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Med Biol Eng Comput. 2017 Aug;55(8):1177-1188. doi: 10.1007/s11517-016-1578-6. Epub 2016 Oct 13.

Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations.

Author information

1
Department of Signals and Systems, Chalmers University of Technology, 412 96, Gothenburg, Sweden. stefan.candefjord@chalmers.se.
2
MedTech West, Sahlgrenska University Hospital, Röda Stråket 10 B, 413 45, Gothenburg, Sweden. stefan.candefjord@chalmers.se.
3
SAFER Vehicle and Traffic Safety Centre at Chalmers, Gothenburg, Sweden. stefan.candefjord@chalmers.se.
4
Department of Signals and Systems, Chalmers University of Technology, 412 96, Gothenburg, Sweden.
5
MedTech West, Sahlgrenska University Hospital, Röda Stråket 10 B, 413 45, Gothenburg, Sweden.
6
Clinical Neurophysiology, Sahlgrenska University Hospital, Blå Stråket 5, 413 45, Gothenburg, Sweden.

Abstract

Traumatic brain injury is the leading cause of death and severe disability for young people and a major public health problem for elderly. Many patients with intracranial bleeding are treated too late, because they initially show no symptoms of severe injury and are not transported to a trauma center. There is a need for a method to detect intracranial bleedings in the prehospital setting. In this study, we investigate whether broadband microwave technology (MWT) in conjunction with a diagnostic algorithm can detect subdural hematoma (SDH). A human cranium phantom and numerical simulations of SDH are used. Four phantoms with SDH 0, 40, 70 and 110 mL are measured with a MWT instrument. The simulated dataset consists of 1500 observations. Classification accuracy is assessed using fivefold cross-validation, and a validation dataset never used for training. The total accuracy is 100 and 82-96 % for phantom measurements and simulated data, respectively. Sensitivity and specificity for bleeding detection were 100 and 96 %, respectively, for the simulated data. SDH of different sizes is differentiated. The classifier requires training dataset size in order of 150 observations per class to achieve high accuracy. We conclude that the results indicate that MWT can detect and estimate the size of SDH. This is promising for developing MWT to be used for prehospital diagnosis of intracranial bleedings.

KEYWORDS:

Finite element method; Intracranial bleedings; Microwave technology; Subdural hematoma phantom; Traumatic brain injury

PMID:
27738858
PMCID:
PMC5544814
DOI:
10.1007/s11517-016-1578-6
[Indexed for MEDLINE]
Free PMC Article

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