Sensitivity of quantitative EEG for seizure identification in the … · 2017. 11. 22. · most are...

Hiba A Haider MDRosana Esteller PhDCecil D Hahn MD

MPHM Brandon Westover

MD PhDJonathan J Halford MDJong W LeeMouhsin M Shafi MD

PhDNicolas Gaspard PhDSusan T Herman MDElizabeth E Gerard MDLawrence J Hirsch MDJoshua A Ehrenberg BSc

R EEG T CNIMSuzette M LaRoche MDFor the Critical Care EEG

Monitoring ResearchConsortium

Correspondence toDr Haiderhibaarifemoryedu

Supplemental dataat Neurologyorg

Sensitivity of quantitative EEG for seizureidentification in the intensive care unit

ABSTRACT

Objective To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure iden-tification in the intensive care unit (ICU)

Methods Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEGdisplays Each epoch was reviewed in 3 formats raw EEG QEEG1 raw and QEEG-only Epochswere also analyzed by a proprietary seizure detection algorithm Nine neurophysiologists re-viewed raw EEGs to identify seizures to serve as the gold standard Nine other neurophysiologistswith experience in QEEG evaluated the epochs in QEEG formats with and without concomitantraw EEG Sensitivity and false-positive rates (FPRs) for seizure identification were calculated andmedian review time assessed

Results Mean sensitivity for seizure identification ranged from 51 to 67 for QEEG-only and63ndash68 for QEEG1 raw FPRs averaged 1h for QEEG-only and 05h for QEEG1 raw Meansensitivity of seizure probability software was 262ndash267 with FPR of 007h Epochs withthe highest sensitivities contained frequent intermittent seizures Lower sensitivities were seenwith slow-frequency low-amplitude seizures and epochs with rhythmic or periodic patternsMedian review times were shorter for QEEG (6 minutes) and QEEG1 raw analysis (145 minutes)vs raw EEG (19 minutes p 5 000003)

Conclusions A panel of QEEG trends can be used by experts to shorten EEG review time for seizureidentification with reasonable sensitivity and low FPRs The prevalence of false detections confirmsthat raw EEG reviewmust be used in conjunction with QEEG Studies are needed to identify optimalQEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel

Classification of evidence review This study provides Class II evidence that QEEG 1 raw inter-preted by experts identifies seizures in patients in the ICU with a sensitivity of 63ndash68 andFPR of 05 seizures per hour Neurologyreg 201687935ndash944

GLOSSARYACNS 5 American Clinical Neurophysiology Society aEEG 5 amplitude-integrated EEG CCEMRC 5 Critical Care EEGMonitoring Research Consortium CDSA 5 color density spectral array cEEG 5 continuous EEG CSA 5 compressedspectral array FPR 5 false-positive rate ICU 5 intensive care unit LPD 5 lateralized periodic discharge Q 5 quantitativeEEG alone QEEG5 quantitative EEGQR5 quantitative EEG with raw EEG R5 raw EEG without quantitative EEG SzD5seizure detection algorithm

Electrographic seizures occur in 8ndash48 of critically ill patients1ndash8 and can be found in anycritical care setting3 Minimizing delay to diagnosis of nonconvulsive status epilepticus is criticalas therapeutic interventions are most effective when initiated early910

Increasing awareness of electrographic seizures has led to a growing demand for continuousEEG (cEEG) monitoring but this is a labor and time-intensive process To facilitate interpre-tation of prolonged EEG recordings several quantitative EEG (QEEG) tools have been devel-oped QEEG is the visual representation of statistically transformed raw EEG signals The most

From the Department of Neurology (HAH JAE SML) Emory University School of Medicine Atlanta GA Neuropace Inc (RE) MountainView CA Division of Neurology (CDH) The Hospital for Sick Children and Department of Paediatrics University of Toronto CanadaDepartment of Neurology (MBW) Massachusetts General Hospital Harvard Medical School Boston Department of Neurology (JJH) MedicalUniversity of South Carolina Charleston Brigham and Womenrsquos Hospital (JWL MMS STH) Harvard Medical School Boston MA UniversiteacuteLibre de Bruxelles (NG) Brussels Belgium Department of Neurology (EEG) Northwestern University Feinberg School of Medicine Chicago ILand Yale University Hospital (LJH) New Haven CT

Coinvestigators are listed at Neurologyorg

Go to Neurologyorg for full disclosures Funding information and disclosures deemed relevant by the authors if any are provided at the end of the article

copy 2016 American Academy of Neurology 935

ordf 2016 American Academy of Neurology Unauthorized reproduction of this article is prohibited

commonly used QEEG tool is compressedspectral array (CSA) which consists of a colordisplay representing power in various frequencybands Other QEEG techniques display EEGdata based on amplitude (amplitude-integratedEEG [aEEG] envelope trend) rhythmicity(rhythmicity spectrogram) or spectral symme-try (asymmetry index and spectrogram) Thesetools are used to highlight significant electro-graphic events on cEEG and identify subtleEEG changes over prolonged periods of timeThere have been few studies assessing the sensi-tivity of QEEG for seizure identification andmost are single-center pediatric studies11ndash21 orfocused on the utility of single trends such asaEEG22 or CSA23 A systematic assessment ofthe accuracy of a panel of QEEG trends used indaily clinical practice is lacking

METHODS This study evaluated the sensitivity of a panel of

commonly applied QEEG techniques with and without the ability

to see the corresponding raw EEG for identification of seizures in

critically ill patients when used by experts frommultiple institutions

Standard protocol approvals registrations and patientconsents This study was approved by the institutional review

board at Emory University and was granted a waiver of informed

consent

cEEG recordings Using a clinical database we identified cEEGrecordings performed in patients admitted to the intensive care

unit (ICU) between 2008 and 2010 for any of the following in-

dications treatment of refractory status epilepticus suspicion of

seizures or management of intracranial pressure Six-hour EEG

epochs from 15 patients with and without seizures were

selected by one of the authors (HAH) to represent a variety

of EEG findings commonly encountered in the critical care

setting such as electrographic seizures rhythmic delta activity

and periodic discharges Digital EEG recordings were obtained

using commercially available CTMRI compatible electrodes

that were placed according to the International 10ndash20 system

All 15 EEG recordings (standardized 16-channels dis-

played longitudinal bipolar montage sampling rate 500 Hz)

were analyzed with QEEG tools available in the Insight II

EEG review software version 11 (Persyst Inc Prescott AZ)

