调强放射治疗子野权重优化方法研究

由于子野分割带来的误差, 使得调强放疗(Intensity Modulated Radiation Therapy, 简称IMRT)计划系统所制作的计划往往不能满足临床要求。 本研究将采用基于共轭梯度法的子野权重优化方法来减小此误差, 提高制作计划的效率和效果。 采用共轭梯度法优化子野权重和微调子野形状, 最终使得子野分割前后强度误差最小。 在精确放疗系统中对常见的临床病例（鼻咽癌和周围性肺癌）进行测试, 通过对比靶区和危及器官的剂量体积直方图以及CT片上的等剂量线, 发现子野权重优化后靶区的平均剂量分别从87.0%提高到100.2%和从90.0%提高到98.4%, 更好地满足临床要求。     

基于共轭梯度法的调强放疗射束强度分布优化

针对逆向调强放疗中强度分布优化涉及的参数多, 且临床上对其优化速度要求高的特点, 将医生期望的靶区剂量和周围正常组织剂量限制转化为二次函数形式的目标函数, 然后利用共轭梯度法对该目标函数进行优化。 最后采用一例C形靶区紧密包围危及器官的模拟病例和一例临床常用的前列腺实例, 在PC机（CPU E7200@2.53GHz, 2.00GB内存, Windows XP）上对强度分布优化效果进行测试, 对模拟病例10 s便找到最优解; 而对前列腺病例20 s便可以找到最优解; 且两个测试病例优化所得强度分布对应的剂量分布均满足要求。 测试结果表明, 采用共轭梯度法优化强度分布具有快速和效果好的优点, 因此可以将其应用在精确放疗系统中。 The beam intensity map optimization of Intensity Modulated Radiation Treatment(IMRT) is a large scale optimization problem because of thousands of parameters involved. A fast and efficient approach was studied in the paper according to the clinical requirement for high speed and good results. Firstly, the clinical prescribed dose of Planning Target Volume(PTV) and dose volume constraints of Normal Tissue and Organ at Risk(OAR) were transformed into a quadratic objective function. And then Conjugate Gradient(CG) was adopted to optimize the objective function. At last, a simulated case and a clinical case were used to test the approach. The results showed that the optimization process need 40 s while satisfied results could be obtained in 10 s for simulated case and the optimization process need 1 min and 20 s while optimized results could be obtained in 20 s for the clinical prostate case. So it can be found that the approach of proposed in this paper is valid and efficient, and can be used to the accurate radiation therapy system.     

基于GPU加速的质子调强放疗鲁棒优化器

开发一种基于图形处理器（GPU）加速的质子调强放疗鲁棒优化器,用于减小质子束射程不确定性和靶区定位偏差对质子放疗的影响。建立的鲁棒优化模型使用的目标函数包括9种边界剂量目标,分别是:无偏差情况、2种射程偏差（偏长与偏短）、6种摆位不确定性（前后、侧向、上下入射方向各2种正负偏差）。首先靶区和危及器官的剂量贡献矩阵使用笔形束算法计算得到,然后使用共轭梯度法优化目标函数让其满足约束条件,这两部分均采用GPU加速。头颈部、肺部和前列腺三个临床病例被用来检测本优化器的性能表现。与传统基于计划靶区（PTV）的质子调强放疗计划相比,鲁棒优化器能够优化出对射程不确定性和摆位误差更加不敏感的治疗计划,让靶区实现了高剂量均匀性的同时危及器官（OARs）也得到了更好的保护。经过100次迭代,三个病例的优化时间均在10 s左右。该结果证明了基于GPU加速的质子调强放疗鲁棒优化器能够在短时间内设计出高鲁棒性的质子治疗计划,从而提高质子放射治疗的可靠性。This paper describes the development of a fast robust optimization tool that takes advantage of the GPU technologies. The objective function of the robust optimization model considered nine boundary dose distributions--two for ±range uncertainties, six for ±set-up uncertainties along anteroposterior (A-P), lateral (R-L) and superior{inferior (S-I) directions, and one for nominal situation. The nine boundary influence matrices were calculated using an in-house dose engine for proton pencil beams of a finite size, while the conjugate gradient method was applied to minimize the objective function. The GPU platform was adopted to accelerate both the proton dose calculation algorithm and the conjugate gradient method. Three clinical cases-one head and neck cancer case, one lung cancer case and one prostate cancer case-were investigated to demonstrate the clinical significance of the proposed robust optimizer. Compared with conventional planning target volume (PTV) based IMPT plans, the proposed method was found to be conducive in designing robust treatment plans that were less sensitive to range and setup uncertainties. The three cases showed that targets could achieve high dose uniformity while organs at risks (OARs) were under better protection against setup and range errors. The run times for the three cases were around 10 s for 100 iterations. The GPU-based fast robust optimizer developed in this study can serve to improve the reliability of traditional proton treatment planning by achieving a high level of robustness in a much shorter time.     

