Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients
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Author(s)
Type
Journal Article
Abstract
Electrical Impedance Tomography (EIT) is a non-invasive imaging technique, which has the potential to expedite the differentiation of ischaemic or haemorrhagic stroke, decreasing the time to treatment. Whilst demonstrated in simulation, there are currently no suitable imaging or classification methods which can be successfully applied to human stroke data. Development of these complex methods is hindered by a lack of quality Multi-Frequency EIT (MFEIT) data. To address this, MFEIT data were collected from 23 stroke patients, and 10 healthy volunteers, as part of a clinical trial in collaboration with the Hyper Acute Stroke Unit (HASU) at University College London Hospital (UCLH). Data were collected at 17 frequencies between 5 Hz and 2 kHz, with 31 current injections, yielding 930 measurements at each frequency. This dataset is the most comprehensive of its kind and enables combined analysis of MFEIT, Electroencephalography (EEG) and Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) data in stroke patients, which can form the basis of future research into stroke classification. Design Type(s) parallel group design • case control design Measurement Type(s) brain activity measurement • nuclear magnetic resonance assay • Computed Tomography of the Brain with Contrast Technology Type(s) electrical impedance tomography • MRI Scanner • computed tomography scanner Factor Type(s) diagnosis Sample Characteristic(s) Homo sapiens • brain
Date Issued
2018-07-03
Online Publication Date
2020-10-07T11:37:41Z
Date Acceptance
2018-04-16
ISSN
2052-4463
Publisher
Nature Research
Start Page
1
End Page
10
Journal / Book Title
Scientific Data
Volume
5
Copyright Statement
© The Author(s) 2018. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any
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link to the Creative Commons license, and indicate if changes were made. The images or other third party
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intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.
org/licenses/by/4.0/
medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were made. The images or other third party
material in this article are included in the article’s Creative Commons license, unless indicated otherwise in
a credit line to the material. If material is not included in the article’s Creative Commons license and your
intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain
permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.
org/licenses/by/4.0/
License URI
Identifier
https://www.nature.com/articles/sdata2018112
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000437103600001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
ACUTE ISCHEMIC-STROKE
RECONSTRUCTION ALGORITHMS
BRAIN
SYSTEM
MODEL
EIT
EEG
Electric Impedance
Electroencephalography
Humans
Neuroimaging
Stroke
Tomography, X-Ray Computed
Humans
Tomography, X-Ray Computed
Electroencephalography
Electric Impedance
Stroke
Neuroimaging
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
ACUTE ISCHEMIC-STROKE
RECONSTRUCTION ALGORITHMS
BRAIN
SYSTEM
MODEL
EIT
EEG
Publication Status
Published
Article Number
ARTN 180112
Date Publish Online
2018-07-03