Category: IEEE Transactions on Biomedical Engineering

Objective: The multiplicative regularization scheme is applied to three-dimensional electrical impedance tomography (EIT) image reconstruction problem to alleviate its ill-posedness. Methods: A cost functional is constructed by multiplying the data misfit functional with the regularization functional. The regularization functional is based on a weighted $L^2$-norm with the edge-preserving characteristic. Gauss–Newton method is used to minimize the cost functional. A method based on the discrete exterior calculus (DEC) theory is introduced to formulate the discrete gradient and divergence operators related to the regularization on unstructured meshes. Results: Both numerical and experimental results show good reconstruction accuracy and anti-noise performance of the algorithm. The reconstruction results using human thoracic data show promising applications in thorax imaging. Conclusion: The multiplicative regularization can be applied to EIT image reconstruction with promising applications in thorax imaging. Significance: In the multiplicative regularization scheme, there is no need to set an artificial regularization parameter in the cost functional. This helps to reduce the workload related to choosing a regularization parameter which may require expertise and many numerical experiments. The DEC-based method provides a systematic and rigorous way to formulate operators on unstructured meshes. This may help EIT image reconstructions using regularizations imposing structural or spatial constraints.

Presents the front cover for this issue of the publication.

Objective: Breast cancer is the second leading cause of cancer death among US women; hence, identifying potential drug targets is an ever increasing need. In this paper, we integrate existing biological information with graphical models to deduce the significant nodes in the breast cancer signaling pathway. Methods: We make use of biological information from the literature to develop a Bayesian network. Using the relevant gene expression data we estimate the parameters of this network. Then, using a message passing algorithm, we infer the network. The inferred network is used to quantitatively rank different interventions for achieving a desired phenotypic outcome. The particular phenotype considered here is the induction of apoptosis. Results: Theoretical analysis pinpoints to the role of Cryptotanshinone, a compound found in traditional Chinese herbs, as a potent modulator for bringing about cell death in the treatment of cancer. Conclusion: Using a mathematical framework, we showed that the combination therapy of mTOR and STAT3 genes yields the best apoptosis in breast cancer. Significance: The computational results we arrived at are consistent with the experimental results that we obtained using Cryptotanshinone on MCF-7 breast cancer cell lines and also by the past results of others from the literature, thereby demonstrating the effectiveness of our model.

Objective: Deep learning has recently been applied to electrical impedance tomography (EIT) imaging. Nevertheless, there are still many challenges that this approach has to face, e.g., targets with sharp corners or edges cannot be well recovered when using circular inclusion training data. This paper proposes an iterative-based inversion method and a convolutional neural network (CNN) based inversion method to recover some challenging inclusions such as triangular, rectangular, or lung shapes, where the CNN-based method uses only random circle or ellipse training data. Methods: First, the iterative method, i.e., bases-expansion subspace optimization method (BE-SOM), is proposed based on a concept of induced contrast current (ICC) with total variation regularization. Second, the theoretical analysis of BE-SOM and the physical concepts introduced there motivate us to propose a dominant-current deep learning scheme for EIT imaging, in which dominant parts of ICC are utilized to generate multi-channel inputs of CNN. Results: The proposed methods are tested with both numerical and experimental data, where several realistic phantoms including simulated pneumothorax and pleural effusion pathologies are also considered. Conclusions and Significance: Significant performance improvements of the proposed methods are shown in reconstructing targets with sharp corners or edges. It is also demonstrated that the proposed methods are capable of fast, stable, and high-quality EIT imaging, which is promising in providing quantitative images for potential clinical applications.

An efficient and precise liver extraction from computed tomography (CT) images is a crucial step for computer-aided hepatic diseases diagnosis and treatment. Considering the possible risk to patient's health due to X-ray radiation of repetitive CT examination, low-dose CT (LDCT) is an effective solution for medical imaging. However, inhomogeneous appearances and indistinct boundaries due to additional noise and streaks artifacts in LDCT images often make it a challenging task. This study aims to extract a liver model from LDCT images for facilitating medical expert in surgical planning and post-operative assessment along with low radiation risk to the patient. Our method carried out liver extraction by employing residual convolutional neural networks (LER-CN), which is further refined by noise removal and structure preservation components. After patch-based training, our LER-CN shows a competitive performance relative to state-of-the-art methods for both clinical and publicly available MICCAI Sliver07 datasets. We have proposed training and learning algorithms for LER-CN based on back propagation gradient descent. We have evaluated our method on 150 abdominal CT scans for liver extraction. LER-CN achieves dice similarity coefficient up to 96.5$pm text{1.8}%$, decreased volumetric overlap error up to 4.30$pm text{0.58}%$, and average symmetric surface distance less than 1.4 $pm text{0.5mm}$. These findings have shown that LER-CN is a favorable method for medical applications with high efficiency allowing low radiation risk to patients.

We present novel voltage stimulation buffers with controlled output current, along with recording circuits featuring adjustable high-pass cut-off filtering to perform efficient stimulation while actively suppressing stimulation artifacts in high-density microelectrode arrays. Owing to the dense packing and close proximity of the electrodes in such systems, a stimulation through one electrode can cause large electrical artifacts on neighboring electrodes that easily saturate the corresponding recording amplifiers. To suppress such artifacts, the high-pass corner frequencies of all available 2048 recording channels can be raised from several Hz to several kHz by applying a “soft-reset” or pole-shifting technique. With the implemented artifact suppression technique, the saturation time of the recording circuits, connected to electrodes in immediate vicinity to the stimulation site, could be reduced to less than 150 μs. For the stimulation buffer, we developed a circuit, which can operate in two modes: either control of only the stimulation voltage or control of current and voltage during stimulation. The voltage-only controlled mode employs a local common-mode feedback operational transconductance amplifier with a near rail-to-rail input/output range, suitable for driving high-capacitive loads. The current/voltage controlled mode is based on a positive current conveyor generating adjustable output currents, whereas its upper and lower output voltages are limited by two feedback loops. The current/voltage controlled circuit can generate stimulation pulses up to 30 μA with less than ±0.1% linearity error in the low-current mode and up to 300 μA with less than ±0.2% linearity error in the high-current mode.

