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@ARTICLE{Liu:265116,
      author       = {R. Liu and S. Charyyev and N. Wahl$^*$ and W. Liu and M.
                      Kang and J. Zhou and X. Yang and F. Baltazar$^*$ and M.
                      Palkowitsch$^*$ and K. Higgins and W. Dynan and J. Bradley
                      and L. Lin},
      title        = {{A}n {I}ntegrated {P}hysical {O}ptimization framework for
                      proton {SBRT} {FLASH} treatment planning allows dose, dose
                      rate, and {LET} optimization using patient-specific ridge
                      filters.},
      journal      = {International journal of radiation oncology, biology,
                      physics},
      volume       = {116},
      number       = {4},
      issn         = {0360-3016},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {DKFZ-2023-00278},
      pages        = {949-959},
      year         = {2023},
      note         = {2023 Jul 15;116(4):949-959},
      abstract     = {Patient-specific ridge filters provide a passive means to
                      modulate proton energy to obtain a conformal dose. Here we
                      describe a new framework for optimization of filter design
                      and spot maps to meet the unique demands of ultra-high dose
                      rate (FLASH) radiotherapy. We demonstrate an Integrated
                      Physical Optimization IMPT (IPO-IMPT) approach for
                      optimization of dose, dose-averaged dose rate (DADR), and
                      dose-averaged LET (LETd).We developed an inverse planning
                      software to design patient-specific ridge filters that
                      spread the Bragg peak from a fixed-energy, 250 MeV beam to a
                      proximal beam-specific planning target volume (BSPTV). The
                      software defines patient-specific ridge filter pin shapes
                      and uses a Monte Carlo calculation engine, based on Geant4,
                      to provide dose and LET influence matrices. Plan
                      optimization, using matRAD, accommodates the IPO-IMPT
                      objective function considering dose, dose rate, and LET
                      simultaneously with minimum MU constraints. The framework
                      enables design of both regularly spaced and sparse-optimized
                      ridge filters, from which some pins are omitted to allow
                      faster delivery and selective LET optimization. To
                      demonstrate the framework, we designed ridge filters for
                      three example lung cancer patients and optimized the plans
                      using IPO-IMPT.The IPO-IMPT framework selectively spared the
                      OARs by reducing LET and increasing dose rate, relative to
                      IMPT planning. Sparse-optimized ridge filters were superior
                      to regularly spaced ridge filters in dose rate. Depending on
                      which parameter is prioritized, volume distributions and
                      histograms for dose, DADR, and LETd, using evaluation
                      structures specific to heart, lung and esophagus, show high
                      levels of FLASH dose rate coverage and/or reduced LETd,
                      while maintaining dose coverage within the BSPT.This
                      proof-of-concept study demonstrates the feasibility of using
                      an IPO-IMPT framework to accomplish proton FLASH
                      stereotactic body proton therapy, accounting for dose, DADR,
                      and LETd simultaneously.},
      keywords     = {FLASH (Other) / IMPT (Other) / LET (Other) /
                      Patient-specific ridge filter (Other) / SBPT (Other) / dose
                      rate (Other) / integrated physical optimization (Other) /
                      sparse optimized ridge filter (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:36736634},
      doi          = {10.1016/j.ijrobp.2023.01.048},
      url          = {https://inrepo02.dkfz.de/record/265116},
}