Specific QEEG tools included in the analysis for review were

seizure probability envelope trend CSA rhythmicity spectro-

gram asymmetry spectrogram and aEEG (figure 1 table e-1 at

Neurologyorg) One hour of QEEG data was displayed per

screen on a 24-inch high-resolution (1600 3 1200 pixels)

monitor such that 44 horizontal pixels represented 10 sec-

onds of raw EEG data

cEEG review Each EEG epoch was reviewed in 3 formats raw

EEG without QEEG (R) QEEG with raw EEG (QR) and QEEG

alone (Q) (figure 2) All 9 raw EEG reviewers were board-eligible or

board-certified epileptologists selected from members of the Critical

Care EEG Monitoring Research Consortium (CCEMRC) Each

completed a training module24 based on the 2012 version of the

American Clinical Neurophysiology Society (ACNS) standardized

ICU EEG nomenclature25 with the aim of improving agreement on

use of the following terms seizures evolution periodic discharges

Figure 1 Example of a 1-hour quantitative EEG (QEEG) panel without automated seizure detection (SzD) as viewed by the QEEG and QEEG1

raw reviewers

All QEEG analyses are displayed as hemispheric averages with blue representing the left hemisphere and red representing the right hemisphere Frequencyscale ranges from 0 to 12 Hz This recording contained 5 electrographic seizures (see gray boxes)

936 Neurology 87 August 30 2016


and rhythmic delta activity Based on published criteria25ndash28

electrographic seizures were defined as a paroxysmal change in

EEG background lasting longer than 10 seconds with evolution

in morphology frequency or spatial distribution

Each R epoch was reviewed by 3 raw EEG reviewers who were

asked tomark the onset and offset of all seizures as well as themaximal

extent of seizure propagation generalized (8 channels) hemispheric

(5ndash8 channels) or focal (4 channels)29 They were also asked to

mark any rhythmic or periodic patterns (as defined by the ACNS

standardized critical care EEG terminology [25]) A gold standard

seizure was defined as a seizure marked by 2 out of 3 of the raw

reviewers with at least 50 overlap in seizure duration (figure e-1)

A separate panel of 9 QEEG experts were selected to review the

Q and QR epochs with 3 reviewers assigned to review each epoch

These QEEG experts had at least 1 year of experience using QEEG

in high-volume clinical practices Epochs were assigned such that

no reviewer reviewed the same epoch in both Q and QR formats

Reviewers were instructed to mark onsets of any events on the

QEEG that they thought were probable seizures Q reviewers did

not have access to raw EEG QR reviewers had access to the entire

raw EEG but were encouraged to only review the raw EEG corre-

sponding to QEEG areas of interest None of the reviewers had

access to patient video as we did not aim to have reviewers distin-

guish clinical from purely electrographic seizures

Seizure identification was considered positive if onset was

marked on a QEEG panel within either 1 or 25 minutes of

the seizure onset determined by the raw EEG reviewers (termed

maximal onset variation) Because the inherent limitations of

screen resolution would artifactually lower sensitivity in the

QEEG arm if using a maximal onset variation of just 1 minute

we allowed up to 25 minutes onset variation from the time of

the seizure onset determined by the raw EEG reviewers

For each Q and QR epoch the sensitivity for seizure identi-

fication was averaged among the 3 reviewers Subsequently the

mean and median sensitivity across all epochs was calculated Sen-

sitivities were computed in this way for both maximal onset var-

iations False-positive rates (FPRs) for seizure identification for

the Q and QR groups were also calculated

Automated seizure detection We assessed the sensitivity and

FPR of a proprietary automated seizure detection algorithm

(SzD) (seizure probability Insight II version 11 Persyst Inc)

with the threshold for seizure detection set to a value of 10 None

of the Q or QR reviewers had access to the SzD display (figure 1)

Review time and rating of QEEG utility The time required

by each R Q and QR reviewer to review each epoch was re-

corded In addition Q and QR reviewers were also asked to rate

the utility of each QEEG technique on a Likert scale ranging

from 1 to 5 (1 5 least useful)

Statistical analysis Means medians and interquartile ranges

for sensitivities and FPR were reported for the Q QR and

Figure 2 Study methodology EEG formatting and review algorithm

ACNS 5 American Clinical Neurophysiology Society CCEMRC 5 Critical Care EEG Monitoring Research Consortium ICU 5 intensive care unit QEEG 5

quantitative EEG SzD 5 seizure detection algorithm

Neurology 87 August 30 2016 937


SzD group for 2 maximal onset variations (1 and 25 minutes)

Median reviewing times and ranges for each epoch as well as over-

all were also reported for the Raw Q and QR reviewers A non-

parametric Friedman test of differences among repeated measures

(Matlab Mathworks Natick MA) was conducted to determine

statistical significance

RESULTS Seizure characteristics Across 15 epochsthere were on average 105 gold standard seizuresper epoch (total 126 range 0ndash49) 32 of seizureswere generalized 36 hemispheric 28 focal andthe remaining 4 were marked as indeterminate

Sensitivity and FPRs for seizure identification Meansensitivity for Q 5 67 and QR 5 68 was usingthe 25-minute maximal onset variation time As ex-pected sensitivity declined with decreasing maximalonset variation Q 5 51 and QR 5 63 whenthe maximal onset variation allowed was 1 minute(table 1) The mean FPRs across all epochs were 1hfor Q reviewers and 05h for QR reviewers (table 1)

Compared to visual identification of seizures in Qand QR groups SzD had a mean sensitivity of 27and 25 when allowing maximal onset variationsof 25 and 1 minute respectively mean FPR was007h

