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 这项拟议的研究涉及肺癌的放射治疗。肺肿瘤通常被包围，至少 部分是由密度比肿瘤低得多的肺组织引起的。在外部光子束放射治疗中， 肺-肿瘤界面的特征在于二次电子的不平衡 和肿瘤表面附近的积聚区域，光束在那里进入和离开它。这转化为 肿瘤表面的剂量不足，并可能损害肿瘤控制。 在常规治疗计划中，这种剂量不足在很大程度上未被发现。尽管目前4DCT图像 对于大多数肺癌患者来说，这些图像主要用于确定肿瘤的范围， 议案另一方面，剂量计算通常在CT图像上执行，所述CT图像在所述剂量上平均。 呼吸循环由于肿瘤移动，这种平均涂抹肺肿瘤界面，导致剂量 可能影响治疗的肿瘤浅表区域的计算错误。 拟议的研究将首先评估剂量不足的程度及其在以下方面的临床意义： 肿瘤控制概率。这将通过使用一种方法来实现，该方法提供了两个重要的 对标准治疗计划技术的改进：（a）将计算剂量分布 分别用于呼吸周期的10个阶段中的每一个，然后组合以评估空间 （B）将使用蒙特卡罗进行计算，最大的计算量是 提供先进的剂量计算算法。第二，我们将检验使用 使无滤波器的射束变平提高了肿瘤控制概率。以前的治疗计划研究 证明了这种治疗是可行的，由于较软的辐射， 光子谱 我们的研究策略有三个具体目标：（1）评估剂量不足的程度，在一个简单的 肺肿瘤模型，即被肺组织包围的球形静态肿瘤， Monte Carlo;（2）评价15例既往接受过治疗的队列的剂量不足程度 患者，使用Monte Carlo回顾性计算10个呼吸时相的剂量分布 （3）比较预测的肿瘤控制概率， 使用常规光子束和平坦化无滤波器束进行治疗。为此，对于每个 对于组群中的患者，将使用无平坦滤波器射束生成新的治疗计划。