ESTRO 36 Abstract Book

S865 ESTRO 36 _______________________________________________________________________________________________

larynx (6), paranasal sinus (4) and two unknown primary cases. Half of the cohort had been diagnosed with ORN of the mandible within a median follow-up time of 3.2 years (range 1.3-5.3) from the end of RT. The toxicity endpoint considered included ORN complication of any grading. The other 40 patients were control cases (no ORN observed) prospectively matched according to primary site and treatment option (PORT or primary RT and chemotherapy type). For given volume v j and dose d i levels, the numerical fraction in a cell of an ACI is composed of the number of patients (denominator) and the number of patients with ORN (numerator) that have a mandible percentage volume between v j and v j+1 exposed to a dose level between d i and d i+1 . Atlases were created for sub-sets of the entire cohort to investigate the effects of pre-RT surgery, chemotherapy, smoking or dental extractions. These risk factors were also tested with univariate statistical analysis. Dosimetric variables including d max and d mean were tested with ROC analysis. Results A dosimetric correlation with ORN incidence was observed in cases where treatment modality was primary RT (as opposed to post-operative RT). An increased ORN incidence was observed towards the large percentage volume and high doses region of the ACI, where a large percentage of the mandible volume had received doses of above 40Gy as well as smaller volume percentages receiving doses above 64Gy. A similar incidence pattern was observed for the ACI that included smoking patients only. The ACI for the sub-set of patients that had undergone dental extractions pre- or post-RT also showed a very similar incidence pattern; however, this sub-set included very few cases. Conclusion The ACI analysis carried out so far has shown a dose response in patients who received primary RT, patients who smoked at the time of diagnosis and patients who had dental extractions. The limited number of cases did not allow for any conclusive statistical significance of the logistic regression and ROC analysis results. This pilot study will be expanded to include cases from other centres to increase the cohort size. EP-1604 Ion induced complex DNA damage: In silico modelling of damage and repair using Geant4-DNA. J.W. Warmenhoven 1 , N.T. Henthorn 1 , M. Sotiropoulos 1 , R.I. Mackay 2 , K.J. Kirkby 1,3 , M.J. Merchant 1,3 1 University of Manchester, Division of Molecular and Clinical Cancer Sciences, Manchester, United Kingdom 2 The Christie NHS Foundation Trust, Christie Medical Physics and Engineering, Manchester, United Kingdom 3 The Christie NHS Foundation Trust, Manchester, United Kingdom Purpose or Objective This work uses Monte Carlo simulation to assess and understand the differences in biological response to various radiation qualities in the context of hadron therapy. The current clinical estimator for this is Relative Biological Effectiveness (RBE), offering a biological dose conversion between radiation qualities. A large variability in reported RBE measurements implies that this parameter does not give the full picture. This variability in RBE is a

major source of uncertainty in ion therapy treatment planning. Recently, LET based biological effect models have been proposed, however, among those reviewed there are uncertainties in the behaviour of key biological parameters. We approach the problem on a mechanistic level, linking nanoscale energy deposition to cellular repair. Material and Methods We present a stochastic model to predict ion induced DNA damage and subsequent repair. DNA damage patterns are predicted using nanodosimetric principles applied to track structure simulations within the Monte Carlo based Geant4-DNA toolkit. A section of detailed DNA geometry is irradiated to study specific DNA double strand break structures; building up a library of break models for a given radiation quality. These patterns are then fed into a modified Geant4-DNA simulation where the DNA double strand break ends are explicitly modelled within a simplified cell nucleus. Double strand break ends then progress along the predefined Non-Homologous End Joining repair pathway according to stochastic, time constant based state changes. This allows the prediction of differences in DNA repair for a range of radiation qualities. Results We show that break complexity and repair kinetics are dependent on the particle LET and particle type, with more complex breaks becoming more probable for higher LET (fig 1.). Our simulations predict a greater number of residual DSBs after 24h when higher LET particles are used (fig 2.), which is in good agreement with the literature. We also observe a difference in break complexity for protons and alpha particles at the same LET due to differences in radiation track structure.

Conclusion Monte Carlo track structure simulation coupled to a mechanistic DNA damage repair simulation is a useful tool for modelling biologically relevant endpoints to cellular radiation injury. We have modelled DSB damage and repair with respect to several beam delivery parameters. The complexity of the biological response caused by different ions of the same LET was found to differ due to the