Adaptive multi-sample-based photoacoustic tomography with imaging quality optimization

TLDR: In this paper, an adaptive multi-sample-based approach is proposed to enhance the SNR of photoacoustic (PA) signals and in addition, detailed information in rebuilt PA images that used to be buried in the noise can be distinguished.

Abstract: The energy of light exposed on human skin is compulsively limited for safety reasons which affects the power of photoacoustic (PA) signal and its signal-to-noise ratio (SNR) level. Thus, the final reconstructed PA image quality is degraded. This Letter proposes an adaptive multi-sample-based approach to enhance the SNR of PA signals and in addition, detailed information in rebuilt PA images that used to be buried in the noise can be distinguished. Both ex vivo and in vivo experiments are conducted to validate the effectiveness of our proposed method which provides its potential value in clinical trials. OCIS codes: 100.2980, 170.1065, 170.5120. doi: 10.3788/COL201513.061001. Research on photoacoustic tomography (PAT) got prosperous development for its being promisingly characterized with noninvasive and nonionizing diagnose of breast cancer, arthritis, and relevant disease. PAT combines the metrics of both ultrasound imaging and pure optical imaging technique, providing high ultrasonic resolution and high optical contrast images [1–5] . Due to the peculiarity that the optical absorption characteristic of blood has a strong relationship with the hemoglobin content, functional imaging as well as structural imaging can also be realized by PAT, making this imaging modality extremely potential in clinical application [6] . The basic principle of PAT is that a tissue is irradiated with short nanosecond laser pulses, and then the absorbed energy may result in a thermo-elastic expansion and subsequent contraction of irradiated volume that generates time-trace photoacoustic (PA) waves, which can be acquired by scanning small-aperture ultrasound detectors over a surface that encloses the source under study. The recorded PA wave can then be reconstructed to spatially resolve the initial absorber distribution and concentration via PA reconstruction algorithms [7–9]. However, biomedical tissue is a highly scattering medium for electromagnetic waves in the optical spectral range, and the propagation ultrasound waves are extremely attenuated before received by ultrasound sensors. Furthermore, the dose of laser beam exposed on the biomedical tissue has to be limited under 20 mJ∕cm 2 for safety operation. Thus, in clinical trials, ultrasound transducer can only receive weak PA signals with low signal-to-noise ratio (SNR) which degraded the final reconstructed PA images [10–14] . This Letter proposes an adaptive multi-sample-based approach to enhance the SNR of PA signals and in addition, detailed information of PAT that used to be buried in the noise and artifacts can be distinguished. The PA reconstruction is an inverse problem of the source pressure. We assume that a tissue with inhomogeneous microwave absorption but a relatively homogeneous acoustic property and the heat diffusion’s effect on the thermoacoustic wave can be ignored. For cases where the scanning radius in a circular scan configuration is much greater than the PA wavelengths, the optical absorption p0ðrÞ within the sample at a given position r is given as [1]