Semiautomated Spike Detection Software Persyst 13 Is Noninferior to Human Readers When Calculating the Spike-Wave Index in Electrical Status Epilepticus in Sleep

J Clin Neurophysiol. 2018 Sep;35(5):370-374. doi: 10.1097/WNP.0000000000000493.

Abstract

Purpose: Our objective was to use semiautomatic methods for calculating the spike-wave index (SWI) in electrical status epilepticus in slow-wave sleep (ESES) and to determine whether this calculation is noninferior to human experts (HEs).

Methods: Each HE marked identical 300-second epochs for all spikes and calculated the SWI in sleep EEGs of patients diagnosed with ESES. Persyst 13 was used to mark spikes (high sensitivity setting) in the same 300-second epochs marked by HEs. The spike-wave index was calculated. Pairwise HE differences and pairwise Persyst 13 (P13)-HE differences for the SWI were calculated. Bootstrap resampling (BCa, N = 3,000) was performed to better estimate mean differences and their 95% confidence bounds between HE and P13-HE pairs. Potential noninferiority of P13 to HEs was tested by comparing the 95% confidence bounds of the mean differences between pairs for the SWI.

Results: Twenty EEG records were analyzed. Each HE marked 100 minutes of EEG. HEs 1, 2, 3, and 4 marked 10,075, 8,635, 9,710, and 9,898 spikes, respectively. The highest and lowest 95% confidence bound of the mean difference in the SWI between HE pairs was: High: 10.3%; Low: -10.2%. Highest and lowest 95% confidence bound of the mean difference in the SWI between P13 and HE pairings was as follows: high, 9.5% and low, -6.7%. The lack of a difference between P13 and HEs supports that the algorithm is not inferior to HEs.

Conclusions: Persyst 13 is noninferior to HEs in calculating the SWI in ESES, thus suggesting that an automated approach to SWI calculation may be a useful clinical tool.

Publication types

  • Comparative Study

MeSH terms

  • Adolescent
  • Brain / physiopathology
  • Child
  • Child, Preschool
  • Diagnosis, Computer-Assisted* / methods
  • Electroencephalography* / methods
  • Humans
  • Pattern Recognition, Automated / methods
  • Retrospective Studies
  • Signal Processing, Computer-Assisted
  • Sleep* / physiology
  • Software*
  • Status Epilepticus / diagnosis*
  • Status Epilepticus / physiopathology*