Compton-based prompt gamma imaging using ordered origin ensemble algorithm with resolution recovery in proton therapy

Zhiyang Yao,Bo Wang,Qinhan Hou,Zhiqiang Chen,Yongshun Xiao

doi:10.1038/s41598-018-37623-2

Abstract

Prompt gamma ray (PG) imaging based on Compton camera (CC) is promising to realize in vivo verification during the proton therapy. However, the finite spatial and energy resolution of current CC, as well as the Doppler broaden effect, degrade the quality and resolution of PG images. In addition, due to the inherent geometrical complexity of Compton camera data, PG imaging can be time-consuming and difficult to reconstruct in real-time, while using standard techniques such as filtered back-projection or maximum likelihood-expectation maximization. In this paper, we propose three modifications of origin ensembles with resolution recovery (OE-RR) algorithm based on Markov chains to accelerate the convergence to equilibrium of OE-RR algorithm and improve the image quality. For evaluation, we performed a Monte Carlo simulation of a three-stage CZT Compton camera with resolution loss to detect the PG produced by a proton beam in a water phantom, and evaluate image quality of the gamma rays emitted during proton irradiation. The results show that our ordered OE-RR algorithm realized a good resolution recovery and accurate estimation of the position, including the peak and the distal falloff of the PG emission with remarkably faster reconstruction, thus demonstrating the feasibility of this new method in non-idealized PG-based proton range verification.

Highlights

ResultsThe center of the volume of interest (VOI) in depth along the center of the phantom (center of the beam)
The proton therapy (PT) for treating cancer has been widely used over the past decades, because of the Bragg peak of proton beam
One previous study showed that the origin ensemble with resolution recovery (OE-RR) algorithm based on Markov chain[8], which is an extended SOE algorithm[11] including resolution recovery (RR), has good performance in terms of image quality while clearly outperforming in reconstruction time

Summary

Results

The center of the VOI in depth along the center of the phantom (center of the beam) They were 2D reconstruction since our reconstructions is to evaluate the difference between the reconstruction and the true value (Monte Carlo simulations) in the same spatial location (i.e. the same plane). The 2D projection images used for obtaining the horizontal profiles were followed by a 2D Gaussian post-smoothing filter with a small full-width half-maximum (FWHM) 2.0 mm to reduce the background noise and reproduce peaks better. The narrower width at 80% positions and better reproduction of falloff and peak positions obtained by ordered OE in Fig. 1 and Table 1, show that event ordered used for OE iterations could provide a better reconstruction compared with event stochastic used.

Methods

Discussion

Conclusion