On differences in radiosensitivity estimation: TCP experiments versus survival curves. A theoretical study

Phys Med Biol. 2015 Aug 7;60(15):N293-9. doi: 10.1088/0031-9155/60/15/N293. Epub 2015 Jul 28.

Abstract

We have compared two methods of estimating the cellular radiosensitivity of a heterogeneous tumour, namely, via cell-survival and via tumour control probability (TCP) pseudo-experiments. It is assumed that there exists intra-tumour variability in radiosensitivity and that the tumour consists predominantly of radiosensitive cells and a small number of radio-resistant cells.Using a multi-component, linear-quadratic (LQ) model of cell kill, a pseudo-experimental cell-survival versus dose curve is derived. This curve is then fitted with a mono-component LQ model describing the response of a homogeneous cell population. For the assumed variation in radiosensitivity it is shown that the composite pseudo-experimental survival curve is well approximated by the survival curve of cells with uniform radiosensitivity.For the same initial cell radiosensitivity distribution several pseudo-experimental TCP curves are simulated corresponding to different fractionation regimes. The TCP model used accounts for clonogen proliferation during a fractionated treatment. The set of simulated TCP curves is then fitted with a mono-component TCP model. As in the cell survival experiment the fit with a mono-component model assuming uniform radiosensitivity is shown to be highly acceptable.However, the best-fit values of cellular radiosensitivity produced via the two methods are very different. The cell-survival pseudo-experiment yields a high radiosensitivity value, while the TCP pseudo-experiment shows that the dose-response is dominated by the most resistant sub-population in the tumour, even when this is just a small fraction of the total.

MeSH terms

  • Cell Survival / radiation effects
  • Dose Fractionation, Radiation
  • Humans
  • Linear Models
  • Models, Biological*
  • Models, Theoretical*
  • Neoplasms / pathology*
  • Neoplasms / radiotherapy*
  • Radiation Tolerance*