Categorization of interictal epileptiform potentials using a graph-theoretic method

Objectives: In patients with epileptic seizures, localization of the source of interictal epileptiform activity is of interest. For correct source loc alization, a favorable signal to noise ratio is important, and to achieve t his, averaging of several epileptiform potentials is often necessary. Befor e averaging, a careful categorization of epileptiform potentials with diffe rent potential distributions is crucial. The aim of this study was to inves tigate whether a a hierarchic, graph-theoretic algorithm could be used for this categorization. Methods: In 4 patients, 50-100 sharp waves with different surface distribut ions were categorized independently with the algorithm, and by visual inspe ction of the traces. As an independent evaluation of the algorithm, a dipol e reconstruction was performed for each sharp wave, and the dipole results for the sharp waves from the different automatically obtained categories we re compared. Results: All patients showed a high degree of correspondence between the re sults of the automatic analysis and the visual estimation. There were clear differences in dipole results between the sharp waves of the different cat egories obtained from the automatic categorization. Conclusion: The results indicate that the graph-theoretic categorization al gorithm provides a reliable clustering of interictal epileptiform potential s, and that the method may become a useful tool in the pre-averaging catego rization of interictal epileptiform potentials prior to source localization . (C) 1998 Elsevier Science Ireland Ltd. All rights reserved.