Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations
Journal article, 2017

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.

Intracranial bleedings

Traumatic brain injury

Finite element method

Subdural hematoma phantom

Microwave technology

Author

Stefan Candefjord

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Biomedical Electromagnetics

JOHAN WINGES

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Malik Ahzaz Ahmad

Yinan Yu

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Thomas Rylander

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Tomas McKelvey

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Andreas Fhager

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Biomedical Electromagnetics

Mikael Elam

Sahlgrenska University Hospital

Mikael Persson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Biomedical Electromagnetics

Medical and Biological Engineering and Computing

0140-0118 (ISSN)

Vol. 55 8 1177-1188

Roots

Basic sciences

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

Areas of Advance

Life Science Engineering (2010-2018)

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

Signal Processing

DOI

10.1007/s11517-016-1578-6

More information

Latest update

6/25/2018