Factors influencing sensitivity and FPRs for seizure

identification Compared to gold standard seizures de-tected on raw EEG review the Q and QR reviewshowed significant variability in sensitivity This wasprimarily due to differing characteristics of the indi-vidual raw EEG recordings (table 1 figures e-1ndashe-3) The highest sensitivities were seen in sampleswith frequent hemispheric seizures (epochs 5 911 Q sensitivity 97 92 and 77 and QR97 79 and 87 respectively) These epochsalso had few or no false-positive detections whichmay reflect the infrequent occurrence of artifact andperiodic patterns in these epochs

Lower sensitivity was seen in epochs with low-frequency slowly evolving low-amplitude seizuresbut sensitivities improved when reviewers had accessto raw EEG (epoch 4 mean Q 5 42 median25 mean QR 5 42 median 50 epoch 10mean Q 5 305 QR 5 69)

Of epochs that demonstrated lower sensitivity on Qthan QR some epochs (eg 1 and 4) also had pooragreement among raw reviewers Epoch 1 containedfrequent lateralized periodic discharges (LPDs) overthe right temporal region that were clearly distinguishedfrom background activity However at times the LPDsevolved to electrographic seizures with a QEEG signa-ture very similar to the LPDs (figure 3) Consequently1 of 3 R reviewers labeled all electrographic seizures asLPDs alone leading to poor raw EEG agreement forthis epoch Epoch 4 had occasional prolonged seizuresin addition to frequent runs of rhythmic delta activity

that did not meet ictal criteria as a source of pooragreement among raw reviewers These are good exam-ples of the controversial ictal-interictal continuum forwhich there is considerable variability in interrateragreement

On the other hand some epochs demonstratedgood agreement on raw EEG review but Q sensitivitywas still suboptimal even with concomitant raw EEGIn epoch 6 (figure e-2) seizures were brief and low-amplitude compared to background Although thisraw EEG pattern resulted in a subtle QEEG signalit was stereotyped and characteristic of an ictal pat-tern This is an example of the power of identifyingan initial signature ictal pattern which can lead torapid identification of subsequent ictal events of sim-ilar morphology

With certain epochs the QR group displayedlower sensitivity compared to Q group (epochs 1 79) These epochs had a predominance of periodic pat-terns that might have led the reviewer to changeimpression from seizure to periodic patterns upon re-viewing the raw EEG

Review time and rating of QEEG utility Median EEGreview times (figure 4) were shorter for QEEG alone(6 minutes) and QR (145 minutes) compared to rawEEG review (19 minutes p 5 000003) Based onself-reported Likert scale ratings CSA andrhythmicity spectrogram were perceived as the mosthelpful QEEG techniques for visual identification ofseizures

DISCUSSION This multicenter study provides ClassII evidence that a panel of multiple QEEG trendsviewed by experts can be used to identify seizures incritically ill adults with reasonable sensitivity andlow FPR and significantly shortens review time com-pared to comprehensive raw EEG interpretation

A prior study23 investigating the sensitivity of a singleQEEG trend (CSA) in 113 adults (39 with seizures)found a median sensitivity of 942 of seizures perrecording Although our study had lower sensitivityour FPR was lower as the aim of our study was to assessthe accuracy of seizure identification by experts and notjust the performance of QEEG as a screening tool

Other studies evaluating QEEG sensitivity wereperformed in pediatric patients One study12 reporteda median sensitivity of 833 of seizures identifiedper recording using color density spectral array(CDSA) and 815 using aEEG Missed seizures fellinto the following categories low voltage (75 mV)short duration (1 minute) focal or seizures thatoccurred in the context of abundant interictal epilep-tiform discharges Our study confirms that epochswith low-frequency and low-amplitude seizures hadlower sensitivities



Table 1 Characteristics of individual epochs sensitivity (using a maximal onset variation of 25 and 1 minute) and false-positive rates

Epoch noNo ofseizures

Seizure characteristics

Maximalonsetvariation min

Sensitivity

False-positiverate mean no ofseizuresh

Duration

Amplitude(compared tobackgroundactivity)

Maximalspatial extent

Typicalfrequency

CoexistingPDs or RDA

Q QR SzD

Q QR SzDMean (median) range across 3 reviewers Mean

1 23 Brief High Focal 1ndash2 Hz FrequentLPDs

25 97 (957) 957ndash100 522 (608) 0ndash957 22 068 017 000

1 898 (913) 782ndash100 391 (217) 0ndash95 1304

2 1 Prolonged High Generalized Obscured bymuscle

No 25 100 (100) 100ndash100 100 (100) 100ndash100 100 000 000 000

1 33 (0) 0ndash0 100 (100) 100ndash100 100

3 1 Prolonged Low Generalizedhemispheric

2ndash3 Hz Frequent RDA 25 33 (0) 0ndash100 33 (0) 0ndash100 0 391 039 017

1 0 (0) 0ndash0 33 (0) 0ndash100 0

4 4 Prolonged Low Focal 1 Hz Frequent RDA 25 42 (25) 25ndash75 42 (50) 25ndash50 0 023 289 000

1 42 (25) 25ndash75 42 (50) 25ndash50 0

5 49 Brief High Hemispheric 4ndash6 Hz No 25 97 (959) 959ndash100 97 (98) 938ndash100 245 000 000 000

1 97 (959) 938ndash100 97 (98) 938ndash100 224

6 7 Brief Equal Focal 6ndash8 Hz No 25 71 (857) 286ndash100 33 (0) 0ndash100 0 000 000 000

1 71 (857) 286ndash100 33 (0) 0ndash100 0

7 4 Brief Equallow Hemispheric 3ndash4 Hz No 25 333 (50) 0ndash50 58 (75) 0ndash100 0 699 10 018

1 166 (25) 0ndash25 50 (50) 0ndash100 0

8 1 Brief High Hemispheric 2ndash3 Hz AbundantPDs

25 67 (100) 0ndash100 100 (100) 100ndash100 100 091 000 000

1 67 (100) 0ndash100 100 (100) 100ndash100 100

9 13 Brief High Generalizedhemispheric

2ndash3 Hz No 25 92 (92) 846ndash100 79 (846) 692ndash846 539 083 000 000

1 87 (85) 769ndash100 769 (769) 692ndash846 462

10 12 Brief Low Focal 1 Hz No 25 305 (33) 166ndash416 69 (833) 417ndash833 0 016 060 000

