Department of Engineering Physics, Tsinghua University, Beijing, 100084, China.
Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China.
Sci Rep. 2019 Feb 4;9(1):1133. doi: 10.1038/s41598-018-37623-2.
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.
基于康普顿相机的正电子射线（PG）成像是质子治疗中实现体内验证的一种有前途的方法。然而，目前康普顿相机的有限空间和能量分辨率以及多普勒展宽效应降低了 PG 图像的质量和分辨率。此外，由于康普顿相机数据固有的几何复杂性，PG 成像可能耗时且难以实时重建，而使用滤波反投影或最大似然-期望最大化等标准技术。在本文中，我们提出了三种基于马尔可夫链的具有分辨率恢复（OE-RR）算法的原始集合修正，以加速 OE-RR 算法达到平衡的收敛速度并提高图像质量。为了进行评估，我们对具有分辨率损失的三级 CZT 康普顿相机进行了蒙特卡罗模拟，以探测水模中质子束产生的 PG，并评估质子辐照期间发射的伽马射线的图像质量。结果表明，我们的有序 OE-RR 算法实现了良好的分辨率恢复和对 PG 发射的位置（包括峰值和远端下降）的准确估计，重建速度明显更快，从而证明了这种新方法在非理想化基于 PG 的质子射程验证中的可行性。
