Print Email Facebook Twitter Keeping your best options open with AI-based treatment planning in prostate and cervix brachytherapy Title Keeping your best options open with AI-based treatment planning in prostate and cervix brachytherapy Author Dickhoff, Leah R.M. (Leiden University Medical Center) Scholman, R.J. (TU Delft Algorithmics; Centrum Wiskunde & Informatica (CWI)) Barten, Danique L.J. (Amsterdam UMC) Kerkhof, Ellen M. (Leiden University Medical Center) Roorda, Jelmen J. (Amsterdam UMC) Velema, Laura A. (Leiden University Medical Center) Stalpers, Lukas J.A. (Amsterdam UMC; Cancer Center Amsterdam) Pieters, Bradley R. (Amsterdam UMC; Cancer Center Amsterdam) Bosman, P.A.N. (TU Delft Algorithmics; Centrum Wiskunde & Informatica (CWI)) Alderliesten, T. (Leiden University Medical Center) Date 2024 Abstract PURPOSE: Without a clear definition of an optimal treatment plan, no optimization model can be perfect. Therefore, instead of automatically finding a single “optimal” plan, finding multiple, yet different near-optimal plans, can be an insightful approach to support radiation oncologists in finding the plan they are looking for. METHODS AND MATERIALS: BRIGHT is a flexible AI-based optimization method for brachytherapy treatment planning that has already been shown capable of finding high-quality plans that trade-off target volume coverage and healthy tissue sparing. We leverage the flexibility of BRIGHT to find plans with similar dose-volume criteria, yet different dose distributions. We further describe extensions that facilitate fast plan adaptation should planning aims need to be adjusted, and straightforwardly allow incorporating hospital-specific aims besides standard protocols. RESULTS: Results are obtained for prostate (n = 12) and cervix brachytherapy (n = 36). We demonstrate the possible differences in dose distribution for optimized plans with equal dose-volume criteria. We furthermore demonstrate that adding hospital-specific aims enables adhering to hospital-specific practice while still being able to automatically create cervix plans that more often satisfy the EMBRACE-II protocol than clinical practice. Finally, we illustrate the feasibility of fast plan adaptation. CONCLUSIONS: Methods such as BRIGHT enable new ways to construct high-quality treatment plans for brachytherapy while offering new insights by making explicit the options one has. In particular, it becomes possible to present to radiation oncologists a manageable set of alternative plans that, from an optimization perspective are equally good, yet differ in terms of coverage-sparing trade-offs and shape of the dose distribution. Subject Automated treatment planningArtificial intelligenceMulti-objective optimizationCervical cancerProstate cancer To reference this document use: http://resolver.tudelft.nl/uuid:08e7746a-54b6-4f9a-a43a-2adfc50fbd51 DOI https://doi.org/10.1016/j.brachy.2023.10.005 ISSN 1538-4721 Source Brachytherapy, 23 (2), 188-198 Part of collection Institutional Repository Document type review Rights © 2024 Leah R.M. Dickhoff, R.J. Scholman, Danique L.J. Barten, Ellen M. Kerkhof, Jelmen J. Roorda, Laura A. Velema, Lukas J.A. Stalpers, Bradley R. Pieters, P.A.N. Bosman, T. Alderliesten Files PDF 1-s2.0-S1538472123016781-main.pdf 2.27 MB Close viewer /islandora/object/uuid:08e7746a-54b6-4f9a-a43a-2adfc50fbd51/datastream/OBJ/view