Kurt E Hecox | Search PubMed

PubMed2005

Locating chronically implanted subdural electrodes using surface reconstruction.

OBJECTIVE: To determine the accuracy of locating subdural electrodes by means of 3-D surface rendering of CT scans. METHODS: Open source software has been developed and posted on the web which segments the electrodes into 3-D surfaces and allows their 3-D locations to be exported to other EEG analysis programs. The accuracy of the technique was determined by studying 410 subdural electrodes implanted in four epilepsy patients. Accuracy was determined by comparing the locations from the rendering analysis to the locations of the same electrodes determined by conventional analysis of their appearance on individual CT slices. RESULTS: The average accuracy of a study of 410 electrodes imaged in four patients repeated two times by three observers was 0.91 (+/- 0.41) mm, with a maximum error of 3.3 mm, about half of the diameter of an electrode. CONCLUSIONS: The location of subdural electrodes can easily and quickly be determined within high-resolution CT scans through the use of 3-D rendering. SIGNIFICANCE: This relatively fast and easy method for determining the location of subdural electrodes should facilitate their use in both clinical and research investigations.

Brain↗

PubMed2003

Seizure anticipation in pediatric epilepsy: use of Kolmogorov entropy.

The purpose of this paper is to demonstrate feasibility of using trends in Kolmogorov entropy to anticipate seizures in pediatric patients with intractable epilepsy. Surface and intracranial recordings of preseizure and seizure activity were obtained from five patients and subjected to time series analysis using Kolmogorov entropy. This metric was compared with correlation dimension and power indices, both known to predict seizures in some adult patients. We used alarm levels and introduced regression analysis as a quantitative approach to the analysis of trends. Surrogate time series evaluated data nonlinearity, as a precondition to the use of nonlinear measures. Seizures were anticipated before clinical or electrographic seizure onset for three of the five patients from the intracranial recordings, and in two of five patients from the scalp recordings. Anticipation times varied between 2 and 40 minutes. This is the first report in which simultaneous surface and intracranial recording are used for seizure prediction in children. We conclude that the Kolmogorov entropy and power indices were as effective as the more commonly used correlation dimension in anticipating seizures. Further, regression analysis of the Kolmogorov entropy time series is feasible, making the analysis of data trends more objective.

Adolescent↗