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首页> 外文期刊>International Journal of Radiation Oncology, Biology, Physics >A novel method to incorporate the spatial location of the lung dose distribution into predictive radiation pneumonitis modeling
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A novel method to incorporate the spatial location of the lung dose distribution into predictive radiation pneumonitis modeling

机译:一种将肺部剂量分布的空间位置纳入预测性放射性肺炎建模的新方法

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Purpose: Studies have proposed that patients who receive radiation therapy to the base of the lung are more susceptible to radiation pneumonitis than patients who receive therapy to the apex of the lung. The primary purpose of the present study was to develop a novel method to incorporate the lung dose spatial information into a predictive radiation pneumonitis model. A secondary goal was to apply the method to a 547 lung cancer patient database to determine whether including the spatial information could improve the fit of our model. Methods and Materials: The three-dimensional dose distribution of each patient was mapped onto one common coordinate system. The boundaries of the coordinate system were defined by the extreme points of each individual patient lung. Once all dose distributions were mapped onto the common coordinate system, the spatial information was incorporated into a Lyman-Kutcher-Burman predictive radiation pneumonitis model. Specifically, the lung dose voxels were weighted using a user-defined spatial weighting matrix. We investigated spatial weighting matrices that linearly scaled each dose voxel according to the following orientations: superior-inferior, anterior-posterior, medial-lateral, left-right, and radial. The model parameters were fit to our patient cohort with the endpoint of severe radiation pneumonitis. The spatial dose model was compared against a conventional dose-volume model to determine whether adding a spatial component improved the fit of the model. Results: Of the 547 patients analyzed, 111 (20.3%) experienced severe radiation pneumonitis. Adding in a spatial parameter did not significantly increase the accuracy of the model for any of the weighting schemes. Conclusions: A novel method was developed to investigate the relationship between the location of the deposited lung dose and pneumonitis rate. The method was applied to a patient database, and we found that for our patient cohort, the spatial location does not influence the risk of pneumonitis.
机译:目的:研究表明,接受肺根部放射治疗的患者比接受肺根尖治疗的患者更易患放射性肺炎。本研究的主要目的是开发一种将肺剂量空间信息纳入预测性放射性肺炎模型的新方法。第二个目标是将该方法应用于547位肺癌患者数据库,以确定是否包括空间信息可以改善我们模型的拟合度。方法和材料:将每个患者的三维剂量分布映射到一个公共坐标系上。坐标系的边界由每个患者肺的极端点定义。一旦将所有剂量分布映射到公共坐标系上,就将空间信息合并到Lyman-Kutcher-Burman预测性放射性肺炎模型中。具体而言,使用用户定义的空间权重矩阵对肺部剂量体素进行加权。我们研究了空间权重矩阵,该矩阵根据以下方向线性缩放每个剂量的体素:上下,前后,内侧,左右和径向。模型参数符合我们的严重队列放射性肺炎患者队列。将空间剂量模型与常规剂量-体积模型进行比较,以确定添加空间分量是否可以改善模型的拟合度。结果:在分析的547例患者中,有111例(20.3%)经历了严重的放射性肺炎。对于任何加权方案,添加空间参数都不会显着提高模型的准确性。结论:开发了一种新的方法来研究肺沉积剂量的位置与肺炎发生率之间的关系。该方法已应用于患者数据库,我们发现对于我们的患者队列,空间位置不会影响肺炎的风险。

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