Detection of thoracic vascular structures by electrical impedance tomography: a systematic assessment of prominence peak analysis of impedance changes

OBJECTIVE Electrical impedance tomography (EIT) is a non-invasive and radiation-free bedside monitoring technology, primarily used to monitor lung function. First experimental data shows that the descending aorta can be detected at different thoracic heights and might allow the assessment of central hemodynamics, i.e. stroke volume and pulse transit time. APPROACH First, the feasibility of localizing small non-conductive objects within a saline phantom model was evaluated. Second, this result was utilized for the detection of the aorta by EIT in ten anesthetized pigs with comparison to thoracic computer tomography (CT). Two EIT belts were placed at different thoracic positions and a bolus of hypertonic saline (10 ml, 20%) was administered into the ascending aorta while EIT data were recorded. EIT images were reconstructed using the GREIT model, based on the individual's thoracic contours. The resulting EIT images were analyzed pixel by pixel to identify the aortic pixel, in which the bolus caused the highest transient impedance peak in time. MAIN RESULTS In the phantom, small objects could be located at each position with a maximal deviation of 0.71 cm. In vivo, no significant differences between the aorta position measured by EIT and the anatomical aorta location were obtained for both measurement planes if the search was restricted to the dorsal thoracic region of interest (ROIs). SIGNIFICANCE It is possible to detect the descending aorta at different thoracic levels by EIT using an intra-aortic bolus of hypertonic saline. No significant differences in the position of the descending aorta on EIT images compared to CT images were obtained for both EIT belts.

[1]  Survi Kyal,et al.  Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Theory and Practice , 2015, IEEE Transactions on Biomedical Engineering.

[2]  T K Hames,et al.  Pulmonary perfusion and ventricular ejection imaging by frequency domain filtering of EIT images , 1992 .

[3]  A. L. Short,et al.  Relationship between electrocardiographic RR and QT interval variabilities and indices of ventricular function in healthy subjects , 2008, Physiological measurement.

[4]  Jean-Philippe Thiran,et al.  Non-invasive monitoring of pulmonary artery pressure from timing information by EIT: experimental evaluation during induced hypoxia , 2016, Physiological measurement.

[5]  O. Chételat,et al.  Parametric estimation of pulse arrival time: a robust approach to pulse wave velocity , 2009, Physiological measurement.

[6]  Richard Bayford,et al.  The effect of serial data collection on the accuracy of electrical impedance tomography images , 2013, Physiological measurement.

[7]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[8]  B. H. Blott,et al.  Pulmonary perfusion and ventricular ejection imaging by frequency domain filtering of EIT (electrical impedance tomography) images. , 1992, Clinical Physics and Physiological Measurement.

[9]  Andy Adler,et al.  Choice of reconstructed tissue properties affects interpretation of lung EIT images , 2014, Physiological measurement.

[10]  D G Altman,et al.  Improving bioscience research reporting: ARRIVE-ing at a solution , 2010, Laboratory animals.

[11]  B. Brown,et al.  Blood Flow Imaging Using Electrical Impedance Tomography , 1991, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991.

[12]  Andy Adler,et al.  Non-invasive monitoring of central blood pressure by electrical impedance tomography: first experimental evidence , 2011, Medical & Biological Engineering & Computing.

[13]  Andy Adler,et al.  Automated robust test framework for electrical impedance tomography. , 2015, Physiological measurement.

[14]  J Solà,et al.  Electrical impedance tomography for non-invasive assessment of stroke volume variation in health and experimental lung injury , 2017, British journal of anaesthesia.

[15]  Andy Adler,et al.  Evaluation of EIT system performance , 2011, Physiological measurement.

[16]  Jean-Philippe Thiran,et al.  Non-invasive monitoring of pulmonary artery pressure at the bedside , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[17]  Andy Adler,et al.  Uniform background assumption produces misleading lung EIT images , 2013, Physiological measurement.

[18]  I. Cuthill,et al.  Improving Bioscience Research Reporting: The ARRIVE Guidelines for Reporting Animal Research † , 2012, Osteoarthritis and cartilage.

[19]  Eugenijus Kaniusas,et al.  Evaluation of reconstruction parameters of electrical impedance tomography on aorta detection during saline bolus injection , 2016 .

[20]  Andy Adler,et al.  Aortic blood pressure measured via EIT: investigation of different measurement settings , 2015, Physiological measurement.

[21]  Peter Herrmann,et al.  Regional Lung Perfusion as Determined by Electrical Impedance Tomography in Comparison With Electron Beam CT Imaging , 2002, IEEE Transactions on Medical Imaging.

[22]  Jean-Philippe Thiran,et al.  Influence of heart motion on cardiac output estimation by means of electrical impedance tomography: a case study , 2015, Physiological measurement.

[23]  Josep Solà,et al.  Heart-lung interactions measured by electrical impedance tomography* , 2011, Critical care medicine.

[24]  E. Costa,et al.  Estimation of Stroke Volume and Stroke Volume Changes by Electrical Impedance Tomography , 2018, Anesthesia and analgesia.

[25]  William R B Lionheart,et al.  Uses and abuses of EIDORS: an extensible software base for EIT , 2006, Physiological measurement.

[26]  S Leonhardt,et al.  Dynamic separation of pulmonary and cardiac changes in electrical impedance tomography , 2008, Physiological measurement.

[27]  William R B Lionheart,et al.  GREIT: a unified approach to 2D linear EIT reconstruction of lung images , 2009, Physiological measurement.