Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Fulham Road, London, SW3 6JJ, United Kingdom.
Gynaecology Unit, Royal Marsden NHS Foundation Trust, Fulham Road, London, SW3 6JJ, United Kingdom.
Phys Med Biol. 2021 Feb 25;66(5):055024. doi: 10.1088/1361-6560/abe029.
Target volume delineation uncertainty (DU) is arguably one of the largest geometric uncertainties in radiotherapy that are accounted for using planning target volume (PTV) margins. Geometrical uncertainties are typically derived from a limited sample of patients. Consequently, the resultant margins are not tailored to individual patients. Furthermore, standard PTVs cannot account for arbitrary anisotropic extensions of the target volume originating from DU. We address these limitations by developing a method to measure DU for each patient by a single clinician. This information is then used to produce PTVs that account for each patient's unique DU, including any required anisotropic component. We do so using a two-step uncertainty evaluation strategy that does not rely on multiple samples of data to capture the DU of a patient's gross tumour volume (GTV) or clinical target volume. For simplicity, we will just refer to the GTV in the following. First, the clinician delineates two contour sets; one which bounds all voxels believed to have a probability of belonging to the GTV of 1, while the second includes all voxels with a probability greater than 0. Next, one specifies a probability density function for the true GTV boundary position within the boundaries of the two contours. Finally, a patient-specific PTV, designed to account for all systematic errors, is created using this information along with measurements of the other systematic errors. Clinical examples indicate that our margin strategy can produce significantly smaller PTVs than the van Herk margin recipe. Our new radiotherapy target delineation concept allows DUs to be quantified by the clinician for each patient, leading to PTV margins that are tailored to each unique patient, thus paving the way to a greater personalisation of radiotherapy.
靶区勾画不确定性（DU）可被视为放疗中最大的几何不确定性之一，通过计划靶区（PTV）边界来考虑这种不确定性。几何不确定性通常是从有限数量的患者中得出的。因此，所得的边界并不针对个体患者。此外，标准 PTV 无法考虑源自 DU 的靶区任意各向异性扩展。我们通过开发一种由单一临床医生为每位患者测量 DU 的方法来解决这些限制。然后，将该信息用于生成考虑每位患者独特 DU 的 PTV，包括任何所需的各向异性分量。我们通过两步不确定性评估策略来实现这一点，该策略不依赖于多个数据样本来捕获患者大体肿瘤体积（GTV）或临床靶区的 DU。为简单起见，我们将在下文中仅将 GTV 作为参考。首先，临床医生勾画两个轮廓集；一个包含所有被认为属于 GTV 的概率为 1 的体素，另一个包含所有概率大于 0 的体素。接下来，指定一个在两个轮廓边界内的真实 GTV 边界位置的概率密度函数。最后，使用该信息以及对其他系统误差的测量值来创建专门用于考虑所有系统误差的患者特异性 PTV。临床示例表明，我们的边界策略可以产生比 van Herk 边界配方小得多的 PTV。我们的新放疗靶区勾画概念允许临床医生为每位患者量化 DU，从而生成针对每个独特患者量身定制的 PTV 边界，为放疗的个性化提供了途径。
