A TCP-NTCP estimation module using DVHs and known radiobiological models and parameter sets.
A TCP-NTCP estimation module using DVHs and known radiobiological models and parameter sets.
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DOI：
10.1120/jacmp.26.149
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发表时间：
2004-01-01
影响因子：
2.1
通讯作者：
Fallone, B Gino
中科院分区：
文献类型：
--
作者：
Warkentin, Brad;Stavrev, Pavel;Fallone, B Gino
放射治疗计划评价依赖于对给定剂量分布引起的肿瘤控制概率（TCP）和正常组织并发症概率（NTCP）的隐式估计。放射生物学建模对放射治疗的一个潜在应用是通过更明确地确定TCP和NTCP值来对治疗计划进行排序。尽管目前放射生物学模型的预测能力有限，无法作为主要的评价工具，但放射生物学模型预测仍然是临床经验的宝贵补充。一个方便的计算模块已经开发用于估计TCP和NTCP所产生的剂量分布计算的治疗计划系统，其特征在于差分（频率）剂量体积直方图（DDVH）。该模块中包含的放射生物学模型包括S形剂量响应和临界体积NTCP模型、Poisson TCP模型以及包含描述线性二次细胞杀伤和再增殖的放射生物学参数的TCP模型。数据库中已收集了不同模型的多组参数值。估计的参数表征几种不同的正常组织和肿瘤类型的辐射响应。该系统还允许用户输入和存储参数，这是特别有用的，因为在文献中可用的参数估计的数量迅速增加。该系统的潜在应用包括以下内容：比较不同治疗计划或治疗类型的结果的放射生物学预测;比较患者DVH队列的观察结果数量与基于不同模型/参数集的预测结果数量;以及测试模型预测对参数值中不确定性的敏感性。因此，该模块有助于合并，使更容易获得当前的放射生物学建模知识，并可能作为一个有用的援助，在放射治疗计划的前瞻性和回顾性分析。
Radiotherapy treatment plan evaluation relies on an implicit estimation of the tumor control probability (TCP) and normal tissue complication probability (NTCP) arising from a given dose distribution. A potential application of radiobiological modeling to radiotherapy is the ranking of treatment plans via a more explicit determination of TCP and NTCP values. Although the limited predictive capabilities of current radiobiological models prevent their use as a primary evaluative tool, radiobiological modeling predictions may still be a valuable complement to clinical experience. A convenient computational module has been developed for estimating the TCP and the NTCP arising from a dose distribution calculated by a treatment planning system, and characterized by differential (frequency) dose-volume histograms (DDVHs). The radiobiological models included in the module are sigmoidal dose response and Critical Volume NTCP models, a Poisson TCP model, and a TCP model incorporating radiobiological parameters describing linear-quadratic cell kill and repopulation. A number of sets of parameter values for the different models have been gathered in databases. The estimated parameters characterize the radiation response of several different normal tissues and tumor types. The system also allows input and storage of parameters by the user, which is particularly useful because of the rapidly increasing number of parameter estimates available in the literature. Potential applications of the system include the following: comparing radiobiological predictions of outcome for different treatment plans or types of treatment; comparing the number of observed outcomes for a cohort of patient DVHs to the predicted number of outcomes based on different models/parameter sets; and testing of the sensitivity of model predictions to uncertainties in the parameter values. The module thus helps to amalgamate and make more accessible current radiobiological modeling knowledge, and may serve as a useful aid in the prospective and retrospective analysis of radiotherapy treatment plans.