Literature DB >> 19454805

Modelling carcinogenesis after radiotherapy using Poisson statistics: implications for IMRT, protons and ions.

Bleddyn Jones1.   

Abstract

Current technical radiotherapy advances aim to (a) better conform the dose contours to cancers and (b) reduce the integral dose exposure and thereby minimise unnecessary dose exposure to normal tissues unaffected by the cancer. Various types of conformal and intensity modulated radiotherapy (IMRT) using x-rays can achieve (a) while charged particle therapy (CPT)-using proton and ion beams-can achieve both (a) and (b), but at greater financial cost. Not only is the long term risk of radiation related normal tissue complications important, but so is the risk of carcinogenesis. Physical dose distribution plans can be generated to show the differences between the above techniques. IMRT is associated with a dose bath of low to medium dose due to fluence transfer: dose is effectively transferred from designated organs at risk to other areas; thus dose and risk are transferred. Many clinicians are concerned that there may be additional carcinogenesis many years after IMRT. CPT reduces the total energy deposition in the body and offers many potential advantages in terms of the prospects for better quality of life along with cancer cure. With C ions there is a tail of dose beyond the Bragg peaks, due to nuclear fragmentation; this is not found with protons. CPT generally uses higher linear energy transfer (which varies with particle and energy), which carries a higher relative risk of malignant induction, but also of cell death quantified by the relative biological effect concept, so at higher dose levels the frank development of malignancy should be reduced. Standard linear radioprotection models have been used to show a reduction in carcinogenesis risk of between two- and 15-fold depending on the CPT location. But the standard risk models make no allowance for fractionation and some have a dose limit at 4 Gy. Alternatively, tentative application of the linear quadratic model and Poissonian statistics to chromosome breakage and cell kill simultaneously allows estimation of relative changes in carcinogenesis that incorporate fractionation and relative biological effects (RBE). This alternative modelling approach allows absolute and relative risk estimations per cell and can be extended to tissues. The classical turnover point in carcinogenesis occurring after a single exposure is a feature of the model; also, the dose-response relationship becomes pseudo-linear with extended fractionation and when heterogeneity of the radiosensitivity parameters is introduced; there is also an inverse relationship between dose per fraction and cancer induction. In principle, this new approach might influence the conduct of proton and ion beam therapy, particularly beam placements and fractionation policies. The theoretical implications for future radiotherapy are considerable, but these predictions should be subjected to cellular and tissue experiments that simulate these forms of treatment, including any secondary neutron production in some cases depending on the beam delivery technique, e.g. in tissue equivalent humanoid phantoms using cell transformation techniques. Since the UK has no working high energy particle beam facility over 100 MeV, British scientists would require use of particle beam facilities in Europe, USA or Japan to perform experiments.

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Year:  2009        PMID: 19454805     DOI: 10.1088/0952-4746/29/2A/S10

Source DB:  PubMed          Journal:  J Radiol Prot        ISSN: 0952-4746            Impact factor:   1.394


  3 in total

1.  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

2.  The etiology of treatment-related lymphopenia in patients with malignant gliomas: modeling radiation dose to circulating lymphocytes explains clinical observations and suggests methods of modifying the impact of radiation on immune cells.

Authors:  Susannah Yovino; Lawrence Kleinberg; Stuart A Grossman; Manisha Narayanan; Eric Ford
Journal:  Cancer Invest       Date:  2013-02       Impact factor: 2.176

3.  Radiotherapy-induced malignancies: review of clinical features, pathobiology, and evolving approaches for mitigating risk.

Authors:  Steve Braunstein; Jean L Nakamura
Journal:  Front Oncol       Date:  2013-04-03       Impact factor: 6.244

  3 in total

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