A framework for in-field and out-of-field patient specific secondary cancer risk estimates from treatment plans using the TOPAS Monte Carlo system

Abstract

Objective: To allow the estimation of secondary cancer risks from radiation therapy treatment plans in a comprehensive and user-friendly Monte Carlo framework. 
Approach: Patient planning CTs were extended superior-inferior using the ICRP Publication 145 computational mesh phantoms and skeletal matching. Dose distributions were calculated with the TOPAS Monte Carlo system using novel mesh capabilities and the DICOM-RT interface. Finally, in-field and out-of-field cancer risk was calculated using both sarcoma and carcinoma risk models with two alternative parameter sets.
Main results: The TOPAS Monte Carlo framework was extended to facilitate epidemiological studies on radiation-induced cancer risk. The framework is efficient and allows automated analysis of large datasets. Out-of-field organ dose was small compared to in-field dose, but the risk estimates indicate a non-negligible contribution to the total radiation induced cancer risk. 
Significance: The implementation of anatomical extension, mesh phantom capabilities, and cancer risk models into the TOPAS Monte Carlo system makes state-of-the-art out-of-field dose calculation and risk estimation accessible to a large pool of users while facilitating further refinement of risk models and sensitivity analysis of patient specific treatment options.