(Wednesday, 7/17/2019) 10:30 AM - 11:00 AM
Room: Exhibit Hall | Forum 1
Purpose: To estimate delivering raneg of proton beam by use of the travel time data extracted from thermoacoustic signal for range verification in heterogeneous medium, under the condition that velocity distrubution of medium is unknown in advance.
Methods: Thermoacoustic signal propagation was simulated by using k-Wave, and proton beams of initial energy within 55-220 MeV were used in a heterogeneous model simulating the complexity of internal organs. Forty ultrasonic sensors were placed around the model, and γ-wave traveltimes were extracted from received waveforms as observation data. Based on a initialized position of thermoacoustic source and velocity distribution, forward modeled traveltime data were calculated by LTI. The inversion equation was constructed using the residuals of modeled and observed data. A parameter separation algorithm was used to solve the inversion equation, and model perturbation was obtained to modify the source position and velocity distribution. The final Bragg peak position can be obtained when the algorithm iteration was converged.
Results: Four sets of proton beam incident position were chosen. The Bragg peak positions simulated by k-Wave were (106,102), (120, 230), (180, 135), (240, 220), respectively. The final positioning errors converged to a range of 0.70 to 1.3 mm. To verify robustness of the algorithm, Gaussian noise with variance from 1 to 3 was added to the traveltime data, and the positioning errors were still less than 1.8 mm. Experiments comparison of the number of sensors shows that reducing number of sensors from 40 to 16 does not significantly increase the positioning error.
Conclusion: Thermoacoustic range verification methods proposed previously often require velocity distributions to be known firstly. Our method inverts the velocity distribution and position of Bragg peak jointly, which is suitable for any heterogeneous medium that is closer to actual situation. The results of simulation test have demonstrated feasibility of the algorithm.
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