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Automated Field-In-Field (FIF) Plan Framework Combining Scripting Application Programming Interface and User-Executed

Hojin Kim1, Jungwon Kwak1, Jinhong Jung1

  • 11 Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.

Technology in Cancer Research & Treatment
|November 3, 2018
PubMed
Summary
This summary is machine-generated.

Automated breast field-in-field planning is now a one-click option, significantly reducing planning time by over 50% without compromising plan quality. This innovation enhances efficiency in radiation oncology workflows.

Keywords:
automated frameworkbreast radiation therapyeclipse scripting API (ESAPI)field-in-field (FIF)forward IMRT

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Medical Imaging

Background:

  • Radiation therapy planning aims to optimize dose delivery while minimizing toxicity.
  • Automating treatment planning processes, such as field-in-field (FIF) techniques, can improve efficiency and consistency.
  • Current scripting capabilities in treatment planning systems may not fully meet all user needs for complex planning tasks.

Purpose of the Study:

  • To develop a one-click automated breast FIF planning solution.
  • To integrate Eclipse Scripting application programming interfaces (APIs) with user-executed programming.
  • To streamline the clinical workflow for breast cancer radiation therapy planning.

Main Methods:

  • Developed a novel framework combining scripting APIs and user-executed programming for automated FIF planning.
  • Utilized Eclipse Scripting to interface with the treatment planning system server and client.
  • Implemented a one-click function for automated plan generation, parameter adjustment, and pushback to the treatment planning system.

Main Results:

  • The automated framework reduced total planning time by over 50% compared to manual FIF planning.
  • Planning efficiency was significantly enhanced, with automated plan generation completed in under 1 minute.
  • Dosimetric analysis showed minimal deviation (within 1%) from manual plans for critical organs (heart, lung) and target coverage.

Conclusions:

  • The integrated approach of scripting and user-executed programming enables efficient automated breast FIF planning.
  • This one-click solution significantly improves planning efficiency without sacrificing plan quality.
  • The developed framework offers a valuable tool for optimizing radiation oncology clinical workflows.