Literature DB >> 10701504

Tumour control probability: a formulation applicable to any temporal protocol of dose delivery.

M Zaider1, G N Minerbo.   

Abstract

An analytic expression for the tumour control probability (TCP), valid for any temporal distribution of dose, is discussed. The TCP model, derived using the theory of birth-and-death stochastic processes, generalizes several results previously obtained. The TCP equation is [equation: see text] where S(t) is the survival probability at time t of the n clonogenic tumour cells initially present (at t = 0), and b and d are, respectively, the birth and death rates of these cells. Equivalently, b = 0.693/Tpot and d/b is the cell loss factor of the tumour. In this expression t refers to any time during or after the treatment; typically, one would take for t the end of the treatment period or the expected remaining life span of the patient. This model, which provides a comprehensive framework for predicting TCP, can be used predictively, or--when clinical data are available for one particular treatment modality (e.g. fractionated radiotherapy)--to obtain TCP-equivalent regimens for other modalities (e.g. low dose-rate treatments).

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Year:  2000        PMID: 10701504     DOI: 10.1088/0031-9155/45/2/303

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  31 in total

1.  The use of TCP based EUD to rank and compare lung radiotherapy plans: in-silico study to evaluate the correlation between TCP with physical quality indices.

Authors:  Abdulhamid Chaikh; Jacques Balosso
Journal:  Transl Lung Cancer Res       Date:  2017-06

Review 2.  Linear quadratic and tumour control probability modelling in external beam radiotherapy.

Authors:  S F C O'Rourke; H McAneney; T Hillen
Journal:  J Math Biol       Date:  2008-09-30       Impact factor: 2.259

3.  A note on modeling of tumor regression for estimation of radiobiological parameters.

Authors:  Hualiang Zhong; Indrin Chetty
Journal:  Med Phys       Date:  2014-08       Impact factor: 4.071

4.  Assessing the shift of radiobiological metrics in lung radiotherapy plans using 2D gamma index.

Authors:  Abdulhamid Chaikh; Jacques Balosso
Journal:  Transl Lung Cancer Res       Date:  2016-06

5.  AAPM recommendations on dose prescription and reporting methods for permanent interstitial brachytherapy for prostate cancer: report of Task Group 137.

Authors:  Ravinder Nath; William S Bice; Wayne M Butler; Zhe Chen; Ali S Meigooni; Vrinda Narayana; Mark J Rivard; Yan Yu
Journal:  Med Phys       Date:  2009-11       Impact factor: 4.071

6.  Beyond the margin recipe: the probability of correct target dosage and tumor control in the presence of a dose limiting structure.

Authors:  Marnix G Witte; Jan-Jakob Sonke; Jeffrey Siebers; Joseph O Deasy; Marcel van Herk
Journal:  Phys Med Biol       Date:  2017-09-20       Impact factor: 3.609

7.  Radiobiologically guided optimisation of the prescription dose and fractionation scheme in radiotherapy using BioSuite.

Authors:  J Uzan; A E Nahum
Journal:  Br J Radiol       Date:  2012-03-28       Impact factor: 3.039

8.  Glioblastoma Recurrence and the Role of O6-Methylguanine-DNA Methyltransferase Promoter Methylation.

Authors:  Katie Storey; Kevin Leder; Andrea Hawkins-Daarud; Kristin Swanson; Atique U Ahmed; Russell C Rockne; Jasmine Foo
Journal:  JCO Clin Cancer Inform       Date:  2019-02

9.  Datamining approaches for modeling tumor control probability.

Authors:  Issam El Naqa; Joseph O Deasy; Yi Mu; Ellen Huang; Andrew J Hope; Patricia E Lindsay; Aditya Apte; James Alaly; Jeffrey D Bradley
Journal:  Acta Oncol       Date:  2010-03-02       Impact factor: 4.089

10.  Second cancers after fractionated radiotherapy: stochastic population dynamics effects.

Authors:  Rainer K Sachs; Igor Shuryak; David Brenner; Hatim Fakir; Lynn Hlatky; Philip Hahnfeldt
Journal:  J Theor Biol       Date:  2007-08-12       Impact factor: 2.691

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