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Protocol parameter extraction and centralization framework for comprehensive and in-depth CT protocol review and

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This study introduces a universal framework for managing computed tomography (CT) protocols, simplifying complex data extraction and enabling efficient review across diverse CT scanner systems. The Python-based solution standardizes protocol data for improved clinical workflow and efficiency.

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Area of Science:

  • Radiology and Medical Imaging
  • Health Informatics
  • Software Engineering in Healthcare

Background:

  • CT protocol management is complex due to proprietary vendor-specific file structures.
  • Lack of a universal format hinders efficient protocol review, version tracking, and cross-protocol comparisons.
  • Expertise from technologists, radiologists, IT professionals, and medical physicists is required.

Purpose of the Study:

  • To develop a universal framework for CT protocol management.
  • To simplify the extraction of technical parameters from raw CT protocol files.
  • To enhance clinical efficiency in routine protocol review, version tracking, and comparisons.

Main Methods:

  • Developed a Python 3 framework to convert proprietary CT protocol files into a universal intermediary format (JSON).
  • Collaboratively identified key technical parameters with medical physicists and lead technologists.
  • Extracted and analyzed protocol files from diverse Siemens and GE CT scanners.
  • Converted JSON data to a human-readable MS Excel format for all systems.

Main Results:

  • Successfully converted raw CT protocol files from multiple vendors into a standardized JSON format.
  • Demonstrated the framework's ability to output data in a human-readable MS Excel format.
  • Provided example results showcasing side-by-side comparisons of protocols with similar clinical indications.

Conclusions:

  • The developed CT protocol management framework offers a universal solution applicable to any CT system.
  • The framework significantly improves clinical efficiency for protocol review, version tracking, and upkeep.
  • Standardizing CT protocol data facilitates better data management and utilization in radiology departments.