Artifacts in contrast-enhanced mammography: are there differences between vendors?
Saish Neppalli1, Meredith A Kessell2, Carolyn R Madeley2
1University of Western Australia Medical School, Perth, Western Australia 6009, Australia; Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia.
Clinical Imaging
|July 26, 2021
Summary
Contrast-Enhanced Mammography (CEM) artifacts differ between GE and Hologic systems. Understanding these vendor-specific imaging artifacts is crucial for accurate breast cancer diagnosis.
Area of Science:
- Medical Imaging
- Radiology
- Breast Imaging
Background:
- Contrast-Enhanced Mammography (CEM) utilizes dual-energy subtracted (DES) imaging to visualize neovascularity in breast tissue.
- Artifacts in DES images can potentially impact diagnostic accuracy.
- Identifying and characterizing these artifacts is essential for reliable interpretation.
Purpose of the Study:
- To review and compare artifacts on dual-energy subtracted (DES) images from two different Contrast-Enhanced Mammography (CEM) equipment vendors.
- To assess the incidence and subjective severity of these artifacts.
Main Methods:
- Retrospective review of 200 CEM studies (100 GE, 100 Hologic) from September 2013 to March 2017.
- Artifact categorization and severity grading by consensus of a breast radiologist and medical imaging technologists.
- Statistical comparison of artifact incidence (relative risk) and severity (Wilcoxon rank-sum test) between vendors.
Main Results:
- Specific artifacts like 'elephant rind' and 'corrugations' were exclusive to Hologic equipment.
- Hologic images showed significantly more 'cloudy fat' and 'negative rim around lesion' artifacts (p<0.05).
- GE images exhibited a higher incidence of 'halo' and 'ripple' artifacts (p<0.05), with greater severity for 'cloudy fat' on Hologic and 'halo'/'ripple' on GE.
Conclusions:
- Vendor-specific differences exist in the type, incidence, and severity of Contrast-Enhanced Mammography artifacts.
- Discrepancies in dual-energy image processing algorithms are likely contributors.
- Further research is warranted to fully understand and mitigate these imaging variations.
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