title: Dose prescription and treatment planning based on FMISO-PET hypoxia.
abstract: OBJECTIVE
  The study presents the implementation of a novel method for incorporating hypoxia information from PET-CT imaging into treatment planning and estimates the efficiency of various optimization approaches. Its focuses on the feasibility of optimizing treatment plans based on the non-linear conversion of PET hypoxia images into radiosensitivity maps from the uptake properties of the tracers used.
  
  
  METHODS
  PET hypoxia images of seven head-and-neck cancer patients were used to determine optimal dose distributions needed to counteract the radiation resistance associated with tumor hypoxia assuming various scenarios regarding the evolution of the hypoxic compartment during the treatment. A research planning system for advanced studies has been used to optimize IMRT plans based on hypoxia information from patient PET images. These resulting plans were compared in terms of target coverage for the same fulfilled constraints regarding the organs at risk.
  
  
  RESULTS
  The results of a planning study indicated the clinical feasibility of the proposed method for treatment planning based on PET hypoxia. Antihypoxic strategies would lead to small improvements in all the patients, but higher effects are expected for the fraction of patients with hypoxic tumors. For these, individualization of the treatment based on hypoxia PET imaging could lead to improved treatment outcome while creating the premises for limiting the irradiation of the surrounding normal tissues.
  
  
  CONCLUSIONS
  The proposed approach offers the possibility of improved treatment results as it takes into consideration the heterogeneity and the dynamics of the hypoxic regions. It also provides early identification of the clinical cases that might benefit from dose escalation as well as the cases that could benefit from other counter-hypoxic measures.
authors.affiliation: Medical Radiation Physics, Stockholm University, Sweden. iuliana.livia.dasu@ki.se
authors.forename: Iuliana
authors.initials: I
authors.lastname: Toma-Dasu
authors.forename: Johan
authors.initials: J
authors.lastname: Uhrdin
authors.forename: Laura
authors.initials: L
authors.lastname: Antonovic
authors.forename: Alexandru
authors.initials: A
authors.lastname: Dasu
authors.forename: Sandra
authors.initials: S
authors.lastname: Nuyts
authors.forename: Piet
authors.initials: P
authors.lastname: Dirix
authors.forename: Karin
authors.initials: K
authors.lastname: Haustermans
authors.forename: Anders
authors.initials: A
authors.lastname: Brahme
mesh_terms: D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D015687:Cell Hypoxia; D005240:Feasibility Studies; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D006801:Humans; D008297:Male; D008875:Middle Aged; D064847:Multimodal Imaging / Q000379:methods*; D049268:Positron-Emission Tomography; D011446:Prospective Studies; D011829:Radiation Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed