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APPIAN: Automated Pipeline for PET Image Analysis.

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Summary

APPIAN automates positron emission tomography (PET) image analysis, including coregistration, partial-volume correction, and kinetic modeling. This user-friendly pipeline ensures reproducible research with automated quality control and accurate quantification.

Keywords:
PETautomationopen sciencepipelinequality controlsoftware

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Area of Science:

  • Medical Imaging
  • Neuroscience
  • Radiochemistry

Background:

  • Positron Emission Tomography (PET) imaging requires complex processing steps for accurate quantitative analysis.
  • Existing open-source PET analysis pipelines often lack comprehensive automation, flexibility, and user-friendliness.
  • Reproducible and reliable research in PET imaging necessitates robust quality control and streamlined workflows.

Purpose of the Study:

  • To develop APPIAN, an automated pipeline for user-friendly and reproducible analysis of PET images.
  • To integrate coregistration, partial-volume correction (PVC), and tracer kinetic modeling into a single, automated workflow.
  • To enhance the reliability, flexibility, and extensibility of automated PET data analysis.

Main Methods:

  • Automated coregistration of PET images to T1-weighted MR images.
  • Implementation of partial-volume correction (PVC) and tracer kinetic modeling.
  • Development of automated quality control (QC) and a web-based graphical user interface (GUI) for visualization and analysis.

Main Results:

  • APPIAN successfully automates PET image processing up to statistical analysis.
  • Automated QC facilitates verification of each processing stage.
  • Validation against the SORTEO database shows 93-100% accuracy in radiotracer concentration recovery after PVC.

Conclusions:

  • APPIAN provides a reliable, flexible, and extensible platform for automated PET image analysis.
  • The pipeline enhances research reproducibility through automated QC and user-friendly visualization.
  • APPIAN achieves high accuracy in quantitative PET analysis, supporting diverse research applications.