基于自适应遗传算法的质子调强放疗扫描路径优化

研究和开发了基于自适应遗传算法的质子调强放疗扫描路径优化方法,并在此基础上对质子调强放疗扫描时间进行初步临床评估。利用自适应遗传算法具有的较强容错性和全空间最优搜索能力开发点扫描质子调强路径优化模块,并将其集成到自主研发的放疗计划系统,选取AAPM TG-119头颈部肿瘤和前列腺肿瘤模拟例题及两例临床病例进行测试,对比扫描路径优化前后质子放疗计划扫描路径长度。对于AAPMTG-119头颈部肿瘤和前列腺肿瘤模拟例题,总扫描路径长度分别降低了27.17%和18.72%,临床头颈部肿瘤和前列腺肿瘤病例总扫描路径长度分别降低了25.36%和32.95%,优化前后路径长度降低比率与零权重扫描点及肿瘤解剖结构有关。基于自适应遗传算法的扫描路径优化方法可减少质子调强放疗计划扫描时间,从而缩短病人治疗时间,可广泛应用于质子重扫描临床技术。The objective of this research is to study and develop a proton spot scanning path optimization method using an improved genetic algorithm for proton therapy and to evaluate the scanning time under clinical conditions. An Improved Adaptive Genetic Algorithm (IAGA) based scanning path optimization module was developed and integrated into the home-grown treatment planning system. Four cases, including two AAPM TG-119 standard cases and two clinical cases, were selected to compare their scanning path length before and after scanning path optimization. For the two AAPM TG-119 cases, the optimized scanning path length dropped by 27.17% and 18.72%, and for the corresponding clinical cases, the optimized scanning path length dropped by 25.36% and 32.95% respectively. The performance of scanning path optimization was affected by the number of zero-weight spots and connected regions in the scanning map. IAGA based scanning path optimization can reduce the total scanning path length in intensity modulated proton therapy and, therefore, can be used in spot rescanning to accommodate organ motion.     

Multi-objective optimization of inverse planning for accurate radiotherapy

The multi-objective optimization of inverse planning based on the Pareto solution set, according to the multi-objective character of inverse planning in accurate radiotherapy, was studied in this paper. Firstly, the clinical requirements of a treatment plan were transformed into a multi-objective optimization problem with multiple constraints. Then, the fast and elitist multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) was introduced to optimize the problem. A clinical example was tested using this method. The results show that an obtained set of non-dominated solutions were uniformly distributed and the corresponding dose distribution of each solution not only approached the expected dose distribution, but also met the dose-volume constraints. It was indicated that the clinical requirements were better satisfied using the method and the planner could select the optimal treatment plan from the non-dominated solution set.     