1 305 (33) 166ndash416 69 (833) 417ndash833 0

11 10 Intermediate High Focal 2ndash25 Hz No 25 77 (800) 70ndash80 87 (900) 80ndash90 20 000 011 033

1 73 (70) 70ndash80 87 (900) 80ndash90 18

12 1 Intermediate High Focal 3ndash5 Hz AbundantGPDs

25 67 (100) 0ndash100 67 (0) 0ndash100 100 116 144 000

1 0 (0) 0ndash0 333 (0) 0ndash100 0

13 0 NA NA NA NA NA NA NA NA 610 033 033

Continued

Neurology

87

August

302

016

939


In another single-center study11 experiencedQEEG readers were significantly more accurate thaninexperienced readers particularly when reviewingthe envelope trend (87 vs 52) Our study sup-ports similar seizure detection rates by experiencedQEEG reviewers Despite the fact that the QEEGpanel utilized in our study consisted of a larger num-ber of QEEG trends (5 trends vs 2 or fewer in priorstudies) the accuracy of seizure identification was nobetter than prior studies This reflects the complexityand variation in our EEG samples seizures of differ-ent morphology and spatial extent may be best iden-tified using one QEEG trend display over another

This study incorporated several methodologic de-tails in an attempt to answer specific clinical questionsWe recruited several experienced electroencephalogra-phers who routinely utilize QEEG from various centersacross the CCEMRC Our methods were more strin-gent compared to real-life practice as we asked QEEGreviewers to mark only probable or likely seizures in aneffort to ascertain a more realistic FPR It was ourexpectation that expert reviewers would be more dis-cerning with better differentiation of nonictal patterns(such as mechanical artifact and arousal patterns) fromseizures We also chose to withhold access to concur-rent video recording in order to provide a more focusedevaluation of the EEG interpretation alone withoutclinical bias Allowing access to the video recordingmay have decreased the rate of false-positive detectionsby allowing proper identification of seizure-mimickingartifacts but would have come at the expense ofincreased review time Despite these stringent condi-tions sensitivities for seizure identification were com-parable to several of the aforementioned studies andFPRs were much lower EEG data was selected by onlyone investigator which may introduce selection biashowever the EEG epochs were intended to containseizures of various frequencies durations and locationsin order to replicate the diversity of seizure patternsseen in daily clinical practice In addition some epochscontained abundant rhythmic and periodic patternswhich are known to be difficult to differentiate fromelectrographic seizures

Prior studies have shown low to moderate interrateragreement for detection of electrographic seizures incritically ill patients even among experts3031 henceour analysis required raw EEG agreement among atleast 2 reviewers to determine gold standard seiz-ures It follows however that some reduction inQEEG sensitivity may arise from suboptimal inter-rater agreement on some QEEG epochs due to thenature of the patterns they contain and not neces-sarily a limitation of using QEEG itself This issupported by the fact that epochs with abundantrhythmic or periodic patterns as well as periods ofreactivity exhibited not only a higher FPR overall

Tab

le1

Con

tinu

ed

Epoc

hno

No

ofse

izur

es

Seizu

rech

arac

teristics

Max

imal

onse

tva

riat

ion

min

Sen

sitivity

False

-pos

itive

rate

mea

nno

of

seizur

esh

Dur

ation

Amplitud

e(com

pare

dto

bac

kgro

und

activity

)Max

imal

spat

iale

xten

tTyp

ical

freq

uenc

yCoe

xisting

PDsor

RDA

QQR

SzD

QQR

SzD

Mea

n(m

edian)

ra

ngeac

ross

3re

view

ers

Mea

n

14

0NA

NA

NA

NA

NA

NA

NA

NA

167

000

000

15

0NA

NA

NA

NA

NA

NA

NA

NA

20

033

017

Mea

nov

erall

126

51

ndash67

63

ndash68

262

ndash267

209

012

008

Abb

reviations

GPD

5ge

neraliz

edpe

riod

icdisc

harg

eLP

D5

lateraliz

edpe

riod

icdisc

harg

ePD

5pe

riod

icdisc

harg

eQ

5qu

antitative

EEG

alon

eQR

5qu

antitative

EEG

withraw

EEGR

DA

5rhythm

icde

lta

activityS

zD5

seizurede

tectionalgo

rithm

Durationof

seizures

define

das

follo

ws

brief10ndash60

seco

nds

interm

ediate

1ndash5

minutes

prolong

ed5

minutes



but also a wider range of FPRs among reviewerssuggesting interrater disagreement in QEEG inter-pretation This highlights an important observationthat periodic patterns may frequently resemble

seizures on QEEG and accurate distinctions canbe difficult even with concomitant raw EEG reviewespecially when periodic patterns evolve into seiz-ures This supports findings from a prior study of

Figure 3 Epoch 1 Periodic discharges mimicking electrographic seizures on quantitative EEG (QEEG)

This epoch contained frequent brief lateralized periodic discharges (LPDs) over the right temporal region that were occa-sionally nonevolving (black arrows) but often evolved into electrographic seizures (red arrows) The QEEG signature seen atthe time of nonevolving periodic discharges (black arrowevent A raw EEG panel A) is very similar to the QEEG pattern seenduring the ictal pattern (red arrowevent B raw EEG panel B) One of 3 raw EEGwithout QEEG reviewers labeled all electro-graphic seizures as LPDs alone Automated seizure detection identified very few of the electrographic seizures (Note thatseizure detection algorithm trend [ldquoseizure probabilityrdquo at the top of the figure] is included here for comparison but was notvisible to quantitative EEG alone or quantitative EEG with raw EEG reviewers)



interrater agreement of the ACNS ICU EEG termi-nology where interrater agreement for evolution ofperiodic patterns was only fair (21)32

