Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA.
Med Phys. 2011 May;38(5):2651-64. doi: 10.1118/1.3582690.
The deterministic Acuros XB (AXB) algorithm was recently implemented in the Eclipse treatment planning system. The goal of this study was to compare AXB performance to Monte Carlo (MC) and two standard clinical convolution methods: the anisotropic analytical algorithm (AAA) and the collapsed-cone convolution (CCC) method.
Homogeneous water and multilayer slab virtual phantoms were used for this study. The multilayer slab phantom had three different materials, representing soft tissue, bone, and lung. Depth dose and lateral dose profiles from AXB v10 in Eclipse were compared to AAA v10 in Eclipse, CCC in Pinnacle3, and EGSnrc MC simulations for 6 and 18 MV photon beams with open fields for both phantoms. In order to further reveal the dosimetric differences between AXB and AAA or CCC, three-dimensional (3D) gamma index analyses were conducted in slab regions and subregions defined by AAPM Task Group 53.
The AXB calculations were found to be closer to MC than both AAA and CCC for all the investigated plans, especially in bone and lung regions. The average differences of depth dose profiles between MC and AXB, AAA, or CCC was within 1.1, 4.4, and 2.2%, respectively, for all fields and energies. More specifically, those differences in bone region were up to 1.1, 6.4, and 1.6%; in lung region were up to 0.9, 11.6, and 4.5% for AXB, AAA, and CCC, respectively. AXB was also found to have better dose predictions than AAA and CCC at the tissue interfaces where backscatter occurs. 3D gamma index analyses (percent of dose voxels passing a 2%/2 mm criterion) showed that the dose differences between AAA and AXB are significant (under 60% passed) in the bone region for all field sizes of 6 MV and in the lung region for most of field sizes of both energies. The difference between AXB and CCC was generally small (over 90% passed) except in the lung region for 18 MV 10 x 10 cm2 fields (over 26% passed) and in the bone region for 5 x 5 and 10 x 10 cm2 fields (over 64% passed). With the criterion relaxed to 5%/2 mm, the pass rates were over 90% for both AAA and CCC relative to AXB for all energies and fields, with the exception of AAA 18 MV 2.5 x 2.5 cm2 field, which still did not pass.
In heterogeneous media, AXB dose prediction ability appears to be comparable to MC and superior to current clinical convolution methods. The dose differences between AXB and AAA or CCC are mainly in the bone, lung, and interface regions. The spatial distributions of these differences depend on the field sizes and energies.
最近在 Eclipse 治疗计划系统中实现了确定性 Acuros XB（AXB）算法。本研究的目的是比较 AXB 与蒙特卡罗（MC）和两种标准临床卷积方法（各向异性分析算法[AAA]和卷积锥体算法[CCC]）的性能。
本研究使用均匀水和多层平板虚拟体模。多层平板体模有三种不同的材料，代表软组织、骨骼和肺。使用 Eclipse 中的 AXB v10 和 Eclipse 中的 AAA v10、Pinnacle3 中的 CCC 以及 EGSnrc MC 模拟，对两种体模的 6 和 18 MV 光子束的开野进行了深度剂量和侧向剂量分布的比较。为了进一步揭示 AXB 与 AAA 或 CCC 之间的剂量差异，在由 AAPM 工作组 53 定义的平板区域和子区域中进行了三维（3D）伽马指数分析。
与 AAA 和 CCC 相比，所有研究计划中的 AXB 计算结果更接近 MC，尤其是在骨骼和肺部区域。MC 与 AXB、AAA 或 CCC 之间的深度剂量分布平均差异在所有场和能量下分别小于 1.1%、4.4%和 2.2%。更具体地说，在骨骼区域的差异高达 1.1%、6.4%和 1.6%；在肺部区域，AXB、AAA 和 CCC 的差异分别高达 0.9%、11.6%和 4.5%。AXB 在发生反向散射的组织界面处也具有比 AAA 和 CCC 更好的剂量预测能力。3D 伽马指数分析（通过 2%/2mm 标准的剂量体素百分比）表明，在所有 6MV 场的骨骼区域和大多数两种能量的大部分场的肺部区域，AAA 和 AXB 之间的剂量差异是显著的（通过率低于 60%）。AXB 与 CCC 之间的差异通常较小（通过率超过 90%），除了在 18MV 10x10cm2 场的肺部区域（通过率超过 26%）和在 5x5 和 10x10cm2 场的骨骼区域（通过率超过 64%）。将标准放宽至 5%/2mm 后，对于所有能量和场，AAA 和 CCC 相对于 AXB 的通过率均超过 90%，除了 18MV 2.5x2.5cm2 场的 AAA 仍未通过。
在不均匀介质中，AXB 剂量预测能力似乎与 MC 相当，优于当前的临床卷积方法。AXB 与 AAA 或 CCC 之间的剂量差异主要在骨骼、肺部和界面区域。这些差异的空间分布取决于场的大小和能量。
