title: The biologic relevance of daily dose variations in adaptive treatment planning.
abstract: OBJECTIVE
  To explore the biologic relevance of deviations from the intended uniform fractionation scheme.
  
  
  METHODS
  We study the effect of the variance of the dose per fraction on the normalized total dose (NTD), which incorporates the linear-quadratic model of radiation effects. In regions of steep dose gradients, we determine the shift between NTD isodose lines and physical isodose lines. We also look at ways to compensate for dose-variation effects through dose adjustments, without changing the number of fractions.
  
  
  RESULTS
  Simple equations quantify effects of dose variation on the NTD. If the standard deviation of the dose is 10% of the daily dose fraction, the effects on the NTD for a given point in the irradiated area are always less than 1%, independent of the biologic parameters. In adaptive dose-correction schemes, the dose correction should be applied uniformly over the remaining fractions, to minimize the variance. Incomplete repair leads to a coupling of doses delivered on different days, which complicates the issue. Repopulation appears to be insignificant in the context of this study (constant overall treatment time).
  
  
  CONCLUSIONS
  A variation of the dose between fractions always leads to a larger biologic effect than does the same total dose delivered with standard uniform fractionation. The increase in NTD is negligible if the standard deviation of the dose is less than 10% of the dose per fraction.
authors.affiliation: Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. tbortfeld@partners.org
authors.forename: Thomas
authors.initials: T
authors.lastname: Bortfeld
authors.forename: Harald
authors.initials: H
authors.lastname: Paganetti
mesh_terms: D000465:Algorithms; D019583:Dose Fractionation, Radiation; D016014:Linear Models; D050397:Radiotherapy, Intensity-Modulated; D012062:Relative Biological Effectiveness; D013997:Time Factors