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Background and purpose: Since 2011, our center has been using a library-based Plan-of-the-Day (PotD) strategy for external beam radiotherapy of cervical cancer patients to reduce normal tissue dose while maintaining adequate target coverage. With the advent of fully online-adaptive techniques such as daily online-adaptive replanning, further dose reduction may be possible. However, it is unknown how this reduction relates to plan library approaches, and how the most recent PotD strategies relate to no adaptation. In this study we compare the performance of our current PotD strategy with non-adaptive and fully online-adaptive techniques in terms of target volume size and normal tissue sparing. Materials and methods: Treatment data of 376 patients treated with the PotD protocol between June 2011 and April 2020 were included. The size of the Planning Target Volumes (PTVs) was reconstructed for different strategies: full online adaptation, no adaptation, and the latest clinical version of the PotD protocol. Normal tissue sparing was estimated by the difference in margin volume to construct the PTV and the volume overlap of the PTV with bladder and rectum. Results: The current version of our PotD approach reduced the PTV margin volume by a median of 250 cm3 compared to no adaptation. Bladder-PTV overlap decreased from a median of 142 to 71 cm3, and from 39 to 16 cm3 for rectum-PTV. Fully online-adaptive approaches could further decrease the PTV volume by 144 cm3 using a 5 mm margin for residual errors. In this scenario, bladder-PTV overlap was reduced to 35 cm3 and rectum-PTV overlap to 11 cm3. Conclusion: The current version of the PotD protocol is an effective technique to improve normal tissue sparing compared to no adaptation. Further sparing can be achieved using fully online-adaptive techniques, but at the cost of a more

Background and purpose: Image-guided adaptive brachytherapy (IGABT) is a key component in the treatment of cervical cancer, but the nature of the clinical workflow makes it vulnerable to suboptimal plans, as the theoretical optimal plan depends heavily on organ configuration. Patient anatomy-based quality-assurance (QA) with overlap volume histograms (OVHs) is a promising tool to detect such suboptimal plans, and in this analysis its suitability as a multi-institutional clinical QA tool is investigated. Materials and methods: A total of 223 plans of 145 patients treated in accordance with the current state-of-the-art IGABT protocols from UMC Utrecht (UMCU) and Erasmus MC (EMC) were included. Machine-learning models were trained to predict dose D2cm3 to bladder, rectum, sigmoid and small bowel with the help of OVHs. For this strategy, points are sampled on the organs-at-risk (OARs), and the distances of the sampled points to the target are computed and combined in a histogram. Machine-learning models can then be trained to predict dose-volume histograms (DVHs) for unseen data. Single-center model robustness to needle use and applicator type and multi-center model translatability were investigated. Performance of models was assessed by the difference between planned (clinical) and predicted D2cm3 values. Results: Intra-validation of UMCU data demonstrated OVH model robustness to needle use and applicator type. The model trained on UMCU data was found to be robust within the same protocol on EMC data, for all investigated OARs. Mean squared error between planned and predicted D2cm3 values of OARs ranged between 0.13 and 0.40 Gy within the same protocol, indicating model translatability. For the former protocol cohort of Erasmus MC large deviations were found between the planned and predicted D2cm3 values, indicating plan deviation from protocol. Mean squared error for this cohort ranged from 0.84 to 4.71 Gy. Conclusion: OV