An important feature of our study was the assess-ment of an automated seizure detection algorithm(SzD) Sensitivity of SzD was much lower comparedwith human identification with Q or QR reviewSimilar to human review lower sensitivities for SzDwere seen in epochs with low amplitude slowly evolv-ing seizures or with abundant periodic patternsAdjusting the manufacturerrsquos default settings for theSzD algorithm may have increased its sensitivity atthe expense of a higher FPR Our results suggest thatautomated seizure detection in the ICU setting willrequire further advances to improve sensitivity in theICU setting before approaching the performance ofexpert QEEG users

QEEG analysis saves significant review time eitheralone or in conjunction with raw EEG corroboratingthe results of another recent study by Moura et al33

They reported a sensitivity of 873 for seizure detec-tion using CDSA and significant time-savings compar-ing QEEG to conventional EEG review (8 6 4minutes for CSA-guided review vs 38 6 17 minutesfor conventional review p 0005) Similar to this

study33 our study demonstrates that time-savings ofQEEG over raw EEG review was greater for epochswith no or few seizures compared to epochs with mul-tiple seizures This may partly have been due to in-structions to mark all seizures no matter how briefwhich is not usually done in routine practice

Prior research suggests that although QEEG dis-plays are a useful screening tool for seizure identifica-tion there is potential for false-positives especiallywhen used by inexperienced personnel2334 Our studydemonstrates that expert review of a panel of QEEGtrends leads to lower FPRs with acceptable sensitivitysimilar to prior studies However intermittent rawEEG assessment is still necessary to confirm seizuressuspected on QEEG Hence we recommend thatQEEG be used as a screening tool to guide directedraw EEG review by an experienced neurophysiologistin order to maximize sensitivity while minimizingfalse-positive detections Additional guidance on theuse of QEEG in clinical practice can be found in theACNS Consensus Statement on Continuous EEG inCritically Ill Adults and Children35

This study demonstrates reasonable overall sensitiv-ity of QEEG for seizure detection but is variable basedon the electrographic pattern Sensitivity is highest for

Figure 4 Comparison of reviewing time for reviewers when using raw EEG without quantitative EEGquantitative EEG with raw EEG and quantitative EEG alone

Note that epochs 2 and 5 required significantly more time for raw review by one reviewer Both of these epochs containedprolonged seizures that were marked as such by 2 of the raw EEG reviewers However one reviewer annotated both ofthese epochs as containing multiple short seizures We suspect that the additional review time was required by thisreviewer in order to distinguish and annotate each seizure



frequent seizures of higher amplitude than backgroundactivity and propagation beyond initial onset Lowersensitivities were seen for brief low-amplitude focalseizures Knowing which patterns are identified lessreadily on QEEG allows the reviewer to understandthe limitations of QEEG review What remains to bedetermined is the clinical impact if any of failing todetect brief focal and infrequent electrographic eventsFurther investigations are needed to optimize the use ofQEEG as a screening tool for identification of seizuresas well as other rhythmic and periodic patterns thatmay not clearly meet seizure criteria but may still beof clinical significance Efforts should include investi-gating which trend combinations as well as time fre-quency and amplitude scales provide a panel thatoptimally displays various seizure types and improvesinterrater agreement Finally research is needed to eval-uate the feasibility of using QEEG in real time at thebedside with interpretation performed by personnelwith no formal EEG training Although automated sei-zure detection software is rapidly evolving with advan-ces in artifact rejection to reduce false detectionsimprovements in sensitivity are still needed These ad-vances in the use of QEEG in the ICU setting havepotential for improving outcomes of critically ill pa-tients by reducing time to accurate recognition andtreatment of electrographic seizures

AUTHOR CONTRIBUTIONSHiba Arif Haider draftingrevising the manuscript study concept or

design analysis or interpretation of data accepts responsibility for con-

duct of research and final approval acquisition of data study supervision

obtaining funding Rosana Esteller draftingrevising the manuscript

analysis or interpretation of data accepts responsibility for conduct of

research and final approval statistical analysis Cecil David Hahn draft-

ingrevising the manuscript study concept or design analysis or interpre-

tation of data accepts responsibility for conduct of research and final

approval acquisition of data Michael Brandon Westover draftingrevis-

ing the manuscript accepts responsibility for conduct of research and

final approval Jonathan J Halford draftingrevising the manuscript


research and final approval Jongwoo Lee draftingrevising the manu-

script analysis or interpretation of data accepts responsibility for conduct

of research and final approval acquisition of data Mouhsin M Shafi

draftingrevising the manuscript analysis or interpretation of data ac-

cepts responsibility for conduct of research and final approval Nicolas

Gaspard draftingrevising the manuscript analysis or interpretation of

data accepts responsibility for conduct of research and final approval

Susan T Herman draftingrevising the manuscript accepts responsibility

for conduct of research and final approval review of EEG data samples

Elizabeth E Gerard draftingrevising the manuscript analysis or inter-

pretation of data accepts responsibility for conduct of research and final

approval acquisition of data Lawrence J Hirsch draftingrevising the

manuscript accepts responsibility for conduct of research and final

approval Joshua Andrew Ehrenberg draftingrevising the manuscript

study concept or design accepts responsibility for conduct of research

and final approval acquisition of data Suzette M LaRoche drafting

revising the manuscript study concept or design analysis or interpreta-

tion of data accepts responsibility for conduct of research and final

approval acquisition of data study supervision

STUDY FUNDINGNo targeted funding reported

DISCLOSUREH Haider Supported by an NINDS R25 Research Education Training

Grant R Esteller C Hahn M Westover J Halford J Lee M Shafi

N Gaspard S Herman E Gerard L Hirsch J Ehrenberg and

S LaRoche report no disclosures relevant to the manuscript Go to

Neurologyorg for full disclosures

Received September 21 2015 Accepted in final form May 19 2016

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2 Friedman D Claassen J Hirsch LJ Continuous electro-

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Anesth Analg 2009109506ndash523

3 Jette N Claassen J Emerson RG Hirsch LJ Frequency

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Continuous electroencephalography in the medical inten-

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Digital video-electroencephalographic monitoring in the

