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Verification of Error Factors and Accuracy Improvement in Speed of Sound Analysis at Ultra-High Frequency

Applying the autoregressive (AR)model in exponential to separate echoes is known as one of the practical methods to analyze the speed of sound (SoS)using scanning acoustic microscopy. However, the accuracy of SoS analysis with AR model in ultra-high frequency (> 100 MHz)is unknown. AR model requires the number of echo components separated in and optimizing this parameter is essential to analyze SoS in high accuracy. Also, the condition of the tissue is one of the elements that can have the influence on the SoS analysis. There, we investigated the relationship between the shape of sliced samples (thickness and surface shape), analysis parameter (AR order)and the accuracy of SoS analysis through the simulations using the Finite-difference time-domain (FDTD)method. Echo simulations were performed with flat samples with thickness varied and sample imitating the actual surface shape of sliced rat liver. From the result, it was suspected that to analyze SoS in high accuracy is difficult if the thickness of the sliced sample is not enough thick. In addition, we found that the surface roughness of sliced samples can occur the disturbance of wave propagation and not only make the accuracy of SoS analysis worse but also make the optimal AR order higher.