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Workflow Efficiency in Vaginal Cuff High Dose Rate Brachytherapy Using Artificial Intelligence-Based Organ

Yohan A Walter1,2, Lane Rosen1, Olivia Moncrief3

  • 1Department of Radiation Oncology, Willis Knighton Cancer Center, Shreveport, LA 71103, USA.

Cancers
|September 13, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) for organ contouring and applicator modeling significantly reduced high dose rate brachytherapy planning time by 13.7 minutes. These AI tools also decreased inter-user variability in treatment planning, improving workflow efficiency and standardization.

Keywords:
artificial intelligencebrachytherapyhigh dose ratequality improvementradiation oncologyradiation therapytreatment planningvaginal cuff brachytherapyworkflow efficiency

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Area of Science:

  • Medical physics
  • Radiation oncology
  • Artificial intelligence in healthcare

Background:

  • High dose rate brachytherapy (HDR-BT) is a resource-intensive cancer treatment.
  • Workflow inefficiencies and inter-user variability are significant challenges in HDR-BT.
  • Artificial intelligence (AI) tools offer potential solutions to these challenges.

Purpose of the Study:

  • To evaluate the impact of AI-based organ contouring (AC) and applicator modeling (AM) on workflow efficiency and inter-user variability in vaginal cuff HDR-BT.
  • To assess the effect of AC and AM on treatment plan quality.

Main Methods:

  • A retrospective analysis of 260 HDR-BT fractions was conducted, comparing cases before and after the implementation of AC and AM.
  • Treatment planning times (contouring, dose planning, total) were recorded using timestamps.
  • Dosimetric data, including organ-at-risk doses (rectum, bladder D2cc) and target coverage (V90-200), were analyzed.
  • Statistical analysis using ANOVA and Tukey tests compared differences between medical physicists before and after AI implementation.

Main Results:

  • Implementation of AC and AM led to a significant reduction in overall planning time by 13.7 ± 1.7 minutes.
  • Inter-user variability in organ and target dose metrics was reduced across most structures.
  • Statistically significant differences in rectum D2cc and target V95 between planners were eliminated after AC and AM implementation.

Conclusions:

  • AI-based organ contouring and applicator modeling substantially enhance workflow efficiency in HDR-BT.
  • These AI tools maintain or improve treatment plan quality while reducing inter-user variability.
  • Standardization of workflows through AI can aid in user training and robust outcome assessment for brachytherapy.