Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Therapeutic Radiation Physics, Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden.
Med Phys. 2023 Mar;50(3):1879-1892. doi: 10.1002/mp.16235. Epub 2023 Feb 7.
Normal tissue complication probability (NTCP) models are often based on doses retrieved from delineated volumes. For retrospective dose-response studies focusing on organs that have not been delineated historically, automatic segmentation might be considered. However, automatic segmentation risks generating considerable delineation errors and knowledge regarding how these errors impact the estimated organ dose is important. Furthermore, organ-at-risk (OAR) dose uncertainties cannot be eliminated and might affect the resulting NTCP model. Therefore, it is also of interest to study how OAR dose errors impact the NTCP modeling results.
To investigate how random delineation errors of the proximal bronchial tree, heart, and esophagus impact the estimated OAR dose, and to investigate how random errors in the doses used for dose-response modeling affect the estimated NTCPs.
We investigated the impact of random delineation errors on the estimated OAR dose using the treatment plans of 39 patients treated with conventionally fractionated radiation therapy of non-small-cell lung cancer. Study-specific reference structures were defined by manually contouring the proximal bronchial tree, heart and esophagus. For each patient and organ, 120 reshaped structures were created by introducing random shifts and margins to the entire reference structure. The mean and near-maximum dose to the reference and reshaped structures were compared. In a separate investigation, the impact of random dose errors on the NTCP model was studied performing dose-response modeling with study sets containing treatment outcomes and OAR doses with and without introduced errors. Universal patient populations with defined population risks, dose-response relationships and distributions of OAR doses were used as ground truth. From such a universal population, we randomly sampled data sets consisting of OAR dose and treatment outcome into reference populations. Study sets of different sizes were created by repeatedly introducing errors to the OAR doses of each reference population. The NTCP models generated with dose errors were compared to the reference NTCP model of the corresponding reference population.
A total of 14 040 reshaped structures with random delineation errors were created. The delineation errors resulted in systematic mean dose errors of less than 1% of the prescribed dose (PD). Mean dose differences above 15% of PD and near-maximum doses differences above 25% of PD were observed for 211 and 457 reshaped structures, respectively. Introducing random errors to OAR doses used for dose-response modeling resulted in systematic underestimations of the median NTCP. For all investigated scenarios, the median differences in NTCP were within 0.1 percentage points (p.p.) when comparing different study sizes.
Introducing random delineation errors to the proximal bronchial tree, heart and esophagus resulted in mean dose and near-maximum dose differences above 15% and 25% of PD, respectively. We did not observe an association between the dose level and the magnitude of the dose errors. For the scenarios investigated in this study, introducing random errors to OAR doses used for dose-response modeling resulted in systematic underestimations of the median NTCP for reference risks higher than the universal population risk. The median NTCP underestimation was similar for different study sizes, all within 0.1 p.p.
正常组织并发症概率（NTCP）模型通常基于从勾画体积中提取的剂量。对于专注于历史上未勾画的器官的回顾性剂量反应研究，可能会考虑自动勾画。然而，自动勾画存在生成大量勾画误差的风险，了解这些误差如何影响估计的器官剂量非常重要。此外，危及器官（OAR）剂量不确定性无法消除，并且可能会影响最终的 NTCP 模型。因此，研究 OAR 剂量误差如何影响 NTCP 建模结果也很有意义。
研究近端支气管树、心脏和食管的随机勾画误差如何影响估计的 OAR 剂量，并研究剂量反应建模中使用的随机剂量误差如何影响估计的 NTCP。
我们通过对 39 例接受非小细胞肺癌常规分割放射治疗的患者的治疗计划，研究了随机勾画误差对估计的 OAR 剂量的影响。特定于研究的参考结构通过手动勾画近端支气管树、心脏和食管来定义。对于每个患者和器官，通过向整个参考结构引入随机移位和边界，创建了 120 个重新成形的结构。比较了参考和重新成形结构的平均剂量和近最大剂量。在另一个研究中，通过使用具有和不具有引入误差的研究集进行剂量反应建模，研究了随机剂量误差对 NTCP 模型的影响。使用具有定义的人群风险、剂量反应关系和 OAR 剂量分布的通用患者群体作为真实情况。从这样的通用人群中，我们随机抽取了由 OAR 剂量和治疗结果组成的数据集到参考人群中。通过对每个参考人群的 OAR 剂量反复引入误差，创建了不同大小的研究集。将具有剂量误差的 NTCP 模型与相应参考人群的参考 NTCP 模型进行比较。
共创建了 14040 个具有随机勾画误差的重新成形结构。勾画误差导致规定剂量（PD）的小于 1%的系统平均剂量误差。观察到平均剂量差异超过 PD 的 15%和近最大剂量差异超过 PD 的 25%的结构分别为 211 个和 457 个。在剂量反应建模中引入 OAR 剂量的随机误差会导致中位 NTCP 的系统低估。对于所有研究的情况，当比较不同的研究规模时，NTCP 的中值差异均在 0.1 个百分点（p.p.）以内。
向近端支气管树、心脏和食管引入随机勾画误差会导致平均剂量和近最大剂量分别超过 PD 的 15%和 25%。我们没有观察到剂量水平与剂量误差大小之间的关联。对于本研究中研究的情况，在剂量反应建模中引入 OAR 剂量的随机误差会导致参考风险高于通用人群风险的中位 NTCP 系统低估。不同研究规模的中位 NTCP 低估相似，均在 0.1 p.p.以内。
