Brain stroke is one of the leading causes of death and disability worldwide [1]. It can be classified as ischemic stroke (i-stroke), e.g., blood flow is restricted by a blood clot, or hemorrhagic stroke (h-stroke), e.g., a bleeding in the brain. Approximately 80% of total stroke cases are ischemic. The most common treatment for i-stroke to date is the use of thrombolytics: drugs that dissolve the blood clots. The clinical decision to apply a thrombolytic should be made within 3-4.5 h from the onset of the stroke symptoms (e.g., [2]), and it relies on imaging methods such as computed tomography (CT) and magnetic resonance imaging (MRI). Further evaluation of stroke evolution is done mainly by imaging to assess the extent of the ischemic injury and to correlate with the functional behavior of the patient. However, to date there is no accurate way to provide reliable information about the key components of i-stroke physiology that include the position and size of the acute stroke (arterial occlusion), the core infarct region that contains irreversibly injured tissues, and the ischemic penumbra, i.e., the tissue that could potentially be restored by rapid revascularization [1], [3].

Electromagnetic Tomography for Detection, Differentiation, and Monitoring of Brain Stroke: A Virtual Data and Human Head Phantom Study.

This article deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g., gradient based) with successive solutions of a direct problem such as the accurate modeling of a whole-microwave measurement system. Moreover, a sufficiently high number of unknowns is required to accurately represent the solution. As the system will be used for detecting a brain stroke (ischemic or hemorrhagic) as well as for monitoring during the treatment, the running times for the reconstructions should be reasonable. The method used is based on high-order finite elements, parallel preconditioners from the domain decomposition method and domain-specific language with the opensource FreeFEM&#x0002B;&#x0002B; solver.

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Numerical Modeling and High-Speed Parallel Computing: New Perspectives on Tomographic Microwave Imaging for Brain Stroke Detection and Monitoring.

Microwave technology has the potential to revolutionize how, when, and what care can be delivered to patients with acute, life-threatening medical conditions. The prospects are that microwave systems can both improve diagnostic ability and accuracy and enable earlier diagnosis. Early diagnosis is a key factor in acute situations, especially when breathing and circulation are affected. Conventional imaging modalities used for diagnostics, such as magnetic resonance imaging (MRI) and X-ray computed tomography (CT), are powerful but normally available only at hospitals.

Microwave Diagnostics Ahead: Saving Time and the Lives of Trauma and Stroke Patients

An intracranial haemorrhage is a life threatening medical emergency, yet only a fraction of the patients receive treatment in time, primarily due to the transport delay in accessing diagnostic equipment in hospitals such as Magnetic Resonance Imaging or Computed Tomography. A mono-static microwave head imaging system that can be carried in an ambulance for the detection and localization of intracranial haemorrhage is presented. The system employs a single ultra-wideband antenna as sensing element to transmit signals in low microwave frequencies towards the head and capture backscattered signals. The compact and low-profile antenna provides stable directional radiation patterns over the operating bandwidth in both near and far-fields. Numerical analysis of the head imaging system with a realistic head model in various situations is performed to realize the scattering mechanism of haemorrhage. A modified delay-and-summation back-projection algorithm, which includes effects of surface waves and a distance-dependent effective permittivity model, is proposed for signal and image post-processing. The efficacy of the automated head imaging system is evaluated using a 3D-printed human head phantom with frequency dispersive dielectric properties including emulated haemorrhages with different sizes located at different depths. Scattered signals are acquired with a compact transceiver in a mono-static circular scanning profile. The reconstructed images demonstrate that the system is capable of detecting haemorrhages as small as 1 cm3. While quantitative analyses reveal that the quality of images gradually degrades with the increase of the haemorrhage’s depth due to the reduction of signal penetration inside the head; rigorous statistical analysis suggests that substantial improvement in image quality can be obtained by increasing the data samples collected around the head. The proposed head imaging prototype along with the processing algorithm demonstrates its feasibility for potential use in ambulances as an effective and low cost diagnostic tool to assure timely triaging of intracranial hemorrhage patients.

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Design and Experimental Evaluation of a Non-Invasive Microwave Head Imaging System for Intracranial Haemorrhage Detection.

Intracranial hemorrhage is a medical emergency that requires rapid detection and medication to restrict any brain damage to minimal. Here, an effective wideband microwave head imaging system for on-the-spot detection of intracranial hemorrhage is presented. The operation of the system relies on the dielectric contrast between healthy brain tissues and a hemorrhage that causes a strong microwave scattering. The system uses a compact sensing antenna, which has an ultra-wideband operation with directional radiation, and a portable, compact microwave transceiver for signal transmission and data acquisition. The collected data is processed to create a clear image of the brain using an improved back projection algorithm, which is based on a novel effective head permittivity model. The system is verified in realistic simulation and experimental environments using anatomically and electrically realistic human head phantoms. Quantitative and qualitative comparisons between the images from the proposed and existing algorithms demonstrate significant improvements in detection and localization accuracy. The radiation and thermal safety of the system are examined and verified. Initial human tests are conducted on healthy subjects with different head sizes. The reconstructed images are statistically analyzed and absence of false positive results indicate the efficacy of the proposed system in future preclinical trials.

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Portable Wideband Microwave Imaging System for Intracranial Hemorrhage Detection Using Improved Back-projection Algorithm with Model of Effective Head Permittivity.

Electromagnetic Tomography, when matured, might present an effective supplement to current imaging modalities for fast and mobile diagnostic of stroke and for safe and easy to apply monitoring imaging technology for assessment of perfusion related brain injuries and an efficacy of treatment. We have advanced the technology from virtual brain imaging stage to an imaging of normal human brain (volunteers study). The developed EMT scanner for human brain imaging and first imaging results are presented here.

Bernhard Seiser

Papers

Electromagnetic tomography for brain imaging: From virtual to human brain