Paper
29 May 2024 Image quality in mammograms with low compressed breast thicknesses
J. Loveland, A. Mackenzie
Author Affiliations +
Proceedings Volume 13174, 17th International Workshop on Breast Imaging (IWBI 2024); 131740Y (2024) https://doi.org/10.1117/12.3026474
Event: 17th International Workshop on Breast Imaging (IWBI 2024), 2024, Chicago, IL, United States
Abstract
Following a number of reports of poor image quality in mammograms with particularly low compressed breast thicknesses in the UK National Health Service Breast Screening Programmes a pilot study was undertaken to more formally assess and quantify the problem. Stratified random sampling was used to select images from a large database of mammograms (OPTIMAM). Visual grading characteristic curves were used to compare image quality between mammograms with compressed breast thicknesses in two ranges: 55mm to 65mm inclusive and less than or equal to 20mm. It was found that breasts with a compressed thickness of 20mm or less were on average ranked lower for image quality than breasts in the 55mm to 65mm thickness range. Evidence was found indicating that in some cases the poor image quality was a result of insufficient dose under automatic exposure control. The most extreme cases contained no useful clinical information at all and arguably the affected clients will not have benefitted from attending breast screening. There is evidence that automatic exposure control systems struggle to deliver high enough exposures for dense breasts with low compressed breast thicknesses. For such cases higher dose manual factors may be beneficial. If AI readers are adopted in the future care must be taken to ensure that under-served, small subgroups such as this are not lost in the overall performance statistics.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
J. Loveland and A. Mackenzie "Image quality in mammograms with low compressed breast thicknesses", Proc. SPIE 13174, 17th International Workshop on Breast Imaging (IWBI 2024), 131740Y (29 May 2024); https://doi.org/10.1117/12.3026474
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KEYWORDS
Breast

Image quality

Mammography

Artificial intelligence

Tissues

X-rays

Automatic exposure

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