The classical transillumination technique has been revitalized through recent advancements in optical technology, enhancing its applicability in the realm of biomedical research. With a new ...perspective on near-axis scattered light, we have harnessed near-infrared (NIR) light to visualize intricate internal light-absorbing structures within animal bodies. By leveraging the principle of differentiation, we have extended the applicability of the Beer–Lambert law even in cases of scattering-dominant media, such as animal body tissues. This approach facilitates the visualization of dynamic physiological changes occurring within animal bodies, thereby enabling noninvasive, real-time imaging of macroscopic functionality in vivo. An important challenge inherent to transillumination imaging lies in the image blur caused by pronounced light scattering within body tissues. By extracting near-axis scattered components from the predominant diffusely scattered light, we have achieved cross-sectional imaging of animal bodies. Furthermore, we have introduced software-based techniques encompassing deconvolution using the point spread function and the application of deep learning principles to counteract the scattering effect. Finally, transillumination imaging has been elevated from two-dimensional to three-dimensional imaging. The effectiveness and applicability of these proposed techniques have been validated through comprehensive simulations and experiments involving human and animal subjects. As demonstrated through these studies, transillumination imaging coupled with emerging technologies offers a promising avenue for future biomedical applications.
To provide another modality for three-dimensional (3D) medical imaging, new techniques were developed to reconstruct a 3D structure in a turbid medium from a single blurred 2D image obtained using ...near-infrared transillumination imaging. One technique uses 1D information of a curvilinear absorber, or the intensity profile across the absorber image. Profiles in different conditions are calculated by convolution with the depth-dependent point spread function (PSF) of the transillumination image. In databanks, profiles are stored as lookup tables to connect the contrast and spread of the profile to the absorber depth. One-to-one correspondence from the contrast and spread to the absorber depth and thickness were newly found. Another technique uses 2D information of the transillumination image of a volumetric absorber. A blurred 2D image is deconvolved with the depth-dependent PSF, thereby producing many images with points of focus on different parts. The depth of the image part can be estimated by searching the deconvolved images for the image part in the best focus. To suppress difficulties of high-spatial-frequency noise, we applied a noise-robust focus stacking method. Experimentation verified the feasibility of the proposed techniques, and suggested their applicability to curvilinear and volumetric absorbers such as blood vessel networks and cancerous lesions in tissues.
Expansion and rupture of abdominal aortic aneurysms (AAA) result in high morbidity and mortality rates. Like stenotic atherosclerotic lesions, AAA accumulate inflammatory cells, but usually exhibit ...much more extensive medial damage. Leukocyte recruitment and expression of pro-inflammatory Th1 cytokines typically characterize early atherogenesis of any kind, and modulation of inflammatory mediators mutes atheroma formation in mice. However, the mechanistic differences between stenotic and aneurysmal manifestations of atherosclerosis remain unexplained. We recently showed that aortic allografts deficient in interferon-gamma (IFN-gamma) signaling developed AAA correlating with skewed Th2 cytokine environments, suggesting important regulatory roles for Th1/Th2 cytokine balance in modulating matrix remodeling and important implications for the pathophysiology of aortic aneurysm and atherosclerosis. Further probing of their distinct aspects of immune and inflammatory responses in vascular diseases should continue to shed new light on the pathophysiologic mechanisms that give rise to aneurysmal versus occlusive manifestations and atherosclerosis.
In this paper we propose a new Delay-PUF architecture that is expected to solve the current problem of Delay-PUF that it is easy to predict the relation between delay information and generated ...information. Our architecture exploits glitches that behave non-linearly from delay variation between gates and the characteristic of pulse propagation of each gate. We call this architecture Glitch PUF. In this paper, we present a concrete structure of Glitch PUF. We then show the evaluation results on the randomness and statistical properties of Glitch PUF. In addition, we present a simple scheme to evaluate Delay-PUFs by simulation at the design stage. We show the consistency of the evaluation results for real chips and those by simulation for Glitch PUF.
