Statistical modeling of ICEEG features that determine resection planning

The interpretation of intracranial EEG (ICEEG) recordings is a complex balance of the significance of specific rhythms and their relative timing to seizure onset. Ictal and interictal findings are evaluated in light of findings from cortical stimulation of eloquent cortex to determine the area of resection.

Patients with ICEEG electrodes and subsequent surgical resection were retrospectively identified. Only the first 15s of ictal activity, which was divided into five 3-s epochs, was considered. Every electrode in each patient was considered a separate observation in a logistic regression model to predict whether the cortex under a given electrode was included in the planned resection.

19 included patients had a total of 37 unique seizures. Recordings from a total of 1306 electrodes were analyzed. The strongest predictors of resection of cortex underlying a given electrode was the presence of low-voltage fast activity in Epoch 1, rhythmic spikes in Epoch 1, interictal paroxysmal fast activity, and low-voltage fast activity in Epoch 2. High-amplitude beta spikes and rhythmic slow waves were also significant predictors in Epoch 1. Interictal spikes had a higher odds ratio of affecting the planned resection if described as "continuous" or "very frequent". The presence of motor or language cortex were the strongest negative predictors of resecting underlying cortex.

Here we describe a novel model of ictal and interictal patterns significantly associated with the inclusion of cortex underlying a given ICEEG electrode in the surgical resection plan.