Schiavi A, Senzacqua M, Pioli S, Mairani A, Magro G, Molinelli S, Ciocca M, Battistoni G, Patera V
Dipartimento SBAI, University of Rome 'La Sapienza', Rome, Italy. INFN, Sezione di Roma 1, Rome, Italy.
Phys Med Biol. 2017 Sep 5;62(18):7482-7504. doi: 10.1088/1361-6560/aa8134.
Ion beam therapy is a rapidly growing technique for tumor radiation therapy. Ions allow for a high dose deposition in the tumor region, while sparing the surrounding healthy tissue. For this reason, the highest possible accuracy in the calculation of dose and its spatial distribution is required in treatment planning. On one hand, commonly used treatment planning software solutions adopt a simplified beam-body interaction model by remapping pre-calculated dose distributions into a 3D water-equivalent representation of the patient morphology. On the other hand, Monte Carlo (MC) simulations, which explicitly take into account all the details in the interaction of particles with human tissues, are considered to be the most reliable tool to address the complexity of mixed field irradiation in a heterogeneous environment. However, full MC calculations are not routinely used in clinical practice because they typically demand substantial computational resources. Therefore MC simulations are usually only used to check treatment plans for a restricted number of difficult cases. The advent of general-purpose programming GPU cards prompted the development of trimmed-down MC-based dose engines which can significantly reduce the time needed to recalculate a treatment plan with respect to standard MC codes in CPU hardware. In this work, we report on the development of fred, a new MC simulation platform for treatment planning in ion beam therapy. The code can transport particles through a 3D voxel grid using a class II MC algorithm. Both primary and secondary particles are tracked and their energy deposition is scored along the trajectory. Effective models for particle-medium interaction have been implemented, balancing accuracy in dose deposition with computational cost. Currently, the most refined module is the transport of proton beams in water: single pencil beam dose-depth distributions obtained with fred agree with those produced by standard MC codes within 1-2% of the Bragg peak in the therapeutic energy range. A comparison with measurements taken at the CNAO treatment center shows that the lateral dose tails are reproduced within 2% in the field size factor test up to 20 cm. The tracing kernel can run on GPU hardware, achieving 10 million primary [Formula: see text] on a single card. This performance allows one to recalculate a proton treatment plan at 1% of the total particles in just a few minutes.
离子束疗法是一种在肿瘤放射治疗中迅速发展的技术。离子能够在肿瘤区域实现高剂量沉积，同时使周围健康组织免受辐射。因此，在治疗计划中，需要尽可能精确地计算剂量及其空间分布。一方面，常用的治疗计划软件解决方案通过将预先计算的剂量分布重新映射到患者形态的三维水等效表示中，采用了简化的束-体相互作用模型。另一方面，蒙特卡罗（MC）模拟明确考虑了粒子与人体组织相互作用的所有细节，被认为是解决异质环境中混合场照射复杂性的最可靠工具。然而，完整的MC计算在临床实践中并不常用，因为它们通常需要大量的计算资源。因此，MC模拟通常仅用于检查有限数量的疑难病例的治疗计划。通用编程GPU卡的出现促使了精简的基于MC的剂量引擎的开发，相对于CPU硬件中的标准MC代码，该引擎可以显著减少重新计算治疗计划所需的时间。在这项工作中，我们报告了fred的开发情况，fred是一种用于离子束治疗计划的新型MC模拟平台。该代码可以使用II类MC算法在三维体素网格中传输粒子。初级和次级粒子都进行跟踪，并沿轨迹记录它们的能量沉积。已经实现了有效的粒子-介质相互作用模型，在剂量沉积的准确性和计算成本之间取得了平衡。目前，最精细的模块是质子束在水中的传输：fred获得的单束铅笔剂量深度分布与标准MC代码在治疗能量范围内布拉格峰的1%-2%内产生的分布一致。与在CNAO治疗中心进行的测量结果比较表明，在高达20厘米的射野尺寸因子测试中，横向剂量尾部的再现误差在2%以内。追踪内核可以在GPU硬件上运行，可以在单张卡上实现1000万个初级粒子的模拟。这种性能使得在几分钟内就能以总粒子数的1%重新计算质子治疗计划。
