Coverage optimized planning: Probabilistic treatment planning based on dose coverage histogram criteria
Coverage optimized planning: Probabilistic treatment planning based on dose coverage histogram criteria
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DOI：
10.1118/1.3273063
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发表时间：
2010-02-01
期刊：
影响因子：
3.8
通讯作者：
Siebers, J. V.
中科院分区：
文献类型：
--
作者：
Gordon, J. J.;Sayah, N.;Siebers, J. V.
这项工作(I)提出了一个基于剂量覆盖直方图(DCH)标准的概率治疗计划框架，称为覆盖优化计划(COP)；(Ii)描述了顶峰治疗计划系统中COP的具体概念验证实施；以及(Iii)对于一组28个前列腺解剖，比较了由该实施生成的COP计划与传统的基于PTV的计划，其计划标准与放射治疗肿瘤组0126协议的高剂量臂中的计划标准相似。设D(V)表示输送到结构的分数体积v的剂量。在常规的调强放射治疗计划中，D(V)具有由静态(计划)剂量分布得出的唯一值。在存在几何不确定性(例如，设置误差)的情况下，D(V)假定值的范围。DCH是D(V)的互补累积分布函数。DCH类似于剂量体积直方图(DVH)。DVH绘制体积v与剂量D的关系图，DCH绘制覆盖概率Q与D的关系图。对于给定的患者，Q是D(V)的实现值超过D的概率(即，几何不确定百分比)。基于PTV的治疗计划可以通过用相应的DCH标准替换DVH优化标准来转换为COP计划。在这种方法中，PTV和计划危险器官体积被丢弃，而DCH标准被直接应用于临床靶区体积(CTV)或危险器官(OAR)。使用与DVH标准类似的策略来优化计划。描述了具体的实现方法。缔约方会议发现，在以下意义上，缔约方会议比基于PTV的标准计划产生更好的计划。虽然目标桨剂量折衷曲线与基于PTV的计划的目标桨剂量折衷曲线相同，但缔约方会议计划能够利用桨剂量的松弛，即桨剂量低于其最佳限度的情况，来扩大目标覆盖面。具体地说，由于COP计划不受预定义的PTV的限制，它们能够通过推动桨剂量达到但不超过其优化限度，在CTV周围提供更广泛的剂量学裕度。COP计划显示，在平均所有28例前列腺解剖时，靶点覆盖率有所提高，这表明COP方法可以为许多患者提供好处。然而，可以利用松弛的桨剂量来增加目标覆盖的程度将根据患者的个体解剖而有所不同。这里研究的概念验证COP实施仅针对CTV最小剂量标准使用了概率DCH标准。所有其他优化标准均为常规DVH标准。在成熟的COP实施中，所有优化标准都将是DCH标准，从而能够对概率剂量分布进行直接规划控制。在肿瘤控制概率和/或正常组织并发症概率方面，有必要进一步研究以确定COP计划的益处。
This work (i) proposes a probabilistic treatment planning framework, termed coverage optimized planning (COP), based on dose coverage histogram (DCH) criteria; (ii) describes a concrete proof-of-concept implementation of COP within the PINNACLE treatment planning system; and (iii) for a set of 28 prostate anatomies, compares COP plans generated with this implementation to traditional PTV-based plans generated with planning criteria approximating those in the high dose arm of the Radiation Therapy Oncology Group 0126 protocol. Let D(v) denote the dose delivered to fractional volume v of a structure. In conventional intensity modulated radiation therapy planning, D(v) has a unique value derived from the static (planned) dose distribution. In the presence of geometric uncertainties (e.g., setup errors) D(v) assumes a range of values. The DCH is the complementary cumulative distribution function of D(v). DCHs are similar to dose volume histograms (DVHs). Whereas a DVH plots volume v versus dose D, a DCH plots coverage probability Q versus D. For a given patient, Q is the probability (i.e., percentage of geometric uncertainties) for which the realized value of D(v) exceeds D. PTV-based treatment plans can be converted to COP plans by replacing DVH optimization criteria with corresponding DCH criteria. In this approach, PTVs and planning organ at risk volumes are discarded, and DCH criteria are instead applied directly to clinical target volumes (CTVs) or organs at risk (OARs). Plans are optimized using a similar strategy as for DVH criteria. The specific implementation is described. COP was found to produce better plans than standard PTV-based plans, in the following sense. While target OAR dose tradeoff curves were equivalent to those for PTV-based plans, COP plans were able to exploit slack in OAR doses, i.e., cases where OAR doses were below their optimization limits, to increase target coverage. Specifically, because COP plans were not constrained by a predefined PTV, they were able to provide wider dosimetric margins around the CTV, by pushing OAR doses up to, but not beyond, their optimization limits. COP plans demonstrated improved target coverage when averaged over all 28 prostate anatomies, indicating that the COP approach can provide benefits for many patients. However, the degree to which slack OAR doses can be exploited to increase target coverage will vary according to the individual patient anatomy. The proof-of-concept COP implementation investigated here utilized a probabilistic DCH criteria only for the CTV minimum dose criterion. All other optimization criteria were conventional DVH criteria. In a mature COP implementation, all optimization criteria will be DCH criteria, enabling direct planning control over probabilistic dose distributions. Further research is necessary to determine the benefits of COP planning, in terms of tumor control probability and/or normal tissue complication probabilities.