Layered Fusion Reconstruction Based on Fuzzy Features for Multi-Conductivity Electrical Impedance Tomography.

In medical imaging, detecting tissue anomalies is vital for accurate diagnosis and effective treatment. Electrical impedance tomography (EIT) is a non-invasive technique that monitors the changes in electrical conductivity within tissues in real time. However, the current challenge lies in simply and accurately reconstructing multi-conductivity distributions. This paper introduces a layered fusion framework for EIT to enhance imaging in multi-conductivity scenarios. The method begins with pre-imaging and extracts the main object from the fuzzy image to form one layer. Then, the voltage difference in the other layer, where the local anomaly is located, is estimated. Finally, the corresponding conductivity distribution is established, and multiple layers are fused to reconstruct the multi-conductivity distribution. The simulation and experimental results demonstrate that compared to traditional methods, the proposed method significantly improves multi-conductivity separation, precise anomaly localization, and robustness without adding uncertain parameters. Notably, the proposed method has demonstrated exceptional accuracy in local anomaly detection, with positional errors as low as 1% and size errors as low as 33%, which significantly outperforms the traditional method with respective minimum errors of 9% and 228%. This method ensures a balance between the simplicity and accuracy of the algorithm. At the same time, it breaks the constraints of traditional linear methods, struggling to identify multi-conductivity distributions, thereby providing new perspectives for clinical EIT.

Posterior Approximate Clustering-Based Sensitivity Matrix Decomposition for Electrical Impedance Tomography.

This paper introduces a sensitivity matrix decomposition regularization (SMDR) method for electric impedance tomography (EIT). Using k-means clustering, the EIT-reconstructed image can be divided into four clusters, derived based on image features, representing posterior information. The sensitivity matrix is then decomposed into distinct work areas based on these clusters. The elimination of smooth edge effects is achieved through differentiation of the images from the decomposed sensitivity matrix and further post-processing reliant on image features. The algorithm ensures low computational complexity and avoids introducing extra parameters. Numerical simulations and experimental data verification highlight the effectiveness of SMDR. The proposed SMDR algorithm demonstrates higher accuracy and robustness compared to the typical Tikhonov regularization and the iterative penalty term-based regularization method (with an improvement of up to 0.1156 in correlation coefficient). Moreover, SMDR achieves a harmonious balance between image fidelity and sparsity, effectively addressing practical application requirements.

Remotely Powered Two-Wire Cooperative Sensors for Bioimpedance Imaging Wearables.

Bioimpedance imaging aims to generate a 3D map of the resistivity and permittivity of biological tissue from multiple impedance channels measured with electrodes applied to the skin. When the electrodes are distributed around the body (for example, by delineating a cross section of the chest or a limb), bioimpedance imaging is called electrical impedance tomography (EIT) and results in functional 2D images. Conventional EIT systems rely on individually cabling each electrode to master electronics in a star configuration. This approach works well for rack-mounted equipment; however, the bulkiness of the cabling is unsuitable for a wearable system. Previously presented cooperative sensors solve this cabling problem using active (dry) electrodes connected via a two-wire parallel bus. The bus can be implemented with two unshielded wires or even two conductive textile layers, thus replacing the cumbersome wiring of the conventional star arrangement. Prior research demonstrated cooperative sensors for measuring bioimpedances, successfully realizing a measurement reference signal, sensor synchronization, and data transfer though still relying on individual batteries to power the sensors. Subsequent research using cooperative sensors for biopotential measurements proposed a method to remove batteries from the sensors and have the central unit supply power over the two-wire bus. Building from our previous research, this paper presents the application of this method to the measurement of bioimpedances. Two different approaches are discussed, one using discrete, commercially available components, and the other with an application-specific integrated circuit (ASIC). The initial experimental results reveal that both approaches are feasible, but the ASIC approach offers advantages for medical safety, as well as lower power consumption and a smaller size.

Electrical Impedance Tomography of Industrial Two-Phase Flow Based on Radial Basis Function Neural Network Optimized by the Artificial Bee Colony Algorithm.