发散型准直器限束孔应用于被动散射质子放疗可行性研究

被动散射质子放疗（Passive Scattering Proton Therapy,PSPT）是质子治疗的主要技术之一,束流通过准直器限束孔（Aperture）时因边缘散射效应导致患者体内剂量分布偏离理想状态。使用蒙特卡洛软件TOPAS（TOol for PArticle Simulation）对质子束流经过发散型与传统型准直器限束孔后进入水模体中的过程建模,分析两种准直器的边缘散射效应对剂量及中子能谱分布的影响,分别测试70,110,160,200,230,250 MeV能量下的质子束流,发现传统Aperture在70 MeV的质子束下边缘散射效应最明显,在距水箱表面0.5 cm深度处横向剂量曲线平坦度、均匀度分别达到4.63%,108.05%,随着深度增加边缘散射效应逐渐减弱,在布拉格峰位置处接近消失。使用发散型准直器限束孔后,在70 MeV下平坦度、均匀度分别降至1.28%,101.31%,对于100,160,200 MeV质子束均有不同程度改善。对于能量接近250 MeV的质子束,发散型准直器限束孔设置下横向剂量曲线并无优势。边缘散射效应导致的剂量不均随水深增加而减弱,对于各个能量质子,使用发散型准直器限束孔后次级中子减少。研究结果表明,发散型准直器限束孔应用于PSPT效果显著,为进一步应用于临床提供数据支撑。Passive Scattering Proton Therapy (PSPT) is one of the main technologies for proton radiation therapy. The dose distribution in the patient deviates from the ideal state due to the edge scattering effect when the beam passes through the aperture. In this paper, TOPAS, a Monte Carlo software, was used to simulate the passive scattering treatment head. The influence of the edge scattering effect of the two aperture sets on the dose distribution was compared. The proton beam at 70, 110, 160, 200, 230 and 250 MeV was tested respectively. We found that the scattering effect of the conventional aperture is most obvious at 70 MeV, and the flatness and hetergeneity of the lateral dose curve at the inlet of 0.5 cm of the tank reach 4.63%, 108.05%, respectively. The dose shift caused by the edge scattering effect decreases with increasing water depth and disappears at the Bragg peak. After using the divergent aperture, the flatness and uniformity at 70 MeV are reduced to 1.28% and 101.31%, respectively, and the 100, 160, and 200 MeV proton beams are improved in different extents. For a proton beam with an energy close to 250 MeV, there is no advantage in the lateral dose curve of the divergent aperture. For all energy protons, the secondary neutrons are reduced with divergent aperture. The results show that the divergent aperture is effective for PSPT and this study provides data support for further application in clinical practice.     

几种不同材料降能器对200 MeV质子放疗特性的蒙特卡罗模拟

能量选择系统是医用质子回旋加速器放疗系统中极其重要的部件,主要用来调节质子束能量,使得从加速器出来的质子束能量满足临床治疗计划的要求。能量选择系统的核心部件是降能器,目前降能器大多采用石墨作为降能材料。近些年提出用铍或者碳化硼替代石墨作为降能器材料的设想,以期望提高质子束流的传输效率。利用蒙特卡罗软件TOPAS模拟200 MeV质子在石墨、铍和碳化硼三种不同材料多楔形结构降能器中的输运过程,统计了穿过降能器后质子以及产生的次级中子的能量通量,并计算了质子束流在穿过不同降能器后的能量分散,据此得到了三种材料降能器厚度与质子能量之间的关系曲线,同时也分析了不同降能器对质子束传输效率的影响以及次级中子产额的情况。通过对比发现,三种材料降能器对束流的能量发散效果相当,而使用铍或者碳化硼都能提高束流传输效率,尤其铍降能器的性能较优。但铍和碳化硼与质子相互作用会产生更多的次级中子,因此在实际应用时需要更多地考虑次级中子对设备的辐射防护。Energy selection system (ESS) is an important component for medical proton cyclotron system. It has been widely used to modulate the proton energy in accordance with treatment requirements. ESS consists of the energy degrader which was mostly made of graphite. Recent years, to improve the transmission efficiency of the proton beams, beryllium and boron carbide have been proposed to substitute the graphite. In this work, the Monte Carlo code, TOPAS, was used to simulate the transport process of 200 MeV proton beams traversing the multi-wedge energy degrader made of graphite, beryllium and boron carbide, respectively. Energy fluxes of the protons and secondary neutrons after degrader, as well as the energy dispersion of the degraded proton beams, were calculated. It is found that the energy dissipation effect is nearly identical for all three kinds of degrader material, but using the beryllium or even boron carbide can improve the proton transmission efficiency. However, more secondary neutrons would be produced when proton beams interact with the beryllium and boron carbide, suggesting the need of additional consideration for radiation shielding to devices.