Dose Uncertainty Management and Probabilistic Planning

剂量不确定性管理和概率规划

• 批准号: 7214972
• 负责人: JEFFREY Vincent SIEBERS
• 金额: $ 33.69万
• 依托单位: VIRGINIA COMMONWEALTH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-12-01 至 2011-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7214972
• 关键词: Acceleration; Accounting; Algorithms; Anatomy; Breathing; Cervix Uteri; Classification; Clinical; Collaborations; Complex; Complication; Coupled; Daily; Development; Dose; Ensure; Evaluation; Evaluation Indexes; Evaluation Methodology; Evolution; Goals; Image; Image Analysis; Individual; Intensity-Modulated Radiotherapy; Lung; Maps; Methods; Morphologic artifacts; Names; Normal tissue morphology; Numbers; Organ; Outcome; Patients; Phase; Population; Positioning Attribute; Probability; Process; Prostate; Public Health; Purpose; Radiation; Radiation therapy; Rate; Research Personnel; Residual state; Structure; Techniques; Testing; Therapeutic; Three-Dimensional Image; Three-Dimensional Imaging; Time; Treatment Effectiveness; Treatment outcome; Uncertainty; Variant; base; day; direct application; image guided therapy; image registration; improved; indexing; novel; programs; response; treatment planning; tumor

The evolution of radiation therapy treatment techniques coupled with improved targeting by 3D onboard imaging and real-time adaptive IMRT replanning makes possible the delivery of more conformal dose distributions to targets with substantially reduced margins in comparison with historical radiation therapy practice. A key component of image guided adaptive radiation therapy (IGART) is planning and tracking of dose distributions on multiple deforming presentations of the patient anatomy. Performing such complex dose calculations in the context of rapid IMRT optimization presents a number of scientific challenges. First dose computation on deforming anatomies may add dose uncertainties, which results in decreased treatment effectiveness. Secondly, optimal IGART application will require that accurate dose calculations be performed much more rapidly than is possible with present algorithms. Finally, even when onboard 3D imaging-based setup adjustments are applied, residual systematic and random uncertainties will remain and need to be considered during planning. The goals of this Project are: (1) To develop methods to evaluate and minimize dose errors and dose uncertainty introduced by adding dose distributions acquired at different presentations of the patient's anatomy so as to accurately quantify and ensure effective dose delivery for IGART. (2) To develop and validate efficient, accurate dose algorithms for use with deformed image sets so as to enable rapid plan re- optimization and plan re-evaluation for IGART. (3) To develop and compare methods to account for residual dosimetric and targeting uncertainties and errors during plan IMRT optimization for IGART treatment delivery. The long term objectives of this Program are to develop and implement optimal IGART methods, to use these methods to enable dose-per-fraction escalation, and to improve patient outcomes through delivery of highly conformal dose distributions with minimal dose uncertainty. This project will benefit public health by developing techniques that will improve quantification of radiation therapy doses delivered to patients throughout their course of radiation therapy as their anatomy changes due to responses to the treatment or other processes. The project will develop techniques to reduce the amount of normal tissues irradiated, thereby enabling a reduction in complication rates and improvement in control rates for patients treated with radiationtherapy.

放射治疗技术的发展，加上3D机载靶向的改进 成像和实时自适应调强放射治疗重新计划使更多适形剂量的输送成为可能 与历史放射治疗相比，靶点分布的边缘显著降低 实践图像引导自适应放射治疗（IGART）的关键组成部分是计划和跟踪放射治疗。 患者解剖结构的多个变形呈现上的剂量分布。表演如此复杂的 在快速IMRT优化的背景下的剂量计算提出了许多科学挑战。第一 对变形解剖结构的剂量计算可能会增加剂量不确定性，这会导致 治疗效果。其次，最佳IGART应用将需要精确的剂量计算， 比现有算法执行得快得多。最后，即使在机载3D 应用基于成像的设置调整，剩余的系统和随机不确定性将保持， 在规划中需要考虑。 本项目的目标是：（1）开发评估和最小化剂量误差和剂量的方法 通过添加在患者的不同呈现下获得的剂量分布引入的不确定性 解剖结构，以便准确量化并确保IGART的有效剂量输送。(2)制定和 验证用于变形图像集的有效、准确的剂量算法，以实现快速计划重新设计 IGART的优化和计划重新评估。(3)制定和比较各种方法， IGART治疗计划调强放疗优化过程中的剂量学和靶向不确定性和误差 交付. 该计划的长期目标是开发和实施最佳IGART方法， 这些方法能够使每部分剂量递增，并通过递送 具有最小剂量不确定性的高度共形剂量分布。 该项目将通过开发改进辐射量化的技术， 随着解剖结构的变化，在整个放射治疗过程中输送给患者的治疗剂量 由于对治疗或其他过程的反应。该项目将开发技术， 照射的正常组织的量，从而能够减少并发症发生率和改善 放射治疗患者的控制率。