Propagation of measurement noise through backprojection reconstruction in electrical impedance tomography

A framework to analyze the propagation of measurement noise through backprojection reconstruction algorithms in electrical impedance tomography (EIT) is presented. Two measurement noise sources were considered: noise in the current drivers and in the voltage detectors. The influence of the acquisition system architecture (serial/semi-parallel) is also discussed. Three variants of backprojection reconstruction are studied: basic (unweighted), weighted and exponential backprojection. The results of error propagation theory have been compared with those obtained from simulated and experimental data. This comparison shows that the approach provides a good estimate of the reconstruction error variance. It is argued that the reconstruction error in EIT images obtained via backprojection can be approximately modeled as a spatially nonstationary Gaussian distribution. This methodology allows us to develop a spatial characterization of the reconstruction error in EIT images.Peer Reviewe

The use of charge -charge correlation in impedance measurements: A test of the EPET method

It is well known that biological tissues possess impedance properties that might be useful in medical diagnostics and treatment. Electrical Impedance Tomography (EIT) images internal electrical properties by using numerical methods to solve Laplace\u27s differential equation. The indirect reconstruction method (IRM), a common method in application, predicts internal electrical property distribution by iteratively computing a forward and inverse solution. This approach reduces the non-linear Laplace\u27s equation into a poorly conditioned series of linear equations, which are solved simultaneously. This method suffers from high computational effort and is susceptible to prediction errors that stem from measurement noise.;As an alternative to Laplace\u27s differential equation, this research applies the quasi-static approximation, Dirichlet boundary conditions and a rectangular shaped domain (with corresponding Green\u27s function for Cartesian coordinates) to solve the integral form of Poisson\u27s equation (Green\u27s 2nd identity). The result is the charge-charge correlation method (CCCM), a well-conditioned relationship between static charge build-up at internal structures and induced domain boundary charge build-up (which corresponds to measured boundary current). The CCCM is applied in a reconstruction technique called Electrical Property Enhanced Tomography (EPET). While related to the existing impedance imaging methods, EPET does not attempt to create the image with the electrical data but rather adds electrical property information to an existing conventional imaging modality (CT or MI) and, in fact, requires the data from the other modality to locate the position of internal structures in the object. Predicted electrical properties are then superimposed over the a priori structural image to yield the electrical property distribution.;To test the feasibility of the CCCM, experiments using agar media placed in a saline bath were performed. The position, size and conductivity of the agar were varied and the CCCM applied to predict the conductivities from external boundary current measurements. Predicted conductivities yielded relative errors less than 10%, results that are equal to or better than the IRM. Additionally, CCCM was able to compute these results with a 104 improvement in speed over the IRM

Propagation of measurement noise through backprojection reconstruction in electrical impedance tomography

A framework to analyze the propagation of measurement noise through backprojection reconstruction algorithms in electrical impedance tomography (EIT) is presented. Two measurement noise sources were considered: noise in the current drivers and in the voltage detectors. The influence of the acquisition system architecture (serial/semi-parallel) is also discussed. Three variants of backprojection reconstruction are studied: basic (unweighted), weighted and exponential backprojection. The results of error propagation theory have been compared with those obtained from simulated and experimental data. This comparison shows that the approach provides a good estimate of the reconstruction error variance. It is argued that the reconstruction error in EIT images obtained via backprojection can be approximately modeled as a spatially nonstationary Gaussian distribution. This methodology allows us to develop a spatial characterization of the reconstruction error in EIT images.Peer Reviewe

