Assessing population‐based to personalized planning strategies for head and neck adaptive radiotherapy
Simply entering population, automatic KBP-enabled or AI-generated planning goals into the new Ethos2.0 TPS produced dosimetrically compliant plans, with AI-guided goals demonstrating the most OAR sparing. Several of these approaches are easy to translate to other treatment sites and will help lower the barrier to entry for x-ray-based online-ART.
Authors
- Andrew Godley (ORCID: https://orcid.org/0000-0002-8896-5231)
- Dominic H. Moon (ORCID: https://orcid.org/0000-0001-9161-7783)
- David J. Sher (ORCID: https://orcid.org/0000-0003-3943-7480)
- Mu‐Han Lin (ORCID: https://orcid.org/0000-0002-7992-5465)
- Steve Jiang (ORCID: https://orcid.org/0000-0002-3083-6752)
- Xinran Zhong (ORCID: https://orcid.org/0000-0002-2530-5228)
- Sean Domal (ORCID: https://orcid.org/0000-0002-5988-5240)
- Biling Wang (ORCID: https://orcid.org/0000-0002-6894-8645)
- David Parsons (ORCID: https://orcid.org/0000-0002-4466-0647)
- Weiguo Lu (ORCID: https://orcid.org/0000-0003-3036-7287)
- Justin Visak
- Austen Maniscalco (ORCID: https://orcid.org/0000-0001-7156-3239)
- Hui‐Ju Wang (ORCID: https://orcid.org/0000-0002-3816-8664)
- Chien‐Yi Liao
- Arnold Pompoš
- Dan Nyguen
Institutions
- The University of Texas Southwestern Medical Center (US)
Publication Details
- Journal
- Journal of Applied Clinical Medical Physics
- Published
- 2024-12-03
- DOI
- https://doi.org/10.1002/acm2.14576
- Citations
- 1
- Primary Topic
- Advanced Radiotherapy Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.61
Funders
- Varian Medical Systems
- National Institutes of Health