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| Description
| - Objective. Interictal epileptiform discharges (IEDs) are electrographic hallmark of epilepsy. Information about the spatiotemporal distribution of IEDs in intracranial EEG is utilized to localize epileptogenic zone during the presurgical evaluation and plan the resection. Visual evaluation of long-term multi-channel intracranial recordings is extremely difficult and prone to bias. Clinicians usually assess only high-amplitude (high signal to noise ratio) discharge and low-amplitude IEDs can be overlooked or considered clinically insignificant. The goal of our study was to develop reliable automatic IED detectors to facilitate analysis of long-term recordings and increase the information yield of intracranial recordings. Methods. Seven intracranial EEG recordings were randomly selected from our database. Samples of five minutes duration from fifteen high-rate IED channels (525 minutes in total) were presented to three experienced EEG specialists for spike labelling. The readers independently reviewed the data and classified IEDs into two groups: obvious and ambiguous. The inter-reader agreement was evaluated and IEDs labelled by at least two readers were considered as a gold standard (GS). We have developed, tested and optimized novel IED detector using GS datasets and compared its performance with published detectors. Our detecting approach estimates the signal envelope distribution to discriminate IEDs from background activity. Results. Readers together labelled 6,518 IEDs (53±21% obvious, 47±21% ambiguous). The reader’s maximal match was 58% in pair and agreement of all three readers was only 30% (Cohen’s kappa 0.14±0.11). Detector’s performance was characterized by sensitivity 91±12% and 8±7 false positives per min and per channel. Its performance was 1.4x better than published detector. Examination of false positives revealed that substantial proportion had shape of reminiscent of IEDs, but with lower amplitude. More
- Objective. Interictal epileptiform discharges (IEDs) are electrographic hallmark of epilepsy. Information about the spatiotemporal distribution of IEDs in intracranial EEG is utilized to localize epileptogenic zone during the presurgical evaluation and plan the resection. Visual evaluation of long-term multi-channel intracranial recordings is extremely difficult and prone to bias. Clinicians usually assess only high-amplitude (high signal to noise ratio) discharge and low-amplitude IEDs can be overlooked or considered clinically insignificant. The goal of our study was to develop reliable automatic IED detectors to facilitate analysis of long-term recordings and increase the information yield of intracranial recordings. Methods. Seven intracranial EEG recordings were randomly selected from our database. Samples of five minutes duration from fifteen high-rate IED channels (525 minutes in total) were presented to three experienced EEG specialists for spike labelling. The readers independently reviewed the data and classified IEDs into two groups: obvious and ambiguous. The inter-reader agreement was evaluated and IEDs labelled by at least two readers were considered as a gold standard (GS). We have developed, tested and optimized novel IED detector using GS datasets and compared its performance with published detectors. Our detecting approach estimates the signal envelope distribution to discriminate IEDs from background activity. Results. Readers together labelled 6,518 IEDs (53±21% obvious, 47±21% ambiguous). The reader’s maximal match was 58% in pair and agreement of all three readers was only 30% (Cohen’s kappa 0.14±0.11). Detector’s performance was characterized by sensitivity 91±12% and 8±7 false positives per min and per channel. Its performance was 1.4x better than published detector. Examination of false positives revealed that substantial proportion had shape of reminiscent of IEDs, but with lower amplitude. More (en)
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| Title
| - Clinical evaluation versus automatic detection of interictal epileptiform discharges – who can we trust?
- Clinical evaluation versus automatic detection of interictal epileptiform discharges – who can we trust? (en)
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| skos:prefLabel
| - Clinical evaluation versus automatic detection of interictal epileptiform discharges – who can we trust?
- Clinical evaluation versus automatic detection of interictal epileptiform discharges – who can we trust? (en)
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| skos:notation
| - RIV/68407700:21230/14:00223610!RIV15-MSM-21230___
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| http://linked.open...avai/riv/aktivita
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| http://linked.open...avai/riv/aktivity
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| http://linked.open...vai/riv/dodaniDat
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| http://linked.open...aciTvurceVysledku
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| http://linked.open.../riv/druhVysledku
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| http://linked.open...iv/duvernostUdaju
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| http://linked.open...titaPredkladatele
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| http://linked.open...dnocenehoVysledku
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| http://linked.open...ai/riv/idVysledku
| - RIV/68407700:21230/14:00223610
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| http://linked.open...riv/jazykVysledku
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| http://linked.open.../riv/klicovaSlova
| - interictal epileptiform discharges; epilepsy; automatic detection (en)
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| http://linked.open.../riv/klicoveSlovo
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| http://linked.open...ontrolniKodProRIV
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| http://linked.open...in/vavai/riv/obor
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| http://linked.open...ichTvurcuVysledku
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| http://linked.open...cetTvurcuVysledku
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| http://linked.open...vavai/riv/projekt
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| http://linked.open...UplatneniVysledku
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| http://linked.open...iv/tvurceVysledku
| - Ježdík, Petr
- Čmejla, Roman
- Janča, Radek
- Kršek, P.
- Jiruška, P.
- Marusič, P.
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| http://localhost/t...ganizacniJednotka
| |
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