RESUMO
PURPOSE: To evaluate the performance of a model-based optimisation process for volumetric modulated arc therapy applied to prostate cancer in a multicentric cooperative group. The RapidPlan (RP) knowledge-based engine was tested for the planning of Volumetric modulated arc therapy with RapidArc on prostate cancer patients. The study was conducted in the frame of the German RapidPlan Consortium (GRC). METHODS AND MATERIALS: 43 patients from one institute of the GRC were used to build and train a RP model. This was further shared with all members of the GRC plus an external site from a different country to increase the heterogeneity of the patient's sampling. An in silico multicentric validation of the model was performed at planning level by comparing RP against reference plans optimized according to institutional procedures. A total of 60 patients from 7 institutes were used. RESULTS: On average, the automated RP based plans resulted fully consistent with the manually optimised set with a modest tendency to improvement in the medium-to-high dose region. A per-site stratification allowed to identify different patterns of performance of the model with some organs at risk resulting better spared with the manual or with the automated approach but in all cases the RP data fulfilled the clinical acceptability requirements. Discrepancies in the performance were due to different contouring protocols or to different emphasis put in the optimization of the manual cases. CONCLUSIONS: The multicentric validation demonstrated that it was possible to satisfactorily optimize with the knowledge based model patients from all participating centres. In the presence of possibly significant differences in the contouring protocols, the automated plans, though acceptable and fulfilling the benchmark goals, might benefit from further fine tuning of the constraints. The study demonstrates that, at least for the case of prostate cancer patients, it is possibile to share models among different clinical institutes in a cooperative framework.