Causal Machine Learning Analysis of Empirical Relative Biological Effectiveness (RBE) for Mandible Osteoradionecrosis in Head and Neck Cancer Radiotherapy.
This study presents a novel application of causal machine learning to evaluate mandible ORN in radiotherapy, identifying DVCs linked to the strongest causal effects and deriving empirical RBEs from equivalent constraint dose analysis based on the tolerance curve. The results indicate that proton RBE may significantly exceed 1.1 in the moderate dose range (40-60 Gy[RBE=1.1]), underscoring the importance of incorporating the variable RBE into PBSPT treatment planning to mitigate the risk of ORN.
Authors
- Lei Zeng (ORCID: https://orcid.org/0000-0001-6517-8772)
- Olivia M. Muller (ORCID: https://orcid.org/0000-0002-1685-329X)
- Samir H. Patel (ORCID: https://orcid.org/0000-0002-8251-574X)
- Johanna Daniel
- Robert L. Foote (ORCID: https://orcid.org/0000-0003-3470-6872)
- Jingyuan Chen (ORCID: https://orcid.org/0000-0002-5042-6179)
- Z.H. Liu (ORCID: https://orcid.org/0000-0002-9199-6493)
- Wei Liu (ORCID: https://orcid.org/0000-0003-4789-362X)
- Tianming Liu (ORCID: https://orcid.org/0000-0003-2245-7231)
- Zhengliang Liu (ORCID: https://orcid.org/0000-0002-0648-5876)
- Yunze Yang
Institutions
- University of Georgia (US)
- WinnMed (US)
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- PubMed
- Published
- 2025-09-25
- Primary Topic
- Head and Neck Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00