title: Cervical cancer regression measured using weekly magnetic resonance imaging during fractionated radiotherapy: radiobiologic modeling and correlation with tumor hypoxia.
abstract: OBJECTIVE
  To measure regression of cancer of the uterine cervix during external beam radiotherapy using magnetic resonance imaging, derive radiobiologic parameters from a mathematical model of tumor regression, and compare these parameters with the pretreatment measurements of tumor hypoxia.
  
  
  METHODS
  A total of 27 eligible patients undergoing external beam radiotherapy for cervical cancer underwent weekly magnetic resonance imaging scans. The tumor volume was assessed on each of these scans and the rate of regression plotted. A radiobiologic model was formulated to simulate the effect on tumor regression of the surviving proportion of cells after 2 Gy (SP(2)), the cell clearance constant (clearance of irreparably damaged cells from the tumor [T(c)]), and accelerated repopulation. Nonlinear regression analysis was used to fit the radiobiologic model to the magnetic resonance imaging-derived tumor volumes and to derive the estimates of SP(2) and T(c) for each patient. These were compared to the pretreatment hypoxia measurements.
  
  
  RESULTS
  The initial tumor volume was 8-209 cm(3). The relative reduction in volume during treatment was 0.02-0.79. The simulations using representative values of the independent biologic variables derived from published data showed SP(2) and T(c) to strongly influence the shape of the volume-response curves. Nonlinear regression analysis yielded a median SP(2) of 0.71 and median T(c) of 10 days. Tumors with a high SP(2) >0.71 were significantly more hypoxic at diagnosis (p = 0.02).
  
  
  CONCLUSIONS
  The results of our study have shown that cervical cancer regresses during external beam radiotherapy, although marked variability is present among patients and is influenced by underlying biologic processes, including cellular sensitivity to radiotherapy and proliferation. Better understanding of the biologic mechanisms might facilitate novel adaptive treatment strategies in future studies.
authors.affiliation: Radiation Medicine Program, Princess Margaret Hospital/Ontario Cancer Institute, University Health Network, Toronto, ON, Canada.
authors.forename: Karen
authors.initials: K
authors.lastname: Lim
authors.forename: Philip
authors.initials: P
authors.lastname: Chan
authors.forename: Robert
authors.initials: R
authors.lastname: Dinniwell
authors.forename: Anthony
authors.initials: A
authors.lastname: Fyles
authors.forename: Masoom
authors.initials: M
authors.lastname: Haider
authors.forename: Young-Bin
authors.initials: YB
authors.lastname: Cho
authors.forename: David
authors.initials: D
authors.lastname: Jaffray
authors.forename: Lee
authors.initials: L
authors.lastname: Manchul
authors.forename: Wilfred
authors.initials: W
authors.lastname: Levin
authors.forename: Richard P
authors.initials: RP
authors.lastname: Hill
authors.forename: Michael
authors.initials: M
authors.lastname: Milosevic
mesh_terms: D000230:Adenocarcinoma / Q000473:pathology / Q000503:physiopathology / Q000532:radiotherapy; D000328:Adult; D000368:Aged; D002294:Carcinoma, Squamous Cell / Q000473:pathology / Q000503:physiopathology / Q000532:radiotherapy; D015687:Cell Hypoxia; D002470:Cell Survival; D019583:Dose Fractionation, Radiation; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008279:Magnetic Resonance Imaging; D008875:Middle Aged; D008954:Models, Biological; D011836:Radiation Tolerance / Q000502:physiology; D011853:Radiobiology; D012044:Regression Analysis; D012062:Relative Biological Effectiveness; D012074:Remission Induction / Q000379:methods; D047368:Tumor Burden / Q000528:radiation effects*; D002583:Uterine Cervical Neoplasms / Q000473:pathology / Q000503:physiopathology / Q000532:radiotherapy*