Automated planning in image-guided adaptive brachytherapy for cervical cancer: Impact analysis on patient workflows in high-volume centers.

Authors

Varsha Hande, Linda Rossi, Henrike Westerveld, Lorne Luthart, Prachi Mittal, Subhajit Panda, Yogesh Ghadi, Remi A Nout, Ben Heijmen, Supriya Chopra

Published in

Journal of contemporary brachytherapy. Volume 18. Issue 2. Pages 163-170. Epub Jun 30, 2026.

Abstract

Image-guided adaptive brachytherapy (IGABT) improves outcomes in locally advanced cervical cancer, but remains resource- and time-intensive, particularly during treatment planning. This study evaluated the impact of automated IGABT treatment planning using a validated model (BiCycle) on workflow optimization and improved planning efficiency.
This study analyzed IGABT planning data collected from Institution 1 (India) and Institution 2 (the Netherlands) between January 2022 and July 2024. Intracavitary (IC) and intracavitary + interstitial (IC + IS) implants planned with 3D CT/MRI imaging were employed. Once the target and organs at risk (OARs) were delineated and the applicator was reconstructed, manual and automated planning times (in minutes) for dwell time optimization and dwell time adjustment (fine-tuning) were compared. Mann-Whitney U test evaluated differences in median time. Time savings with automated brachytherapy planning were modelled as increased treatment capacity.
Sixty-nine plans from both institutions were analyzed, consisting of 30 automated and 39 manual plans. The median time for dwell time position selection and optimization was 4.59 minutes (interquartile range [IQR]: 4.00-5.90) using automated planning, and 21 minutes (IQR: 12.00-30.00) using manual planning. The median time for treatment dwell time adjustment was 5 minutes (IQR: 3.46-8.50) using automated planning, and 15 minutes (IQR: 11.00-24.00) using manual planning. In high-volume centers treating up to four patients daily, automation could save as much as two hours daily and enhance treatment capacity by 25%.
Automating IGABT treatment planning significantly reduces planning time and improve efficiency.

PMID:
42488745
Bibliographic data and abstract were imported from PubMed on 23 Jul 2026.

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