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

Abstract

ABSTRACT. The aim of this study was to display malignant induction probability (MIP) maps alongside dose distribution maps for radiotherapy using X-ray and charged particles such as protons. Dose distributions for X-rays and protons are used in an interactive MATLABH program (MathWorks, Natick, MA). The MIP is calculated using a published linear quadratic model, which incorporates fractionation effects, cell killing and cancer induction as a function of dose, as well as relative biological effect. Two virtual situations are modelled: (a) a tumour placed centrally in a cubic volume of normal tissue and (b) the same tumour placed closer to the skin surface. The MIP is calculated for a variety of treatment field options. The results show that, for protons, the MIP increases with field numbers. In such cases, proton MIP can be higher than that for X-rays. Protons produce the lowest MIPs for superficial targets because of the lack of exit dose. The addition of a dose bath to all normal tissues increases the MIP by up to an order of magnitude. This exploratory study shows that it is possible to achieve threedimensional displays of carcinogenesis risk. The importance of treatment geometry, including the length and volume of tissue traversed by each beam, can all influence MIP. Reducing the volume of tissue irradiated is advantageous, as reducing the number of cells at risk reduces the total MIP. This finding lends further support to the use of treatment gantries as well as the use of simpler field arrangements for particle therapy provided normal tissue tolerances are respected.

3D calculation of radiation‐induced second cancer risk including dose and tissue response heterogeneities

“…and are approximately an order of magnitude lower than the example value given bySachs and Brenner (Ref. 10) and an order of magnitude higher than values used in an earlier 2D geometric study (Ref 31…”

“…It is assumed that ϵ [Eq. (9)] is a patient-specific quantity and therefore cancels when comparing two given treatment plans on the same patient, 31 RelMIP ≈…”

Efficacy of dose escalation on TCP, recurrence and second cancer risks: a mathematical study

“…Mathematical framework for second cancer risks Several models have been developed in the literature to estimate radiation-induced second cancer risks, and some of them include, but are not limited to, Lindsay et al, 17 Sachs and Brenner, 18 Manem et al 19 and Timlin et al 20 Also, several types of risks (for instance, relative risk, absolute risk, life time risk) are used to estimate radiation-induced carcinogenic risk. In this work, we used excess relative risk (ERR) similar to the work by Sachs and Brenner.…”

Particle therapy

“…If the radiotherapy community is to play a full part in delivering the best quality of life for patients post-treatment, better prediction of the likely incidence of second cancers together with rational field placement might influence treatment strategies. Timlin et al [8] describe a possible methodology, and perform example comparison of simple X-ray and proton treatments for either superficial or deepseated target volumes. It is clear from these indicative examples that proton therapy does not always necessarily result in a reduced long-term risk of second malignancy compared with X-ray treatment.…”