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A Clinician's discrimination between radiation therapy treatment plans is traditionally a subjective process, based on experience and existing protocols. A more objective and quantitative approach to distinguish between treatment plans is to use radiobiological or dosimetric objective functions, based on radiobiological or dosimetric models. The efficacy of models is not well understood, nor is the correlation of the rank of plans resulting from the use of models compared to the traditional subjective approach. One such radiobiological model is the Normal Tissue Complication Probability (NTCP). Dosimetric models or indicators are more accepted in clinical practice. In this study, three radiobiological models, Lyman NTCP, critical volume NTCP and relative seriality NTCP, and three dosimetric models, Mean Lung Dose (MLD) and the Lung volumes irradiated at 10Gy (V10) and 20Gy (V20), were used to rank a series of treatment plans using, harm to normal (Lung) tissue as the objective criterion. None of the models considered in this study showed consistent correlation with the Radiation Oncologists plan ranking. If radiobiological or dosimetric models are to be used in objective functions for lung treatments, based on this study it is recommended that the Lyman NTCP model be used because it will provide most consistency with traditional clinician ranking.

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IntroductionTime‐consuming manual methods have been required to register cone‐beam computed tomography (CBCT) images with plans in the Pinnacle3 treatment planning system in order to replicate delivered treatments for adaptive radiotherapy. These methods rely on fiducial marker (FM) placement during CBCT acquisition or the image mid‐point to localise the image isocentre. A quality assurance study was conducted to validate an automated CBCT‐plan registration method utilising the Digital Imaging and Communications in Medicine (DICOM) Structure Set (RS) and Spatial Registration (RE) files created during online image‐guided radiotherapy (IGRT).Methods CBCTs of a phantom were acquired with FMs and predetermined setup errors using various online IGRT workflows. The CBCTs, DICOM RS and RE files were imported into Pinnacle3 plans of the phantom and the resulting automated CBCT‐plan registrations were compared to existing manual methods. A clinical protocol for the automated method was subsequently developed and tested retrospectively using CBCTs and plans for six bladder patients.ResultsThe automated CBCT‐plan registration method was successfully applied to thirty‐four phantom CBCT images acquired with an online 0 mm action level workflow. Ten CBCTs acquired with other IGRT workflows required manual workarounds. This was addressed during the development and testing of the clinical protocol using twenty‐eight patient CBCTs. The automated CBCT‐plan registrations were instantaneous, replicating delivered treatments in Pinnacle3 with errors of ±0.5 mm. These errors were comparable to mid‐point‐dependant manual registrations but superior to FM‐dependant manual registrations.ConclusionThe automated CBCT‐plan registration method quickly and reliably replicates delivered treatments in Pinnacle3 for adaptive radiotherapy.