Jussi Toivanen, Antti Paldanius, Bachir Dekdouk, Valentina Candiani, Asko Hänninen, Tuomo Savolainen, Daniel Strbian, Nina Forss, Nuutti Hyvönen, Jari Hyttinen, Ville Kolehmainen
PurposeWe present a simulation-based feasibility study of electrical impedance tomography (EIT) for continuous bedside monitoring of intracerebral hemorrhages (ICH) and detection of secondary hemorrhages.ApproachWe 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.ResultsThe 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.ConclusionsOur 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.
Frequency-domain (FD) optical tomography instruments modulate the intensity of the light source at a radio frequency and measure the amplitude and phase shift of the detected photon density wave. The differing spatial sensitivities of amplitude and phase to the optical properties of tissue suggest that inclusion of phase data can improve the image reconstruction accuracy. This study describes our methodology for improved use of FD data in conjunction with a Monte Carlo (MC) forward solver (Monte Carlo eXtreme; MCX) and a voxel-based model of a two-year-old child’s head. The child participated our previous study where subjects were stimulated with affective (slow brushing) and non-affective touch (fast brushing) to their right forearm, and the responses were measured from the left hemisphere with our in-house 16-channel high-density FD system. We implemented the computation of the FD sensitivity profiles to the MCX photon simulation software, and validated the output against our in-house MC code. We used simulated and the real experimental touch response data to observe the effects of including both FD data types to the image reconstruction instead of amplitude data alone. For the simulated and experimental case, we observed that the inclusion of phase data increases the reconstructed contrast in the brain. The individual touch responses showed similarity to the group-level results in our original publication with 16 subjects and amplitude data alone, and other literature.
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