HCPBM [Heavy Charged Particles in Biology & Medicine] and ENLIGHT [European Network for Light Ions] meetings, Oropa (Italy), June 2005

Proton radiobiology and its clinical implications

Denser ionisation clustering and complex DNA damage in proton Bragg peaks far exceeds that seen with conventional X-rays. This results in more efficient cell sterilisation, quantified by the relative biological effectiveness (RBE). Currently, a 1.1 RBE is used to determine the clinical proton doses by dividing the usual X-rays dose by this amount. This number, derived from short-term experiments, has been criticised as being irrelevant to late normal tissue (NT) effects following radiotherapy and included many control irradiations using lower voltage X-rays (with elevated RBE values) than those used in the clinic. In principle, an increased RBE could be used for each organ at risk, by using extensions of the clinically successful linear quadratic model.

Protons undoubtedly reduce or eliminate NT radiation dose in tissues distantly located from a tumour, but the necessity to include NT margins around a tumour can result in a higher volume of NT than tumour being irradiated. Deleterious side-effects can follow if the NT RBE exceeds 1.1, including in tissue very close to these margins and which are only partially spared.

Use of a constant 1.1 RBE can ‘overdose’ NT, which may require a greater dose reduction such as 1.2 in the brain; some tumours may be ‘under-dosed’ (since they might require a lesser or no reduction in dose). More sophisticated proton experiments show that RBE values of 1.1–1.5 and higher occur in some situations. There are now mathematical models of varying degrees of complexity that can estimate the RBE from the dose, LET and the low-LET radiosensitivities. True multidisciplinary cooperation is required to implement such new ideas in proton therapy in order to improve safety and effectiveness.

Further Radiobiologic Modeling of Palliative Radiotherapy: Use of Virtual Trials

PURPOSE

To study duration of response in palliative radiotherapy in a population of tumors.

METHODS AND MATERIALS

Models of dynamic changes in cell number with time were used to develop a function for the remission time (T(rem)) after palliative radiotherapy: [See Equation], where BED is the biologically effective dose, t(1) the duration of symptoms (i.e., the time between the onset of symptoms and the initiation of radiotherapy), K the daily BED repopulation equivalent, alpha the linear radiosensitivity parameter in the linear-quadratic model, and z the tumor regression rate.

RESULTS

Simulations of clinical trials show marked variations in remission statistics depending on the tumor characteristics and are highly compatible with the results of clinical trials. Dose escalation produces both a higher proportion and extended duration of remissions, especially in tumors with high alpha/beta ratios and K values, but the predicted dose responses of acute and late side effects show that caution is necessary. The prospect of using particle beam therapy to reduce normal tissue radiation exposures or using hypoxic sensitizers to improve the tumor cell kill might significantly improve the results of palliative radiotherapy in carefully selected patients and could also be used for safer palliative re-treatments in patients with the potential for prolonged survival. The effect of tumor heterogeneity in determining palliative responses probably exceeds that in radical radiotherapy; as few as 100 patients in each treatment arm produce statistically unreliable results.

CONCLUSIONS

Virtual trials of palliative radiotherapy can be useful to test the effects of competing schedules and better determine future strategies, including improved design of clinical trials as well as combinations of radiotherapy with other anticancer modalities.