In electrical impedance tomography (EIT) detection of industrial two-phase flows, the Gauss-Newton algorithm is often used for imaging. In complex cases with multiple bubbles, this method has poor imaging accuracy. To address this issue, a new algorithm called the artificial bee colony-optimized radial basis function neural network (ABC-RBFNN) is applied to industrial two-phase flow EIT for the first time. This algorithm aims to enhance the accuracy of image reconstruction in electrical impedance tomography (EIT) technology. The EIDORS-v3.10 software platform is utilized to generate electrode data for a 16-electrode EIT system with varying numbers of bubbles. This generated data is then employed as training data to effectively train the ABC-RBFNN model. The reconstructed electrical impedance image produced from this process is evaluated using the image correlation coefficient (ICC) and root mean square error (RMSE) criteria. Tests conducted on both noisy and noiseless test set data demonstrate that the ABC-RBFNN algorithm achieves a higher ICC value and a lower RMSE value compared to the Gauss-Newton algorithm and the radial basis function neural network (RBFNN) algorithm. These results validate that the ABC-RBFNN algorithm exhibits superior noise immunity. Tests conducted on bubble models of various sizes and quantities, as well as circular bubble models, demonstrate the ABC-RBFNN algorithm's capability to accurately determine the size and shape of bubbles. This outcome confirms the algorithm's generalization ability. Moreover, when experimental data collected from a 16-electrode EIT experimental device is employed as test data, the ABC-RBFNN algorithm consistently and accurately identifies the size and position of the target. This achievement establishes a solid foundation for the practical application of the algorithm.

E-Skin Using Fringing Field Electrical Impedance Tomography with an Ionic Liquid Domain.

Electrical impedance tomography (EIT) is a promising technique for large area tactile sensing for robotic skin. This study presents a novel EIT-based force and touch sensor that features a latex membrane acting as soft skin and an ionic liquid domain. The sensor works based on fringing field EIT where the touch or force leads to a deformation in the latex membrane causing detectable changes in EIT data. This article analyses the performance of this electronic skin in terms of its dynamical behaviour, position accuracy and quantitative force sensing. Investigation into the sensor's performance showed it to be hypersensitive, in that it can reliably detect forces as small as 64 mN. Furthermore, multi-touch discrimination and annular force sensing is displayed. The hysteresis in force sensing is investigated showing a very negligible hysteresis. This is a direct result of the latex membrane and the ionic liquid-based domain design compared to more traditional fabric-based touch sensors due to the reduction in electromechanical coupling. A novel test is devised that displayed the dynamic performance of the sensor by showing its ability to record a 1 Hz frequency, which was applied to the membrane in a tapping fashion. Overall, the results show a considerable progress in ionic liquid EIT-based sensors. These findings place the EIT-based sensors that comprise a liquid domain, at the forefront of research into tactile robotic skin.

Dynamic Hand Gesture Recognition Using Electrical Impedance Tomography.

Electrical impedance tomography (EIT) has been applied in the field of human-computer interaction due to its advantages including the fact that it is non-invasive and has both low power consumption and a low cost. Previous work has focused on static gesture recognition based on EIT. Compared with static gestures, dynamic gestures are more informative and can achieve more functions in human-machine collaboration. In order to verify the feasibility of dynamic gesture recognition based on EIT, a traditional excitation drive pattern is optimized in this paper. The drive pattern of the fixed excitation electrode is tested for the first time to simplify the measurement process of the dynamic gesture. To improve the recognition accuracy of the dynamic gestures, a dual-channel feature extraction network combining a convolutional neural network (CNN) and gated recurrent unit (GRU), namely CG-SVM, is proposed. The new center distance loss is designed in order to simultaneously supervise the intra-class distance and inter-class distance. As a result, the discriminability of the confusing data is improved. With the new excitation drive pattern and classification network, the recognition accuracy of different interference data has increased by 2.7~14.2%. The new method has stronger robustness, and realizes the dynamic gesture recognition based on EIT for the first time.

Investigation of selected respiratory effects of (dex)medetomidine in healthy Beagles.

