Abstracts

Rationale: It is important to accurately localize the epileptogenic zone (EZ) during presurgical planning. EEG source imaging has shown its capability to substantially increase the spatial resolution while keeping the temporal resolution of EEG [1]. We aim to develop techniques that can localize the EZ from noninvasive high density EEG recordings. In this study, we show that a novel electrophysiological source imaging algorithm – fast spatiotemporal iteratively reweighted edge sparsity (FAST-IRES) [2] – accurately estimates the location and extent of epileptic sources from ictal recordings. The source imaging analysis results are validated by surgical resection volume in a cohort of focal drug-resistant epilepsy patients who were seizure free at least 1-year post-op follow up.

Methods: 30 seizures from 75-channel scalp EEG were analyzed in a cohort of 15 focal epilepsy patients. All patients received surgical resection and were declared seizure-free (ILAE I-II) based on at least 1-year post-op follow up. Surgical resection regions were determined by comparing each patient’s pre-op and post-op MRI. Localization error (LE), spatial dispersion (SD), precision, sensitivity, and specificity of source imaging results were calculated with respect to the surgical resection region. As ictal events vary in duration, approximately the first 2 seconds of increased ictal activity were input into the solver.

Results: As shown in Figure 1, the FAST-IRES estimations are concordant with the resection region. The value for each metric is as follows: 6.9 ± 3.9 mm LE, 10.1 ± 6.7 mm SD, 0.41 ± 0.27 precision, 0.63 ± 0.22 recall, and 0.85 ± 0.11 specificity. All values are reported as mean ± standard deviation. In the patient example, the estimation overlaps well with the resection.

Conclusions: These results demonstrate the merit of noninvasive EEG source localization from ictal recordings, and that FAST-IRES provides excellent performance that is highly concordant with successful surgical resection. Further investigation can be performed on connectivity analysis during ictal events to better assess seizure propagation and which temporal features are best tied to the EZ. In addition, non-seizure free patients can be analyzed to determine if different cortical regions are detected than were resected. We can also compare the ictal imaging results with interictal biomarkers, such as different types of interictal spikes, to better understand which epileptic features best delineate the EZ.


References:

[1] B. He, A. Sohrabpour, E. Brown, and Z. Liu, "Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics," Ann Review of Biomed Eng, 20, 171-196, 2018.

[2] A. Sohrabpour, Z. Cai, S. Ye, B. Brinkmann, G. Worrell, and B. He, “Noninvasive electromagnetic source imaging of spatiotemporally distributed epileptogenic brain sources,” Nat Commun, 11, 1946, 2020.


Funding: NIH R01NS096761, R01NS127849, and T32 EB029365.