Management of Breathing effects in Radiotherapy Planning

描述（由申请人提供）：调强放射治疗已被证明在应用于肺部治疗时可改善放射治疗剂量分布，尤其是在输送可与患者呼吸周期配准的情况下。然而，许多与呼吸配准调强放射治疗计划相关的技术问题尚未得到解决，并且缺乏潜在的计划和实施方法之间的比较。本项目的主要目标是确定增加的计划和输送复杂性与累积患者剂量分布的改善以及对治疗结果的预期影响之间的权衡。在跨学科合作中，将开发共享的跨平台工具集、技术和测试数据集，并最终公开存档供其他研究人员使用。在此框架内，计划技术，以模拟一系列潜在的临床选择，从简单到复杂，将开发，包括：简单的利润，占肿瘤运动的统计方式，门控，并完全同步IMRT输送与呼吸阶段。据推测，相当一部分模拟肺患者（无法实现屏气技术）将从使用呼吸配准计划和输送中获得预期结局受益。在特定目标SA #1（4-D优化）中，将开发所有相关输送技术的时空（“4-D”）IMRT计划和优化方法。在SA #2（不确定性和每日变化的管理）中，这些方法将被推广到明确说明不确定性和每日变化。在SA #3（临床影响）中，将针对模拟患者计划的统计学显著性队列，估计技术在可能的剂量测定和结局改善方面的潜在影响。这项研究将提供，首先，指导了解潜在的结果影响的4-D放射治疗;第二，强大的解决方案，具有挑战性的4-D治疗计划问题;第三，共享数据和软件工具，为其他研究人员在4-D规划领域。

DESCRIPTION (provided by applicant): Intensity modulated radiation therapy has been shown to improve radiotherapy dose distributions when applied to lung treatments, especially if the delivery can be registered to the patient's breathing cycle. However, many technical issues associated with breathing-registered IMRT treatment planning have not yet been addressed, and comparisons between potential planning and delivery approaches are lacking. The primary goal of this project is to determine the tradeoffs between increased planning and delivery complexity vs. improvements in cumulative patient dose distributions and the expected impact on treatment outcomes. In an interdisciplinary collaboration, a shared cross-platform toolset, techniques, and test data sets will be developed and eventually publicly archived for use by other researchers. Within this framework, planning techniques to simulate a range of potential clinical options, from simple to complex, will be developed, including: simple margins, accounting for tumor motion in a statistical way, gating, and fully synchronizing IMRT delivery with breathing-phase. It is hypothesized that a significant fraction of simulated lung patients (who cannot achieve breath-hold techniques) will have a predicted outcome benefit from the use of breathing-registered planning and delivery. In Specific Aim SA #1 (4-D optimization), temporo-spatial ("4-D") IMRT planning and optimization methods for all relevant delivery techniques will be developed. In SA #2 (Management of uncertainties and daily variations), those methods will be generalized to explicitly account for uncertainties and day-to-day variations. In SA #3 (Clinical impact), the potential impact of the techniques in terms of likely dosimetric and outcome improvements will be estimated for a statistically significant cohort of simulated patient plans. This research will provide, firstly, guidance for understanding the potential outcomes impact of 4-D radiotherapy treatments; secondly, robust solutions to challenging 4-D treatment planning problems; and thirdly, shared data and software tools for other researchers in the area of 4-D planning.