A robust optimisation genetic algorithm for HDR prostate brachytherapy including all major uncertainties II: Algorithm evaluation on 49 patients

Introduction: Treatment plans in high-dose-rate (HDR) prostate brachytherapy (BT) are currently optimised to meet clinical objectives in the nominal plan; however, uncertainties cause the scenario delivered to deviate from this plan and may fail objectives. A robust optimiser generates plans that maximise the probability of dose-volume-histogram (DVH) metrics passing in the delivered scenario. Method: A probabilistic robust optimiser was evaluated on 49 patients. Three objective functions were maximised to obtain the Pareto front consisting of 200 robust-optimised treatment plans. Each objective function approximated the robustness of three DVH metrics: (1) the minimum dose to the hottest 90% of the prostate, \({D}₉₀P\), the maximum doses to the (2) urethra, \({D}0.01 ccU\), and (3) rectum, \({D}0.1 ccR\). Pareto front plans were robustly evaluated using 1000 probabilistic uncertainty scenarios, outputting the pass-rates for \({D}₉₀P\), \({D}0.01 ccU\), \({D}0.1 ccR\), and all three simultaneously, the overall pass-rate. The best robust-optimised plan was selected from the Pareto front and compared to the TPS-optimised plan for ten patients by a radiation oncologist, then 49 patient robust-optimised plans were compared. Results: All robust-optimised plans had higher overall pass-rates (mean: 50.7 ± 1.5%, SD: 14.2%) compared to the TPS-optimised plans (mean: 32.0 ± 1.5%, SD: 12.3%). This was also the case with the \({D}0.01 ccU\) pass-rates with the robust-optimised plans having a mean of 66.0 ± 1.3% (SD: 12.1) compared with 47.2 ± 1.3% (SD: 9.3%). The pass-rates for \({D}₉₀P\) were higher for the robust-optimised plans (mean: 85.6 ± 1.1%, SD: 9.5%) in 36 patients, the TPS-optimised mean was 82.2 ± 1.1% (SD: 13.8%). Twenty-seven patients had higher \({D}0.1 ccR\) pass-rates in the robust-optimised plans with a mean of 94.54 ± 0.56% (SD: 7.35%) compared with 93.71 ± 0.56% (SD: 6.73%). Conclusion: A robust optimisation algorithm generated treatment plans with higher robustness than the TPS-optimised plans for nine out of ten patients, evaluated by a radiation oncologist, in an average time of 1-minute-49-seconds.