Electrical Impedance Tomography for Perfusion Imaging and Monitoring

Abstract

Electrical impedance tomography (EIT) is a medical imaging technology that uses boundary electrodes to inject stimulus currents and measure the resulting potential distributions. These potentials are measured using electrodes which are in turn used to reconstruct conductivity changes within the body.EIT has been studied for its ability to image both the flow of blood and the delivery of blood to a tissue (perfusion). However, cardiac-related signals are challenging to image accurately due to their small amplitude and the limited sensitivity of EIT systems to impedance changes deep in the body. This thesis presents techniques to improve perfusion imaging with EIT by generating more accurate meshes and using internal electrodes to obtain higher sensitivity in the centre of the body. This work develops a tool to generate accurate, customized meshes from diagnostic computed tomography (CT) images, and a technique to reconstruct images with internal electrodes. Custom models reconstructed the location of impedance changes due to ventilation with higher accuracy, and internal electrodes yielded an increase in internal sensitivity over traditional external configurations. Shifting the position of electrodes on an internal probe by as little as 1% of the tank radius in simulation created artefacts in images reconstructed using existing approaches without motion correction. A novel technique to correct for probe motion is presented that improved reconstruction accuracy and reduced background noise compared to existing techniques. The presented work contributes to increasing internal sensitivity of EIT measurements and demonstrates that refined meshes and internal electrodes may improve measures of perfusion and help to make EIT a viable tool for continuous perfusion monitoring at the bedside.iii Thank you to Dr. Étienne Fortin-Pellerin and the team at Université de Sherbrooke for their support with so many experiments, and welcoming me into their lab.I would also like to thank Dr. Alistair Boyle for his valuable insights into the field of EIT and my colleagues who have made my time at Carleton so enjoyable.Finally, a huge thank you to my family. My parents, Marlys and Doug, and my sisters, Alyssa and Caitlyn have supported this work in so many ways, both in the workshop helping with prototypes and proofreading. A special thank you to my partner Sana for her patience, help and support along this journey.