title: Assessment of interpatient heterogeneity in tumor radiosensitivity for nonsmall cell lung cancer using tumor-volume variation data.
abstract: OBJECTIVE
  In our previous work, the authors showed that a distribution of cell surviving fractions S2 in a heterogeneous group of patients could be derived from tumor-volume variation curves during radiotherapy for head and neck cancer. In this research study, the authors show that this algorithm can be applied to other tumors, specifically in nonsmall cell lung cancer. This new application includes larger patient volumes and includes comparison of data sets obtained at independent institutions.
  
  
  METHODS
  Our analysis was based on two data sets of tumor-volume variation curves for heterogeneous groups of 17 patients treated for nonsmall cell lung cancer with conventional dose fractionation. The data sets were obtained previously at two independent institutions by using megavoltage computed tomography. Statistical distributions of cell surviving fractions S2 and clearance half-lives of lethally damaged cells T(1/2) have been reconstructed in each patient group by using a version of the two-level cell population model of tumor response and a simulated annealing algorithm. The reconstructed statistical distributions of the cell surviving fractions have been compared to the distributions measured using predictive assays in vitro.
  
  
  RESULTS
  Nonsmall cell lung cancer presents certain difficulties for modeling surviving fractions using tumor-volume variation curves because of relatively large fractional hypoxic volume, low gradient of tumor-volume response, and possible uncertainties due to breathing motion. Despite these difficulties, cell surviving fractions S2 for nonsmall cell lung cancer derived from tumor-volume variation measured at different institutions have similar probability density functions (PDFs) with mean values of 0.30 and 0.43 and standard deviations of 0.13 and 0.18, respectively. The PDFs for cell surviving fractions S2 reconstructed from tumor volume variation agree with the PDF measured in vitro.
  
  
  CONCLUSIONS
  The data obtained in this work, when taken together with the data obtained previously for head and neck cancer, suggests that the cell surviving fractions S2 can be reconstructed from the tumor volume variation curves measured during radiotherapy with conventional fractionation. The proposed method can be used for treatment evaluation and adaptation.
authors.affiliation: Department of Radiation Oncology, University of Washington, 1959 NE Pacific Street, Seattle, Washington 98195-6043.
authors.forename: Alexei V
authors.initials: AV
authors.lastname: Chvetsov
authors.affiliation: London Regional Cancer Program, London Health Sciences Centre, 790 Commissioners Road East, London, Ontario 46A 4L6, Canada.
authors.forename: Slav
authors.initials: S
authors.lastname: Yartsev
authors.affiliation: Department of Radiation Oncology, University of Washington, 1959 NE Pacific Street, Seattle, Washington 98195-6043.
authors.forename: Jeffrey L
authors.initials: JL
authors.lastname: Schwartz
authors.affiliation: Department of Radiation Oncology, University of Washington, 1959 NE Pacific Street, Seattle, Washington 98195-6043.
authors.forename: Nina
authors.initials: N
authors.lastname: Mayr
mesh_terms: D000465:Algorithms; D002289:Carcinoma, Non-Small-Cell Lung / Q000473:pathology / Q000503:physiopathology / Q000532:radiotherapy*; D002470:Cell Survival / Q000528:radiation effects; D003198:Computer Simulation; D019583:Dose Fractionation, Radiation; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D008175:Lung Neoplasms / Q000473:pathology / Q000503:physiopathology / Q000532:radiotherapy*; D008954:Models, Biological; D011836:Radiation Tolerance; D016019:Survival Analysis; D014054:Tomography; D047368:Tumor Burden