Time-Frequency Fingerprint Analysis in SEEG Source-Space to Identify the Epileptogenic Zone.

Area of Science:

• Epileptology
• Neuroimaging
• Neurosurgery

Background:

• Accurate localization of the epileptogenic zone (EZ) is crucial for successful epilepsy surgery, especially in cases with complex cortical malformations.
• Traditional sensor-space analysis of stereo-EEG (SEEG) data may have limitations in precisely pinpointing the seizure onset zone in intricate brain structures.

Observation:

• A case study involving a 25-year-old female with extensive bilateral perisylvian polymicrogyria (PMG) presented with intractable focal seizures.
• The patient exhibited complex cortical malformations, posing a challenge for conventional epilepsy localization techniques.

Findings:

• Seizure fingerprint analysis applied in the source-space of SEEG data, utilizing the sLORETA imaging algorithm within the Brainstorm software, successfully identified the EZ.
• This source-level analysis provided a more accurate localization of the epileptogenic zone compared to sensor-space methods.
• The identified EZ was targeted with MR-guided laser interstitial thermal therapy (LITT), leading to complete postoperative seizure freedom.

Implications:

• Transitioning seizure fingerprint analysis from sensor-space to source-space significantly enhances the precision of EZ localization in patients with complex cortical malformations.
• This advanced analytical approach holds the potential to improve surgical planning and optimize outcomes for individuals suffering from intractable epilepsy.
• The successful application of source-space analysis followed by LITT demonstrates a promising strategy for managing challenging epilepsy cases.