Abstract
Blood oxygenation measurement with photoacoustic techniques has the advantages of good ultrasonic resolution and high intrinsic optical absorption contrast and is non-invasive compared with other measurement techniques. The purpose of this study is to develop a photoacoustic-imaging-based quantitative measurement technique for the determination of blood oxygen saturation in-vivo application, and verify its feasibility by computer simulation to improve the problems of blood oxygen saturation estimated by traditional method. In this study, we first make discussions for problems of traditional least-squares-based matrix inverse method. The well quantitative measurement of blood oxygen saturation by the traditional method have to satisfy the basic assumption that the signal peak value is proportional to the absorption coefficient. However, in real situations, tissues above the target blood vessel will vary the laser fluence on the target vessel at different wavelengths. Thus, traditional “Least Squares” method can not offer good blood-oxygenation measurement. Furthermore, fluence above target vessel will be perturbed due to an absorption perturbation which also influences the basic assumption. In computer simulations, we used a Monte Carlo simulation of photon transport, and determined the appropriate number of photon packets and structure of target vessel to achieve stabilized SO2 measurement by used the energy deposition results at several wavelengths, and the measurement results showed that the blood oxygenation estimated by the traditional “Least Squares” method is lower than the default blood oxygenation values. To foster the practicability of this photoacoustic blood oxygenation measurement technique, here a “Fluence Compensation” algorithm is proposed to obtain fluence compensation coefficients with an optimization algorithm, which compensates the fluence changes depending on different wavelengths, and the proposed algorithm provides better estimation for blood oxygenation. It is demonstrated that our mathematical model has the potential to perform blood-oxygenation measurement for in vivo applications.