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[蒙特卡罗方法与放射外科治疗计划制定中的并行估计]

[The Monte Carlo method and parallel estimation in the drawing up of radiosurgery treatment plans].

作者信息

Scielzo G, Grillo Ruggieri F, Schwarz M, Rivolta A, Brunelli B, Surridge M, Gill A, Rietbrock C

机构信息

Servizio di Fisica Sanitaria, Azienda Ospedaliera S. Giovanni Battista, Molinette, Torino.

出版信息

Radiol Med. 1998 Jun;95(6):647-55.

PMID:9717550
Abstract

PURPOSE

We investigated the practical application of a calculation algorithm based on the Monte Carlo method to stereotactic radiosurgery treatment planning. In radiosurgery, high dose gradients and the lack of electronic disequilibrium make high resolution matrices and high computing power and speed necessary to obtain accurate dose distribution. To date, the main obstacle to the wider-spread use of the Monte Carlo method has been the huge computing time necessary to obtain a dose distribution on current hardware.

MATERIAL AND METHODS

In this project, developed within the ESPRIT program, funded by the European Union, a Parsytec CC (Cognitive Computing) computer was used with 9 processors (Power PC 604, 133 Mhz, RAM 64 Mb) with IBM AIX/EPX OS and availability for Fortran parallel codes compilation, connected to a PC for data input, results rendering, and dose distribution calculation with a conventional algorithm for comparison with the Monte Carlo code (an EGS4 user code). The module named Rapt Region Extractor performs data compression with an octree method without decreasing resolution, for RAM and computing time requirements to remain acceptable. A model of the 6 MV photon beam from Clinac 2100C Varian linear accelerator was devised, based on incident photon energy spectrum and, for each collimator dimension, on bidimensional dose distribution orthogonal to beam direction measured at SSd = SAD = 100 cm.

RESULTS

Parallelization was carried out on event numbers, allowing a simulation speed to number of processor ratio close to unity. A new random number generator was used, capable of correctly running on the parallel architecture. The simulation procedure includes: 1) CT acquisition in DICOM 3.0 format, Analyze or with scanner; 2) Target delineation, treatment arc definition. 3) Dose calculation, with both conventional and Monte Carlo methods. 4) Dose distribution rendering on every transverse, sagittal or coronal planes overlapped in color wash on anatomical representation. Comparison between conventional and Monte Carlo algorithms were carried out on an anthropomorphic phantom and 10 real patients, with 2.5 mm anatomical resolution and standard deviation never exceeding 2%. A simulation with 10,000,000 events and 1% maximum variance can be run in 43'. When PTV is an homogeneous areas the differences between the two methods are around 5%, while when PTV is localized in dishomogeneous areas discrepancies reach 20% in the bone.

CONCLUSIONS

In conclusion, the feasibility of direct simulation with the Monte Carlo method in radiosurgery has been demonstrated within time and hardware costs compatible with clinical practice.

摘要

目的

我们研究了基于蒙特卡罗方法的计算算法在立体定向放射外科治疗计划中的实际应用。在放射外科中,高剂量梯度以及缺乏电子平衡使得需要高分辨率矩阵和高计算能力及速度来获得准确的剂量分布。迄今为止,蒙特卡罗方法更广泛应用的主要障碍是在当前硬件上获得剂量分布所需的巨大计算时间。

材料与方法

在由欧盟资助的ESPRIT计划内开展的本项目中,使用了一台Parsytec CC(认知计算)计算机,其配备9个处理器(Power PC 604,133 Mhz,随机存取存储器64 Mb),运行IBM AIX/EPX操作系统,可用于Fortran并行代码编译,并连接到一台个人计算机用于数据输入、结果呈现以及使用传统算法进行剂量分布计算,以便与蒙特卡罗代码(一个EGS4用户代码)进行比较。名为Rapt Region Extractor的模块采用八叉树方法进行数据压缩,而不降低分辨率,以使随机存取存储器和计算时间要求保持在可接受范围内。基于入射光子能谱以及针对每个准直器尺寸,依据在源皮距(SSD)=源轴距(SAD)=100 cm处测量的与射束方向正交的二维剂量分布,设计了Varian Clinac 2100C直线加速器的6 MV光子束模型。

结果

在事件数量上进行了并行化处理,使得模拟速度与处理器数量之比接近1。使用了一种能够在并行架构上正确运行的新随机数生成器。模拟过程包括:1)以DICOM 3.0格式、Analyze格式或通过扫描仪进行CT采集;2)靶区勾画、治疗弧定义。3)使用传统方法和蒙特卡罗方法进行剂量计算。4)在每个横断、矢状或冠状平面上进行剂量分布呈现,并以彩色叠加在解剖学图像上。在一个人体模型和10例真实患者身上对传统算法和蒙特卡罗算法进行了比较,解剖分辨率为2.5 mm,标准差从未超过2%。使用10000000个事件且最大方差为1%的模拟可在43分钟内运行完成。当计划靶体积(PTV)为均匀区域时,两种方法之间的差异约为5%,而当PTV位于不均匀区域时,在骨组织中的差异可达20%。

结论

总之,已证明在与临床实践兼容的时间和硬件成本范围内,蒙特卡罗方法在放射外科中进行直接模拟是可行的。

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