Impact of delineation errors on the estimated organ at risk dose and of dose errors on the normal tissue complication probability model

Background 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. Purpose 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. Methods 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. Results 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 a