This paper presents an effective design method for inductors which is based on the multi-objective optimization accelerated by the artificial neural network (ANN). In the learning phase prior to the ...optimization phase, ANN is trained for 1000 input-output data sets obtained from the finite-element analysis for randomly generated dimensional parameters. The magnetic hysteresis of the ferrite core is modeled by the play model to evaluate the hysteresis losses. The multi-objective optimization problems are solved by the genetic algorithm in which the magnetic loss is effectively computed by the trained ANN to reduce the core volume as well as magnetic loss. The Pareto solutions for an EI-shaped ferrite core are obtained for different inductances. It is shown that the proposed method works much faster than the conventional optimization, and the magnetic loss and the inductance of the optimized inductor agree well with the experimental results.
•Estimation of the cross-sectional absorption distribution in turbid media.•Estimation from intensity and the path length distribution of backscattered light.•Nonlinear inversion technique with the ...fixed point iteration method.•Solution in practical time and in the robust process against measurement noise.
This report presents a proposal of a new technique to estimate the cross-sectional absorption distribution of turbid media from backscattered light by solving a nonlinear inverse problem. After illuminating a beam of light on the surface of a turbid object and measuring the backscattered light as a function of distance from the light incident point, we divide the object into multiple virtual layers to estimate the absorption distribution. The path lengths of photon propagation in the respective layers are calculated using Monte Carlo simulation. The absorption coefficient of each virtual layer can be estimated from the backscattered intensity and the path length distribution in a depth direction. For solving this inverse problem, the linear calculation results are useful as initial solutions. Then the final solutions are obtained from iteration of the nonlinear calculation. Convergence into a unique solution and robustness of the solution against the measurement noise were confirmed. The effectiveness of the proposed technique was verified through simulation and measurement. By lateral scanning of a source–detector pair, we can reconstruct a cross-sectional image of the turbid medium to the depth to which the detected light reaches.
The prognosis of patients with intrahepatic cholangiocarcinoma (ICC) is extremely poor and the recurrence rate after curative operation is very high. There is no standard treatment to prevent ...recurrence of ICC. In this study, we investigated the clinical utilization of a dendritic cell vaccine plus activated T-cell transfer in an adjuvant setting for postoperative ICC.
36 patients with ICC were vaccinated at least 3 times with autologous tumor lysate pulsed dendritic cells plus ex-vivo activated T-cell transfer. The 5-year progression-free survival (PFS) and overall survival (OS) were measured and compared with those of 26 patients who received the curative operation alone as a concurrent control. The registration number was UMIN000005820.
The median PFS and OS were 18.3 and 31.9 months in the patients receiving adjuvant immunotherapy and 7.7 and 17.4 months in the group receiving surgery alone (p = 0.005 and 0.022, respectively). In the treated group, patients whose skin reactions were 3 cm or more at the vaccine site showed dramatically better prognosis (PFS p < 0.001, OS p = 0.001).
A postoperative dendritic cell vaccine plus activated T-cell transfer would be a feasible and effective treatment for preventing recurrence and achieving long-term survival in ICC patients.
Recent studies in transillumination imaging for developing an optical computed tomography device for small animal and human body parts have used deep learning networks to suppress the scattering ...effect, estimate depth information of light-absorbing structures, and reconstruct three-dimensional images of de-blurred structures. However, they still have limitations, such as knowing the information of the structure in advance, only processing simple structures, limited effectiveness for structures with a depth of about 15 mm, and the need to use separated deep learning networks for de-blurring and estimating information. Furthermore, the current technique cannot handle multiple structures distributed at different depths next to each other in the same image. To overcome the mentioned limitations in transillumination imaging, this study proposed a pixel-by-pixel scanning technique in combination with deep learning networks (Attention Res-UNet for scattering suppression and DenseNet-169 for depth estimation) to estimate the existence of each pixel and the relative structural depth information. The efficacy of the proposed method was evaluated through experiments that involved a complex model within a tissue-equivalent phantom and a mouse, achieving a reconstruction error of 2.18% compared to the dimensions of the ground truth when using the fully convolutional network. Furthermore, we could use the depth matrix obtained from the convolutional neural network (DenseNet-169) to reconstruct the absorbing structures using a binary thresholding method, which produced a reconstruction error of 6.82%. Therefore, only one convolutional neural network (DenseNet-169) must be used for depth estimation and explicit image reconstruction. Therefore, it reduces time and computational resources. With depth information at each pixel, reconstruction of 3D image of the de-blurred structures could be performed even from a single blurred image. These results confirm the feasibility and robustness of the proposed pixel-by-pixel scanning technique to restore the internal structure of the body, including intricate networks such as blood vessels or abnormal tissues.
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