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a delayed prolonged increase in intracranial pressure and

metabolic crisis Crit Care Med 2007352830ndash2836

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intracerebral hemorrhage a factor in progressive midline

shift and outcome Neurology 2003601441ndash1446

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dence and impact of nonconvulsive and convulsive seizures

after traumatic brain injury as detected by continuous

electroencephalographic monitoring J Neurosurg 1999

91750ndash760

9 Lowenstein DH Alldredge BK Status epilepticus at an

urban public hospital in the 1980s Neurology 199343

483ndash488

10 Mazarati AM Baldwin RA Sankar R Wasterlain CG

Time-dependent decrease in the effectiveness of antiepi-

leptic drugs during the course of self-sustaining status epi-

lepticus Brain Res 1998814179ndash185

11 Akman CI Micic V Thompson A Riviello JJ Jr Seizure

detection using digital trend analysis factors affecting util-

ity Epilepsy Res 20119366ndash72

12 Stewart CP Otsubo H Ochi A Sharma R Hutchison JS

Hahn CD Seizure identification in the ICU using quan-

titative EEG displays Neurology 2010751501ndash1508

13 Abend NS Dlugos D Herman S Neonatal seizure detec-

tion using multichannel display of envelope trend Epilep-

sia 200849349ndash352

14 Bourez-Swart MD van Rooij L Rizzo C et al Detection

of subclinical electroencephalographic seizure patterns

with multichannel amplitude-integrated EEG in full-

term neonates Clin Neurophysiol 20091201916ndash1922

15 El-Dib M Chang T Tsuchida TN Clancy RR Amplitude-

integrated electroencephalography in neonates Pediatr Neu-

rol 200941315ndash326

16 Rennie JM Chorley G Boylan GB Pressler R Nguyen Y

Hooper R Non-expert use of the cerebral function



monitor for neonatal seizure detection Arch Dis Child

Fetal Neonatal Ed 200489F37ndashF40

17 Shah DK de Vries LS Hellstrom-Westas L Toet MC

Inder TE Amplitude-integrated electroencephalography in

the newborn a valuable tool Pediatrics 2008122863ndash865

18 Shellhaas RA Soaita AI Clancy RR Sensitivity of

amplitude-integrated electroencephalography for neonatal

seizure detection Pediatrics 2007120770ndash777

19 Toet MC van der Meij W de Vries LS Uiterwaal CS van

Huffelen KC Comparison between simultaneously re-

corded amplitude integrated electroencephalogram (cere-

bral function monitor) and standard electroencephalogram

in neonates Pediatrics 2002109772ndash779

20 Pensirikul AD Beslow LA Kessler SK et al Density spec-

tral array for seizure identification in critically ill children

J Clin Neurophysiol 201330371ndash375

21 Topjian AA Fry M Jawad AF et al Detection of electro-

graphic seizures by critical care providers using color den-

sity spectral array after cardiac arrest is feasible Pediatr Crit

Care Med 201516461ndash467

22 Nitzschke R Muller J Engelhardt R Schmidt GN Sin-

gle-channel amplitude integrated EEG recording for the

identification of epileptic seizures by nonexpert physicians

in the adult acute care setting J Clin Monit Comput

201125329ndash337

23 Williamson CA Wahlster S Shafi MM Westover MB

Sensitivity of compressed spectral arrays for detecting seiz-

ures in acutely ill adults Neurocrit Care 20142032ndash39

24 ACNS Nomenclature Training Module Critical Care EEG

Monitoring Research Consortium [online] Available at

httpwwwacnsorgresearchcritical-care-eeg-monitoring-

research-consortium-ccemrceducation Accessed April 3

2016

25 Hirsch LJ LaRoche SM Gaspard N et al American

Clinical Neurophysiology Societyrsquos standardized critical

care EEG terminology 2012 version J Clin Neurophysiol

2013301ndash27

26 Hirsch LJ Brenner RP Drislane FW et al The ACNS

subcommittee on research terminology for continuous

EEG monitoring proposed standardized terminology for

rhythmic and periodic EEG patterns encountered in crit-

ically ill patients J Clin Neurophysiol 200522128ndash135

27 Beniczky S Hirsch LJ Kaplan PW et al Unified EEG

terminology and criteria for nonconvulsive status epilepti-

cus Epilepsia 201354(suppl 6)28ndash29

28 Kaplan PW EEG criteria for nonconvulsive status epilep-

ticus Epilepsia 200748(suppl 8)39ndash41

29 S RS S OS Husain AM Seizure burden score a quanti-

tative description of seizure intensity in continuous EEG

recordings Presented at the 4th London-Innsbruck Col-

loquium on Status Epilepticus and Acute Seizures 2013

Salzburg Austria

30 Ronner HE Ponten SC Stam CJ Uitdehaag BM Inter-

observer variability of the EEG diagnosis of seizures in

comatose patients Seizure 200918257ndash263

31 Halford JJ Shiau D Desrochers JA et al Inter-rater agree-

ment on identification of electrographic seizures and peri-

odic discharges in ICU EEG recordings Clin

Neurophysiol 20151261661ndash1669

32 Gaspard N Hirsch LJ LaRoche SM Hahn CD

Westover MB Critical Care EEGMRC Interrater agree-

ment for critical care EEG terminology Epilepsia 2014

551366ndash1373

33 Moura LM Shafi MM Ng M et al Spectrogram screen-

ing of adult EEGs is sensitive and efficient Neurology

20148356ndash64





35 Herman ST Abend NS Bleck TP et al Consensus state-

ment on continuous EEG in critically ill adults and chil-

dren part II personnel technical specifications and

clinical practice J Clin Neurophysiol 20153296ndash108

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DOI 101212WNL0000000000003034201687935-944 Published Online before print July 27 2016Neurology

Hiba A Haider Rosana Esteller Cecil D Hahn et al Sensitivity of quantitative EEG for seizure identification in the intensive care unit

This information is current as of July 27 2016

ServicesUpdated Information amp

httpwwwneurologyorgcontent879935fullhtmlincluding high resolution figures can be found at

Supplementary Material

003034DC3httpwwwneurologyorgcontentsuppl20161206WNL0000000000


003034DC1httpwwwneurologyorgcontentsuppl20160727WNL0000000000Supplementary material can be found at