Objectives: Restenosis remains a challenge for the treatment of atherosclerosis due to the damage of the endothelial layer and induced proliferation of the smooth muscle cell. Methods: A new RF heating strategy was proposed to selectively ablate the atherosclerosis plaque, and to thermally inhibit the proliferation of smooth muscle cells, while keeping the endothelial cells intact. To achieve the goal, an internal cooling agent and distributed electrodes have been integrated in the new designed balloon catheter to focus the shape conformal energy onto the plaque shape. A three-dimensional (3-D) model with experimentally fitted parameters has been established to demonstrate the heating ability of the design and evaluate the microelectrodes configurations for different plaque geometries. Results: The 3-D shape of the lesions resulting from different electrodes settings is obtained. It is found that by individual control of the micro-electrodes, special shapes of the lesions can be formed, which can match the eccentric crescent plaques. Besides, through changing of the polarity of the electrodes, separate lesions can be reached. This suggests the possibility for treatment of disconnected plaques in situ. Conclusion: By the control of RF heating and convection coefficient of the internal cooling agent, a targeted heating region away from the inner surface of the blood vessel can be realized. Significance: This study has illustrated the possibility of achieving a precision thermal treatment of atherosclerosis in favor of inhibiting further restenosis.

Objective: Fusion of magnetic resonance imaging (MRI) breast images with microwave tomography is accomplished through a soft prior technique, which incorporates spatial information (from MRI), i.e., accurate boundary location of different regions of interest, into the regularization process of the microwave image reconstruction algorithm. Methods: Numerical experiments were completed on a set of three-dimensional (3-D) breast geometries derived from MR breast data with different parenchymal densities, as well as a simulated tumor to evaluate the performance over a range of breast shapes, sizes, and property distributions. Results: When the soft prior regularization technique was applied, both permittivity and conductivity relative root mean square error values decreased by more than 87% across all breast densities, except in two cases where the error decrease was only 55% and 78%. In addition, the incorporation of structural priors increased contrast between tumor and fibroglandular tissue by 59% in permittivity and 192% in conductivity. Conclusion: This study confirmed that the soft prior algorithm is robust in 3-D and can function successfully across a range of complex geometries and tissue property distributions. Significance: This study demonstrates that our microwave tomography is capable of recovering accurate tissue property distributions when spatial information from MRI is incorporated through soft prior regularization.

Objective: The aim of the study was to show if pulse rise times (PRTs) extracted from photoplethysmographic (PPG) pulse waves (PWs) have an association with peripheral arterial disease (PAD) or its endovascular treatment, percutanoeus transluminal angioplasty (PTA) of the superficial femoral artery. Methods: Lower and upper limb PPG PWs were recorded and analyzed from 24 patients who suffered from PAD. The measurements were conducted before and after the treatment, and one month later by using transmission-mode PPG-probes placed in the index finger and second toe. Ankle-to-brachial pressure index and toe pressures were used as references in clinical patient measurements. PRTs, i.e., the time from the foot point to the peak point of the PW, were extracted from the PWs and compared bilaterally. The results from the PAD patients were also compared with 31 same-aged and 34 younger control subjects. Results: Statistically significant differences were found between the pretreatment PRTs of the treated limb of the PAD patients and the same-aged control subjects ($p< 10^{-9}$, Mann–Whitney U-test). The changes in the PRT of the treated lower limb were observed immediately after the PTA ($p< 0.001$, Student's t-test), and after one month ($p< 0.0005$), whereas the PRTs of the non-treated lower limb and upper limb did not indicate changes between different examinations. Conclusion: Results show that a PRT greater than 240 ms indicates PAD-lesions in the lower limb. Significance: This proof-of-concept study suggests that the PRT could be an effective and easy-to-use indicator for PAD a- d monitoring the effectiveness of its treatment.

Objective: We aim to improve operational robustness of liquid scanning probes. Two main failure modes to be addressed are an obstruction of the flow path of the processing liquid and a deviation from the desired gap distance between probe and sample. Methods: We introduce a multi-functional design element, a microfluidic bypass channel, which can be operated in dc and in ac mode, each preventing one of the two main failure modes. Results: In dc mode, the bypass channel is filled with liquid and exhibits resistive behavior, enabling the probe to passively react to an obstruction. In the case of an obstruction of the flow path, the processing liquid is passively diverted through the bypass to prevent its leakage and to limit the buildup of high pressure levels. In ac mode, the bypass is filled with gas and has capacitive characteristics, allowing the gap distance between the probe and the sample to be monitored by observing a phase shift in the motion of two gas–liquid interfaces. For a modulation of the input pressure at 4 Hz, significant changes of the phase shift were observed up to a gap distance of 25 μm. Conclusion: The presented passive design element counters both failure modes in a simple and highly compatible manner. Significance: Liquid scanning probes enabling targeted interfacing with biological surfaces are compatible with a wide range of workflows and bioanalytical applications. An improved operational robustness would facilitate rapid and widespread adoption of liquid scanning probes in research as well as in diagnostics.