RESUMO
BACKGROUND: Compared to conventional radiotherapy (XT), proton therapy (PT) may improve normal tissue complication probabilities (NTCP). However, PT typically requires higher adaptation rates due to an increased sensitivity to anatomical changes. Systematic online adaptation may address this issue, but it requires additional replanning time, decreasing patient throughput. Therefore, less patients would benefit in such case from PT for a given machine capacity, with results in worse NTCP. AIM: To investigate the trade-off between PT patient throughput and NTCP gain as a function of the time needed for adaptation. METHODS: A retrospective database of 14 lung patients with two repeated 4DCTs was used to compare NTCP values between XT and PT for NTCP2ym (2-year mortality), NTCPdysphagia and NTCPpneumonitis. Four scenarios were considered for PT: no adaptation using clinical robustness parameters (4D robust optimization, 3 % range error and PTV-equivalent setup errors); systematic online adaptation with clinical robustness parameters; setup errors reduced to 4 mm and to 2 mm. Dose was accumulated on the planning CT. The number of patients treated with PT depended on the extra time needed for adaptation, assuming an 8-hours capacity (assuming 14 patients a day; thus minimum 34.2 min per treatment session if there is no or instantaneous adaptation). RESULTS: Baseline NTCP gains (PT against XT without adaptation) equaled 6.9 %, 6.1 %, and 7.7 % for NTCP2ym, NTCPdysphagia and NTCPpneumonitis, respectively. Using instantaneous online adaptation and setup errors of 2 mm, the overall gains were then 10.7 %, 13.6 % and 12.4 %. Taking into account loss of capacity, 13.7 min was the maximum extra-time allowed to complete adaptation and maintain an advantage on all three metrics for the 2-mm setup error scenario. CONCLUSION: This study highlights the critical importance of keeping short online adaptation times when using systems with limited capacity like PT.
RESUMO
Objective.To compare a not adapted (NA) robust planning strategy with three fully automated online adaptive proton therapy (OAPT) workflows based on the same optimization method: dose mimicking (DM). The added clinical value and limitations of the OAPT methods are investigated for head and neck cancer (HNC) patients.Approach.The three OAPT strategies aimed at compensating for inter-fractional anatomical changes by mimiking different dose distributions on corrected cone beam CT images (corrCBCTs). Order by complexity, the OAPTs were: (1) online adaptive dose restoration (OADR) where the approved clinical dose on the planning-CT (pCT) was mimicked, (2) online adaptation using DM of the deformed clinical dose from the pCT to corrCBCTs (OADEF), and (3) online adaptation applying DM to a predicted dose on corrCBCTs (OAML). Adaptation was only applied in fractions where the target coverage criteria were not met (D98% < 95% of the prescribed dose). For 10 HNC patients, the accumulated dose distributions over the 35 fractions were calculated for NA, OADR, OADEF, and OAML.Main results.Higher target coverage was observed for all OAPT strategies compared to no adaptation. OADEF and OAML outperformed both NA and OADR and were comparable in terms of target coverage to initial clinical plans. However, only OAML provided comparable NTCP values to those from the clinical dose without statistically significant differences. When the NA initial plan was evaluated on corrCBCTs, 51% of fractions needed adaptation. The adaptation rate decreased significantly to 25% when the last adapted plan with OADR was selected for delivery, to 16% with OADEF, and to 21% with OAML. The reduction was even greater when the best plan among previously generated adapted plans (instead of the last one) was selected.Significance. The implemented OAPT strategies provided superior target coverage compared to no adaptation, higher OAR sparing, and fewer required adaptations.
