title: Reoptimization of Intensity Modulated Proton Therapy Plans Based on Linear Energy Transfer.
abstract: We describe a treatment plan optimization method for intensity modulated proton therapy (IMPT) that avoids high values of linear energy transfer (LET) in critical structures located within or near the target volume while limiting degradation of the best possible physical dose distribution.
  
  
  
  To allow fast optimization based on dose and LET, a GPU-based Monte Carlo code was extended to provide dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dose objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of LET and physical dose (LET×D). To first approximation, LET×D represents a measure of the additional biological dose that is caused by high LET.
  
  
  
  The method is effective for treatments where serial critical structures with maximum dose constraints are located within or near the target. We report on 5 patients with intracranial tumors (high-grade meningiomas, base-of-skull chordomas, ependymomas) in whom the target volume overlaps with the brainstem and optic structures. In all cases, high LET×D in critical structures could be avoided while minimally compromising physical dose planning objectives.
  
  
  
  LET-based reoptimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose-based and relative biological effectiveness (RBE)-based planning. The method makes IMPT treatments safer by mitigating a potentially increased risk of side effects resulting from elevated RBE of proton beams near the end of range.
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts. Electronic address: junkelbach@mgh.harvard.edu.
authors.forename: Jan
authors.initials: J
authors.lastname: Unkelbach
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts; Faculty of Physics, Ruprecht-Karls-Universität Heidelberg, Heidelberg, Germany.
authors.forename: Pablo
authors.initials: P
authors.lastname: Botas
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Drosoula
authors.initials: D
authors.lastname: Giantsoudi
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Bram L
authors.initials: BL
authors.lastname: Gorissen
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts.
authors.forename: Harald
authors.initials: H
authors.lastname: Paganetti
mesh_terms: D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D001933:Brain Stem / Q000000981:diagnostic imaging; D002817:Chordoma / Q000000981:diagnostic imaging / Q000532:radiotherapy; D004806:Ependymoma / Q000000981:diagnostic imaging / Q000532:radiotherapy; D006801:Humans; D018499:Linear Energy Transfer; D008577:Meningeal Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D008579:Meningioma / Q000000981:diagnostic imaging / Q000532:radiotherapy; D009010:Monte Carlo Method; D009897:Optic Chiasm / Q000000981:diagnostic imaging; D009900:Optic Nerve / Q000000981:diagnostic imaging; D058958:Organs at Risk / Q000000981:diagnostic imaging; D061766:Proton Therapy / Q000379:methods*; D058996:Quality Improvement; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D012062:Relative Biological Effectiveness; D019292:Skull Base Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy