Evaluation of a stochastic reconstruction algorithm for use in Compton camera imaging and beam range verification from secondary gamma emission during proton therapy.
Evaluation of a stochastic reconstruction algorithm for use in Compton camera imaging and beam range verification from secondary gamma emission during proton therapy.
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DOI：
10.1088/0031-9155/57/11/3537
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发表时间：
2012-06-07
影响因子：
3.5
通讯作者：
Polf J
中科院分区：
文献类型：
--
作者：
Mackin D;Peterson S;Beddar S;Polf J
在本文中，我们研究的可行性，使用随机起源系综（SOE）算法重建图像的二次伽马发射质子放疗过程中从测量数据与三级康普顿相机。本研究的目的是评价质子辐照过程中使用SOE算法产生的伽马射线图像的质量，并测量图像再现射束远端衰减的程度。对于我们的评估，我们进行了Monte Carlo模拟的理想的三级康普顿相机定位在上面，并正交于质子笔形束照射的组织模型。射束质子与体模中的核的散射产生次级伽马射线，其由康普顿相机检测并用作SOE算法的输入。我们研究了SOE重建图像作为迭代次数、体素概率参数和SOE算法所使用的检测到的伽马的数量的函数。通过计算和比较SOE重建图像的归一化均方误差（NMSE），定量评估了SOE算法的性能。我们还研究了SOE重建图像预测辐照组织中二次伽马产生的远端衰减的能力。我们的研究结果表明，使用SOE算法生成的图像在约10，000次迭代中收敛，对于超过此次数的迭代，图像NMSE几乎没有改善。我们发现，图像的统计噪声与检测到的伽马的数量与SOE体素概率参数值的比率成反比。在我们的研究中，SOE预测的重建图像的远端衰减与蒙特卡罗计算的体模中伽马发射轮廓的远端衰减一致，在伽马发射轮廓的最大发射（100%）和90%、50%和20%远端衰减位置的±0.6 mm范围内。我们的结论是，SOE算法是一种有效的方法，从一个理想的康普顿照相机收集的数据重建图像的质子笔形束，这些图像准确地模拟质子照射过程中的二次γ发射的远端衰减。
In this paper, we study the feasibility of using the stochastic origin ensemble (SOE) algorithm for reconstructing images of secondary gammas emitted during proton radiotherapy from data measured with a three-stage Compton camera. The purpose of this study was to evaluate the quality of the images of the gamma rays emitted during proton irradiation produced using the SOE algorithm and to measure how well the images reproduce the distal falloff of the beam. For our evaluation, we performed a Monte Carlo simulation of an ideal three-stage Compton camera positioned above and orthogonal to a proton pencil beam irradiating a tissue phantom. Scattering of beam protons with nuclei in the phantom produces secondary gamma rays, which are detected by the Compton camera and used as input to the SOE algorithm. We studied the SOE reconstructed images as a function of the number of iterations, the voxel probability parameter, and the number of detected gammas used by the SOE algorithm. We quantitatively evaluated the capabilities of the SOE algorithm by calculating and comparing the normalized mean square error (NMSE) of SOE reconstructed images. We also studied the ability of the SOE reconstructed images to predict the distal falloff of the secondary gamma production in the irradiated tissue. Our results show that the images produced with the SOE algorithm converge in ~10,000 iterations, with little improvement to the image NMSE for iterations above this number. We found that the statistical noise of the images is inversely proportional to the ratio of the number of gammas detected to the SOE voxel probability parameter value. In our study, the SOE predicted distal falloff of the reconstructed images agrees with the Monte Carlo calculated distal falloff of the gamma emission profile in the phantom to within ±0.6 mm for the positions of maximum emission (100%) and 90%, 50%, and 20% distal falloff of the gamma emission profile. We conclude that the SOE algorithm is an effective method for reconstructing images of a proton pencil beam from the data collected by an ideal Compton camera and that these images accurately model the distal falloff of secondary gamma emission during proton irradiation.
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影响因子：
3.5
作者：
Peterson SW;Robertson D;Polf J
通讯作者：
Polf J
影响因子：
3.5
作者：
Knopf, A.;Parodi, K.;Bortfeld, T.
通讯作者：
Bortfeld, T.
DOI：
10.1016/s0168-9002(97)00048-x
发表时间：
1997-04-11
影响因子：
1.4
作者：
Brun, R;Rademakers, F
通讯作者：
Rademakers, F
影响因子：
--
作者：
PARZEN, E
通讯作者：
PARZEN, E
影响因子：
3.8
作者：
SIDDON, RL
通讯作者：
SIDDON, RL