Segment-based dose optimization using a genetic algorithm
Segment-based dose optimization using a genetic algorithm
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DOI：
10.1088/0031-9155/48/18/303
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发表时间：
2003-09-21
影响因子：
3.5
通讯作者：
Xing, L
中科院分区：
文献类型：
--
作者：
Cotrutz, C;Xing, L
调强放射治疗（IMRT）逆向计划通常分两步进行。首先，使用剂量优化算法优化治疗射束的强度图。然后，使用叶排序算法将它们中的每一个分解为多个片段以进行交付。另一种方法是预先分配固定数量的场孔，并直接优化孔的形状和重量。虽然后一种方法具有消除叶排序步骤的优点，但是孔径形状的优化不如基于小射束的优化简单，因为剂量对射野形状及其权重的复杂依赖性。在这项工作中，我们报告了一个基于段的优化遗传算法。与梯度迭代法或模拟退火法不同，该算法从候选规划群体中寻找最优解。在这种技术中，每个解决方案使用三个染色体进行编码：一个用于每个片段的左岸叶子的位置，第二个用于右岸的位置，第三个用于由前两个染色体定义的片段的权重。通过交叉和变异算子，确保种群中所有解的三个染色体之间正确交换信息，实现了向最优值的收敛。该算法被应用到一个幻影和前列腺的情况下，并与使用基于波束的优化所获得的结果进行比较。从这项研究中得出的主要结论是，段的形状和重量的遗传优化可以产生高度适形的剂量分布。此外，我们的研究还证实了以前的研究结果，即通常需要较少的片段来生成与使用基于波束的优化获得的计划相当的计划。因此，该技术可能在促进IMRT治疗计划中具有有用的应用。
Intensity modulated radiation therapy (IMRT) inverse planning is conventionally done in two steps. Firstly, the intensity maps of the treatment beams are optimized using a dose optimization algorithm. Each of them is then decomposed into a number of segments using a leaf-sequencing algorithm for delivery. An alternative approach is to pre-assign a fixed number of field apertures and optimize directly the shapes and weights of the apertures. While the latter approach has the advantage of eliminating the leaf-sequencing step, the optimization of aperture shapes is less straightforward than that of beamlet-based optimization because of the complex dependence of the dose on the field shapes, and their weights. In this work we report a genetic algorithm for segment-based optimization. Different from a gradient iterative approach or simulated annealing, the algorithm finds the optimum solution from a population of candidate plans. In this technique, each solution is encoded using three chromosomes: one for the position of the left-bank leaves of each segment, the second for the position of the right-bank and the third for the weights of the segments defined by the first two chromosomes. The convergence towards the optimum is realized by crossover and mutation operators that ensure proper exchange of information between the three chromosomes of all the solutions in the population. The algorithm is applied to a phantom and a prostate case and the results are compared with those obtained using beamlet-based optimization. The main conclusion drawn from this study is that the genetic optimization of segment shapes and weights can produce highly conformal dose distribution. In addition, our study also confirms previous findings that fewer segments are generally needed to generate plans that are comparable with the plans obtained using beamlet-based optimization. Thus the technique may have useful applications in facilitating IMRT treatment planning.