Accounting for and harnessing RBE variability in proton therapy

质子治疗中考虑和利用 RBE 变异性

• 批准号: 9751238
• 负责人: Oleg Vassiliev
• 金额: $ 28.08万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9751238
• 关键词: Accounting; Affect; Biological; Childhood Ependymoma; Clinical; Computer Simulation; Computer software; Data; Data Analyses; Databases; Dimensions; Dose; Effectiveness; Elements; Foundations; Goals; Linear Energy Transfer; Location; Meta-Analysis; Methodology; Methods; Modeling; Normal tissue morphology; Outcome; Patients; Photons; Physical Function; Planning Techniques; Process; Protons; Publishing; Radiation therapy; Relative Biological Effectiveness; Research; Residual Tumors; Source; Structure; Therapeutic; Time; Tissues; Treatment outcome; Uncertainty; Variant; base; cancer radiation therapy; clinically relevant; clinically significant; cohort; density; experience; experimental study; ionization; phenomenological models; physical property; predictive tools; proton beam; proton therapy; spectral energy; tool; treatment planning; virtual clinical trial; Accounting; Affect; Biological; Childhood Ependymoma; Clinical; Computer Simulation; Computer software; Data; Data Analyses; Databases; Dimensions; Dose; Effectiveness; Elements; Foundations; Goals; Linear Energy Transfer; Location; Meta-Analysis; Methodology; Methods; Modeling; Normal tissue morphology; Outcome; Patients; Photons; Physical Function; Planning Techniques; Process; Protons; Publishing; Radiation therapy; Relative Biological Effectiveness; Research; Residual Tumors; Source; Structure; Therapeutic; Time; Tissues; Treatment outcome; Uncertainty; Variant; base; cancer radiation therapy; clinically relevant; clinically significant; cohort; density; experience; experimental study; ionization; phenomenological models; physical property; predictive tools; proton beam; proton therapy; spectral energy; tool; treatment planning; virtual clinical trial

The proposed study concerns proton beam radiotherapy of cancer. In the current standard of practice, treatment planning for proton therapy is based on the assumption that the relative biological effectiveness (RBE) of protons is 1.1 for all beam energies, dose levels and locations within the treated volume. Under this assumption, optimization of a treatment plan involves optimization of the physical dose only. However, it is well known that proton RBE is not constant. Abundant experimental data show unambiguously that the RBE increases with decreasing proton energy and with decreasing dose. Both these quantities vary within the treated volume and so does the RBE. This means that achieving an optimal distribution of the physical dose does not necessarily produce a treatment plan that is optimal in terms of the expected biological outcomes. The proposed study will develop a methodology and tools that will facilitate a new treatment plan optimization strategy that accounts for RBE variability, directly optimizes expected biological effects of a treatment, and thereby maximizes the likelihood of achieving best treatment outcomes. The main hypothesis of this study is that: Variations in proton RBE caused by variations of dose and beam energy spectrum can be modelled within uncertainties not exceeding those of experimental RBEs. The model can be incorporated in the treatment planning process so that for each patient a three dimensional RBE distribution is calculated. The computed RBEs will differ significantly from the generic RBE of 1.1 in clinically relevant structures. This hypothesis will be investigated by the following specific aims: 1. To develop a phenomenological model of RBE as a function of dose and beam energy spectrum. 2. To develop a proton treatment planning methodology where in addition to dose distribution, the variable RBE distribution is computed. 3. To investigate through treatment planning studies (in-silico or “virtual” clinical trials) the feasibility of the new methodology and to determine the potential clinical significance of RBE deviations from the generic RBE of 1.1.

拟议的研究涉及癌症的质子束放疗。在当前的实践标准中， 质子治疗的治疗计划基于以下假设：相对生物学有效性 对于处理体积的所有束能量，剂量水平和位置，质子的（RBE）为1.1。在此 假设治疗计划的优化仅涉及对物理剂量的优化。但是，很好 知道质子RBE不是恒定的。大量的实验数据明确表明RBE 随着质子能量降低和剂量减少而增加。这两个数量在 处理数量，RBE也是如此。这意味着实现身体剂量的最佳分布 不一定会制定一个治疗计划，该治疗计划在预期的生物学结果方面是最佳的。 拟议的研究将开发一种方法和工具，以促进新的治疗计划 考虑RBE变异性的优化策略，直接优化了A的预期生物学效应 治疗，从而最大程度地提高了达到最佳治疗结果的可能性。 这项研究的主要假设是：由剂量和束变化引起的质子RBE的变化 能量谱可以在不超过实验RBE的不确定性中进行建模。模型 可以纳入治疗计划过程，以便每位患者三维RBE 计算分布。计算的RBE将与临床上的通用RBE显着不同。 相关结构。以下具体目的将研究该假设：1。 RBE的现象学模型是剂量和束能谱的函数。 2。开发质子 治疗计划方法论除了剂量分布，可变的RBE分布是 计算。 3。通过治疗计划研究（内部或“虚拟”临床试验）进行研究 新方法的研究，并确定RBE偏离通用的潜在临床意义 RBE为1.1。