Model-based tomographic optoacoustic reconstruction in media with small speed of sound variations

The majority of optoacoustic reconstruction algorithms are based on the assumption that the speed of sound within the imaging sample is constant and equal to the speed of sound in the coupling medium, typically water. However, small speed of sound changes between different organs and structures are common in actual samples. The variations in the speed of sound within biological tissues are usually below 10% with respect to the speed of sound in water. Under these circumstances, the acoustic wave propagation can be modeled as acoustic rays and the main effect of the acoustic heterogeneities is the time-shifting of the optoacoustic signals. Herein, we describe a model-based reconstruction algorithm capable of accounting for such small speed of sound variations. It is based on modifying the integration curve in the forward optoacoustic model according to the time-shifting produced by differences in the speed of sound. The forward model is then discretized and inverted algebraically by means of the LSQR algorithm. The algorithm was tested experimentally with tissue-mimicking agar phantoms containing glycerine to simulate a higher speed of sound than water. The improvement in the image quality as compared to the results obtained by assuming a uniform speed of sound is discussed in this work.