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A real-time contouring feedback tool for consensus-based contour training.

Christopher L Nelson1, Callistus Nguyen1, Raymond Fang1

  • 1Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.

Frontiers in Oncology
|September 29, 2023
PubMed
Summary
This summary is machine-generated.

Contouring variability in radiotherapy is a challenge. A new tool provides real-time feedback, significantly reducing contouring errors for radiation oncology trainees and improving accuracy for structures like the heart and left ventricle.

Keywords:
consensus contouringcontour trainingcontour variabilitylocalized signed surface distanceradiotherapy planning

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Medical Imaging

Background:

  • Contouring variability in radiotherapy remains a significant challenge.
  • Radiation oncologist feedback, while beneficial, is often impractical for trainees.
  • Developing automated tools for consistent contouring is crucial for improving treatment accuracy.

Purpose of the Study:

  • To develop and evaluate a novel contour training tool that provides real-time feedback to reduce inter-observer variability.
  • To assess the tool's effectiveness in improving the accuracy and consistency of organ segmentation for radiotherapy planning.

Main Methods:

  • A localized signed square distance (LSSD) metric was developed for real-time contour comparison.
  • Nine trainees utilized the tool with six training cases, including heart and left ventricle (LV) segmentation.
  • Contour accuracy was assessed by comparing initial and final LSSD maps, with retention evaluated after 30 days.

Main Results:

  • Statistically significant reductions in ΔLSSD were observed for both heart and LV contours across all training cases.
  • Mean LSSD for heart and LV improved from initial values (SD: 4.2, 4.8) to final values (SD: 0.8, 0.7) during training.
  • Excellent retention of contour accuracy was demonstrated for the heart and LV 30 days post-training.

Conclusions:

  • The developed contour training tool effectively reduces contouring variability.
  • Real-time feedback significantly improves the accuracy of trainee contours for critical structures.
  • This tool offers a practical solution for enhancing radiotherapy contouring consistency and quality.