Dual Modality Imaging System for Breast Cancer Research

Abstract

In the 25-40% of the general female population with radiodense breast parenchyma, clinically occult lesions may be invisible in the screen-film mammogram. Even if suspicious masses are detected, determination of the benign or malignant nature of a mass is often impossible from the x-ray image. There is thus a need for diagnostic procedures that can noninvasively help characterize suspicious breast lesions. Scintimammography is an imaging technique that shows promise as an adjunct diagnostic tool in problem solving mammography, for monitoring recurrence after surgery, and in the assessment of multidrug-resistance. However, because clinical Anger cameras have only moderate spatial resolution and are difficult to position close to the breast, small lesions are difficult to detect. In addition, no direct means exists of correlating mammographic and scintigraphic information because of the significantly different shape of the breast in mammography (compressed) and scintimammography (prone, pendulant). We are developing an imaging system that overcomes these problems by combining digital x-ray mammography and gamma emission scintigraphy in a single, integrated system. The system is mounted on a standard upright mammography unit, and can easily be placed in a typical mammography room, providing accessibility even for small breast imaging clinics not associated with major medical centers.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2004
Accession Number
ADA429091

Entities

People

  • Mark B. Williams

Organizations

  • University of Virginia

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Breast Cancer
  • Detection
  • Detectors
  • Diagnostic Imaging
  • Emission Spectra
  • Gamma Decay
  • Gamma Rays
  • High Resolution
  • Imaging Techniques
  • Measurement
  • Medical Personnel
  • Neoplasms
  • Standards
  • Three Dimensional
  • Two Dimensional
  • X Rays
  • X-Ray Detectors

Fields of Study

  • Medicine
  • Physics

Readers

  • Computer Vision.
  • Oncology and Biomarker-Based Cancer Detection.