Modeling late rectal toxicities based on a parameterized representation of the 3D dose distribution
Modeling late rectal toxicities based on a parameterized representation of the 3D dose distribution
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DOI：
10.1088/0031-9155/56/7/013
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发表时间：
2011-04-07
影响因子：
3.5
通讯作者：
Partridge, Mike
中科院分区：
文献类型：
--
作者：
Buettner, Florian;Gulliford, Sarah L.;Partridge, Mike
存在许多基于剂量体积直方图 (DVH) 或剂量表面直方图 (DSH) 预测毒性的模型。这种方法有几个缺点，首先，将剂量分布减少到直方图会导致空间信息的丢失，其次，直方图的箱彼此高度相关。此外，过去提出的一些复杂的非线性模型缺乏直接的物理解释和预测概率而不是二元结果的能力。我们提出了直肠壁剂量 3D 分布的参数化表示，其中明确包括剂量分布偏心率及其横向和纵向范围形式的几何信息。我们使用基于非线性核的概率模型根据参数化剂量分布来预测晚期直肠毒性，并使用 MRC RT01 试验 (ISCTRN 47772397) 的数据评估其预测能力。考虑的终点是直肠出血、稀便和总体毒性评分。我们提取简单的规则来识别与特别低的并发症风险相关的 3D 剂量模式。基于几何和体积测量参数化表示的正常组织并发症概率 (NTCP) 模型得出的预测直肠出血、稀便和整体毒性的曲线下面积 (AUC) 分别为 0.66、0.63 和 0.67。相比之下，基于标准 DVH 的 NTCP 模型表现较差，所有三个端点的 AUC 均为 0.59。总之，我们提出了基于直肠壁剂量参数化表示的低维、可解释和非线性 NTCP 模型。这些模型比基于标准 DVH 的模型具有更高的预测能力，并且其低维度允许识别与低并发症风险相关的 3D 剂量模式。
Many models exist for predicting toxicities based on dose-volume histograms (DVHs) or dose-surface histograms (DSHs). This approach has several drawbacks as firstly the reduction of the dose distribution to a histogram results in the loss of spatial information and secondly the bins of the histograms are highly correlated with each other. Furthermore, some of the complex nonlinear models proposed in the past lack a direct physical interpretation and the ability to predict probabilities rather than binary outcomes. We propose a parameterized representation of the 3D distribution of the dose to the rectal wall which explicitly includes geometrical information in the form of the eccentricity of the dose distribution as well as its lateral and longitudinal extent. We use a nonlinear kernel-based probabilistic model to predict late rectal toxicity based on the parameterized dose distribution and assessed its predictive power using data from the MRC RT01 trial (ISCTRN 47772397). The endpoints under consideration were rectal bleeding, loose stools, and a global toxicity score. We extract simple rules identifying 3D dose patterns related to a specifically low risk of complication. Normal tissue complication probability (NTCP) models based on parameterized representations of geometrical and volumetric measures resulted in areas under the curve (AUCs) of 0.66, 0.63 and 0.67 for predicting rectal bleeding, loose stools and global toxicity, respectively. In comparison, NTCP models based on standard DVHs performed worse and resulted in AUCs of 0.59 for all three endpoints. In conclusion, we have presented low-dimensional, interpretable and nonlinear NTCP models based on the parameterized representation of the dose to the rectal wall. These models had a higher predictive power than models based on standard DVHs and their low dimensionality allowed for the identification of 3D dose patterns related to a low risk of complication.