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@ARTICLE{Sevilla:299491,
      author       = {A. C. Sevilla and G. Cabal and N. Wahl$^*$ and M. E. Puerta
                      and J. C. Rivera},
      title        = {{A} robust optimization model for intensity-modulated
                      radiotherapy: {C}heap-{M}inimax.},
      journal      = {Medical physics},
      volume       = {52},
      number       = {5},
      issn         = {0094-2405},
      address      = {Hoboken, NJ},
      publisher    = {Wiley},
      reportid     = {DKFZ-2025-00451},
      pages        = {3360-3376},
      year         = {2025},
      note         = {Volume 52, Issue 5 p. 3360-3376},
      abstract     = {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 $20\%$ reduction in V 40
                      Gy $V_{40 \, \text{Gy}}$ for the rectum and a 10\% reduction
                      in V 60 Gy $V_{60 \, \text{Gy}}$ for the bladder compared to
                      the minimax model. In breast cancer cases, the c-minimax
                      model improved robustness by 23.7\% relative to the PTV
                      approach and by 18.2\% compared to the minimax model.
                      Additionally, the c-minimax model reduced V 20 Gy $V_{20 \,
                      \text{Gy}}$ for the ipsilateral lung by 3.7\% and the mean
                      heart dose by 1.2 Gy (20\%) compared to minimax. Both the
                      c-minimax and minimax models reduced D 5 \% $D_{5\\%}$ skin
                      dose by 10.9 Gy (18.9\%) and 11.1 Gy (19.3\%), respectively,
                      compared to the PTV approach.The c-minimax model
                      successfully overcomes the limitations of the PTV approach
                      and the over-conservativeness of the minimax model,
                      demonstrating significant advantages in managing
                      uncertainties in complex cases, such as breast cancer. By
                      providing superior robustness compared to PTV and reducing
                      OAR doses relative to minimax, the model offers a flexible
                      and clinically feasible strategy to enhance treatment
                      quality. The marked reduction in high-dose regions
                      (hotspots) in superficial tissues and skin highlights its
                      potential to lower toxicity risks and improve patient
                      outcomes. These results provide quantitative evidence of the
                      practical benefits of robustness-compromise-oriented
                      approaches in IMRT.},
      keywords     = {IMRT (Other) / robust optimization (Other) / uncertainty
                      (Other)},
      cin          = {E040},
      ddc          = {610},
      cid          = {I:(DE-He78)E040-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40012139},
      doi          = {DOI:10.1002/mp.17709},
      url          = {https://inrepo02.dkfz.de/record/299491},
}