Publications Repository - Gdańsk University of Technology

OBJECTIVE: To test the utility of a novel semi-automated method for detecting, validating, and quantifying high-frequency oscillations (HFOs): ripples (80-200 Hz) and fast ripples (200-600 Hz) in intra-operative electrocorticography (ECoG) recordings. METHODS: Sixteen adult patients with temporal lobe epilepsy (TLE) had intra-operative ECoG recordings at the time of resection. The computer-annotated ECoG recordings were visually inspected and false positive detections were removed. We retrospectively determined the sensitivity, specificity, positive and negative predictive value (PPV/NPV) of HFO detections in unresected regions for determining post-operative seizure outcome. RESULTS: Visual validation revealed that 2.81% of ripple and 43.68% of fast ripple detections were false positive. Inter-reader agreement for false positive fast ripple on spike classification was good (ICC = 0.713, 95% CI: 0.632-0.779). After removing false positive detections, the PPV of a single fast ripple on spike in an unresected electrode site for post-operative non-seizure free outcome was 85.7 [50-100%]. Including false positive detections reduced the PPV to 64.2 [57.8-69.83%]. CONCLUSIONS: Applying automated HFO methods to intraoperative electrocorticography recordings results in false positive fast ripple detections. True fast ripples on spikes are rare, but predict non-seizure free post-operative outcome if found in an unresected site. SIGNIFICANCE: Semi-automated HFO detection methods are required to accurately identify fast ripple events in intra-operative ECoG recordings.

Authors

• Shennan Aibel Weiss,
• Brent Berry,
• Inna Chervoneva,
• Zachary Waldman,
• Jonathan Guba,
• Mark R. Bower,
• dr Michał Tomasz Kucewicz link open in new tab ,
• Benjamin Brinkmann,
• Vaclav Kremen,
• Fatemeh Khadjevand,
• Yogatheesan Varatharajah,
• Hari Guragain,
• Ashwini Sharan,
• Chengyuan Wu,
• Richard Staba,
• Jerome Engel Jr.,
• Michael R. Sperling,
• Gregory Worrell