ABSTRACT
Purpose: We present a simulation-based feasibility study of electrical impedance tomography (EIT) for continuous bedside monitoring of intracerebral hemorrhages (ICH) and detection of secondary hemorrhages. Approach: We simulated EIT measurements for six different hemorrhage sizes at two different hemorrhage locations using an anatomically detailed computational head model. Using this dataset, we test the ICH monitoring and detection performance of our tailor-made, patient-specific stroke-monitoring algorithm that utilizes a novel combination of nonlinear region-of-interest difference imaging, parallel level sets regularization and a prior-conditioned least squares algorithm. We compare the results of our algorithm to the results of two reference algorithms, a total variation regularized absolute imaging algorithm and a linear difference imaging algorithm. Results: The tailor-made stroke-monitoring algorithm is capable of indicating smaller changes in the simulated hemorrhages than either of the reference algorithms, indicating better monitoring and detection performance. Conclusions: Our simulation results from the anatomically detailed head model indicate that EIT equipped with a patient-specific stroke-monitoring algorithm is a promising technology for the unmet clinical need of having a technology for continuous bedside monitoring of brain status of acute stroke patients.
