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.
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.
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.
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