Noninvasive Stroke Volume Monitoring by Electrical Impedance Tomography

In clinical practice it is of vital importance to track the health of a patient's cardiovascular system via the continuous measurement of hemodynamic parameters. Cardiac output (CO) and the related stroke volume (SV) are two such parameters of central interest as they are closely linked with oxygen delivery and the health of the heart. Many techniques exist to measure CO and SV, ranging from highly invasive to noninvasive ones. However, none of the noninvasive approaches are reliable enough in clinical settings. To overcome this limitation, we investigated the feasibility and practical applicability of noninvasively measuring SV via electrical impedance tomography (EIT), a safe and low-cost medical imaging modality. In a first step, the unclear origins of cardiosynchronous EIT signals were investigated in silico on a 4D bioimpedance model of the human thorax. Our simulations revealed that the EIT heart signal is dominated by ventricular activity, giving hope for a heart amplitude-based SV estimation. We further showed via simulations that this approach seems feasible in controlled scenarios but also suffers from some limitations. That is, EIT-based SV estimation is impaired by electrode belt displacements and by changes in lung conductivity (e.g. by respiration or liquid redistribution). We concluded that the absolute measurement of SV by EIT is challenging, but trending - that is following relative changes - of SV is more promising. In a second step, we investigated the practical applicability of this approach in three experimental studies. First, EIT was applied on 16 mechanically ventilated patients in the intensive care unit (ICU) receiving a fluid challenge to improve their hemodynamic situation. We showed that the resulting relative changes in SV could be tracked using the EIT lung amplitude, while this was not possible via the heart amplitude. The second study, performed on patients in the operating room (OR), had to be prematurely terminated due to too low variations in SV and technical challenges of EIT in the OR. Finally, the third experimental study aimed at testing an improved measurement setup that we designed after having identified potential limitations of available clinical EIT systems. This setup was tested in an experimental protocol on 10 healthy volunteers undergoing bicycle exercises. Despite the use of subject-specific 3D EIT, neither the heart nor the lung amplitudes could be used to assess SV via EIT. Changes in electrode contact and posture seem to be the main factors impairing the assessment of SV. In summary, based on in silico and in vivo investigations, we revealed various challenges related to EIT-based SV estimation. While our simulations showed that trending of SV via the EIT heart amplitude should be possible, this could not be confirmed in any of the experimental studies. However, in the ICU, where sufficiently controlled EIT measurements were possible, the EIT lung amplitude showed potential to trend changes in SV. We concluded that EIT amplitude-based SV estimation can easily be impaired by various factors such as electrode contact or small changes in posture. Therefore, this approach might be limited to controlled environments with the least possible changes in ventilation and posture. Future research should scrutinize the lung amplitude-based approach in dedicated simulations and clinical trials

Improving Electrical Impedance Tomography of brain function with a novel servo-controlled electrode helmet

Electrical Impedance Tomography (EIT) is a medical imaging technique which reconstructs the internal conductivity of an object from boundary measurements. EIT has the potential to provide a novel means of imaging in acute stroke, epilepsy or traumatic brain injury. Previous studies, whilst demonstrating the potential of the technique, have not been successful clinically.The work in this thesis aims to address fundamental limitations including measurement drift in electronic hardware, lack of an anatomically realistic tank phantom for rigorous testing, poor electrode-skin contact and mis-location of scalp electrodes. Chapter 1 provides an introduction of the principles of bioimpedance and EIT, as well as a review of previous clinical studies. Chapter 2 details the development of a novel anatomically realistic head phantom, simulating the human adult head with scalp electrodes, using a 3D printer and cylindrical holes to provide simulated conductivity. This replicated the varying spatial conductivity of the skull within 5 % of the true value. Two multifrequency EIT systems with parallel voltage recording were optimised for recording in the adult head with scalp electrodes, in chapter 3. Measurement drift was reduced by better case design and temperature control and data quality was improved with an updated interface to the current source and signal processing. The UCL ScouseTom system, performed best, with lower noise in all resistor and tank measurements, but the differences were masked during scalp recordings. Further, both systems produced similar results in the realistic adult head tank from chapter 2. Recent advances in EIT imaging coupled with the developments in chapters 2 and 3 provided opportunity to reassess the feasibility of monitoring epilepsy with EIT. Biologically representative perturbations was localised to within 8 mm in the head tank, with less than half the image error of previous studies. However, the key limitations of application time and measurement drift with scalp electrodes had yet to be addressed. Therefore the focus of the work in chapter 5 and chapter 6 was the design and testing of a novel self-adjusting electrode helmet. Skin-electrode impedance was continuously optimised by constant pressure, rotation and feedback control, and position sensors returned the co-ordinates of electrode tips. Finally, experiments with this helmet were undertaken to assess the feasibility of future clinical recordings