Biomechanical simulations of intracerebral hemorrhage expansion show tissue displacement has significant impact on electrical impedance tomography results

Abstract

Objective: Intracerebral hemorrhage (ICH) occupies intracranial space and causes brain tissue displacement and fluid volume shifts. We assess how hematoma expansion (HE) affects electrical impedance tomography (EIT) measurements and reconstructed images of the conductivity change caused by HE. Methods: We developed a novel multi-physics model of ICH with mechanical tissue deformation during HE. We simulated EIT measurements with the multi-physics model and a traditional static model using five ICH locations. The effects of tissue deformation on the results of monitoring of ICH with EIT were assessed by comparing the measurement data from the multi-physics and traditional models and by comparing the corresponding reconstructed conductivity change from two image reconstruction algorithms. Results: The simulated measurement data and the reconstructed images of the conductivity change using the multi-physics and the traditional model are radically different regardless of the image reconstruction algorithm used. Conclusions: The effect of tissue displacement caused by HE on EIT monitoring of ICH is significant. Specifically, the displacement of cerebrospinal fluid (CSF) can mask the effects of increased ICH blood volume. However, the effects of displaced CSF could be easier to detect with EIT than the ICH blood volume increase and thus could be used as an indicator of HE in EIT bedside monitoring of ICH and improve the detectability of HE, especially for ICH located deep in the brain. Significance: Currently there are virtually no imaging methods for continuous monitoring of stroke. There has been recent resurgence in interest to develop electrical impedance tomography (EIT) devices and algorithms for monitoring progression of stroke. In-silico studies show promising results, but there are very little clinical results. In-silico models are usually used for development and evaluation of algorithms for EIT image reconstruction. In previous studies the stroke has been usually modeled as local change in electrical conductivity and the fluid and tissue displacement caused by the increased blood volume in ICH has not been considered. In this paper we present a novel multi-physics model of ICH, simulated EIT measurement results and reconstructed images with comparisons to the traditionally used ICH modeling methods. Our multi-physics approach to modeling of ICH shows that the effect of tissue and fluid displacement during HE needs consideration when developing clinical applications of EIT.