Keeping your best options open with AI-based treatment planning in prostate and cervix brachytherapy
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:23 |
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| Enthalten in: |
Brachytherapy - 23(2024), 2 vom: 31. März, Seite 188-198 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Dickhoff, Leah R M [VerfasserIn] |
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| Links: |
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| Themen: |
Artificial intelligence |
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| Anmerkungen: |
Date Completed 25.03.2024 Date Revised 25.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.brachy.2023.10.005 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Automated treatment planning | |
| 650 | 4 | |a Cervical cancer | |
| 650 | 4 | |a Multi-objective optimization | |
| 650 | 4 | |a Prostate cancer | |
| 700 | 1 | |a Scholman, Renzo J |e verfasserin |4 aut | |
| 700 | 1 | |a Barten, Danique L J |e verfasserin |4 aut | |
| 700 | 1 | |a Kerkhof, Ellen M |e verfasserin |4 aut | |
| 700 | 1 | |a Roorda, Jelmen J |e verfasserin |4 aut | |
| 700 | 1 | |a Velema, Laura A |e verfasserin |4 aut | |
| 700 | 1 | |a Stalpers, Lukas J A |e verfasserin |4 aut | |
| 700 | 1 | |a Pieters, Bradley R |e verfasserin |4 aut | |
| 700 | 1 | |a Bosman, Peter A N |e verfasserin |4 aut | |
| 700 | 1 | |a Alderliesten, Tanja |e verfasserin |4 aut | |
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