title: CT image biomarkers to improve patient-specific prediction of radiation-induced xerostomia and sticky saliva.
abstract: Current models for the prediction of late patient-rated moderate-to-severe xerostomia (XER12m) and sticky saliva (STIC12m) after radiotherapy are based on dose-volume parameters and baseline xerostomia (XERbase) or sticky saliva (STICbase) scores. The purpose is to improve prediction of XER12mand STIC12mwith patient-specific characteristics, based on CT image biomarkers (IBMs).
  
  
  
  Planning CT-scans and patient-rated outcome measures were prospectively collected for 249 head and neck cancer patients treated with definitive radiotherapy with or without systemic treatment. The potential IBMs represent geometric, CT intensity and textural characteristics of the parotid and submandibular glands. Lasso regularisation was used to create multivariable logistic regression models, which were internally validated by bootstrapping.
  
  
  
  The prediction of XER12mcould be improved significantly by adding the IBM "Short Run Emphasis" (SRE), which quantifies heterogeneity of parotid tissue, to a model with mean contra-lateral parotid gland dose and XERbase. For STIC12m, the IBM maximum CT intensity of the submandibular gland was selected in addition to STICbaseand mean dose to submandibular glands.
  
  
  
  Prediction of XER12mand STIC12mwas improved by including IBMs representing heterogeneity and density of the salivary glands, respectively. These IBMs could guide additional research to the patient-specific response of healthy tissue to radiation dose.
authors.affiliation: Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands. Electronic address: l.v.van.dijk@umcg.nl.
authors.forename: Lisanne V
authors.initials: LV
authors.lastname: van Dijk
authors.affiliation: Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands.
authors.forename: Charlotte L
authors.initials: CL
authors.lastname: Brouwer
authors.affiliation: Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands.
authors.forename: Arjen
authors.initials: A
authors.lastname: van der Schaaf
authors.affiliation: Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands.
authors.forename: Johannes G M
authors.initials: JGM
authors.lastname: Burgerhof
authors.affiliation: Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands.
authors.forename: Roelof J
authors.initials: RJ
authors.lastname: Beukinga
authors.affiliation: Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands.
authors.forename: Johannes A
authors.initials: JA
authors.lastname: Langendijk
authors.affiliation: Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands.
authors.forename: Nanna M
authors.initials: NM
authors.lastname: Sijtsema
authors.affiliation: Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, The Netherlands.
authors.forename: Roel J H M
authors.initials: RJHM
authors.lastname: Steenbakkers
mesh_terms: D000328:Adult; D000368:Aged; D015415:Biomarkers; D005260:Female; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012463:Saliva / Q000528:radiation effects*; D012469:Salivary Glands / Q000528:radiation effects; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014987:Xerostomia / Q000209:etiology*
chemical_list: D015415:Biomarkers
keywords: Head and neck; IMRT; Image biomarkers; NTCP; Sticky saliva; Xerostomia