Electrical impedance tomography (EIT) is a noninvasive, radiation-free, and low-cost imaging modality for monitoring the conductivity distribution inside a patient. Nowadays, time-difference EIT (tdEIT) is used extensively as it has fast imaging speed and can reflect the dynamic changes of diseases, which make it attractive for a number of medical applications. Moreover, modeling errors are compensated to some extent by subtraction of voltage measurements collected before and after the change. However, tissue conductivity varies with frequency and tdEIT does not efficiently exploit multi-frequency information as it only uses measurements associated with a single frequency. This paper proposes a tdEIT algorithm that imposes spectral constraints on the framework of the linear least squares problem. Simulation and phantom experiments are conducted to compare the proposed spectral constraints algorithm (SC) with the damped least squares algorithm (DLS), which is a stable tdEIT algorithm used in clinical practice. The condition number and rank of the matrices needing inverses are analyzed, and image quality is evaluated using four indexes. The possibility of multi-tissue imaging and the influence of spectral errors are also explored. Significant performance improvement is achieved by combining multi-frequency and time-difference information. The simulation results show that, in one-step iteration, both algorithms have the same condition number and rank, but SC effectively reduces image noise by 20.25% compared to DLS. In addition, deformation error and position error are reduced by 8.37% and 7.86%, respectively. In two-step iteration, the rank of SC is greatly increased, which suggests that more information is employed in image reconstruction. Image noise is further reduced by an average of 32.58%, and deformation error and position error are also reduced by 20.20% and 31.36%, respectively. The phantom results also indicate that SC has stronger noise suppression and target identification abilities, and this advantage is more obvious with iteration. The results of multi-tissue imaging show that SC has the unique advantage of automatically extracting a single tissue to image. SC enables tdEIT to utilize multi-frequency information in cases where the spectral constraints are known and then provides higher quality images for applications.

Acute pulmonary embolism represents the third most prevalent cardiovascular pathology, following coronary heart disease and hypertension. Its untreated mortality rate is as high as 20–30%, which represents a significant threat to patient survival. In view of the current lack of real-time monitoring techniques for acute pulmonary embolism, this study primarily investigates the potential of the pulsatility electrical impedance tomography (EIT) technique for the detection and real-time monitoring of acute pulmonary embolism through the collection and imaging of the pulsatile signal of pulmonary blood flow. A before-and-after self-control experiment was conducted on anaesthetised domestic pigs (N = 12, 20.75 ± 2.56 kg). The changes in pulmonary perfusion caused by an acute pulmonary embolism (artificially induced) were monitored in real time using the pulsation method. This enabled the extraction of indicators such as Amplitude, Forward (Negative) Slope, and SARC, which were used to assess the local pulmonary blood flow perfusion state. Furthermore, the degree of ventilation/perfusion matching in the lungs was evaluated concurrently with the analysis of the pulmonary ventilation area. Subsequently, a control verification was conducted utilising the conventional invasive hypertonic saline (5 ml 10% NaCl) contrast technique. The perfusion alterations subsequent to embolism in the pulsatility method are highly concordant with those observed in the hypertonic saline method, as evidenced by the imaging and indicator data. In particular, the perfusion area on the side of the embolism is markedly diminished, and the absolute values of all perfusion indicators are significantly reduced. Among these, Amplitude (P < 0.001) and SARC (P < 0.001) exhibit the most pronounced alterations. Furthermore, the extracted indicators from regional ventilation demonstrated notable discrepancies, the V/Q match% (P < 0.001) and Dead Space% (P < 0.001) exhibited the most pronounced sensitivity to alterations in acute pulmonary embolism. Subsequently, a control verification was conducted utilising the hypertonic saline method, which revealed a high degree of consistency between the two methods in the detection of acute pulmonary embolism (Kappa = 0.75, P < 0.05). The EIT imaging method, which is based on the analysis of blood flow pulsation, has the potential to reflect in real time the changes in pulmonary blood flow that occur before and after an embolism. This provides a new avenue for the non-invasive real-time monitoring of patients with acute pulmonary embolism in a clinical setting.