OBJECTIVE: To investigate the effects of sedative doses of intravenous (IV) medetomidine (MED) or dexmedetomidine (DEX) on selected respiratory variables in dogs. STUDY DESIGN: Randomized, blinded, crossover study. ANIMALS: A total of eight healthy adult research Beagles. METHODS: Dogs breathing room air had an electrical impedance tomography belt placed around the chest and were maintained in right lateral recumbency. Respiratory rate (fR) in movements minute-1 (mpm) and changes in thoracic impedance (ΔZ) in arbitrary units (AU) were recorded for 120 seconds before (T0) and exactly 10 minutes (T10) after the administration of IV DEX (10 µg kg-1) or MED (20 µg kg-1), with a minimum washout period of 10 days between treatments. Minute ΔZ (ΔZ˙) was calculated by multiplying median ΔZ with fR. Data are presented as median (interquartile range). Significance for an overall effect of drugs (DEX versus MED) or treatment (T0 versus T10) was quantified with a two-way analysis of variance for repeated measures, followed by, when appropriate, Wilcoxon's signed rank test for each factor. RESULTS: Overall, fR decreased from 26 (22-29) mpm at T0 to 13 (10-21) mpm at T10 (p = 0.003) and ΔZ increased from 1.133 (0.856-1.599) AU at T0 to 1.650 (1.273-2.813) AU at T10 (p = 0.007), but ΔZ˙ did not change [30.375 (23.411-32.445) AU minute-1 at T0 and 30.581 (22.487-35.091) AU minute-1 at T10]. There was no difference between DEX and MED. Most dogs developed a peculiar breathing pattern characterized by clusters of breaths followed by short periods of apnoea. CONCLUSIONS AND CLINICAL RELEVANCE: Both drugs caused a change in breathing pattern, reduction in fR and increase in ΔZ but did not affect ΔZ˙. It is likely that (dex)medetomidine resulted in reduction in fR and increase in tidal volume without impacting minute volume.

A novel time-difference electrical impedance tomography algorithm using multi-frequency information.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: SC enables tdEIT to utilize multi-frequency information in cases where the spectral constraints are known and then provides higher quality images for applications.

Towards a System for Tracking Drug Delivery Using Frequency Excited Gold Nanoparticles.

Nanoparticle-based drugs are rapidly evolving to treat different conditions and have considerable potential. A new system based on the combination of electrical impedance tomography (EIT) imaging and a power amplifier with a RF coil has been developed to study the effect of gold nanoparticles (AuNPs) when excited in the MHz frequency range. We show that samples including AuNPs have a temperature increase of 1-1.5 °C due to the presence of RF excitation at 13.56 MHz which provides a higher rate of change for solutions without AuNPs. They also show more than a 50% increase in conductivity in difference imaging as the result of this excitation. The change for samples without AuNPs is 40%.

A Simultaneous and Continuous Excitation Method for High-Speed Electrical Impedance Tomography with Reduced Transients and Noise Sensitivity.

This paper presents a concept for soft field tomographic scan of all the projections of electromagnetic waves emanating from an array of electrodes. Instead of the sequential excitation of all pairs of electrodes in the list of all projections, the new method present here consists of a single and continuous excitation. This excitation signal is the linear combination of the excitation signals in the projection set at different AC frequencies. The response to a given projection is discriminated by selecting the corresponding AC frequency component in the signal spectra of the digitally demodulated signals. The main advantage of this method is the suppression of transients after each projection, which is particularly problematic in electrical impedance tomography due to contact impedance phenomena and skin effect. The second benefit over the sequential scan method is the increased number of samples for each measurement for reduced noise sensitivity with digital demodulation. The third benefit is the increased temporal resolution in high-speed applications. The main drawback is the increased number of signal sources required (one per electrode). This paper focuses on electrical impedance tomography, based on earlier work by the authors. An experimental proof-of-concept using a simple 4-electrodes electrical impedance tomographic system is presented using simulations and laboratory data. The method presented here may be extended to other modalities (ultrasonic, microwave, optical, etc.).

Real-time conductivity imaging of temperature and tissue property changes during radiofrequency ablation: an ex vivo model using weighted frequency difference.

