Back-projection distortions in applied potential tomography images due to non-uniform reference conductivity distributions

Validation of a 3D reconstruction algorithm for EIT of human brain function in a realistic head-shaped tank

Previous work has demonstrated that electrical impedance tomography can be used to image human brain activity during evoked responses, but two-thirds of the reconstructed images fail to localize an impedance change to the expected stimulated cortical area. The localization failure may be caused by modelling the head as a homogenous sphere in the reconstruction algorithm. This assumption may lead to errors when used to reconstruct data obtained from the human head. In this study a 3D reconstruction algorithm, based on a model of the head as a homogenous sphere, was characterized by simulating the algorithm model, the head shape and the presence of the skull in saline-filled tanks. EIT images of a sponge, 14 cm3 volume with a resistivity contrast of 12%, were acquired in three different positions in tanks filled with 0.2% saline. In a hemispherical tank, 19 cm in diameter, the sponge was localized to within 3.4-10.7% of the tank diameter. In a head-shaped tank, the errors were between 3.1 and 13.3% without a skull and between 10.3 and 18.7% when a real human skull was present. A significant increase in localization error therefore occurs if an algorithm based on a homogeneous sphere is used on data acquired from a head-shaped tank. The increased error is due to the presence of the skull, as no significant increase in error occurred if a head-shaped tank was used without the skull present, compared to the localization error within the hemispherical tank. The error due to the skull significantly shifted the impedance change within the skull towards the centre of the image. Although the increased localization error due to the skull is not sufficient to explain the localization errors of up to 50% of the image diameter present in the images of some human subjects, the future use of a realistic head model in the reconstruction algorithm is likely to reduce the localization error in the human images due to the presence of the skull.

Three-dimensional electrical impedance tomography of human brain activity

Regional cerebral blood flow and blood volume changes that occur during human brain activity will change the local impedance of that cortical area, as blood has a lower impedance than that of brain. Theoretically, such impedance changes could be measured from scalp electrodes and reconstructed into images of the internal impedance of the head. Electrical Impedance Tomography (EIT) is a newly developed technique by which impedance measurements from the surface of an object are reconstructed into impedance images. It is fast, portable, inexpensive, and noninvasive, but has a relatively low spatial resolution. EIT images were recorded with scalp electrodes and an EIT system, specially optimized for recording brain function, in 39 adult human subjects during visual, somatosensory, or motor activity. Reproducible impedance changes of about 0.5% occurred in 51/52 recordings, which lasted from 6 s after the stimulus onset to 41 s after stimulus cessation. When these changes were reconstructed into impedance images, using a novel 3-D reconstruction algorithm, 19 data sets demonstrated significant impedance changes in the appropriate cortical region. This demonstrates, for the first time, that significant impedance changes, which could form the basis for a novel neuroimaging technology, may be recorded in human subjects with scalp electrodes. The final images contained spatial noise and strategies to reduce this in future work are presented.

Improvement of the positional accuracy of EIT images of the head using a Lagrange multiplier reconstruction algorithm with diametric excitation

A novel algorithm for the reconstruction of dynamic images using diametric excitation has been developed. The algorithm is specifically designed to image impedance changes in the brain using boundary data obtained from scalp electrodes by incorporating a priori information. The a priori information is obtain by solving the forward problem using a finite-element model (FEM) which includes the discontinuity of the skull resistivity. The advantages with this new approach are that the sensitivity and accuracy of the location of the impedance changes are improved compared to methods based on adjacent excitation.

Incorporating a priori information into the Sheffield filtered backprojection algorithm

The Sheffield image reconstruction algorithm is based on the assumption that the initial conductivity distribution of the body being imaged is uniform. In many situations this assumption is violated. Previous attempts at incorporating a priori information by modifications to the backprojection matrices were ineffective. An alternative method of including a priori information became apparent following the recent reformulation of the Sheffield image reconstruction algorithm. Applying matrix algebra to the image reconstruction equations reveals that the incorporation of a priori information can be considered as either a modification to the original backprojection matrix or a component of a composite data filter. A simple two-dimensional model of the adult head was chosen to test this approach. The results of imaging studies using synthetic data derived from this model show that a priori information has been successfully incorporated into the image reconstruction process. The ability to include a priori information into the image reconstruction process may have significant implications for the more challenging applications of EIT such as imaging the adult head.