% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Bennan:169036,
      author       = {A. B. A. Bennan$^*$ and J. Unkelbach and N. Wahl$^*$ and P.
                      Salome$^*$ and M. Bangert$^*$},
      title        = {{J}oint optimization of photon - carbon ion treatments for
                      {G}lioblastoma.},
      journal      = {International journal of radiation oncology, biology,
                      physics},
      volume       = {111},
      number       = {2},
      issn         = {0360-3016},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {DKFZ-2021-01203},
      pages        = {559-572},
      year         = {2021},
      note         = {#EA:E040#LA:E040#/2021 Oct 1;111(2):559-572},
      abstract     = {Carbon ions are radiobiologically more effective than
                      photons and are beneficial for treating radioresistant gross
                      tumour volumes (GTV). However, due to a reduced
                      fractionation effect, they may be disadvantageous for
                      treating infiltrative tumours, where healthy tissue inside
                      the clinical target volume (CTV) must be protected through
                      fractionation. This work addresses the question: what is the
                      ideal combined photon-carbon ion fluence distribution for
                      treating infiltrative tumours given a specific fraction
                      allocation between photons and carbon ions?We present a
                      method to simultaneously optimize sequentially delivered
                      intensity modulated photon (IMRT) and carbon ion (CIRT)
                      treatments based on cumulative biological effect,
                      incorporating both the variable RBE of carbon ions and the
                      fractionation effect within the linear quadratic model. The
                      method is demonstrated for six Glioblastoma patients in
                      comparison to current clinical standard of independently
                      optimized CIRT - IMRT plans.Compared to the reference plan,
                      joint optimization strategies yield inhomogeneous photon and
                      carbon ion dose distributions that cumulatively deliver a
                      homogeneous biological effect distribution. In the optimal
                      distributions, the dose to CTV is mostly delivered by
                      photons while carbon ions are restricted to the GTV with
                      variations depending on tumour size and location.
                      Improvements in conformity of high dose regions are
                      reflected by a mean EQD2 reduction of 3.29 ± 1.22 Gy in a
                      dose fall-off margin around the CTV. Carbon ions may deliver
                      higher doses to the center of the GTV, while photon
                      contributions are increased at interfaces with CTV and
                      critical structures. This results in a mean EQD2 reduction
                      of 8.3 ± 2.28 Gy, where the brainstem abuts the target
                      volumes.We have developed a biophysical model to optimize
                      combined photon-carbon ion treatments. For six glioblastoma
                      patient cases, we show that our approach results in a more
                      targeted application of carbon ions that (1) reduces dose in
                      normal tissues within the target volume which can only be
                      protected through fractionation (2) boosts central target
                      volume regions in order to reduce integral dose. Joint
                      optimization of IMRT - CIRT treatments enable the
                      exploration of a new spectrum of plans that can better
                      address physical and radiobiological treatment planning
                      challenges.},
      cin          = {E040 / E050},
      ddc          = {610},
      cid          = {I:(DE-He78)E040-20160331 / I:(DE-He78)E050-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:34058258},
      doi          = {10.1016/j.ijrobp.2021.05.126},
      url          = {https://inrepo02.dkfz.de/record/169036},
}