We demonstrated the feasibility of time difference and weighted frequency difference conductivity imaging for real-time monitoring of temperature distribution and ablation region estimation during radiofrequency (RF) ablation. The electrical conductivity spectrum of biological tissue reflects mobility of ions in intra- and extra-cellular fluids and changes in cellular morphology induced by heating. The time series conductivity spectra were measured in an ex vivo bovine liver by a high-speed electrical impedance tomography (EIT) system. The EIT system was protected by filters to suppress RF energy and allow interleaved real-time imaging. We recorded time and weighted frequency-difference conductivity images and direct temperature variations at the ablation region and control region during 8 min ablation and for the following 66 min of cooling. Conductivity variation in regions of interest was compared with temperature recordings. Contours of conductivity change were visualized and compared to estimate the ablation area. EIT images confirmed increase of conductivity at all frequencies and loss of frequency conductivity change associated with loss of cellular structure. Time difference conductivity images showed changes due to both heating during ablation and heat dissipation following ablation together with tissue property changes. Weighted frequency-difference images presented persistent changes following heating due to the morphological change in the ablation zone.

Research trends and hotspots in the field of electrical impedance tomography for mechanical ventilation: a bibliometric analysis.

Background: Electrical impedance tomography (EIT) is a relatively recent functional imaging technique that is both noninvasive and radiation free. EIT measures the associated voltage when a weak current is applied to the surface of the human body to determine the distribution of electrical resistance within tissues. We performed a bibliometrics-based review to explore the geographic hotspots of current research and future trends developing in the field of EIT for mechanical ventilation. Methods: The Web of Science database was searched from its inception to June 25, 2023. CiteSpace software was used to visualize and analyze the relevant literature and identify the most impactful literature, trends, and hotspots. Results: 363 articles describing EIT use in mechanical ventilation were identified. A fluctuating growth in the number of publications was observed from 1998 to 2023. Germany had the highest number of articles (n=154), followed by Italy (n=53) and China (n=52). A cluster analysis of keyword co-occurrence revealed that "titration", "ventilator-related lung injury", and "oxygenation" were the most actively researched terms associated with the use of EIT in mechanically ventilated patients. Conclusions: Significant progress has been made in EIT research for mechanical ventilation. EIT research is limited to a small number of countries with a present research focus on the prevention and treatment of ventilator-related lung injury, oxygenation status, and prone ventilation. These topics are expected to remain research hotspots in the future.

Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system.

Objective.Wearable electrical impedance tomography (EIT) can be used to monitor regional lung ventilation and perfusion at the bedside. Due to its special system architecture, the amplitude of the injected current is usually limited compared to stationary EIT system. This study aims to evaluate the performance of current injection patterns with various low-amplitude currents in healthy volunteers.Approach.A total of 96 test sets of EIT measurement was recorded in 12 healthy subjects by employing adjacent and opposite current injection patterns with four amplitudes of small current (i.e. 1 mA, 500 uA, 250 uA and 125 uA). The performance of the two injection patterns with various currents was evaluated in terms of signal-to-noise ratio (SNR) of thorax impedance, EIT image metrics and EIT-based clinical parameters.Main results.Compared with adjacent injection, opposite injection had higher SNR (p< 0.01), less inverse artifacts (p< 0.01), and less boundary artifacts (p< 0.01) with the same current amplitude. In addition, opposite injection exhibited more stable EIT-based clinical parameters (p< 0.01) across the current range. For adjacent injection, significant differences were found for three EIT image metrics (p< 0.05) and four EIT-based clinical parameters (p< 0.01) between the group of 125 uA and the other groups.Significance.For better performance of wearable pulmonary EIT, currents greater than 250 uA should be used in opposite injection, 500 uA in adjacent one, to ensure a high level of SNR, a high quality of reconstructed image as well as a high reliability of clinical parameters.

Evaluation of lung homogeneity in neonates and small infants during general anaesthesia using electrical impedance tomography: a prospective observational study.

