TY - JOUR
T1 - Towards artificial intelligence-based automated treatment planning in clinical practice
T2 - A prospective study of the first clinical experiences in high-dose-rate prostate brachytherapy
AU - Barten, Danique L. J.
AU - Pieters, Bradley R.
AU - Bouter, Anton
AU - van der Meer, Marjolein C.
AU - Maree, Stef C.
AU - Hinnen, Karel A.
AU - Westerveld, Henrike
AU - Bosman, Peter A. N.
AU - Alderliesten, Tanja
AU - van Wieringen, Niek
AU - Bel, Arjan
N1 - Publisher Copyright: © 2022 American Brachytherapy Society
PY - 2023/3/1
Y1 - 2023/3/1
N2 - Purpose: This prospective study evaluates our first clinical experiences with the novel ‘‘BRachytherapy via artificial Intelligent GOMEA-Heuristic based Treatment planning'' (BRIGHT) applied to high-dose-rate prostate brachytherapy. MethodS AND MATERIALs: Between March 2020 and October 2021, 14 prostate cancer patients were treated in our center with a 15Gy HDR-brachytherapy boost. BRIGHT was used for bi-objective treatment plan optimization and selection of the most desirable plans from a coverage-sparing trade-off curve. Selected BRIGHT plans were imported into the commercial treatment planning system Oncentra Brachy. In Oncentra Brachy a dose distribution comparison was performed for clinical plan choice, followed by manual fine-tuning of the preferred BRIGHT plan when deemed necessary. The reasons for plan selection, clinical plan choice, and fine-tuning, as well as process speed were monitored. For each patient, the dose-volume parameters of the (fine-tuned) clinical plan were evaluated. Results: In all patients, BRIGHT provided solutions satisfying all protocol values for coverage and sparing. In four patients not all dose-volume criteria of the clinical plan were satisfied after manual fine-tuning. Detailed information on tumour coverage, dose-distribution, dwell time pattern, and insight provided by the patient-specific trade-off curve, were used for clinical plan choice. Median time spent on treatment planning was 42 min, consisting of 16 min plan optimization and selection, and 26 min undesirable process steps. ConclusionS: BRIGHT is implemented in our clinic and provides automated prostate high-dose-rate brachytherapy planning with trade-off based plan selection. Based on our experience, additional optimization aims need to be implemented to further improve direct clinical applicability of treatment plans and process efficiency.
AB - Purpose: This prospective study evaluates our first clinical experiences with the novel ‘‘BRachytherapy via artificial Intelligent GOMEA-Heuristic based Treatment planning'' (BRIGHT) applied to high-dose-rate prostate brachytherapy. MethodS AND MATERIALs: Between March 2020 and October 2021, 14 prostate cancer patients were treated in our center with a 15Gy HDR-brachytherapy boost. BRIGHT was used for bi-objective treatment plan optimization and selection of the most desirable plans from a coverage-sparing trade-off curve. Selected BRIGHT plans were imported into the commercial treatment planning system Oncentra Brachy. In Oncentra Brachy a dose distribution comparison was performed for clinical plan choice, followed by manual fine-tuning of the preferred BRIGHT plan when deemed necessary. The reasons for plan selection, clinical plan choice, and fine-tuning, as well as process speed were monitored. For each patient, the dose-volume parameters of the (fine-tuned) clinical plan were evaluated. Results: In all patients, BRIGHT provided solutions satisfying all protocol values for coverage and sparing. In four patients not all dose-volume criteria of the clinical plan were satisfied after manual fine-tuning. Detailed information on tumour coverage, dose-distribution, dwell time pattern, and insight provided by the patient-specific trade-off curve, were used for clinical plan choice. Median time spent on treatment planning was 42 min, consisting of 16 min plan optimization and selection, and 26 min undesirable process steps. ConclusionS: BRIGHT is implemented in our clinic and provides automated prostate high-dose-rate brachytherapy planning with trade-off based plan selection. Based on our experience, additional optimization aims need to be implemented to further improve direct clinical applicability of treatment plans and process efficiency.
KW - AI-based plan optimization
KW - Clinical experience
KW - HDR
KW - Prostate brachytherapy
KW - Trade-off
UR - http://www.scopus.com/inward/record.url?scp=85147164962&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.brachy.2022.11.013
DO - https://doi.org/10.1016/j.brachy.2022.11.013
M3 - Article
C2 - 36635201
SN - 1538-4721
VL - 22
SP - 279
EP - 289
JO - BRACHYTHERAPY
JF - BRACHYTHERAPY
IS - 2
ER -