Aortic blood pressure measured via EIT: investigation of different measurement settings. (26th May 2015)

• Record Type: Journal Article
• Authors: Braun, Fabian; Proença, Martin; Rapin, Michael; Lemay, Mathieu; Adler, Andy; Grychtol, Bartłomiej; Solà, Josep; Thiran, Jean-Philippe
• Is Part Of: Physiological measurement. Volume 36:Number 6(2015:Jun.)
• Page Start: 1147
• Page End: 1159
• Publication Date: 2015-05-26
• Subjects: electrical impedance tomography -- EIT -- aortic blood pressure -- aorta -- bio-impedance simulation -- non-invasive -- continuous; Physiology -- Measurement -- Periodicals; Patient monitoring -- Periodicals; 612
• DOI: 10.1088/0967-3334/36/6/1147
• Languages: English
• ISSNs: 0967-3334

Abstract

Abstract: Electrical impedance tomography (EIT) allows the measurement of intra-thoracic impedance changes related to cardiovascular activity. As a safe and low-cost imaging modality, EIT is an appealing candidate for non-invasive and continuous haemodynamic monitoring. EIT has recently been shown to allow the assessment of aortic blood pressure via the estimation of the aortic pulse arrival time (PAT). However, finding the aortic signal within EIT image sequences is a challenging task: the signal has a small amplitude and is difficult to locate due to the small size of the aorta and the inherent low spatial resolution of EIT. In order to most reliably detect the aortic signal, our objective was to understand the effect of EIT measurement settings (electrode belt placement, reconstruction algorithm). This paper investigates the influence of three transversal belt placements and two commonly-used difference reconstruction algorithms (Gauss–Newton and GREIT) on the measurement of aortic signals in view of aortic blood pressure estimation via EIT. A magnetic resonance imaging based three-dimensional finite element model of the haemodynamic bio-impedance properties of the human thorax was created. Two simulation experiments were performed with the aim to (1) evaluate the timing error in aortic PAT estimation and (2) quantify the strength of the aortic signal in each pixel of the EIT image sequences. Both experiments reveal better performance for images reconstructed with Gauss–Newton (with a noise figure of 0.5 or above) and a belt placement at the height of the heart or higher. According to the noise-free scenarios simulated, the uncertainty in the analysis of the aortic EIT signal is expected to induce blood pressure errors of at least ± 1.4 mmHg.