Optimizing photoacoustic-based thermal image formation by comparing four different methods

Abstract

In order to improve efficiency and security in heat applications during hyperthermia, it is important to monitor tissue temperature during treatments. Photoacoustic (PA) pressure wave amplitude has a temperature dependence given by the Gruenesein parameter. Therefore, changes in photoacoustic signal amplitude carry information about temperature variation in tissue. Therefore, PA has been proposed as an imaging technique to monitor temperature during hyperthermia. However, no study has compared the performance of different algorithms to generate PA-based thermal images. Here, four methods to estimate variations in PA signal amplitude for thermal PA image formation were investigated: peak-to-peak, integral of the modulus, autocorrelation maximum value, and energy of the signal. Changes in PA signal amplitude were evaluated using a 1D window moving across the entire image. PA images were acquired for temperatures ranging from 36°C to 42°C using a phantom immersed in a temperature controlled thermal bath. In terms of signal to noise ratio (SNR), the performance was similar for all algorithms and using larger windows resulted in a higher SNR. Bias varied from 1.5°C to −1.5°C for temperatures 3°C higher than the baseline. In conclusion, four methods were evaluated to optimize PA thermal images formation.