Improving dose coverage of tumor periphery in radiotherapy of lung cancer through the use of flattening filter free beams

通过使用无平坦滤波器光束改善肺癌放射治疗中肿瘤周边的剂量覆盖

• 批准号: 9218692
• 负责人: Oleg Vassiliev
• 金额: $ 8万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9218692
• 关键词: Achievement; Affect; Algorithms; Anatomy; Biological Models; Cancer Patient; Data; Data Reporting; Data Set; Dose; Electron Transport; Electrons; Feasibility Studies; Image; Location; Lung; Lung Neoplasms; Malignant neoplasm of lung; Methodology; Modeling; Morphologic artifacts; Motion; Patient Selection; Patients; Peripheral; Phase; Photons; Planning Techniques; Probability; Radiation; Radiation therapy; Recurrence; Relapse; Research; Resolution; Risk; Selection Criteria; Spatial Distribution; Structure of parenchyma of lung; Surface; Techniques; Testing; Thinness; Translating; X-Ray Computed Tomography; base; cancer radiation therapy; clinical practice; clinically significant; cohort; density; image registration; improved; respiratory; standard care; success; time use; treatment planning; tumor; virtual

PROJECT SUMMARY The proposed study concerns radiation therapy for lung cancer. Lung tumors are usually surrounded, at least partially, by lung tissue that has a much lower density than the tumor. In external photon-beam radiotherapy, the lung-tumor interface is characterized by disequilibrium of secondary electrons that results in dose build-up and build-down regions near the tumor surface, where the beam enters and exits it. This translates into underdosage of tumor surface, and potentially compromises tumor control. In routine treatment planning this underdosage is largely undetected. Even though presently 4DCT images are acquired for most lung cancer patients, these images are used primarily to determine the extent of tumor motion. Dose calculations, on the other hand, are typically performed on a CT image averaged over the respiratory cycle. Because the tumor moves, such averaging smears the lung-tumor interface, leading to dose calculation errors in superficial regions of the tumor that may compromise treatment. The proposed study will first evaluate the magnitude of the underdosage and its clinical significance in terms of tumor control probability. This will be accomplished by utilizing a methodology that offers two important improvements over the standard treatment planning techniques: (a) dose distributions will be calculated separately for each of 10 phases of the respiratory cycle, and then combined so as to evaluate the spatial distribution of the dose delivered to the tumor; (b) calculations will be performed with Monte Carlo, the most advanced dose calculation algorithm available. Second, we will test the hypothesis that the use of flattening filter-free beams improves tumor control probability. Previous treatment planning studies have demonstrated that such treatments are feasible and that dose in build-up regions is higher owing to a softer photon spectrum. Our research strategy has three specific aims: (1) evaluate the magnitude of the underdosage in a simple model of a lung tumor, namely a spherical static tumor surrounded by lung tissue, calculating doses with Monte Carlo; (2) evaluate the magnitude of the underdosage for a cohort of 15 previously treated patients, calculating dose distributions retrospectively with Monte Carlo for each of the 10 respiratory phases separately, and then combining them; (3) compare predicted tumor control probabilities between treatments with conventional photon beams and flattening filter free beams. For this purpose, for each patient in the cohort a new treatment plan will be generated using flattening filter free beams.

项目摘要 拟议的研究涉及肺癌的放射治疗。肺肿瘤通常被包围，至少至少 部分地，通过肺组织的密度远低于肿瘤。在外部光子光束放疗中， 肺肿瘤界面的特征是二次电子不平衡，导致剂量积累 并在肿瘤表面附近建造朝下的区域，光束进入并退出。这转化为 肿瘤表面的衰老不足，并可能损害肿瘤控制。 在常规治疗计划中，这种款项在很大程度上未被发现。即使目前的4DCT图像是 这些图像用于大多数肺癌患者，主要用于确定肿瘤的程度 运动。另一方面，剂量计算通常在CT图像上进行 呼吸周期。由于肿瘤移动，因此平均涂抹肺肿瘤界面，导致剂量 肿瘤表面区域的计算误差可能会损害治疗。 拟议的研究将首先评估次数不足的大小及其临床意义。 肿瘤控制概率。这将通过利用提供两个重要的方法来实现 对标准治疗计划技术的改进：（a）将计算剂量分布 分别在呼吸周期的10个阶段中的每个阶段中分别，然后合并以评估空间 分配给肿瘤的剂量的分布； （b）将使用最多的蒙特卡洛进行计算 可用的高级剂量计算算法。其次，我们将测试使用的假设 扁平过滤器的光束可提高肿瘤控制概率。以前的治疗计划研究 证明这种治疗是可行的，并且由于较软，在积聚区域的剂量更高 光子光谱。 我们的研究策略具有三个特定的目的：（1）简单地评估不足的大小 肺肿瘤的模型，即被肺组织包围的球形静态肿瘤 蒙特卡洛； （2）评估先前治疗的15个队列的阶层不足的幅度 患者，用蒙特卡洛（Monte Carlo）在10个呼吸阶段进行回顾性剂量分布 单独，然后将它们结合在一起； （3）比较预测的肿瘤控制概率 使用常规光子梁和扁平过滤器束的处理。为此，每个目的 队列中的患者将使用扁平过滤器束生成新的治疗计划。