Cerebral edema after brain injury can lead to brain damage and death if diagnosis and treatment are delayed. This study investigates the feasibility of employing electrical impedance tomography (EIT) as a non-invasive imaging tool for monitoring the development of cerebral edema, in which impedance imaging of the brain related to brain water content is compared with intracranial pressure (ICP). We enrolled forty patients with cerebral hemorrhage who underwent lateral external ventricular drain with intraventricular ICP and EIT monitoring for 3 h after initiation of dehydration treatment. The average reconstructed impedance value (ARV) calculated from EIT images was compared with ICP. Dehydration effects induced changes in ARV and ICP showed a close negative correlation in all patients, and the mean correlation reached R 2 = 0.78 ± 0.16 ( p < .001). A regression equation ( R 2 = 0.62, p < .001) was formulated from the total of measurement data. The 95% limits of agreement were − 6.13 to 6.13 mmHg. Adaptive clustering and variance analysis of normalized changes in ARV and ICP showed 92.5% similarity and no statistically significant differences ( p > .05). Moreover, the sensitivity, specificity and area under the curve of changes in ICP >10 mmHg were 0.65, 0.73 and 0.70 respectively. The findings show that EIT can monitor changes in brain water content associated with cerebral edema, which could provide a real-time and non-invasive imaging tool for early identification of cerebral edema and the evaluation of mannitol dehydration.

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Periodical changes in bioimpedance caused by blood perfusion are relatively fast and weak; therefore, a fast, high-precision imaging system is required. A novel electrical impedance tomography (EIT) system is proposed for real-time perfusion imaging. Synchronous parallel sampling is combined with timely excitation switching control to achieve fast acquisition and maintain high sampling accuracy. To further improve the overall precision of the system, a bipolar-mirror feedback voltage controlled current source and an internal calibration unit was used to improve the current precision and measurement accuracy, respectively. Test results of the resistor model show that the system has a signal-to-noise ratio of 81 dB at 50 kHz and achieves an imaging rate of 100 frames/ s. A preliminary test shows that the reconstructed EIT images reveal a complete cycle of blood exchange between the heart and lungs. Our system may provide a useful research platform for real-time and non-invasive blood perfusion imaging, which could be used in in vivo studies.

Electrical impedance tomography (EIT) is a promising medical technique for monitoring brain injury through the reflection of electrical impedance changes in internal brain tissues. However, the contact impedances at the electrode-scalp interfaces can still notably affect the EIT accuracy. Hence, we propose a method for real-time monitoring the multi-channel contact impedances of cerebral EIT using a reference electrode attached close to the head vertex. This method allows to approximate inter-channel differences and changes over time of multi-channel contact impedances. The experimental results on 36 volunteers show that the maximum relative inter-channel difference obtained from 16 disposable surface electrodes reaches 18.7%, and the maximum relative change over time reaches 19.2%. The proposed method can assist clinicians in real-time monitoring of contact conditions from the multiple electrode-scalp interfaces during the clinical application of the cerebral EIT.

Individualized lung-protective ventilation strategy is essential for patients with COVID-19. In this study, a wireless, low-power and miniaturized electrical impedance tomography (EIT) system was developed for remote and long-term monitoring of lung ventilation for patients with COVID-19 in the isolation ward of ICU. A new strategy of combining filtering and improved voltage-controlled current was employed to design the current source for a simplified system structure, and a new differential receiver circuit consisting of a buffer amplification and a differential amplification was proposed to design the voltage measurement unit for high precision. Moreover, a Bluetooth interface was adopted for wireless data transmission, and components characterized by low power consumption were selected to minimize the system power consumption. The proposed EIT system occupies a total size of 6.5*4.5*0.6 cm 3 and can work stably within 25 m from the wireless terminal installed with host EIT software. The system has a signal-to-noise of 70 dB at 50 kHz, stability of 0.1% relative change, and power consumption of 114 mW, as tested with a resistor phantom. Further, a comparison between the proposed system and a commercial ICU EIT device was conducted on nine healthy volunteers for ventilation monitoring. The correlation between lung volume and relative impedance changes was higher than 0.9 for both EIT systems (p<0.001). The analysis of the corresponding EIT images revealed that both systems delivered comparable images in terms of linearity, repeatability and regional ventilation distribution. The test and experimental results suggested that the proposed system could conveniently provide reliable data acquisition for remote and long-term lung ventilation monitoring.