title: Generation of prescriptions robust against geometric uncertainties in dose painting by numbers.
abstract: BACKGROUND
  In the context of dose painting by numbers delivered with intensity-modulated radiotherapy, the robustness of dose distributions against geometric uncertainties can be ensured by robust optimization. As robust optimization is seldom available in treatment planning systems (TPS), we propose an alternative method that reaches the same goal by modifying the heterogeneous dose prescription (based on (18)FDG-PET) and guarantees coverage in spite of systematic and random errors with known standard deviations Σ and σ, respectively.
  
  
  METHODS
  The objective was that 95% of all voxels in the GTVPET received at least 95% of the prescribed dose despite geometric errors. The prescription was modified by a geometric dilation of αΣ for systematic errors and a deconvolution by a Gaussian function of width σ for random errors. For a 90% confidence interval, α = 2.5. Planning was performed on a TomoTherapy system, such that 95% of the voxels received at least 95% of the modified prescription and less than 5% of the voxels received more than 105% of the modified prescription. The applicability of the method was illustrated for two head-and-neck tumors.
  
  
  RESULTS
  Systematic and random displacements larger than αΣ and σ degraded coverage. Down to 62.8% of the points received at least 95% of prescribed dose for the largest considered displacements (5 mm systematic translation and 3 mm standard deviation for random errors). When systematic and random displacements were smaller than αΣ and σ, no degradation of target coverage was observed.
  
  
  CONCLUSIONS
  The method led to treatment plans with target coverage robust against geometric uncertainties without the need to incorporate these in the optimizer of the TPS. The methodology was illustrated for head-and-neck cancer but can be potentially extended to all treatment sites.
authors.affiliation: Université catholique de Louvain, Center of Molecular Imaging, Radiotherapy and Oncology, Institut de Recherche Expérimentale et Clinique , Brussels , Belgium.
authors.forename: Edmond
authors.initials: E
authors.lastname: Sterpin
authors.forename: Sarah
authors.initials: S
authors.lastname: Differding
authors.forename: Guillaume
authors.initials: G
authors.lastname: Janssens
authors.forename: Xavier
authors.initials: X
authors.lastname: Geets
authors.forename: Vincent
authors.initials: V
authors.lastname: Grégoire
authors.forename: John A
authors.initials: JA
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging / Q000532:radiotherapy; D016001:Confidence Intervals; D019788:Fluorodeoxyglucose F18; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D006801:Humans; D009369:Neoplasms / Q000532:radiotherapy; D016011:Normal Distribution; D049268:Positron-Emission Tomography; D055656:Prescriptions; D019275:Radiopharmaceuticals; D011879:Radiotherapy Dosage; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D035501:Uncertainty
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18