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Batch Export: An automated framework for curated data extraction via the Eclipse treatment planning system.

Ryan Truong1, Lance C Moore1, Casey Bojechko1

  • 1Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California, USA.

Journal of Applied Clinical Medical Physics
|December 11, 2025
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Summary
This summary is machine-generated.

We developed an open-source application to quickly export patient data from the Eclipse treatment planning system (TPS). This tool streamlines data retrieval for machine learning applications, significantly improving efficiency over manual methods.

Keywords:
automationradiation therapytreatment planning

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Area of Science:

  • Medical Physics
  • Radiotherapy
  • Machine Learning

Background:

  • Deep learning models require large datasets for radiation therapy tasks like dose prediction.
  • Current DICOM-RT data export from Eclipse TPS is inefficient and unscalable for large datasets.
  • Efficient data retrieval is crucial for advancing downstream research applications.

Purpose of the Study:

  • To simplify and enhance the efficiency of patient data retrieval from the Eclipse TPS.
  • To develop a streamlined application for parallel export of treatment plans, images, and structure sets.
  • To overcome the limitations of manual data export for large-scale research.

Main Methods:

  • Developed a C#.NET application with a GUI using the Prism library.
  • Integrated EvilDICOM for seamless connection to the Eclipse patient database.
  • Compared application data export times against manual export methods based on DICOM file volume.

Main Results:

  • The application significantly reduced export times compared to manual methods, especially for multiple patients.
  • Exporting 20 patients' data (∼3000 DICOM files) took 10.22 minutes with the application versus 22.93 minutes manually.
  • The application demonstrated linear-time performance and scalability for over 17,000 DICOM files.

Conclusions:

  • An open-source application was created for rapid and scalable patient data acquisition from Eclipse TPS.
  • The tool effectively addresses challenges associated with manual DICOM file export in large volumes.
  • This facilitates machine learning model training and other research requiring extensive patient data.