3 March 2017 Biological tissue component evaluation by measuring photoacoustic spectrum
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Photoacoustic imaging has garnered constant attention as a non-invasive modality for visualizing details of the neovascularization structure of tumors, or the distribution of oxygen saturation, which is related to the tumor grade. However, photoacoustic imaging is applicable not only for vascular imaging but also for diagnosing properties of various tissues such as skin or muscle diseases, fat related to arteriosclerosis or fatty liver, cartilage related to arthritis, and fibrous tissues related to hepatitis. The photoacoustic signal intensity is wavelength-dependent and proportional to the absorption coefficient and thermal acoustic conversion efficiency (i.e. Grüneisen parameter) of the target biological tissue. To ascertain the appropriate wavelength range for biological tissue imaging and to evaluate tissue properties, photoacoustic spectra of various tissues (e.g., skin, muscle, and adipose tissue) were measured using a hydrophone (9 mm diameter) at 680–1600 nm wavelengths. Results confirmed that respective tissues have unique photoacoustic spectra. However, almost all samples have peaks around 1200 nm and 1400–1500 nm for wavelengths where the light absorbance of lipid or water is high. The main components of biological tissues are water, protein, and lipid. Results confirmed that photoacoustic spectra reflect the tissue components well. To evaluate the feasibility of the tissue characterization using photoacoustic methods, the photoacoustic signal intensity ratio between two wavelength regions was calculated as described above. Signal intensity ratios agreed well with the composition ratio between water and lipid in samples. These analyses verified the feasibility of evaluating tissue properties using photoacoustic methods.
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Takeshi Namita, Yuya Murata, Junji Tokuyama, Kengo Kondo, Makoto Yamakawa, and Tsuyoshi Shiina "Biological tissue component evaluation by measuring photoacoustic spectrum", Proc. SPIE 10064, Photons Plus Ultrasound: Imaging and Sensing 2017, 100645B (3 March 2017); doi: 10.1117/12.2252393; https://doi.org/10.1117/12.2252393

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