References httpwwwneurologyorgcontent879935fullhtmlref-list-1

This article cites 33 articles 9 of which you can access for free at

Subspecialty Collections

httpwwwneurologyorgcgicollectioneeg_see_epilepsy-seizuresEEG see EpilepsySeizures

httpwwwneurologyorgcgicollectioneeg_EEGfollowing collection(s) This article along with others on similar topics appears in the

Permissions amp Licensing

httpwwwneurologyorgmiscaboutxhtmlpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in

Reprints

httpwwwneurologyorgmiscaddirxhtmlreprintsusInformation about ordering reprints can be found online

rights reserved Print ISSN 0028-3878 Online ISSN 1526-632X1951 it is now a weekly with 48 issues per year Copyright copy 2016 American Academy of Neurology All

reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology

commonly used QEEG tool is compressedspectral array (CSA) which consists of a colordisplay representing power in various frequencybands Other QEEG techniques display EEGdata based on amplitude (amplitude-integratedEEG [aEEG] envelope trend) rhythmicity(rhythmicity spectrogram) or spectral symme-try (asymmetry index and spectrogram) Thesetools are used to highlight significant electro-graphic events on cEEG and identify subtleEEG changes over prolonged periods of timeThere have been few studies assessing the sensi-tivity of QEEG for seizure identification andmost are single-center pediatric studies11ndash21 orfocused on the utility of single trends such asaEEG22 or CSA23 A systematic assessment ofthe accuracy of a panel of QEEG trends used indaily clinical practice is lacking

METHODS This study evaluated the sensitivity of a panel of

commonly applied QEEG techniques with and without the ability

to see the corresponding raw EEG for identification of seizures in

critically ill patients when used by experts frommultiple institutions

Standard protocol approvals registrations and patientconsents This study was approved by the institutional review

board at Emory University and was granted a waiver of informed

consent

cEEG recordings Using a clinical database we identified cEEGrecordings performed in patients admitted to the intensive care

unit (ICU) between 2008 and 2010 for any of the following in-

dications treatment of refractory status epilepticus suspicion of

seizures or management of intracranial pressure Six-hour EEG

epochs from 15 patients with and without seizures were

selected by one of the authors (HAH) to represent a variety

of EEG findings commonly encountered in the critical care

setting such as electrographic seizures rhythmic delta activity

and periodic discharges Digital EEG recordings were obtained

using commercially available CTMRI compatible electrodes

that were placed according to the International 10ndash20 system

All 15 EEG recordings (standardized 16-channels dis-

played longitudinal bipolar montage sampling rate 500 Hz)

were analyzed with QEEG tools available in the Insight II

EEG review software version 11 (Persyst Inc Prescott AZ)

Specific QEEG tools included in the analysis for review were

seizure probability envelope trend CSA rhythmicity spectro-

gram asymmetry spectrogram and aEEG (figure 1 table e-1 at

Neurologyorg) One hour of QEEG data was displayed per

screen on a 24-inch high-resolution (1600 3 1200 pixels)

monitor such that 44 horizontal pixels represented 10 sec-

onds of raw EEG data

cEEG review Each EEG epoch was reviewed in 3 formats raw

EEG without QEEG (R) QEEG with raw EEG (QR) and QEEG

alone (Q) (figure 2) All 9 raw EEG reviewers were board-eligible or

board-certified epileptologists selected from members of the Critical

Care EEG Monitoring Research Consortium (CCEMRC) Each

completed a training module24 based on the 2012 version of the

American Clinical Neurophysiology Society (ACNS) standardized

ICU EEG nomenclature25 with the aim of improving agreement on

use of the following terms seizures evolution periodic discharges

Figure 1 Example of a 1-hour quantitative EEG (QEEG) panel without automated seizure detection (SzD) as viewed by the QEEG and QEEG1

raw reviewers

All QEEG analyses are displayed as hemispheric averages with blue representing the left hemisphere and red representing the right hemisphere Frequencyscale ranges from 0 to 12 Hz This recording contained 5 electrographic seizures (see gray boxes)




















































































Sensitivity


Duration



Typicalfrequency


Q QR SzD



25 97 (957) 957ndash100 522 (608) 0ndash957 22 068 017 000

1 898 (913) 782ndash100 391 (217) 0ndash95 1304


No 25 100 (100) 100ndash100 100 (100) 100ndash100 100 000 000 000

1 33 (0) 0ndash0 100 (100) 100ndash100 100



1 0 (0) 0ndash0 33 (0) 0ndash100 0


1 42 (25) 25ndash75 42 (50) 25ndash50 0


1 97 (959) 938ndash100 97 (98) 938ndash100 224


1 71 (857) 286ndash100 33 (0) 0ndash100 0


1 166 (25) 0ndash25 50 (50) 0ndash100 0


25 67 (100) 0ndash100 100 (100) 100ndash100 100 091 000 000

1 67 (100) 0ndash100 100 (100) 100ndash100 100



1 87 (85) 769ndash100 769 (769) 692ndash846 462


1 305 (33) 166ndash416 69 (833) 417ndash833 0


1 73 (70) 70ndash80 87 (900) 80ndash90 18


25 67 (100) 0ndash100 67 (0) 0ndash100 100 116 144 000

1 0 (0) 0ndash0 333 (0) 0ndash100 0


Continued

Neurology

87

August

302

016

939





Tab

le1

Con

tinu

ed

Epoc

hno

No

ofse

izur

es

Seizu

rech

arac

teristics

Max

imal

onse

tva

riat

ion

min

Sen

sitivity

False

-pos

itive

rate

mea

nno

of

seizur

esh

Dur

ation

Amplitud

e(com

pare

dto

bac

kgro

und

activity

)Max

imal

spat

iale

xten

tTyp

ical

freq

uenc

yCoe

xisting

PDsor

RDA

QQR

SzD

QQR

SzD

Mea

n(m

edian)

