A photoacoustic 3D imaging system for animal experiments was made. This system is special because it has a hemispherical detector array. To test its performance, we used a chart from the field of optics as a sample. We checked the whole imaging range using the ISO 12233 chart, which is used to test digital camera images. We found that there was no distortion in the xy-plane and the system had high resolution. We also tested it using a high image quality mode with a different scanning sequence. In this study, live albino mice with white hairs were anesthetized and photographed. Using hair removal cream, we were able to visualize the vascular network throughout their bodies, including blood vessels in organs such as the liver and kidneys. The smallest vessels we were able to visualize were less than 0.1 mm in diameter. We used photoacoustic (PA) images to relatively estimate the oxygen saturation of the mice's blood at two different wavelengths, which we refer to as the S-factor. By analyzing the PA images, we were able to estimate the arterial and venous systems of the whole body, as well as the difference in S-factor between the two systems within the liver. When the mice were euthanized and examined post-mortem, we observed that the S-factor of the whole body decreased and the difference in S-factor between the two systems within the liver was lost.
Photoacoustic tomography (PAT) is a novel modality that can visualize blood vessels without contrast agents. It clearly shows blood vessels near the body surface. However, these vessels obstruct the observation of deep blood vessels. As the existence range of each vessel is determined by the distance from the body surface, they can be separated if the position of the skin is known. However, skin tissue, which does not contain hemoglobin, does not appear in PAT results, therefore, manual estimation is required. As this task is very labor-intensive, its automation is highly desirable. Therefore, we developed a method to estimate the body surface using the cloth-simulation technique, which is a commonly used method to create computer graphics (CG) animations; however, it has not yet been employed for medical image processing. In cloth simulations, the virtual cloth is represented by a two-dimensional array of mass nodes. The nodes are connected with each other by springs. Once the cloth is released from a position away from the body, each node begins to move downwards under the effect of gravity, spring, and other forces; some of the nodes hit the superficial vessels and stop. The cloth position in the stationary state represents the body surface. The body surface estimation, which required approximately 1 h with the manual method, is automated and it takes only approximately 10 s with the proposed method. The proposed method could facilitate the practical use of PAT.
We have constructed a prototype photoacoustic mammography system (PAM-02) capable of simultaneously acquiring photoacoustic (PA) and ultrasound (US) images. Each PA, US, and fused PA/US image can be acquired over a wide area of the breast using the scanning module of a US transducer, a PA detector, and optical prisms. The resolution of the PA images exhibits improvement from 2 to 1 mm compared to images acquired using our previous prototype. The maximum scan area of PAM-02 is 90 mm along the horizontal axis and 150 mm along the vertical axis. In a phantom experiment, the available depth was at least 45 mm. A representative example of the application of the PAM-02 prototype in clinical research at Kyoto University is presented and shows S-factor images, which are considered an approximation parameter related to hemoglobin saturation of tumor-related blood vessels. We confirmed the applicability of the system for anatomical and biological research.
In this study, we characterized a newly developed imaging system, "dual illumination mode photoacoustic tomography
(PAT) system". The PAT system can simultaneously or separately illuminate biological tissues from a forward and
backward direction toward an array transducer. The shape of the custom-made transducer is rectangular, which allows
direct illumination of tissue surfaces in front of the array transducer through a holding plate from the backward direction.
The transducer frequency was designed at 1 MHz by considering the trade-off relationship between ultrasound
attenuation and image resolution. A Ti:Sa laser optically pumped with a Q-switched Nd:YAG laser, having a tunable
wavelength of 700 to 900 nm, was chosen for deep light penetration in tissues. The laser light was sufficiently expanded
and homogenized to keep the level of laser-pulse fluence on the sample surface under the ANSI safety limit. System
performance was tested with phantoms. The results of our study showed that the system visualized all the absorbers
embedded in a 50-mm-thick tissue-mimicking phantom with a lateral resolution of 2~3 mm.
In this study, we propose an advanced model-based reconstruction algorithm for three-dimensional photoacoustic
imaging. The algorithm is based on accurate forward photoacoustic models and an optimization algorithm which
minimizes the square of the error between the measured acoustic signals and the signals predicted by the forward
models. The forward photoacoustic models incorporate system-configuration and detector-dependent factors such as
frequency response and finite size effect. A conjugate gradient-based optimization algorithm is used for reconstructing
images. In addition, we make use of the symmetry and locality of the photoacoustic waves in the computations of the
forward photoacoustic models in order to reduce the memory requirements and computation time in three-dimensional
image reconstruction. The results show that the proposed algorithm provides high-resolution and high-quality
photoacoustic images.
Photoacoustic (PA) tomography is a rapidly developing imaging modality which can provide high contrast and
spatial-resolution images of light absorption distribution in tissue. However, the quantitative reconstruction of
absorption distribution is still a challenge. In this study, we propose an adaptive and quantitative reconstruction
algorithm for reducing amplification of noises and artifacts in deep position due to light fluence compensation. In
this method, the quantitative processing is integrated into the iterative reconstruction, and absorption coefficient
distribution is iteratively updated. At each iteration step, the residual is calculated from detected PA signals and
the signals calculated from a forward model by using the initial pressure which is calculated from the production
of voxel value and the light fluence. By minimizing the residual, the reconstructed values are converged to the
true absorption coefficient distributions. Since this method uses a global optimized compensation, better CNR
can be obtained. The results of simulation and phantom experiment indicate that the proposed method provide
better CNR at deep region. We expect that the capability of increasing imaging depth will broaden clinical
applications.
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