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@ARTICLE{Fabiano:154707,
      author       = {S. Fabiano and M. Bangert$^*$ and M. Guckenberger and J.
                      Unkelbach},
      title        = {{A}ccounting for range uncertainties in the optimization of
                      combined proton-photon treatments via stochastic
                      optimization.},
      journal      = {International journal of radiation oncology, biology,
                      physics},
      volume       = {108},
      number       = {3},
      issn         = {0360-3016},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {DKFZ-2020-00965},
      pages        = {792-801},
      year         = {2020},
      note         = {2020 Nov 1;108(3):792-801},
      abstract     = {Proton treatment slots are still a limited resource.
                      Combined proton-photon treatments, in which most fractions
                      are delivered with photons and only a few with protons, may
                      represent a practical solution to optimize the allocation of
                      proton resources over the patient population. We demonstrate
                      how a limited number of proton fractions can be optimally
                      used in multi-modality treatments, also addressing the issue
                      of the robustness of combined treatments against proton
                      range uncertainties.Combined proton-photon treatments are
                      planned by simultaneously optimizing intensity-modulated
                      radiation therapy (IMRT) and proton therapy (IMPT) plans
                      while accounting for the fractionation effect through the
                      biologically effective dose (BED) model. The method is
                      investigated for different tumor sites (a spinal metastasis,
                      a sacral chordoma, and an atypical meningioma) in which
                      organs at risk (OARs) are located within or near the tumor.
                      Stochastic optimization is applied to mitigate range
                      uncertainties.In optimal combinations, proton and photon
                      fractions deliver similar doses to OARs overlaying the
                      target volume to protect these dose-limiting normal tissues
                      through fractionation. Meanwhile, parts of the tumor are
                      hypofractionated with protons. Thus, the total dose
                      delivered with photons is reduced compared to simple
                      combinations where each modality delivers the prescribed
                      dose per fraction to the target volume. The benefit of
                      optimal combinations persists when range errors are
                      accounted for via stochastic optimization.Limited proton
                      resources are optimally used in combined treatments if parts
                      of the tumor are hypofractionated with protons while
                      near-uniform fractionation is maintained in serial OARs.
                      Proton range uncertainties can be efficiently accounted for
                      through stochastic optimization and are not an obstacle for
                      clinical application.},
      cin          = {E040},
      ddc          = {610},
      cid          = {I:(DE-He78)E040-20160331},
      pnm          = {315 - Imaging and radiooncology (POF3-315)},
      pid          = {G:(DE-HGF)POF3-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32361008},
      doi          = {10.1016/j.ijrobp.2020.04.029},
      url          = {https://inrepo02.dkfz.de/record/154707},
}