Visual and semi-automatic non-invasive detection of interictal fast ripples: A potential biomarker of epilepsy in children with tuberous sclerosis complex
- PMID: 29673547
- DOI: 10.1016/j.clinph.2018.03.010
Visual and semi-automatic non-invasive detection of interictal fast ripples: A potential biomarker of epilepsy in children with tuberous sclerosis complex
Abstract
Objectives: We aim to establish that interictal fast ripples (FR; 250-500 Hz) are detectable on scalp EEG, and to investigate their association to epilepsy.
Methods: Scalp EEG recordings of a subset of children with tuberous sclerosis complex (TSC)-associated epilepsy from two large multicenter observational TSC studies were analyzed and compared to control children without epilepsy or any other brain-based diagnoses. FR were identified both by human visual review and compared with semi-automated review utilizing a deep learning-based FR detector.
Results: Seven out of 7 children with TSC-associated epilepsy had scalp FR compared to 0 out of 4 children in the control group (p = 0.003). The automatic detector has a sensitivity of 98% and false positive rate with average of 11.2 false positives per minute.
Conclusions: Non-invasive detection of interictal scalp FR was feasible, by both visual and semi-automatic detection. Interictal scalp FR occurred exclusively in children with TSC-associated epilepsy and were absent in controls without epilepsy. The proposed detector achieves high sensitivity of FR detection; however, expert review of the results to reduce false positives is advised.
Significance: Interictal FR are detectable on scalp EEG and may potentially serve as a biomarker of epilepsy in children with TSC.
Keywords: Epilepsy; Fast ripples; High frequency oscillations; Tuberous sclerosis complex.
Copyright © 2018 International Federation of Clinical Neurophysiology. All rights reserved.
Comment in
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Oh surprise! Fast ripples on scalp EEG.Clin Neurophysiol. 2018 Jul;129(7):1449-1450. doi: 10.1016/j.clinph.2018.04.612. Epub 2018 Apr 30. Clin Neurophysiol. 2018. PMID: 29753620 No abstract available.
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