthy tissue.
Funding: 5T32NS091006-08 (J.J.L.)
NINDS 1K23NS121401-01 (E.C.)
Burroughs Wellcome Career Award (E.C.)
Neurophysiology