[Application of electrical impedance tomography imaging technology combined with generative adversarial network in pulmonary ventilation monitoring].

Electrical impedance tomography (EIT) plays a crucial role in the monitoring of pulmonary ventilation and regional pulmonary function test. However, the inherent ill-posed nature of EIT algorithms results in significant deviations in the reconstructed conductivity obtained from voltage data contaminated with noise, making it challenging to obtain accurate distribution images of conductivity change as well as clear boundary contours. In order to enhance the image quality of EIT in lung ventilation monitoring, a novel approach integrating the EIT with deep learning algorithm was proposed. Firstly, an optimized operator was introduced to enhance the Kalman filter algorithm, and Tikhonov regularization was incorporated into the state-space expression of the algorithm to obtain the initial lung image reconstructed. Following that, the imaging outcomes were fed into a generative adversarial network model in order to reconstruct accurate lung contours. The simulation experiment results indicate that the proposed method produces pulmonary images with clear boundaries, demonstrating increased robustness against noise interference. This methodology effectively achieves a satisfactory level of visualization and holds potential significance as a reference for the diagnostic purposes of imaging modalities such as computed tomography.

Leveraging Oriented Lateral Walls of Nerve Guidance Conduit with Core-Shell MWCNTs Fibers for Peripheral Nerve Regeneration.

Peripheral nerve regeneration and functional recovery rely on the chemical, physical, and structural properties of nerve guidance conduits (NGCs). However, the limited support for long-distance nerve regeneration and axonal guidance has hindered the widespread use of NGCs. This study introduces a novel nerve guidance conduit with oriented lateral walls, incorporating multi-walled carbon nanotubes (MWCNTs) within core-shell fibers prepared in a single step using a modified electrohydrodynamic (EHD) printing technique to promote peripheral nerve regeneration. The structured conduit demonstrated exceptional stability, mechanical properties, and biocompatibility, significantly enhancing the functionality of NGCs. In vitro cell studies revealed that RSC96 cells adhered and proliferated effectively along the oriented fibers, demonstrating a favorable response to the distinctive architectures and properties. Subsequently, a rat sciatic nerve injury model demonstrated effective efficacy in promoting peripheral nerve regeneration and functional recovery. Tissue analysis and functional testing highlighted the significant impact of MWCNT concentration in enhancing peripheral nerve regeneration and confirming well-matured aligned axonal growth, muscle recovery, and higher densities of myelinated axons. These findings demonstrate the potential of oriented lateral architectures with coaxial MWCNT fibers as a promising approach to support long-distance regeneration and encourage directional nerve growth for peripheral nerve repair in clinical applications.

High density trans-admittance mammography development and preliminary phantom tests.

BACKGROUND: Malignant breast tumor tissue has a significantly different electrical impedance spectrum than surrounding normal tissues. This has led to the development of impedance imaging as a supplementary or alternative method to X-ray mammography for screening and assessment of breast cancers. However low spatial resolution and poor signal to noise ratio has limited the clinical application. METHODS: In order to improve spatial resolution we developed a trans-admittance mammography (TAM) system including an array of 60×60 current sensing electrodes. We adopted a similar setup to X-ray mammography where the breast is situated between two holding plates. The top plate is a large solid metal electrode for applying a sinusoidal voltage over a range of frequencies from 50 Hz to 500 kHz. The bottom plate has 3600 current sensing electrodes that are kept at the ground potential. Currents are generated from the top voltage-applying electrode and spread throughout the breast, entering the TAM system through the array of current sensing electrodes on the bottom plate. The TAM system measures the exit currents through 6 switching modules connected to 600 electrodes each. Each switching module is connected to 12 ammeter channels which are switched sequentially to 50 of the 600 electrodes each measurement time. Each ammeter channel is comprised of a current-to-voltage converter, a gain amplifier, filters, an analog to digital converter, and a digital phase sensitive demodulator. RESULTS: We found an average noise level of 38 nA, amplitude stability of less than 0.2%, crosstalk of better than -60 dB and 70 dB signal to noise ratio over all channels and operating frequencies. Images were obtained in time difference and frequency difference modes in a saline phantom. CONCLUSION: We describe the design, construction, and calibration of a high density TAM system in detail. Successful high resolution time and frequency difference images showed regions of interest with the expected admittivity changes in the frequency spectrum.

Feasibility of anomaly detection and characterization using trans-admittance mammography with 60 × 60 electrode array.

Electrical impedance imaging has the potential to detect an early stage of breast cancer due to higher admittivity values compared with those of normal breast tissues. The tumor size and extent of axillary lymph node involvement are important parameters to evaluate the breast cancer survival rate. Additionally, the anomaly characterization is required to distinguish a malignant tumor from a benign tumor. In order to overcome the limitation of breast cancer detection using impedance measurement probes, we developed the high density trans-admittance mammography (TAM) system with 60 × 60 electrode array and produced trans-admittance maps obtained at several frequency pairs. We applied the anomaly detection algorithm to the high density TAM system for estimating the volume and position of breast tumor. We tested four different sizes of anomaly with three different conductivity contrasts at four different depths. From multifrequency trans-admittance maps, we can readily observe the transversal position and estimate its volume and depth. Specially, the depth estimated values were obtained accurately, which were independent to the size and conductivity contrast when applying the new formula using Laplacian of trans-admittance map. The volume estimation was dependent on the conductivity contrast between anomaly and background in the breast phantom. We characterized two testing anomalies using frequency difference trans-admittance data to eliminate the dependency of anomaly position and size. We confirmed the anomaly detection and characterization algorithm with the high density TAM system on bovine breast tissue. Both results showed the feasibility of detecting the size and position of anomaly and tissue characterization for screening the breast cancer.

Evaluation of anomaly detection algorithm using trans-admittance mammography with 60 × 60 electrode array.

Electrical impedance imaging has a potential to detect an early stage of breast cancer due to higher admittivity values compared with those of normal breast tissues. Specially, tumor size and extent of axillary lymph node involvement are important parameters to evaluate the breast cancer survival rate. We applied the anomaly detection algorithm to the high density trans-admittance mammography system for estimating the size and position of breast cancer. We tested 4 different size of anomaly with 3 different conductivity contrasts at 5 different depths. From a frequency difference trans-admittance map, we can readily observe the transversal position and estimate its size and depth. However, the size estimation was dependent on the admittivity contrast between anomaly and background. It requires the robust detection algorithm regardless of the conductivity contrast.