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ePAD: An Image Annotation and Analysis Platform for Quantitative Imaging.

Daniel L Rubin1, Mete Ugur Akdogan1, Cavit Altindag1

  • 1Department of Biomedical Data Science, Radiology, and Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA.

Tomography (Ann Arbor, Mich.)
|March 12, 2019
PubMed
Summary
This summary is machine-generated.

The electronic Physician Annotation Device (ePAD) streamlines quantitative analysis of medical images for cancer research. This free, web-based tool aids researchers and clinicians in evaluating treatment response and supports clinical trial efficiency.

Keywords:
AIM (Annotation and Image Markup)DICOM SR (DICOM Structure Report)biomarker evaluationfeature extractionmedical image annotation

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Area of Science:

  • Medical imaging
  • Radiology
  • Oncology

Background:

  • Quantitative lesion assessment in medical imaging is crucial but time-consuming for cancer therapy response evaluation.
  • Adopting novel quantitative imaging biomarkers in clinical trials presents significant challenges.
  • Existing workflows lack efficient tools for comprehensive image annotation and analysis.

Purpose of the Study:

  • To introduce the electronic Physician Annotation Device (ePAD) as a solution for quantitative medical image analysis in cancer research.
  • To highlight ePAD's capabilities in supporting clinical trials, decision support, and workflow management.
  • To demonstrate ePAD's extensibility and interoperability for diverse cancer imaging use cases.

Main Methods:

  • ePAD is a freely available, web-based, zero-footprint software application.
  • It offers tools for viewing, annotating, and quantitatively analyzing radiology images.
  • Features include calculation of quantitative imaging biomarkers, clinical decision support, workflow management, and standardized data output.

Main Results:

  • ePAD facilitates quantitative imaging biomarker analysis for surrogate endpoint identification in clinical trials.
  • It provides clinicians with decision support tools for cancer response evaluation.
  • ePAD ensures interoperability through standardized annotation formats and supports community-driven platform extension via a plugin architecture.

Conclusions:

  • ePAD is a versatile platform addressing challenges in quantitative medical image analysis for cancer research and clinical trials.
  • Its features support researchers, clinicians, and administrators, enhancing efficiency and data standardization.
  • The platform's open architecture fosters collaboration and adaptation for future cancer imaging applications.