ETACT-An Innovative Approach to Scintimammography

Abstract

This project investigates the use of a novel approach to scintimammography (SMM) known as emission tuned aperture computed tomography (ETACT) . In ETACT, a series of projections of the radionuclide distribution in the breast are acquired with fiducial markers. These data are reconstructed into tomographic slices. The hypothesis of this project is that ETACT will increase the diagnostic accuracy of SMM, and can be applied in a simple and practical manner. We have developed simulation models and have used these tools to investigate aperture size, angular disparity, number of projections, and the effect of attenuation and scatter. Apertures of 3-4 mm were determined to be optimal for ETACT. Smaller angular disparity of the projections led to slightly improved contrast but lower axial resolution. Seven projections is a good compromise between image quality and clinical practicality. Monte Carlo simulations have confirmed the findings of our simpler simulations that excluded the effects of scatter and attenuation. Biorthogonal merging of two ETACT image sets leads to improved lesion visualization. We are currently investigating the use of optical, fiducial markers, finalizing the phantom experiments and developing a clinical ETACT prototype.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2001
Accession Number
ADA398373

Entities

People

  • Frederic H. Fahey

Organizations

  • Wake Forest School of Medicine

Tags

Communities of Interest

  • Air Platforms
  • Biomedical

DTIC Thesaurus Topics

  • Breast Cancer
  • Computer Simulations
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Geometry
  • Health Services
  • Imaging Techniques
  • Medical Personnel
  • Monte Carlo Method
  • Prostheses And Implants
  • Prosthetics
  • Simulations
  • Three Dimensional
  • Tomography
  • Two Dimensional
  • X-Ray Computed Tomography

Fields of Study

  • Medicine
  • Physics

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.
  • Medical Imaging.