ra

ngeac

ross

3re

view

ers

Mea

n

14

0NA

NA

NA

NA

NA

NA

NA

NA

167

000

000

15

0NA

NA

NA

NA

NA

NA

NA

NA

20

033

017

Mea

nov

erall

126

51

ndash67

63

ndash68

262

ndash267

209

012

008

Abb

reviations

GPD

5ge

neraliz

edpe

riod

icdisc

harg

eLP

D5

lateraliz

edpe

riod

icdisc

harg

ePD

5pe

riod

icdisc

harg

eQ

5qu

antitative

EEG

alon

eQR

5qu

antitative

EEG

withraw

EEGR

DA

5rhythm

icde

lta

activityS

zD5

seizurede

tectionalgo

rithm

Durationof

seizures

define

das

follo

ws

brief10ndash60

seco

nds

interm

ediate

1ndash5

minutes

prolong

ed5

minutes






























































2004621743ndash1748


























91750ndash760



483ndash488













sia 200849349ndash352







rol 200941315ndash326





























201125329ndash337








2016




2013301ndash27















Salzburg Austria











551366ndash1373



20148356ndash64










Look Whatrsquos New






















Reprints





















































































Sensitivity


Duration



Typicalfrequency


Q QR SzD



25 97 (957) 957ndash100 522 (608) 0ndash957 22 068 017 000

1 898 (913) 782ndash100 391 (217) 0ndash95 1304


No 25 100 (100) 100ndash100 100 (100) 100ndash100 100 000 000 000

1 33 (0) 0ndash0 100 (100) 100ndash100 100



1 0 (0) 0ndash0 33 (0) 0ndash100 0


1 42 (25) 25ndash75 42 (50) 25ndash50 0


1 97 (959) 938ndash100 97 (98) 938ndash100 224


1 71 (857) 286ndash100 33 (0) 0ndash100 0


1 166 (25) 0ndash25 50 (50) 0ndash100 0


25 67 (100) 0ndash100 100 (100) 100ndash100 100 091 000 000

1 67 (100) 0ndash100 100 (100) 100ndash100 100



1 87 (85) 769ndash100 769 (769) 692ndash846 462


1 305 (33) 166ndash416 69 (833) 417ndash833 0


1 73 (70) 70ndash80 87 (900) 80ndash90 18


25 67 (100) 0ndash100 67 (0) 0ndash100 100 116 144 000

1 0 (0) 0ndash0 333 (0) 0ndash100 0


Continued

Neurology

87

August

302

016

939





Tab

le1

Con

tinu

ed

Epoc

hno

No

ofse

izur

es

Seizu

rech

arac

teristics

Max

imal

onse

tva

riat

ion

min

Sen

sitivity

False

-pos

itive

rate

mea

nno

of

seizur

esh

Dur

ation

Amplitud

e(com

pare

dto

bac

kgro

und

activity

)Max

imal

spat

iale

xten

tTyp

ical

freq

uenc

yCoe

xisting

PDsor

RDA

QQR

SzD

QQR

SzD

Mea

n(m

edian)

ra

ngeac

ross

3re

view

ers

Mea

n

14

0NA

NA

NA

NA

NA

NA

NA

NA

167

000

000

15

0NA

NA

NA

NA

NA

NA

NA

NA

20

033

017

Mea

nov

erall

126

51

ndash67

63

ndash68

262

ndash267

209

012

008

Abb

reviations

GPD

5ge

neraliz

edpe

riod

icdisc

harg

eLP

D5

lateraliz

edpe

riod

icdisc

harg

ePD

5pe

riod

icdisc

harg

eQ

5qu

antitative

EEG

alon

eQR

5qu

antitative

EEG

withraw

EEGR

DA

5rhythm

icde

lta

activityS

zD5

seizurede

tectionalgo

rithm

Durationof

seizures

define

das

follo

ws

brief10ndash60

seco

nds

interm

ediate

1ndash5

minutes

prolong

ed5

minutes






























































2004621743ndash1748


























91750ndash760



483ndash488













sia 200849349ndash352







rol 200941315ndash326





























201125329ndash337








2016




2013301ndash27















Salzburg Austria











551366ndash1373



20148356ndash64










Look Whatrsquos New






















Reprints







Tab

le1

Con

tinu

ed

Epoc

hno

No

ofse

izur

es

Seizu

rech

arac

teristics

Max

imal

onse

tva

riat

ion

min

Sen

sitivity

False

-pos

itive

rate

mea

nno

of

seizur

esh

Dur

ation

Amplitud

e(com

pare

dto

bac

kgro

und

activity

)Max

imal

spat

iale

xten

tTyp

ical

freq

uenc

yCoe

xisting

PDsor

RDA

QQR

SzD

QQR

SzD

Mea

n(m

edian)

ra

ngeac

ross

3re

view

ers

Mea

n

14

0NA

NA

NA

NA

NA

NA

NA

NA

167

000

000

15

0NA

NA

NA

NA

NA

NA

NA

NA

20

033

017

Mea

nov

erall

126

51

ndash67

63

ndash68

262

ndash267

209

012

008

Abb

reviations

GPD

5ge

neraliz

edpe

riod

icdisc

harg

eLP

D5

lateraliz

edpe

riod

icdisc

harg

ePD

5pe

riod

icdisc

harg

eQ

5qu

antitative

EEG

alon

eQR

5qu

antitative

EEG

withraw

EEGR

DA

5rhythm

icde

lta

activityS

zD5

seizurede

tectionalgo

rithm

Durationof

seizures

define

das

follo

ws

brief10ndash60

seco

nds

interm

ediate

1ndash5

minutes

prolong

ed5

minutes






























































2004621743ndash1748


























91750ndash760



483ndash488













sia 200849349ndash352







rol 200941315ndash326





























201125329ndash337








2016




2013301ndash27















Salzburg Austria











551366ndash1373



20148356ndash64










Look Whatrsquos New






















Reprints































































2004621743ndash1748


























91750ndash760



483ndash488













sia 200849349ndash352







rol 200941315ndash326





























201125329ndash337








2016




2013301ndash27















Salzburg Austria











551366ndash1373



20148356ndash64










Look Whatrsquos New






















Reprints




























201125329ndash337








2016




2013301ndash27















Salzburg Austria











551366ndash1373



20148356ndash64










Look Whatrsquos New






















Reprints




















Reprints




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