An on-line processing strategy for head movement interferences removal of dynamic brain electrical impedance tomography based on wavelet decomposition

Robust electrical impedance tomography for biological application: A mini review

Electrical impedance tomography (EIT) has been used by researchers across several areas because of its low-cost and no-radiation properties. Researchers use complex conductivity in bioimpedance experiments to evaluate changes in various indicators within the image target. The diverse volumes and edges of biological tissues and the large impedance range impose dedicated demands on hardware design. The EIT hardware with a high signal-to-noise ratio (SNR), fast scanning and suitable for the impedance range of the image target is a fundamental foundation that EIT research needs to be equipped with. Understanding the characteristics of this technique and state-of-the-art design will accelerate the development of the robust system and provide a guidance for the superior performance of next-generation EIT. This review explores the hardware strategies for EIT proposed in the literature.

Advances in electrical impedance tomography-based brain imaging

Novel advances in the field of brain imaging have enabled the unprecedented clinical application of various imaging modalities to facilitate disease diagnosis and treatment. Electrical impedance tomography (EIT) is a functional imaging technique that measures the transfer impedances between electrodes on the body surface to estimate the spatial distribution of electrical properties of tissues. EIT offers many advantages over other neuroimaging technologies, which has led to its potential clinical use. This qualitative review provides an overview of the basic principles, algorithms, and system composition of EIT. Recent advances in the field of EIT are discussed in the context of epilepsy, stroke, brain injuries and edema, and other brain diseases. Further, we summarize factors limiting the development of brain EIT and highlight prospects for the field. In epilepsy imaging, there have been advances in EIT imaging depth, from cortical to subcortical regions. In stroke research, a bedside EIT stroke monitoring system has been developed for clinical practice, and data support the role of EIT in multi-modal imaging for diagnosing stroke. Additionally, EIT has been applied to monitor the changes in brain water content associated with cerebral edema, enabling the early identification of brain edema and the evaluation of mannitol dehydration. However, anatomically realistic geometry, inhomogeneity, cranium completeness, anisotropy and skull type, etc., must be considered to improve the accuracy of EIT modeling. Thus, the further establishment of EIT as a mature and routine diagnostic technique will necessitate the accumulation of more supporting evidence.

Removing Clinical Motion Artifacts During Ventilation Monitoring With Electrical Impedance Tomography: Introduction of Methodology and Validation With Simulation and Patient Data

Objective

Electrical impedance tomography (EIT) is a bedside tool for lung ventilation and perfusion assessment. However, the ability for long-term monitoring diminished due to interferences from clinical interventions and motion artifacts. The purpose of this study is to investigate the feasibility of the discrete wavelet transform (DWT) to detect and remove the common types of motion artifacts in thoracic EIT.

Methods

Baseline drifting, step-like and spike-like interferences were simulated to mimic three common types of motion artifacts. The discrete wavelet decomposition was employed to characterize those motion artifacts in different frequency levels with different wavelet coefficients, and those motion artifacts were then attenuated by suppressing the relevant wavelet coefficients. Further validation was conducted in two patients when motion artifacts were introduced through pulsating mattress and deliberate body movements. The db8 wavelet was used to decompose the contaminated signals into several sublevels.

Results

In the simulation study, it was shown that, after being processed by DWT, the signal consistency improved by 92.98% for baseline drifting, 97.83% for the step-like artifact, and 62.83% for the spike-like artifact; the signal similarity improved by 77.49% for baseline drifting, 73.47% for the step-like artifact, and 2.35% for the spike-like artifact. Results from patient data demonstrated the EIT image errors decreased by 89.24% (baseline drifting), 88.45% (step-like artifact), and 97.80% (spike-like artifact), respectively; the data correlations between EIT images without artifacts and the processed were all > 0.95.

Conclusion

This study found that DWT is a universal and effective tool to detect and remove these motion artifacts.

Real-time monitoring hypoxia at high altitudes using electrical bioimpedance technique: an animal experiment

Hypoxia poses a serious threat to pilots. The aim of this study was to examine the efficacy of electrical bioimpedance (EBI) in detecting the onset of hypoxia in real time in a rabbit hypoxia model. Thirty-two New Zealand rabbits were divided equally into four groups (control group and three hypoxia groups, i.e., mild, moderate, and severe). Hypoxia was induced by simulating various altitudes in the hypobaric oxygen chamber (3,000 m, 5,000 m, and 8,000 m). Both cerebral impedance and blood oxygen (Sp_O2) were monitored continuously. Results showed that the cerebral impedance increased immediately during the period of increasing altitude and decreased quickly to the initial baseline at the phase of descending altitude. Moreover, the change of cerebral impedance in the mild hypoxia group (3,000 m) was significantly smaller than those in the other two groups (5,000 m and 8,000 m, P < 0.05). The changes in cerebral impedance and Sp_O2 were significantly correlated based on the total of measurement data (r² = 0.628, P < 0.001). Furthermore, the agreement analysis performed with Bland-Altman and standardized residual plots exhibited high concordance between cerebral impedance and Sp_O2. Receiver operator characteristic analysis manifested that the sensitivity, specificity, and area under the curve using cerebral impedance for changes in Sp_O2 >10% were 0.735, 0.826, and 0.845, respectively. These findings demonstrated that EBI could sensitively and accurately monitor changes of cerebral impedance induced by hypoxia, which might provide a potential tool for the real-time and noninvasive monitoring of hypoxic condition of pilots in flight for early identification of hypoxia.NEW & NOTEWORTHY This study is the first to examine the efficacy of electrical bioimpedance (EBI) in detecting the onset of high-altitude hypoxia in real time. The novelty of this research includes three aspects. First, the cerebral impedance of rabbits increased immediately during the rising of altitude and decreased quickly to the initial baseline at the phase of descending altitude. Second, there was a significant correlation and high concordance between cerebral impedance and Sp_O2. Third, cerebral impedance could determine the change of Sp_O2 resulting from hypoxia.

Real-Time Detection of Hemothorax and Monitoring its Progression in a Piglet Model by Electrical Impedance Tomography: A Feasibility Study

Hemothorax is a serious medical condition that can be life-threatening if left untreated. Early diagnosis and timely treatment are of great importance to produce favorable outcome. Although currently available diagnostic techniques, e.g., chest radiography, ultrasonography, and CT, can accurately detect hemothorax, delayed hemothorax cannot be identified early because these examinations are often performed on patients until noticeable symptoms manifest. Therefore, for early detection of delayed hemothorax, real-time monitoring by means of a portable and noninvasive imaging technique is needed. In this study, we employed electrical impedance tomography (EIT) to detect the onset of hemothorax in real time on eight piglet hemothorax models. The models were established by injection of 60 ml fresh autologous blood into the pleural cavity, and the subsequent development of hemothorax was monitored continuously. The results showed that EIT was able to sensitively detect hemothorax as small as 10 ml in volume, as well as its location. Also, the development of hemothorax over a range of 10 ml up to 60 ml was well monitored in real time, with a favorable linear relationship between the impedance change in EIT images and the volume of blood injected. These findings demonstrated that EIT has a unique potential for early diagnosis and continuous monitoring of hemothorax in clinical practice, providing medical staff valuable information for prompt identification and treatment of delayed hemothorax.