## Tumour control probability modelling: Basic principles and applications in treatment planning.

Nahum, A. E., Sanchez-Nieto, B.
(2001)
*Tumour control probability modelling: Basic principles and applications in treatment planning.*
PHYSICA MEDICA, 17 (Supple).
pp. 13-23.
ISSN 1120-1797

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## Abstract

Tumour control probability modelling: Basic principles and applications in treatment planning. The endpoint of true clinical interest in radiotherapy is the probability of controlling the tumour (TCP); we want therefore to convert a dose distribution in the tumour to a TCP value. The basic relationship between absorbed dose and cell survival is known (the L-Q model), the endpoint is precisely quantifiable, and hence a mechanistic approach can be taken. The Nahum-Tait-Webb model is derived, with the explicit inclusion of the -betaD(2) term. The resulting Poisson- statistics based expression TCP = exp(-N-s) yields extremely steep TCP vs. D curves and thus inter-patient variation in a is added through the parameter sigma (alpha) For a non-uniform tumour dose, the (differential) DVH yields volumes V-o,V-l (and hence cell numbers No,i = rho (el)Vo,i) at total dose D-i (n fractions of d(i)) and thus N-s = Sigma N-o,N-i exp[-alphaD(i) - (1+(beta/alpha )d(i))]. Non-homogeneous dose distributions are analyzed and it is shown that TCP always decreases as a symmetrical dose distribution is broadened constant mean dose) but much less drastically as sigma (alpha) is increased. Further, the effective uniform dose is shown to be much closer to mean than to minimum dose for realistic tumour DVHs. The Delta TCP concept is introduced as a way of assessing the im act of the different 'cold' or 'hot' dose bins on the TCP, using, the parameters: alpha = 0.29 Gy(-1), sigma (alpha)=0.07 Gy(-1), alpha/beta =10 Gy and rho (c)=10(7) cells/cm(3) which were found to fit the Hanks' prostate local control data. The effect of a boost to part of the tumour is also analysed. TCP models can yield valuable insights into the consequences of non-uniform dose distributions, e.g. those produced by IMRT, brachytherapy and unsealed source therapy. However, several effects are not presently modelled, e.g. hypoxia. Finally the lack of clinical data specific to different tumours is emphasised; efforts to fit TCP models to clinical data tend to yield large uncertainties on the 'best' parameters.

Item Type: | Article |
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Authors (ICR Faculty only): | Nahum, Alan |

All Authors: | Nahum, A. E., Sanchez-Nieto, B. |

Uncontrolled Keywords: | radiotherapy; tumour control probability; L-Q model; dose- volume histograms PROSTATE-CANCER; RADIATION-THERAPY; DOSE DISTRIBUTIONS; TARGET VOLUME; CONFORMAL RADIOTHERAPY; LOCAL-CONTROL; RADIOSENSITIVITY; HETEROGENEITY; RADIORESISTANCE; IMPLEMENTATION |

Research teams: | Closed research groups > Other closed groups |

Depositing User: | EPrints Services |

Date Deposited: | 10 Aug 2007 20:35 |

Last Modified: | 18 Mar 2015 17:43 |

URI: | http://publications.icr.ac.uk/id/eprint/295 |

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