Evidence map›Paper›PMID 27453817›Full record

ArticleNeuroImage. Clinical2016

Bedside functional brain imaging in critically-ill children using high-density EEG source modeling and multi-modal sensory stimulation.

Danny Eytan, Elizabeth W Pang, Sam M Doesburg, Vera Nenadovic, Bojan Gavrilovic, Peter Laussen, Anne-Marie Guerguerian

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.8field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 6 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Danny EytanDepartment of Critical Care Medicine, Neurosciences and Mental Health Program, Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, Canada.
Elizabeth W PangDivision of Neurology, Department of Paediatrics, Neurosciences and Mental Health Program, Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, Canada.
Sam M DoesburgDepartment of Biomedical Physiology and Kinesiology, Behavioural and Cognitive Neuroscience Institute, Simon Fraser University, Burnaby, Canada.
Vera NenadovicDivision of Neurology, Department of Paediatrics, Neurosciences and Mental Health Program, Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, Canada.
Bojan GavrilovicInstitute of Biomaterials and Biomedical Engineering, Department of Critical Care Medicine, Neurosciences and Mental Health Program, Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, Canada.
Peter LaussenDepartment of Critical Care, David and Stacey Cynamon Chair in Critical Care Medicine, The Hospital for Sick Children, Department of Anaesthesia, University of Toronto, Toronto, Canada.
Anne-Marie GuerguerianDepartment of Critical Care, Neuroscience and Mental Health Program, Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, Canada.
Hospital for Sick Children · CAUniversity of Toronto · CASimon Fraser University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG) for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory), and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage critically-ill children and adults, and potentially patients not suited for magnetic resonance imaging technologies.

Indexed as

Brain MappingElectroencephalographyAcoustic StimulationAdolescentBrainBrain InjuriesChildChild, PreschoolCritical IllnessEvoked PotentialsFemaleGlasgow Coma ScaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleBedside cerebral functionBrain injuryChildrenElectroencephalography (EEG)Evoked potentialsNeuroimagingPediatrics

Identifiers

PMID27453817
PMCPMC4942736
OpenAlexW2465058324

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.