DocumentCode
49398
Title
Microwave-Based Stroke Diagnosis Making Global Prehospital Thrombolytic Treatment Possible
Author
Persson, Mats ; Fhager, Andreas ; Trefna, H.D. ; Yinan Yu ; McKelvey, Tomas ; Pegenius, Goran ; Karlsson, Jan-Erik ; Elam, Mikael
Author_Institution
Dept. of Signals & Syst., Chalmers Univ. of Technol., Goteborg, Sweden
Volume
61
Issue
11
fYear
2014
fDate
Nov. 2014
Firstpage
2806
Lastpage
2817
Abstract
Here, we present two different brain diagnostic devices based on microwave technology and the associated two first proof-of-principle measurements that show that the systems can differentiate hemorrhagic from ischemic stroke in acute stroke patients, as well as differentiate hemorrhagic patients from healthy volunteers. The system was based on microwave scattering measurements with an antenna system worn on the head. Measurement data were analyzed with a machine-learning algorithm that is based on training using data from patients with a known condition. Computer tomography images were used as reference. The detection methodology was evaluated with the leave-one-out validation method combined with a Monte Carlo-based bootstrap step. The clinical motivation for this project is that ischemic stroke patients may receive acute thrombolytic treatment at hospitals, dramatically reducing or abolishing symptoms. A microwave system is suitable for prehospital use, and therefore has the potential to allow significantly earlier diagnosis and treatment than today.
Keywords
Monte Carlo methods; biomedical equipment; brain; computerised tomography; learning (artificial intelligence); medical disorders; medical image processing; microwave imaging; neurophysiology; patient treatment; Monte Carlo-based bootstrap step; acute stroke patients; acute thrombolytic treatment; antenna system; brain diagnostic devices; computer tomography imaging; detection methodology; global prehospital thrombolytic treatment; healthy volunteers; hemorrhagic patients; ischemic stroke patients; leave-one-out validation method; machine-learning algorithm; measurement data; microwave scattering measurements; microwave technology; microwave-based stroke diagnosis; proof-of-principle measurements; Antenna measurements; Antennas; Biomedical measurement; Frequency measurement; Hemorrhaging; Microwave measurement; Microwave theory and techniques; Microwave system; stroke diagnostics; subspace distance classification;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2014.2330554
Filename
6832574
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