Multi-frequency electrical impedance tomography (MFEIT) was proposed over 10 years ago as a potential spectroscopic impedance imaging method. At least seven systems have been developed for imaging the lung, heart, breast and brain, yet none has yet achieved clinical acceptance. While the absolute impedance varies considerably between different tissues, the changes in the spectrum due to physiological changes are expected to be quite small, especially when measured through a volume. This places substantial requirements on the MFEIT instrumentation to maintain a flat system frequency response over a broad frequency range (dc-MHz). In this work, the EIT measurement problem is described from a multi-frequency perspective. Solutions to the common problems are considered from recent MFEIT systems, and the debate over four-terminal or two-terminal (multiple source) architecture is revisited. An analysis of the sources of MFEIT errors identifies the major sources of error as stray capacitance and common-mode voltages which lead to a load dependence in the frequency response of MFEIT systems. A system that employs active electrodes appears to be the most able to cope with these errors (Li et al 1996). A distributed system with digitization at the electrode is suggested as a next step in MFEIT system development.

A new, compact UCLH Mk 2.5 EIT system has been developed and calibrated for EIT imaging of the head. Improvements include increased input and output impedances, increased bandwidth and improved CMRR (80 dB) and linearity over frequencies and load (0.2% on a single channel, +/-0.7% on a saline tank over 20 Hz-256 kHz and 10-65 Omega). The accuracy of the system is sufficient to image severe acute stroke according to the specification from recent detailed anatomical modelling (Horesh et al 2005 3rd European Medical and Biological Engineering Conference EMBEC'05). A preliminary human study has validated the main specifications of the modelling, the range of trans-impedance from the head (8-70 Omega) using a 32 electrode, 258 combination protocol and contact impedances of 300 Omega to 2.7 kOmega over 20 Hz to 256 kHz.

MFEIT (multi-frequency electrical impedance tomography) could distinguish between ischaemic and haemorrhagic stroke and permit the urgent use of thrombolytic drugs in patients with ischaemic stroke. The purpose of this study was to characterize the UCLH Mk 2 MFEIT system, designed for this purpose, with 32 electrodes and a multiplexed 2 kHz to 1.6 MHz single impedance measuring circuit. Data were collected in seven subjects with brain tumours, arteriovenous malformations or chronic stroke, as these resembled the changes in haemorrhagic or ischaemic stroke. Calibration studies indicated that the reliable bandwidth was only 16-64 kHz because of front-end components placed to permit simultaneous EEG recording. In raw in-phase component data, the SD of 16-64 kHz data for one electrode combination across subjects was 2.45 +/- 0.9%, compared to a largest predicted change of 0.35% estimated using the FEM of the head. Using newly developed methods of examining the most sensitive channels from the FEM, and nonlinear imaging constrained to the known site of the lesion, no reproducible changes between pathologies were observed. This study has identified a specification for accuracy in EITS in acute stroke, identified the size of variability in relation to this in human recordings, and presents new methods for analysis of data. Although no reproducible changes were identified, we hope this will provide a foundation for future studies in this demanding but potentially powerful novel application.

Electrical impedance tomography (EIT) has the potential to produce images during epileptic seizures. This might improve the accuracy of the localization of epileptic foci in patients undergoing presurgical assessment for curative neurosurgery. It has already been shown that impedance increases by up to 22% during induced epileptic seizures in animal models, using cortical or implanted electrodes in controlled experiments. The purpose of this study was to determine if reproducible raw impedance changes and EIT images could be collected during epileptic seizures in patients who were undergoing observation with video-electroencephalography (EEG) telemetry as part of evaluation prior to neurosurgery to resect the region of brain causing the epilepsy. A secondary purpose was to develop an objective method for processing and evaluating data, as seizures arose at unpredictable times from a noisy baseline. Four-terminal impedance measurements from 258 combinations were collected continuously using 32 EEG scalp electrodes in 22 seizure episodes from 7 patients during their presurgical assessment together with the standard EEG recordings. A reliable method for defining the pre-seizure baseline and recording impedance data and EIT images was developed, in which EIT and EEG could be acquired simultaneously after filtering of EIT artefact from the EEG signal. Fluctuations of several per cent over minutes were observed in the baseline between seizures. During seizures, boundary voltage changes diverged with a standard deviation of 1-54% from the baseline. No reproducible changes with the expected time course of some tens of seconds and magnitude of about 0.1% could be reliably measured. This demonstrates that it is feasible to acquire EIT images in parallel with standard EEG during presurgical assessment but, unfortunately, expected EIT changes on the scalp of about 0.1% are swamped by much larger movement and systematic artefact. Nevertheless, EIT has the unique potential to provide invaluable neuroimaging data for this purpose and may still become possible with improvements in electrode design and instrumentation.

Although electrical impedance tomography (EIT) for ventilation monitoring is on the verge of clinical trials, pulmonary perfusion imaging with EIT remains a challenge, especially in spontaneously breathing subjects. In anticipation of more research on this subject, we believe a thorough review is called for. In this paper, findings related to the physiological origins and electrical characteristics of this signal are summarized, highlighting properties that are particularly relevant to EIT. The perfusion impedance change signal is significantly smaller in amplitude compared with the changes due to ventilation. Therefore, the hardware used for this purpose must be more sensitive and more resilient to noise. In previous works, some signal- or image-processing methods have been required to separate these two signals. Three different techniques are reviewed in this paper, including the ECG-gating method, frequency-domain-filtering-based methods and a principal-component-analysis-based method. In addition, we review a number of experimental studies on both human and animal subjects that employed EIT for perfusion imaging, with promising results in the diagnosis of pulmonary embolism (PE) and pulmonary arterial hypertension as well as other potential applications. In our opinion, PE is most likely to become the main focus for perfusion EIT in the future, especially for heavily instrumented patients in the intensive care unit (ICU).