Background: Prolonged mechanical ventilation can create heterogeneous ventilation patterns, which increase the risk of lung injury in infants. However, little is understood about the risk of brief exposure to mechanical ventilation during anaesthesia. The aim of this prospective observational study was to describe the regional pattern of lung ventilation during general anaesthesia in healthy neonates and infants, using electrical impedance tomography. Methods: Twenty infants (age 3 days to 12 months), without known lung disease and receiving general anaesthesia with endotracheal intubation for supine positioned surgery, were included in the study. Anaesthesia and ventilation management was at the discretion of the treating clinician. Standardised lung imaging using electrical impedance tomography was made at six time points during anaesthesia from induction to post-extubation. At each time point, the gravity-dependent and right-left lung centre of ventilation was calculated. Results: Tidal ventilation favoured the dorsal lung regions at induction, with a median (inter-quartile range) centre of ventilation (CoV) of 58.2 (53.9-59.3)%. After intubation, there was a redistribution of ventilation to the ventral lung, with the greatest change occurring early in surgery: CoV of 53.8 (52.3-55.2)%. After extubation, CoV returned to pre-intubation values: 56.5 (54.7-58)%. Across all time points, the pattern of ventilation favoured the right lung. Conclusions: General anaesthesia creates heterogenous patterns of ventilation similar to those reported during prolonged mechanical ventilation. This potentially poses a risk for lung injury that may not be recognised clinically. These results suggest the need to better understand the impact of general anaesthesia on the developing lung. Clinical trial registration: Australian New Zealand Clinical Trials Registry (ACTRN 12616000818437, 22 June 2016).

A novel framework for three-dimensional electrical impedance tomography reconstruction of maize ear via feature reconfiguration and residual networks.

Electrical impedance tomography (EIT) provides an indirect measure of the physiological state and growth of the maize ear by reconstructing the distribution of electrical impedance. However, the two-dimensional (2D) EIT within the electrode plane finds it challenging to comprehensively represent the spatial distribution of conductivity of the intact maize ear, including the husk, kernels, and cob. Therefore, an effective method for 3D conductivity reconstruction is necessary. In practical applications, fluctuations in the contact impedance of the maize ear occur, particularly with the increase in the number of grids and computational workload during the reconstruction of 3D spatial conductivity. These fluctuations may accentuate the ill-conditioning and nonlinearity of the EIT. To address these challenges, we introduce RFNetEIT, a novel computational framework specifically tailored for the absolute imaging of the three-dimensional electrical impedance of maize ear. This strategy transforms the reconstruction of 3D electrical conductivity into a regression process. Initially, a feature map is extracted from measured boundary voltage via a data reconstruction module, thereby enhancing the correlation among different dimensions. Subsequently, a nonlinear mapping model of the 3D spatial distribution of the boundary voltage and conductivity is established, utilizing the residual network. The performance of the proposed framework is assessed through numerical simulation experiments, acrylic model experiments, and maize ear experiments. Our experimental results indicate that our method yields superior reconstruction performance in terms of root-mean-square error (RMSE), correlation coefficient (CC), structural similarity index (SSIM), and inverse problem-solving time (IPST). Furthermore, the reconstruction experiments on maize ears demonstrate that the method can effectively reconstruct the 3D conductivity distribution.

Portable noninvasive technologies for early breast cancer detection: A systematic review.

Breast cancer remains a leading cause of cancer mortality worldwide, with early detection crucial for improving outcomes. This systematic review evaluates recent advances in portable non-invasive technologies for early breast cancer detection, assessing their methods, performance, and potential for clinical implementation. A comprehensive literature search was conducted across major databases for relevant studies published between 2015 and 2024. Data on technology types, detection methods, and diagnostic performance were extracted and synthesized from 41 included studies. The review examined microwave imaging, electrical impedance tomography (EIT), thermography, bioimpedance spectroscopy (BIS), and pressure sensing technologies. Microwave imaging and EIT showed the most promise, with some studies reporting sensitivities and specificities over 90 %. However, most technologies are still in early stages of development with limited large-scale clinical validation. These innovations could complement existing gold standards, potentially improving screening rates and outcomes, especially in underserved populations, whiles decreasing screening waiting times in developed countries. Further research is therefore needed to validate their clinical efficacy, address implementation challenges, and assess their impact on patient outcomes before widespread adoption can be recommended.

Separation of ventilation and perfusion of electrical impedance tomography image streams using multi-dimensional ensemble empirical mode decomposition.

