Department of Oncology, University of Oxford, Oxford OX3 7DQ, United Kingdom; Department of Physics, University of Adelaide, Adelaide, South Australia 5005, Australia.
Department of Physics, University of Adelaide, Adelaide, South Australia 5005, Australia; Department of Medical Physics, Royal Adelaide Hospital, Adelaide, South Australia 5000, Australia.
Phys Med. 2020 Feb;70:184-195. doi: 10.1016/j.ejmp.2020.01.025. Epub 2020 Feb 7.
Multiple Coulomb scattering (MCS) poses a challenge in proton CT (pCT) image reconstruction. The assumption of straight paths is replaced with Bayesian models of the most likely path (MLP). Current MLP-based pCT reconstruction approaches assume a water scattering environment. We propose an MLP formalism based on accurate determination of scattering moments in inhomogeneous media.
Scattering power relative to water (RScP) was calculated for a range of human tissues and investigated against relative stopping power (RStP). Monte Carlo simulation was used to compare the new inhomogeneous MLP formalism to the water approach in a slab geometry and a human head phantom. An MLP-Spline-Hybrid method was investigated for improved computational efficiency.
A piecewise-linear correlation between RStP and RScP was shown, which may assist in iterative pCT reconstruction. The inhomogeneous formalism predicted Monte Carlo proton paths through a water cube with thick bone inserts to within 1.0 mm for beams ranging from 210 to 230 MeV incident energy. Improvement in accuracy over the conventional MLP ranged from 5% for a 230 MeV beam to 17% for 210 MeV. There was no noticeable gain in accuracy when predicting 200 MeV proton paths through a clinically relevant human head phantom. The MLP-Spline-Hybrid method reduced computation time by half while suffering negligible loss of accuracy.
We have presented an MLP formalism that accounts for material composition. In most clinical cases a water scattering environment can be assumed, however in certain cases of significant heterogeneity the proposed algorithm may improve proton path estimation.
多次库仑散射（MCS）给质子 CT（pCT）图像重建带来了挑战。最可能路径（MLP）的贝叶斯模型取代了直线路径的假设。目前基于 MLP 的 pCT 重建方法假设水散射环境。我们提出了一种基于在非均匀介质中准确确定散射矩的 MLP 形式。
计算了一系列人体组织的相对水散射功率（RScP），并对其与相对阻止本领（RStP）进行了研究。使用蒙特卡罗模拟比较了新的非均匀 MLP 形式与水方法在平板几何形状和人体头部体模中的差异。研究了 MLP-Spline-Hybrid 方法以提高计算效率。
RStP 与 RScP 之间显示出分段线性相关性，这可能有助于迭代 pCT 重建。非均匀形式预测了从 210 到 230 MeV 入射能量的光束穿过水立方和厚骨插入物的蒙特卡罗质子路径，精度在 1.0mm 以内。与传统 MLP 相比，精度提高了 5%，对于 230 MeV 束，精度提高了 17%。当预测通过具有临床相关性的人体头部体模的 200 MeV 质子路径时，准确性没有明显提高。MLP-Spline-Hybrid 方法将计算时间缩短了一半，而准确性几乎没有损失。
我们提出了一种考虑材料组成的 MLP 形式。在大多数临床情况下，可以假设水散射环境，但在某些显著异质性的情况下，所提出的算法可能会改善质子路径估计。
