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@ARTICLE{Borys:302266,
      author       = {D. Borys and J. Gajewski and T. Becher$^*$ and Y. Censor
                      and R. Kopec and M. Rydygier and A. Schiavi and T. Skóra
                      and A. Spaleniak and N. Wahl$^*$ and A. Wochnik and A.
                      Rucinski},
      title        = {{GPU}-accelerated {FRED}opt package for simultaneous dose
                      and {LET}dproton radiotherapy plan optimization via
                      superiorization methods.},
      journal      = {Physics in medicine and biology},
      volume       = {70},
      number       = {15},
      issn         = {0031-9155},
      address      = {Bristol},
      publisher    = {IOP Publ.},
      reportid     = {DKFZ-2025-01292},
      pages        = {155011},
      year         = {2025},
      note         = {70(15), 155011},
      abstract     = {This study presents FREDopt, a newly developed
                      GPU-accelerated open-source optimization software for
                      simultaneous proton dose and dose-averaged LET (LETd)
                      optimization in IMPT treatment planning. FREDopt was
                      implemented entirely in Python, leveraging CuPy for GPU
                      acceleration and incorporating fast Monte Carlo (MC)
                      simulations from the FRED code. The treatment plan
                      optimization workflow includes pre-optimization and
                      optimization, the latter equipped with a novel
                      superiorization of feasibility-seeking algorithms.
                      Feasibility-seeking requires finding a point that satisfies
                      prescribed constraints. Superiorization interlaces
                      computational perturbations into iterative
                      feasibility-seeking steps to steer them toward a superior
                      feasible point, replacing the need for costly full-fledged
                      constrained optimization. The method was validated on two
                      treatment plans of patients treated in a clinical proton
                      therapy center, with dose and LETd distributions compared
                      before and after reoptimization. Simultaneous dose and LETd
                      optimization using FREDopt led to a substantial reduction of
                      LETd and (dose)×(LETd) in organs at risk (OARs) while
                      preserving target dose conformity. Computational performance
                      evaluation showed execution times of 14-50 minutes,
                      depending on the algorithm and target volume
                      size-satisfactory for clinical and research applications
                      while enabling further development of the well-tested,
                      documented open-source software.},
      keywords     = {feasibility seeking (Other) / linear energy transfer (LET)
                      (Other) / proton therapy (Other) / radiation therapy (Other)
                      / superiorization (Other) / treatment plan optimization
                      (Other)},
      cin          = {E040},
      ddc          = {530},
      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:40562074},
      doi          = {10.1088/1361-6560/ade841},
      url          = {https://inrepo02.dkfz.de/record/302266},
}