Objective.In the future, thoracic electrical impedance tomography (EIT) monitoring may include continuous and simultaneous tracking of both breathing and heart activity. However, an effective way to decompose an EIT image stream into physiological processes as ventilation-related and cardiac-related signals is missing.Approach.This study analyses the potential ofMulti-dimensional Ensemble Empirical Mode Decompositionby application of theComplete Ensemble Empirical Mode Decomposition with Adaptive Noiseand a novel frequency-based combination criterion for detrending, denoising and source separation of EIT image streams, collected from nine healthy male test subjects with similar age and constitution.Main results.In this paper, a novel approach to estimate the lung, the heart and the perfused regions of an EIT image is proposed, which is based on theRoot Mean Square Errorbetween the index of maximal respiratory and cardiac variation to their surroundings. The summation of the indexes of the respective regions reveals physiologically meaningful time signals, separated into the physiological bandwidths of ventilation and heart activity at rest. Moreover, the respective regions were compared with the relative thorax movement and photoplethysmogram (PPG) signal. In linear regression analysis and in the Bland-Altman plot, the beat-to-beat time course of both the ventilation-related signal and the cardiac-related signal showed a high similarity with the respective reference signal.Significance.Analysis of the data reveals a fair separation of ventilatory and cardiac activity realizing the aimed source separation, with optional detrending and denoising. For all performed analyses, a feasible correlation of 0.587 to 0.905 was found between the cardiac-related signal and the PPG signal.

Locoregional lung ventilation distribution in girls with adolescent idiopathic scoliosis and healthy adolescents. The immediate effect of Schroth 'derotational breathing' exercise in a controlled-trial.

BACKGROUND: Scoliosis curves present transverse plane deviations due to vertebral rotation. The Schroth method supports thoracic derotation by training patients to exert "derotational" breathing based on assumed enhanced ventilation in areas called "humps" in scoliosis and a patient's ability to voluntarily direct ventilation in less ventilated areas called "flats." OBJECTIVE: To assess the asymmetric ventilation distribution and the ability of patients to direct their ventilation to perform derotational breathing. METHODS: Twelve girls with adolescent idiopathic scoliosis and 12 healthy girls performed 3 × 3 min of rest, maximal, and derotational breathing. Electrical impedance tomography was used to record locoregional lung ventilation distribution (LLVD) within 4 thoracic regions of interest: anterior right (ROI 1), anterior left (ROI 2), posterior right (ROI 3), and posterior left (ROI 4) quadrants. Humps and flats were the sums of ROI '2 + 3' and ROI '1 + 4,' respectively. RESULTS: Overall, no difference in LLVD was observed in the flats and humps between groups. At rest, the LLVD in the humps was more elevated than that in the flats (51.5 ± 8.1% versus 43.6 ± 7.9%; p = .021) when considering both groups. Maximal and derotational breathing led to a more homogeneous LLVD between the humps and flats. CONCLUSION: The postulated derotational breathing effect was not confirmed.

Evaluating bronchial anastomotic stenosis dynamically by electrical impedance tomography in a lung transplant recipient: a case report.

Background: Lung transplantation has become the first-choice treatment method for end-stage pulmonary disease patients. However, various postoperative airway complications hinder the progress of lung transplantation, with the most frequently reported complication being bronchial stenosis. Pendelluft is an intrapulmonary air redistribution in areas with different time constants and this phenomenon is largely unobservable. Meanwhile, pendelluft is the movement of gas in the lung without a change in tidal volume and can contribute to injury by introducing regional overdistension and tidal recruitment. Electrical impedance tomography (EIT) is a radiation-free and noninvasive imaging tool that can be used to evaluate pulmonary ventilation and perfusion. EIT is also a novel imaging technique that allows real-time detection of pendelluft. Case Description: A single lung transplant recipient had bronchial anastomotic stenosis caused by necrosis. The patient was admitted to the intensive care unit for the second time due to worsening oxygenation. We evaluated the patient's pulmonary ventilation and perfusion and pendelluft effect dynamically by EIT. The saline bolus injection method was used to evaluate pulmonary perfusion distribution. We removed the bronchial anastomosis necrosis using bronchoscopy biopsy forceps. The ventilation/perfusion (V/Q) matching in the transplanted lung improved compared to that before necrosis removal. After necrosis removal, the global pendelluft in the lung transplant recipient improved. Conclusions: EIT can be used to quantitatively evaluate the pendelluft and V/Q matching due to bronchial stenosis in lung transplantation. This case also demonstrated the potential of EIT as a dynamic pulmonary functional imaging tool for lung transplantation.