Literature DB >> 11459732

Radiation carcinogenesis modelling for risk of treatment-related second tumours following radiotherapy.

K A Lindsay1, E G Wheldon, C Deehan, T E Wheldon.   

Abstract

Radiobiological modelling of the risk of radiation-induced tumours following high dose radiation implies a general form for the dose-response relationship. Generally, risk will rise with radiation dose at low doses, reach a maximum value and then decline with further increase in dose. The magnitude of risk and the dose at which this risk is maximum are strongly dependent on the kinetics of repopulation by surviving normal and mutant cells and on genetic factors likely to differ between tissues and between individuals. The most reliable way to reduce the risk of second tumours is to reduce radiation dose further at sites where the dose is already low. These sites are usually distant from the primary treatment volume. For illustrative purposes, we have compared the predicted relative risks of second tumours at "distant sites" for treatment plans giving similar dose distributions (dose volume histograms) at the primary site. We suggest that dose reduction to distant sites could be of significant benefit in reducing the risk of second tumours. Further improvement will require more detailed knowledge of the radiation sensitivities and mutagenicities, together with the repopulation kinetics of the various cell lineages within the treatment volume.

Entities:  

Mesh:

Year:  2001        PMID: 11459732     DOI: 10.1259/bjr.74.882.740529

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  22 in total

1.  A new view of radiation-induced cancer.

Authors:  I Shuryak; R K Sachs; D J Brenner
Journal:  Radiat Prot Dosimetry       Date:  2010-11-27       Impact factor: 0.972

2.  The balance between initiation and promotion in radiation-induced murine carcinogenesis.

Authors:  Igor Shuryak; Robert L Ullrich; Rainer K Sachs; David J Brenner
Journal:  Radiat Res       Date:  2010-09       Impact factor: 2.841

3.  Solid tumor risks after high doses of ionizing radiation.

Authors:  Rainer K Sachs; David J Brenner
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-06       Impact factor: 11.205

4.  A new view of radiation-induced cancer: integrating short- and long-term processes. Part II: second cancer risk estimation.

Authors:  Igor Shuryak; Philip Hahnfeldt; Lynn Hlatky; Rainer K Sachs; David J Brenner
Journal:  Radiat Environ Biophys       Date:  2009-06-05       Impact factor: 1.925

Review 5.  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

6.  Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses.

Authors:  J Nguyen; M Moteabbed; H Paganetti
Journal:  Med Phys       Date:  2015-01       Impact factor: 4.071

7.  Malignant induction probability maps for radiotherapy using X-ray and proton beams.

Authors:  C Timlin; M Houston; B Jones
Journal:  Br J Radiol       Date:  2011-12       Impact factor: 3.039

8.  Repopulation of interacting tumor cells during fractionated radiotherapy: stochastic modeling of the tumor control probability.

Authors:  Hatim Fakir; Lynn Hlatky; Huamin Li; Rainer Sachs
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

9.  Risk-optimized proton therapy to minimize radiogenic second cancers.

Authors:  Laura A Rechner; John G Eley; Rebecca M Howell; Rui Zhang; Dragan Mirkovic; Wayne D Newhauser
Journal:  Phys Med Biol       Date:  2015-04-28       Impact factor: 3.609

10.  Cancer risk estimates from the combined Japanese A-bomb and Hodgkin cohorts for doses relevant to radiotherapy.

Authors:  Uwe Schneider; Linda Walsh
Journal:  Radiat Environ Biophys       Date:  2007-12-21       Impact factor: 1.925

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.