title: Direct use of multivariable normal tissue complication probability models in treatment plan optimisation for individualised head and neck cancer radiotherapy produces clinically acceptable treatment plans.
abstract: OBJECTIVE
  Recently, clinically validated multivariable normal tissue complication probability models (NTCP) for head and neck cancer (HNC) patients have become available. We test the feasibility of using multivariable NTCP-models directly in the optimiser for inverse treatment planning of radiotherapy to improve the dose distributions and corresponding NTCP-estimates in HNC patients.
  
  
  METHODS
  For 10 HNC cases, intensity-modulated radiotherapy plans were optimised either using objective functions based on the 'generalised equivalent uniform dose' (OFgEUD) or based on multivariable NTCP-models (OFNTCP). NTCP-models for patient-rated xerostomia, physician-rated RTOG grade II-IV dysphagia, and various patient-rated aspects of swallowing dysfunction were incorporated. The NTCP-models included dose-volume parameters as well as clinical factors contributing to a personalised optimisation process. Both optimisation techniques were compared by means of 'pseudo Pareto fronts' (target dose conformity vs. the sum of the NTCPs).
  
  
  RESULTS
  Both optimisation techniques resulted in clinically realistic treatment plans with only small differences. For nine patients the sum-NTCP was lower for the OFNTCP optimised plans (on average 5.7% (95%CI 1.7-9.9%, p<0.006)). Furthermore, the OFNTCP provided the advantages of fewer unknown optimisation parameters and an intrinsic mechanism of individualisation.
  
  
  CONCLUSIONS
  Treatment plan optimisation using multivariable NTCP-models directly in the OF is feasible as has been demonstrated for HNC radiotherapy.
authors.affiliation: University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, The Netherlands. Electronic address: R.G.J.Kierkels@umcg.nl.
authors.forename: Roel G J
authors.initials: RG
authors.lastname: Kierkels
authors.affiliation: University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, The Netherlands.
authors.forename: Erik W
authors.initials: EW
authors.lastname: Korevaar
authors.affiliation: University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, The Netherlands.
authors.forename: Roel J H M
authors.initials: RJ
authors.lastname: Steenbakkers
authors.affiliation: Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
authors.forename: Tomas
authors.initials: T
authors.lastname: Janssen
authors.affiliation: University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, The Netherlands.
authors.forename: Aart A
authors.initials: AA
authors.lastname: van't Veld
authors.affiliation: University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, The Netherlands.
authors.forename: Johannes A
authors.initials: JA
authors.lastname: Langendijk
authors.affiliation: University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, The Netherlands; Radiotherapeutic Institute Friesland, Leeuwarden, The Netherlands.
authors.forename: Cornelis
authors.initials: C
authors.lastname: Schilstra
authors.affiliation: University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, The Netherlands.
authors.forename: Arjen
authors.initials: A
authors.lastname: van der Schaaf
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005240:Feasibility Studies; D005260:Female; D006258:Head and Neck Neoplasms / Q000532:radiotherapy*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011336:Probability; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods; D015203:Reproducibility of Results
keywords: Head and neck cancer; IMRT; Multivariable NTCP-models; Pareto fronts; Plan optimisation