Management of Breathing effects in Radiotherapy Planning

描述（由申请人提供）：强度调制放射治疗已被证明可以改善放射治疗的剂量分布，当应用于肺部治疗时，特别是如果传输可以记录到患者的呼吸周期。然而，与呼吸登记IMRT治疗计划相关的许多技术问题尚未得到解决，并且缺乏潜在计划和交付方法之间的比较。该项目的主要目标是确定增加计划和交付复杂性与改善累积患者剂量分布和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，并最终将其公开存档，供其他研究人员使用。在这个框架内，将开发计划技术来模拟一系列潜在的临床选择，从简单到复杂，包括：简单边缘，以统计方式计算肿瘤运动，门控，以及与呼吸期完全同步的IMRT递送。据推测，很大一部分模拟肺患者（无法实现屏气技术）将从使用呼吸记录计划和分娩中获得预期的结果。在具体目标sa# 1 （4-D优化）中，将开发所有相关交付技术的时空（“4-D”）IMRT规划和优化方法。在SA #2（不确定性和日常变化的管理）中，这些方法将被推广到明确地解释不确定性和日常变化。在SA #3（临床影响）中，将对模拟患者计划的统计显着队列进行估计，以可能的剂量学和结果改善方面的技术的潜在影响。本研究将提供，首先，指导了解四维放射治疗的潜在结果影响；其次，为具有挑战性的4-D治疗计划问题提供强大的解决方案；第三，为其他研究人员在四维规划领域共享数据和软件工具。

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.