Fluence-convolution broad-beam (FCBB) dose calculation
Fluence-convolution broad-beam (FCBB) dose calculation
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DOI：
10.1088/0031-9155/55/23/003
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发表时间：
2010-12-07
影响因子：
3.5
通讯作者：
Chen, Mingli
中科院分区：
文献类型：
--
作者：
Lu, Weiguo;Chen, Mingli
调强放射治疗优化需要一个快速但相对准确的算法来计算迭代剂量与小的内存需求。在本文中，我们提出了一个剂量计算算法，接近这些目标。通过将无限小笔形束核分解为中心轴分量和横向扩展函数，并取束眼视图，建立了一种非体素、非子束的剂量计算公式。LSF和CAX都是通过调试程序确定的，使用双锥卷积/叠加（CCCS）方法作为标准剂量引擎。所提出的剂量计算涉及注量图与LSF的2D卷积，随后是基于CAX查找表的射线追踪，具有放射性距离和发散校正，导致空间和时间上的复杂度为O（N（3））。这种简单的算法比CCCS方法快几个数量级。在不预先计算子束的情况下，其实现也比传统的基于体素的子束叠加（VBS）方法小几个数量级。我们比较了所提出的算法与CCCS方法使用模拟和临床病例。一致性一般在3%以内的均匀体模和5%的异质性和临床病例。结合“自适应全剂量校正”，该算法适用于调强放疗优化过程中的迭代剂量计算。
IMRT optimization requires a fast yet relatively accurate algorithm to calculate the iteration dose with small memory demand. In this paper, we present a dose calculation algorithm that approaches these goals. By decomposing the infinitesimal pencil beam (IPB) kernel into the central axis (CAX) component and lateral spread function (LSF) and taking the beam's eye view (BEV), we established a non-voxel and non-beamlet-based dose calculation formula. Both LSF and CAX are determined by a commissioning procedure using the collapsed-cone convolution/superposition (CCCS) method as the standard dose engine. The proposed dose calculation involves a 2D convolution of a fluence map with LSF followed by ray tracing based on the CAX lookup table with radiological distance and divergence correction, resulting in complexity of O(N(3)) both spatially and temporally. This simple algorithm is orders of magnitude faster than the CCCS method. Without pre-calculation of beamlets, its implementation is also orders of magnitude smaller than the conventional voxel-based beamlet-superposition (VBS) approach. We compared the presented algorithm with the CCCS method using simulated and clinical cases. The agreement was generally within 3% for a homogeneous phantom and 5% for heterogeneous and clinical cases. Combined with the 'adaptive full dose correction', the algorithm is well suitable for calculating the iteration dose during IMRT optimization.