title: Feasibility and robustness of dose painting by numbers in proton therapy with contour-driven plan optimization.
abstract: OBJECTIVE
  To prove the ability of protons to reproduce a dose gradient that matches a dose painting by numbers (DPBN) prescription in the presence of setup and range errors, by using contours and structure-based optimization in a commercial treatment planning system.
  
  
  METHODS
  For two patients with head and neck cancer, voxel-by-voxel prescription to the target volume (GTVPET) was calculated from (18)FDG-PET images and approximated with several discrete prescription subcontours. Treatments were planned with proton pencil beam scanning. In order to determine the optimal plan parameters to approach the DPBN prescription, the effects of the scanning pattern, number of fields, number of subcontours, and use of range shifter were separately tested on each patient. Different constant scanning grids (i.e., spot spacing = Δx = Δy = 3.5, 4, and 5 mm) and uniform energy layer separation [4 and 5 mm WED (water equivalent distance)] were analyzed versus a dynamic and automatic selection of the spots grid. The number of subcontours was increased from 3 to 11 while the number of beams was set to 3, 5, or 7. Conventional PTV-based and robust clinical target volumes (CTV)-based optimization strategies were considered and their robustness against range and setup errors assessed. Because of the nonuniform prescription, ensuring robustness for coverage of GTVPET inevitably leads to overdosing, which was compared for both optimization schemes.
  
  
  RESULTS
  The optimal number of subcontours ranged from 5 to 7 for both patients. All considered scanning grids achieved accurate dose painting (1% average difference between the prescribed and planned doses). PTV-based plans led to nonrobust target coverage while robust-optimized plans improved it considerably (differences between worst-case CTV dose and the clinical constraint was up to 3 Gy for PTV-based plans and did not exceed 1 Gy for robust CTV-based plans). Also, only 15% of the points in the GTVPET (worst case) were above 5% of DPBN prescription for robust-optimized plans, while they were more than 50% for PTV plans. Low dose to organs at risk (OARs) could be achieved for both PTV and robust-optimized plans.
  
  
  CONCLUSIONS
  DPBN in proton therapy is feasible with the use of a sufficient number subcontours, automatically generated scanning patterns, and no more than three beams are needed. Robust optimization ensured the required target coverage and minimal overdosing, while PTV-approach led to nonrobust plans with excessive overdose. Low dose to OARs can be achieved even in the presence of a high-dose escalation as in DPBN.
authors.affiliation: Center of Molecular Imaging, Radiotherapy and Oncology, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels B-1200, Belgium.
authors.forename: A M
authors.initials: AM
authors.lastname: Barragán
authors.affiliation: Center of Molecular Imaging, Radiotherapy and Oncology, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels B-1200, Belgium.
authors.forename: S
authors.initials: S
authors.lastname: Differding
authors.affiliation: Ion Beam Applications S.A., Louvain-la-Neuve 1348, Belgium.
authors.forename: G
authors.initials: G
authors.lastname: Janssens
authors.affiliation: Center of Molecular Imaging, Radiotherapy and Oncology, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels B-1200, Belgium.
authors.forename: J A
authors.initials: JA
authors.lastname: Lee
authors.affiliation: Center of Molecular Imaging, Radiotherapy and Oncology, Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels B-1200, Belgium.
authors.forename: E
authors.initials: E
authors.lastname: Sterpin
mesh_terms: D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging / Q000532:radiotherapy; D005240:Feasibility Studies; D019788:Fluorodeoxyglucose F18; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D006801:Humans; D058958:Organs at Risk; D009959:Oropharyngeal Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D010363:Pattern Recognition, Automated / Q000379:methods; D049268:Positron-Emission Tomography; D061766:Proton Therapy / Q000379:methods*; D011522:Protons; D011874:Radiometry; D019275:Radiopharmaceuticals; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D000077195:Squamous Cell Carcinoma of Head and Neck; D013997:Time Factors; D014057:Tomography, X-Ray Computed
chemical_list: D011522:Protons; D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18