Prognostic factors of local control and disease free survival in centrally located non-small cell lung cancer treated with stereotactic body radiation therapy

Background: Stereotactic body radiation therapy (SBRT) results in high local control (LC) rates in patients with non-small cell lung cancer (NSCLC). For central lung tumors, risk-adapted fractionation schedules are used and underdosage to the Planned Target Volume (PTV) is often accepted to respect the dose constraints of the organs at risk in order to avoid high rates of toxicity. The purpose of this study was to analyze the effect of PTV underdosage and other possible prognostic factors on localand disease control after SBRT in patients with central lung tumors. Material and Methods: Patients with centrally located NSCLC treated with SBRT were included. The doses were converted into biologically equivalent dose using a/b-value of 10 Gy (BED10). Underdosage to the PTV was defined as the (percentage of) PTV receiving less than 100 Gy BED10; (%)PTV < 100 BED10. Potential prognostic factors for LC and Disease Free Survival (DFS) were evaluated using Cox regression analysis. Results: Two hundred and twenty patients received 12 fractions of SBRT. LC-rates were 88% at 2 years and 81% at 3 years. Twenty-seven patients developed a local recurrence. Both the PTV < 100 BED10 and %PTV < 100 BED10 were not prognostic for LC. Tumor size and forced expiratory volume in 1 second (FEV1) were independently prognostic for LC. Disease progression was reported in 75 patients with DFS-rates of 66% at 2 years and 56% at 3 years. Disea

Impact of model and dose uncertainty on model-based selection of oropharyngeal cancer patients for proton therapy

Background: Proton therapy is becoming increasingly available, so it is important to apply objective and individualized patient selection to identify those who are expected to benefit most from proton therapy compared to conventional intensity modulated radiation therapy (IMRT). Comparative treatment planning using normal tissue complication probability (NTCP) evaluation has recently been proposed. This work investigates the impact of NTCP model and dose uncertainties on model-based patient selection. Material and Methods: We used IMRT and intensity modulated proton therapy (IMPT) treatment plans of 78 oropharyngeal cancer patients, which were generated based on automated treatment planning and evaluated based on three published NTCP models. A reduction in NTCP of more than a certain threshold (e.g. 10% lower NTCP) leads to patient selection for IMPT, referred to as ‘nominal’ selection. To simulate the effect of uncertainties in NTCP-model coefficients (based on reported confidence intervals) and planned doses on the accuracy of model-based patient selection, the Monte Carlo method was used to sample NTCP-model coefficients and doses from a probability distribution centered at their nominal values. Patient selection accuracy within a certain sample was defined as the fraction of patients which had similar selection in both the ‘nominal’ and ‘sampled’ scenario. Results: For all three NTCP models, the median patient selection accuracy was found to be above 70% when only NTCP-model uncertainty was considered. Selection accuracy decreased with increasing uncertainty resulting from differences between planned and delivered dose. In case of excessive dose uncertainty, selection accuracy decreased to 60%. Conclusion: Model and dose uncertainty highly influence the accuracy of model-based patient selection for proton therapy. A reduction of NTCP-model uncertainty is necessary to reach more accurate model-based patient selection