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Automated data mining of a plan-check database and example application.

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Summary
This summary is machine-generated.

This study developed automated software to analyze Mobius3D data, enabling efficient bulk analysis of patient treatment plans and quality assurance results for research and clinical applications.

Keywords:
Mobius3Dplan-checkstatistical process controltreatment planning

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Data Science

Background:

  • Mobius3D is a quality assurance system for radiation therapy planning and delivery.
  • Significant amounts of patient and treatment data are generated but not easily accessible for analysis.

Purpose of the Study:

  • To develop automated data mining software for bulk analysis of Mobius3D treatment and patient data.
  • To create tools for efficient extraction and interpretation of quality assurance results.

Main Methods:

  • Developed an interface using Python, MATLAB, and Java to read JSON files from Mobius3D.
  • Created two GUIs: Mobius3D-Database (M3D-DB) for plan-check results and Mobius3D organ at risk (M3DOAR) for dose-volume histogram analysis.
  • Implemented filtering and sorting capabilities for treatment parameters, sites, and patient demographics.

Main Results:

  • M3D-DB effectively summarizes and filters large volumes of plan-check data.
  • M3DOAR facilitates analysis of dose-volume data for patient cohorts, useful for clinical trials.
  • The software enables mass analysis of target dose-volume histograms.

Conclusions:

  • Demonstrated a method to access and mine extensive treatment data stored within Mobius3D.
  • The developed software supports research, clinical trials, and patient/treatment planning system quality assurance.
  • Scripting enables efficient utilization of previously inaccessible data for improved radiotherapy practices.