TY  - JOUR
AU  - Sevilla, Andrés C
AU  - Cabal, Gonzalo
AU  - Wahl, Niklas
AU  - Puerta, María E
AU  - Rivera, Juan C
TI  - A robust optimization model for intensity-modulated radiotherapy: Cheap-Minimax.
JO  - Medical physics
VL  - 52
IS  - 5
SN  - 0094-2405
CY  - Hoboken, NJ
PB  - Wiley
M1  - DKFZ-2025-00451
SP  - 3360-3376
PY  - 2025
N1  - Volume 52, Issue 5 p. 3360-3376
AB  - Over the past three decades, the intensity-modulated radiotherapy (IMRT) has become a standard technique, enabling highly conformal dose distributions tailored to specific clinical objectives. Despite these advancements, IMRT treatment plans are significantly susceptible to uncertainties during both the planning and delivery phases. The most commonly used strategy to address these uncertainties is the margin-based or planning target volume (PTV) approach, which relies on the so-called dose cloud approximation. However, the PTV concept has notable limitations, particularly in complex scenarios where target volumes are superficial or located near critical structures. In contrast, the advent of intensity-modulated particle therapy has driven the development of robust optimization models, which have emerged as a promising alternative for managing uncertainties. Among these, the worst-case scenario or minimax strategy is the most widely employed. While minimax can be directly applied to photon treatments, its use in IMRT often leads to overly conservative plans or plans that are very similar to those obtained using the conventional margin-based PTV approach.In this work, we present a robust optimization model particularly suitable for photon treatments. The new approach, called Cheap-Minimax, is a generalization of the minimax strategy used for particle therapy and aims to improve the balance between plan robustness and the price of robustness in terms of dose to organs at risk (OARs), an issue particularly pronounced in photon treatments.The c-minimax model was implemented in the MatRad treatment planning system, developed at the German Cancer Research Center (DKFZ). It was applied to 20 clinical cases, comprising 5 prostate cancer cases and 15 breast cancer cases. The results were compared with those obtained using the conventional minimax model and the PTV-based approach.For prostate cancer cases, the c-minimax model maintained a robustness comparable to the PTV approach, while achieving a 20
KW  - IMRT (Other)
KW  - robust optimization (Other)
KW  - uncertainty (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:40012139
DO  - DOI:DOI:10.1002/mp.17709
UR  - https://inrepo02.dkfz.de/record/299491
ER  -