Stroom J C, de Boer H C, Huizenga H, Visser A G
University Hospital Rotterdam, Daniel den Hoed Cancer Center, Department of Clinical Physics, The Netherlands.
Int J Radiat Oncol Biol Phys. 1999 Mar 1;43(4):905-19. doi: 10.1016/s0360-3016(98)00468-4.
Following the ICRU-50 recommendations, geometrical uncertainties in tumor position during radiotherapy treatments are generally included in the treatment planning by adding a margin to the clinical target volume (CTV) to yield the planning target volume (PTV). We have developed a method for automatic calculation of this margin.
Geometrical uncertainties of a specific patient group can normally be characterized by the standard deviation of the distribution of systematic deviations in the patient group (Sigma) and by the average standard deviation of the distribution of random deviations (sigma). The CTV of a patient to be planned can be represented in a 3D matrix in the treatment room coordinate system with voxel values one inside and zero outside the CTV. Convolution of this matrix with the appropriate probability distributions for translations and rotations yields a matrix with coverage probabilities (CPs) which is defined as the probability for each point to be covered by the CTV. The PTV can then be chosen as a volume corresponding to a certain iso-probability level. Separate calculations are performed for systematic and random deviations. Iso-probability volumes are selected in such a way that a high percentage of the CTV volume (on average > 99%) receives a high dose (> 95%). The consequences of systematic deviations on the dose distribution in the CTV can be estimated by calculation of dose histograms of the CP matrix for systematic deviations, resulting in a so-called dose probability histogram (DPH). A DPH represents the average dose volume histogram (DVH) for all systematic deviations in the patient group. The consequences of random deviations can be calculated by convolution of the dose distribution with the probability distributions for random deviations. Using the convolved dose matrix in the DPH calculation yields full information about the influence of geometrical uncertainties on the dose in the CTV.
The model is demonstrated to be fast and accurate for a prostate, cervix, and lung cancer case. A CTV-to-PTV margin size which ensures at least 95% dose to (on average) 99% of the CTV, appears to be equal to about 2Sigma + 0.7sigma for three all cases. Because rotational deviations are included, the resulting margins can be anisotropic, as shown for the prostate cancer case.
A method has been developed for calculation of CTV-to-PTV margins based on the assumption that the CTV should be adequately irradiated with a high probability.
遵循国际辐射单位与测量委员会（ICRU）-50号建议，放射治疗期间肿瘤位置的几何不确定性通常通过在临床靶区（CTV）周围添加边界来纳入治疗计划，从而得出计划靶区（PTV）。我们开发了一种自动计算此边界的方法。
特定患者群体的几何不确定性通常可以通过该患者群体中系统偏差分布的标准差（Sigma）以及随机偏差分布的平均标准差（sigma）来表征。待计划患者的CTV可以在治疗室坐标系的三维矩阵中表示，CTV内部的体素值为1，外部为0。将此矩阵与平移和旋转的适当概率分布进行卷积，会得到一个具有覆盖概率（CP）的矩阵，该矩阵定义为每个点被CTV覆盖的概率。然后可以将PTV选择为对应于某个等概率水平的体积。对系统偏差和随机偏差分别进行计算。选择等概率体积的方式应使得CTV体积的很大一部分（平均>99%）接受高剂量（>95%）。通过计算系统偏差的CP矩阵的剂量直方图，可以估计系统偏差对CTV中剂量分布的影响，从而得到所谓的剂量概率直方图（DPH）。DPH表示患者群体中所有系统偏差的平均剂量体积直方图（DVH）。随机偏差的影响可以通过将剂量分布与随机偏差的概率分布进行卷积来计算。在DPH计算中使用卷积后的剂量矩阵可得出关于几何不确定性对CTV中剂量影响的完整信息。
该模型在前列腺癌、宫颈癌和肺癌病例中被证明快速且准确。对于所有三种情况，确保（平均）99%的CTV至少接受95%剂量的CTV到PTV边界大小似乎约等于2Sigma + 0.7sigma。由于包含了旋转偏差，所得边界可能是各向异性的，如前列腺癌病例所示。
基于CTV应以高概率得到充分照射的假设，开发了一种计算CTV到PTV边界的方法。
