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Artifacts in contrast-enhanced mammography: are there differences between vendors?

      Highlights

      • The type, incidence and severity of CEM artifacts differ between equipment vendors.
      • Vendor specific algorithms that create DE CEM images may play an important role.
      • Research into the clinical impact of CEM artifacts is needed.
      • “Cloudy fat” may mask or mimic subtly enhancing lesions.
      • Archiving raw LE and HE image data could allow re-processing and machine learning.

      Abstract

      Purpose

      Contrast-Enhanced Mammography (CEM) produces a dual-energy subtracted (DES) image that demonstrates iodine uptake (neovascularity) in breast tissue. We aim to review a range of artifacts on DES images produced using equipment from two different vendors and compare their incidence and subjective severity.

      Methods

      We retrospectively reviewed CEM studies performed between September 2013 and March 2017 using GE Senographe Essential (n = 100) and Hologic Selenia Dimensions (n = 100) equipment. Artifacts were categorized and graded in severity by a subspecialist breast radiologist and one of two medical imaging technologists in consensus. The incidence of artifacts between vendors was compared by calculating the relative risk, and the severity gradings were compared using a Wilcoxon rank-sum test.

      Results

      Elephant rind, corrugations and the black line on chest wall artifact were seen exclusively in Hologic images.
      Artifacts such as cloudy fat, negative rim around lesion and white line on pectoral muscle were seen in significantly more Hologic images (p < 0.05) whilst halo, ripple, skin line enhancement, black line on pectoral muscle, bright pectorals, chest wall high-lighting and air gap were seen in significantly more GE images (p < 0.05).
      The severity gradings for cloudy fat had a significantly higher mean rank in Hologic images (p < 0.001) whilst halo and ripple artifacts had a significantly higher mean rank in GE images (p < 0.001 and p = 0.028 respectively).

      Conclusion

      The type, incidence and subjective severity of CEM-specific artifacts differ between vendors. Further research is needed, but differences in algorithms used to produce the DE image are postulated to be a significant contributor.

      Keywords

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