BACKGROUND: Electrical impedance tomography (EIT) with indicator dilution may be clinically useful to measure relative lung perfusion, but there is limited information on the performance of this technique. METHODS: Thirteen pigs (50-66 kg) were anaesthetised and mechanically ventilated. Sequential changes in ventilation were made: (i) right-lung ventilation with left-lung collapse, (ii) two-lung ventilation with optimised PEEP, (iii) two-lung ventilation with zero PEEP after saline lung lavage, (iv) two-lung ventilation with maximum PEEP (20/25 cm HO to achieve peak airway pressure 45 cm HO), and (v) two-lung ventilation under unilateral pulmonary artery occlusion. Relative lung perfusion was assessed with EIT and central venous injection of saline 3%, 5%, and 10% (10 ml) during breath holds. Relative perfusion was determined by positron emission tomography (PET) using Gallium-labelled microspheres. EIT and PET were compared in eight regions of equal ventro-dorsal height (right, left, ventral, mid-ventral, mid-dorsal, and dorsal), and directional changes in regional perfusion were determined. RESULTS: Differences between methods were relatively small (95% of values differed by less than 8.7%, 8.9%, and 9.5% for saline 10%, 5%, and 3%, respectively). Compared with PET, EIT underestimated relative perfusion in dependent, and overestimated it in non-dependent, regions. EIT and PET detected the same direction of change in relative lung perfusion in 68.9-95.9% of measurements. CONCLUSIONS: The agreement between EIT and PET for measuring and tracking changes of relative lung perfusion was satisfactory for clinical purposes. Indicator-based EIT may prove useful for measuring pulmonary perfusion at bedside.
Three magnetometers based on dc superconducting quantum interference devices (SQUIDs) fabricated from YBa2Cu3O7 x have been operated in a magnetically shielded room using a flux-locked loop involving additional positive feedback with bias current reversal. Two of these devices, integrated multiloop dc SQUIDs with outer diameters of 7 mm, achieved white noise levels of 10 fT/√Hz for bicrystal junctions and 30 fT/√Hz for step‐edge junctions. The third magnetometer involved a flux transformer with a 10×10 mm2 pickup coil connected to a 16-turn input coil which was inductively coupled to a bicrystal SQUID. This device achieved a white noise of 16.2 fT/√Hz. High quality magnetocardiograms were obtained without signal averaging.
Conference Contributions (12)
Student Theses (1)
J. Koch. Enhancing conduction velocity estimation by atrial electrogram analysis. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Bachelorarbeit. 2020
The conduction velocity (CV) is a very promising measure that can be used to deduce physiological pathologies causing abnormal electrical pathways in the cardiac tissue. Critical sites that cause arrhythmia can be located and ablated during a cardiac electrophysiological study. The local activation time (LAT) maps are used to calculate the CV by approximating the measured LAT points with a plane composed of Gaussian radial basis functions (RBFs). However, the measured LATs can be distorted by signal interferences or noise and, thus, do not always correspond to the true activation time of the tissue. Therefore, including an uncer- tainty measure of the LATs in the algorithm could help to improve the CV estimation. The neighborhood area determines the averaging and the local precision of the CV. Furthermore, the input parameters for the surface reconstruction, such as the number of neighborhood points and the width of the Gaussians are decisive factors for a successful fitting and should be investigated. In this thesis, a method estimating the uncertainty of LATs through intracardiac electrograms (EGMs) analysis is elaborated and included in the CV estimation algorithm. The LATs of the surface fitting are weighted in the surface reconstruction to prevent outliers falsifying the CV estimation. A study revealing the influence of the RBF parameters, such as the width of the Gaussian bell and the number of neighborhood points for averaging, is conducted. Given the present results, the estimated uncertainty of LAT points has delivered more stable results for the CV estimation. Furthermore, our work has led us to conclude, that the CV estimation algorithm is very sensitive to changes in width of the Gaussian function. Eventually, the thesis reports possible causes for errors in the CV estimation and suggests further optimization possibilities.