Utilizing a computerized spike detection system to analyze long periods of IEEG we identified correlation between interictal IED location and the seizure onset zone in 11 of 19 patients. In the other 8 patients, the mean distribution of interictal IEDs was a poor marker for identifying the seizure onset region. In addition, when comparing across sixteen different 30-minute segments of IEEG for each individual patient, those with and without overall correlation, IED density varied significantly between sections for all but one patient. Thus in the majority of the patients, brief recordings of IEDs are unlikely to be useful in localizing seizure onset.
Prior studies have utilized short IEEG epochs to determine if IEDs can serve as a marker to identify seizure onset electrodes (Hufnagel, et al., 2000
, Asano, et al., 2003
). Asano et al. 2003
studied a patient population similar to our own, children mostly with cortical dysplasia, and found that the electrode with the highest IED frequency was contained within the seizure onset region in 13 of 13 patients. IED frequency had the best correlation, though amplitude and leading spike were almost as good at identifying seizure onset electrodes. In contrast, only 11 of 19 of our patients had the highest IED frequency within the seizure onset zone. Our findings are in keeping with a larger study in adults and children also using a computer based spike detector were the seizure onset electrode was within 2cm of the maximal spike frequency electrode in only 53% of patients (Hufnagel, et al., 2000
Interictal IEDs are clinically used in a variety of ways to help identify the region of surgical resection. Our data suggest that electrodes with the highest frequency of IEDs over long-periods of IEEG correlate with the electrodes involved in the seizure onset in about two-thirds of pediatric patients with medically refractory epilepsy. When only a single 30-minute segment of recording is used, there is less consistent correlation between the electrodes generating IEDs and the seizure onset zone. Indeed, in all but one patient, the IED density pattern in a random 30-minute segment did not consistently correlate with seizure onset zone. These data suggest that the use of short epochs of subdural electrode recordings to identify regions of highest spike density is generally insufficient to provide an accurate localization of IED density. However, since at least a single segment in all but one patient correlated with seizure onset, picking the correct time to quantify seizure density could help delineate the seizure onset zone.
From a clinical perspective, can we use our findings to improve seizure free outcomes following surgery? Previous reports, utilizing IEEG, describe increased surgical success if both the area of “prominent interictal spiking and background abnormalities” and seizure onset are resected (Wyllie, et al., 1987
, Paolicchi, et al., 2000
, Krsek, et al., 2008
). Their findings imply a distinct location for IEDs and seizure onset in a subset of patients. Our data quantify this relationship that IEDs had a distinct localization from seizure onset in about forty percent of our patients. A potential hypothesis from combining these studies is that IEDs have a distinct localization and a causal relationship to seizure generation. One complicating factor in this discussion is the issue of generators vs. propagators of IEDs. It may be that regions generating IEDs may be vital to seizure generation, but that those that merely conduct discharges confound efforts to localize the ictal onset zone. Further quantitative studies looking at IED timing, correlation and propagation may shed considerable light on this issue. In the end, the question of what constitutes a seizure and what are the cellular and network elements that are necessary to generate it are central to this discussion.
A prominent finding in this study was the variability of IEDs in any given electrode over time, and relative changes in IED frequencies between electrodes over time. A number of physiological factors likely play an important role in this variability. Prior studies in the temporal lobe have implicated sleep as being one of the major sources of variability in the location of IEDs over time (Sammaritano, et al., 1991
, Staba, et al., 2002
). The frequency of IEDs and their spatial spread were greater in slow wave sleep than in wakefulness or REM sleep. Increased number of IEDs following a seizure has been reported, which may be affected by post-ictal sleep state (Gotman & Marciani, 1985
, Gotman & Koffler, 1989
). Epilepsy syndrome and localization may also play a role in the relationship between IEDs, sleep, and seizures, particularly in temporal lobe epilepsy (Spencer, et al., 2008
). Our data suggest that there is a great deal of variability in frequency of IEDs in extra-temporal epilepsy.
Another potential cause for IED variability, in addition to sleep state, is alterations in anti-epileptic drug levels during the phase II surgical evaluation. Studies have reported a mixed relationship between IED frequency, and AED levels (Rodin, et al., 1974
, Milligan, et al., 1983
, Gotman & Marciani, 1985
, Gotman & Koffler, 1989
, Spencer, et al., 2008
). Many of the patients in our study had medication adjustments over the course of their IEEG monitoring. An additional consideration for the variability in IED number is whether data epochs are pre ictal. There is as of yet no consensus whether there is a reproducible change in the temporal distribution of IEDs as seizures approach (Lieb, et al., 1978
, Gotman, et al., 1982
, Lange, et al., 1983
, Katz, et al., 1991
). These factors were not examined in the current study.
Cortical dysplasia, Palmini grade 2A, was the most predominant finding on pathology and these patients had IEDs that both correlated and did not correlate with seizure onset. Similar to prior studies in patients with cortical dysplasia (Turkdogan, et al., 2005
), we found a mixture of seizure onset morphologies including rhythmic spiking, low voltage fast activity onsets, and rhythmic slowing at onset. Of the 13 patients with a rhythmic spiking morphology at seizure onset, 7 had IED frequency correlating with seizure onset. In contrast all the patients with the low voltage seizure onset displayed a correlation between IED frequency and seizure onset, suggesting that IED frequency may be a better marker for seizure onset electrodes in patients with low voltage fast activity on IEEG at seizure onset. It will be important to replicate these findings on a second set of patients.
In this study we utilized automated, computer-based EEG analysis to quantify IEDs over long periods of IEEG and identified patients with and without a correlation between IED and seizure onset regions. The improvement in computer technology over the past decade has allowed implementation of methods capable of easily analyzing IEDs over 8 hours of IEEG in up to 140 electrodes per patient. While our results are promising for using computer based detection methods to quantify IEDs it remains an open question as to how best utilize and refine these methods to improve outcome from epilepsy surgery, shorten length of stay, and potentially maximize the utility of intra-operative electrocorticography during electrode placement and resection. Even more importantly, this study raises important questions about how seizures and interictal epileptiform discharges are generated in human brain, and how to define and map epileptic networks.