| Literature DB >> 29969115 |
Nir Goren1, James Avery1, Thomas Dowrick1, Eleanor Mackle1, Anna Witkowska-Wrobel1, David Werring2, David Holder1.
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.Entities:
Mesh:
Year: 2018 PMID: 29969115 PMCID: PMC6029572 DOI: 10.1038/sdata.2018.112
Source DB: PubMed Journal: Sci Data ISSN: 2052-4463 Impact factor: 6.444