The conductivity modeling approach in pulsed field ablation of tumors and atrial fibrillation highlights the advantages of in situ , real-time monitoring for intraoperative diagnostics to increase the ablation success. It also supports the computation of the electric field distribution for assessing the ablation zone. Pulsed electric fields increase the permeability of cell membranes, a process known as electroporation, which results in nonlinear changes in cell and tissue conductivity. This phenomenon can be described by a nonlinear conductivity model. Due to individual differences, measurement errors, and limited knowledge of the system, model parameters are inherently uncertain, reducing model reliability and accuracy. Moreover, not knowing the parameter sensitivity can make it difficult to simplify the model and realize the real-time calculation. In this study, we using a universal method to investigate the effect of uncertainty in model parameters on the outcomes and the sensitivity profiles of model parameters for two extensively used nonlinear conductivity models. The results demonstrate that the model robustness and the parameters of interest can be used as selection criteria for choosing an appropriate conductivity model. The Heaviside-based nonlinear conductivity model was then chosen for a simulation of pulmonary vein isolation based on pulsed field ablation. The most sensitive parameters in the assessment of ablation depth are pretreatment conductivity and ablation threshold, which are utilized to determine the ablation border. Ultimately, we propose some suggestions for strengthening ablation prediction and diagnosis by focusing on the most sensitive parameters in order to reduce model uncertainty and increase model confidence. This strategy can be used in various mathematical and simulation models to enhance the credibility of the model and reduce the model complexity.

The low-voltage droop of high-voltage pulses is required to provide stable pulsed electric fields in many applications. Increasing the capacitance of energy storage capacitors increases both the size and the cost of the system. In this paper, four compensation stages based on the resonant circuit have been inserted into a 16-stage solid-state Marx generator to compensate for the voltage droop in different conditions. The nearly linear part of the sinusoidal voltage is precisely added to the load during discharging as compensation, and the rectangular pulsed voltage with little droop can be realized. Different numbers of compensation stages and different resonant inductances can compensate the droop to different levels, which means the compensation effect is also adjustable. Moreover, these compensation stages can operate as common stages in Marx generators as long as we open-circuit the resonant circuits. Since the capacitors in resonant compensation stages are also charged in parallel with capacitors in common stages, no auxiliary power supply is required. Simulating and experimental results show that the droop of a 9 kV pulse can be ideally compensated over a 500 Ω resistive load at various pulse widths. The pulse width should be shorter than the length of the nearly linear part of the sinusoidal voltage.

Ventilation/perfusion (V/Q) matching represents a crucial indicator of lung function. The current for assessing V/Q in a clinical setting are inadequate for bedside monitoring purposes. They are characterised by invasiveness and an increased risk of infection. Accordingly, the present study was based on a high-performance electrical impedance tomography (EIT) system developed by our team, with the objective of exploring the feasibility of using it for non-invasive assessment of V/Q at the bedside. This was achieved by acquiring and imaging pulmonary blood flow pulsation signals and combining them with pulmonary ventilation impedance information. Continuous lung EIT imaging data were acquired at 40 fps through different body positions and breath-holding in anaesthetised domestic pigs (N = 8, 17.50 ± 1.51 kg). By analysing the blood flow pulsation impedance information, lung perfusion-related data were extracted and combined with lung ventilation impedance data to establish a pulsatility V/Q assessment method. Furthermore, the monitoring of pulmonary perfusion using hypertonic saline (5 ml of 10% NaCl) was employed as a control experiment. The results demonstrate that the V/Q results obtained through the utilisation of both methodologies exhibit a notable degree of variability in response to alterations in body position and the state of breath holding. The V/Q results obtained using the pulsatility method and the saline method were subjected to analysis using the Bland–Altman agreement test. During end-expiration breath-holding in the supine position, the results were as follows: 95% CI = 2.36% to 10.26%, bias = 6.309%. During end-inspiration breath-holding in the supine position, the results were as follows: 95% CI = 0.07% to 12.23%, bias = 6.150%. During end-expiration breath-holding in the prone position, the results were as follows: 95% CI = -0.40% to 14.43%, bias = 7.014%. During end-inspiration breath-holding in the prone position, the results were as follows: 95% CI = 1.92% to 11.17%, bias = 6.541%. Moreover, a Pearson correlation analysis revealed a significant correlation between the V/Q match% of the two methods (r = 0.7248; 95% CI = 0.50% to 0.86%; p < 0.0001). Consequently, EIT imaging based on the pulsatility method is capable of assessing V/Q alterations resulting from diverse body positions and changes during breath-holding. This approach offers a novel concept for bedside monitoring of patients.