59. Robust treatment planning in proton therapy
Invited abstract in session MD-12: Applications of optimisation under uncertainty, stream Applications: AI, uncertainty management and sustainability.
Monday, 16:30-18:30Room: B100/8009
Authors (first author is the speaker)
| 1. | Nicole Cristina Cassimiro de Oliveira
|
| Computational & Applied Mathematics, University of Campinas (UNICAMP) | |
| 2. | Aurelio Oliveira
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| Computational & Applied Mathematics, UNICAMP | |
| 3. | Juliana Campos de Freitas
|
| Maringa State University |
Abstract
Proton therapy is a precise cancer treatment technique, but uncertainties in the Bragg peak position can impact its effectiveness. This study focuses on mathematical optimization to enhance treatment robustness. A minimax-based model is proposed to minimize the maximum tumor dose while preserving critical organs. The model is validated with TROTS database cases, particularly in head and neck cancer, where structures like the oral cavity, larynx, and brainstem are highly sensitive to radiation. To address anatomical and positioning variations, a multi-objective optimization approach is introduced, incorporating goal programming. This strategy balances tumor coverage and organ-at-risk protection, resulting in more reliable treatment plans. The findings highlight the potential of mathematical models to improve proton therapy’s safety and effectiveness.
Keywords
- Multi-objective optimization
- Linear and nonlinear optimization
- Optimization under uncertainty
Status: accepted
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