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Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients

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 metho...

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Autores principales: Goren, Nir, Avery, James, Dowrick, Thomas, Mackle, Eleanor, Witkowska-Wrobel, Anna, Werring, David, Holder, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029572/
https://www.ncbi.nlm.nih.gov/pubmed/29969115
http://dx.doi.org/10.1038/sdata.2018.112
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author Goren, Nir
Avery, James
Dowrick, Thomas
Mackle, Eleanor
Witkowska-Wrobel, Anna
Werring, David
Holder, David
author_facet Goren, Nir
Avery, James
Dowrick, Thomas
Mackle, Eleanor
Witkowska-Wrobel, Anna
Werring, David
Holder, David
author_sort Goren, Nir
collection PubMed
description 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.
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spelling pubmed-60295722018-07-06 Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients Goren, Nir Avery, James Dowrick, Thomas Mackle, Eleanor Witkowska-Wrobel, Anna Werring, David Holder, David Sci Data Data Descriptor 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. Nature Publishing Group 2018-07-03 /pmc/articles/PMC6029572/ /pubmed/29969115 http://dx.doi.org/10.1038/sdata.2018.112 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any 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/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Goren, Nir
Avery, James
Dowrick, Thomas
Mackle, Eleanor
Witkowska-Wrobel, Anna
Werring, David
Holder, David
Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients
title Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients
title_full Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients
title_fullStr Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients
title_full_unstemmed Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients
title_short Multi-frequency electrical impedance tomography and neuroimaging data in stroke patients
title_sort multi-frequency electrical impedance tomography and neuroimaging data in stroke patients
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029572/
https://www.ncbi.nlm.nih.gov/pubmed/29969115
http://dx.doi.org/10.1038/sdata.2018.112
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