TY - JOUR
T1 - Fast and fully-automated multi-criterial treatment planning for adaptive HDR brachytherapy for locally advanced cervical cancer
AU - Oud, Michelle
AU - Kolkman-Deurloo, Inger Karine
AU - Mens, Jan Willem
AU - Lathouwers, Danny
AU - Perkó, Zoltán
AU - Heijmen, Ben
AU - Breedveld, Sebastiaan
PY - 2020
Y1 - 2020
N2 - Purpose: To develop and evaluate a fast, automated multi-criterial treatment planning approach for adaptive high-dose-rate (HDR) intracavitary + interstitial brachytherapy (BT) for locally advanced cervical cancer. Methods and materials: Twenty-two previously delivered single fraction MRI-based HDR treatment plans (SFclin) were used to guide training of our in-house system for multi-criterial autoplanning, aiming for an autoplan quality superior to the training plans, while respecting the clinically desired “pear-shaped” dose distribution. Next, the configured algorithm was used to automatically generate treatment plans for 63 other fractions (SFauto). The SFauto plans were compared to the corresponding SFclin plans in blind pairwise comparisons by an expert clinician. Then, the effect of adaptive autoplanning on total treatment (TT) plans (external beam + 3 BT fractions) was evaluated for 16 patients by simulating the clinically applied adaptive strategy to generate TTauto plans and compare them with the corresponding clinical treatments (TTclin). Results: In the blind comparisons, all SFauto plans were considered clinically acceptable. In 62/63 comparisons, SFauto plans were considered at least as good as, or better than the corresponding SFclin. The average optimization time for autoplanning was 20.5 ± 19.2 s (range 4.4–106.4 s) per plan. In 14 of 16 TTauto plans, the desired total dose of 90 Gy (EQD2) was obtained, compared to only 9 in the corresponding TTclin, while autoplanning also decreased bladder and rectum doses. Conclusions: Fast, fully-automated multi-criterial treatment planning for adaptive HDR-BT for locally advanced cervical cancer is feasible. Autoplans were superior to corresponding clinical plans.
AB - Purpose: To develop and evaluate a fast, automated multi-criterial treatment planning approach for adaptive high-dose-rate (HDR) intracavitary + interstitial brachytherapy (BT) for locally advanced cervical cancer. Methods and materials: Twenty-two previously delivered single fraction MRI-based HDR treatment plans (SFclin) were used to guide training of our in-house system for multi-criterial autoplanning, aiming for an autoplan quality superior to the training plans, while respecting the clinically desired “pear-shaped” dose distribution. Next, the configured algorithm was used to automatically generate treatment plans for 63 other fractions (SFauto). The SFauto plans were compared to the corresponding SFclin plans in blind pairwise comparisons by an expert clinician. Then, the effect of adaptive autoplanning on total treatment (TT) plans (external beam + 3 BT fractions) was evaluated for 16 patients by simulating the clinically applied adaptive strategy to generate TTauto plans and compare them with the corresponding clinical treatments (TTclin). Results: In the blind comparisons, all SFauto plans were considered clinically acceptable. In 62/63 comparisons, SFauto plans were considered at least as good as, or better than the corresponding SFclin. The average optimization time for autoplanning was 20.5 ± 19.2 s (range 4.4–106.4 s) per plan. In 14 of 16 TTauto plans, the desired total dose of 90 Gy (EQD2) was obtained, compared to only 9 in the corresponding TTclin, while autoplanning also decreased bladder and rectum doses. Conclusions: Fast, fully-automated multi-criterial treatment planning for adaptive HDR-BT for locally advanced cervical cancer is feasible. Autoplans were superior to corresponding clinical plans.
KW - Adaptive treatment
KW - Adaptive treatment planning
KW - Automated treatment planning
KW - Cervical cancer
KW - High-dose-rate brachytherapy
KW - Multi-criteria optimization
UR - http://www.scopus.com/inward/record.url?scp=85084195222&partnerID=8YFLogxK
U2 - 10.1016/j.radonc.2020.04.017
DO - 10.1016/j.radonc.2020.04.017
M3 - Article
AN - SCOPUS:85084195222
VL - 148
SP - 143
EP - 150
JO - Radiotherapy & Oncology
JF - Radiotherapy & Oncology
SN - 0167-8140
ER -