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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Artifact reduction in contrast-enhanced mammography.

Gisella Gennaro1, Enrica Baldan2, Elisabetta Bezzon2

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Insights Into Imaging
|May 13, 2022
PubMed
Summary

A new dual-energy subtraction (DES) algorithm effectively reduces artifacts in contrast-enhanced mammography (CEM) images. The algorithm preserves lesion contrast enhancement, improving image quality for breast cancer screening.

Keywords:
ArtifactContrast agentMammography

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Area of Science:

  • Radiology
  • Medical Imaging
  • Breast Cancer Detection

Background:

  • Contrast-enhanced mammography (CEM) is crucial for breast cancer screening.
  • Dual-energy subtraction (DES) in CEM can be affected by artifacts.
  • Artifacts may obscure or mimic lesions, impacting diagnostic accuracy.

Purpose of the Study:

  • To assess a novel algorithm's efficacy in reducing DES artifacts in CEM.
  • To determine if the new algorithm preserves lesion contrast enhancement.

Main Methods:

  • A retrospective study involved 134 CEM cases from women at high risk for breast cancer.
  • Four expert readers compared standard DES images with those processed by the new algorithm.
  • Artifact intensity and lesion contrast uptake were visually assessed and rated on an ordinal scale.

Main Results:

  • The new algorithm significantly reduced or eliminated common artifacts: 84.5% of breast-in-breast, 84.2% of ripple, and 56.9% of skinfold enhancement artifacts.
  • Artifact intensity was reduced in 12.1% to 28.8% of images.
  • Crucially, lesion contrast enhancement visibility remained unchanged compared to standard DES.

Conclusions:

  • The novel DES algorithm effectively minimizes CEM-related artifacts.
  • The algorithm successfully preserves the visualization of potential lesion contrast enhancement.
  • This technology holds promise for enhancing the diagnostic performance of CEM.