Related Experiment Video
Updated: May 11, 2026
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
Mammogram image quality as a potential contributor to disparities in breast cancer stage at diagnosis: an
Garth H Rauscher1, Emily F Conant, Jenna A Khan
1School of Public Health, Division of Epidemiology and Biostatistics, University of Illinois at Chicago, M/C 923, Chicago, IL 60612, USA. garthr@uic.edu
Background:
In an ongoing study of racial/ethnic disparities in breast cancer stage at diagnosis, we consented patients to allow us to review their mammogram images, in order to examine the potential role of mammogram image quality on this disparity.
Methods:
In a population-based study of urban breast cancer patients, a single breast imaging specialist (EC) performed a blinded review of the index mammogram that prompted diagnostic follow-up, as well as recent prior mammograms performed approximately one or two years prior to the index mammogram. Seven indicators of image quality were assessed on a five-point Likert scale, where 4 and 5 represented good and excellent quality. These included 3 technologist-associated image quality (TAIQ) indicators (positioning, compression, sharpness), and 4 machine associated image quality (MAIQ) indicators (contrast, exposure, noise and artifacts). Results are based on 494 images examined for 268 patients, including 225 prior images.
Results:
Whereas MAIQ was generally high, TAIQ was more variable. In multivariable models of sociodemographic predictors of TAIQ, less income was associated with lower TAIQ (p < 0.05). Among prior mammograms, lower TAIQ was subsequently associated with later stage at diagnosis, even after adjusting for multiple patient and practice factors (OR = 0.80, 95% CI: 0.65, 0.99).
Conclusions:
Considerable gains could be made in terms of increasing image quality through better positioning, compression and sharpness, gains that could impact subsequent stage at diagnosis.
