Abstract
Mammography, the most effective early breast cancer detection technique, is associated with the risk of missed lesions in dense breasts, and excessive X-ray exposure. Accurate estimations of glandularity and radiation dose are important during screening. We propose a novel, inexpensive method for accurate glandularity quantification using pixel values in clinical digital mammograms and X-ray exposure spectra. Glandularities were calculated for 314 mammograms in Japanese women, and the Dance formula c-factor was applied to estimate breast doses. To investigate the relationship between breast thickness and missed lesions, images were classified into four categories based on the rate of missed lesions, and correlated with breast thickness. Glandularity decreased with increasing compressed breast thickness, indicating that commonly used breast doses (assumed 50% glandularity) significantly overestimate thin breasts and underestimate thick breasts. The missed lesion rate was higher for thinner compressed breast thicknesses. Accurate glandularity estimation could thus promote individualized screening mammography.
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Yamamuro, M. et al. (2016). Accurate Quantification of Glandularity and Its Applications with Regard to Breast Radiation Doses and Missed Lesion Rates During Individualized Screening Mammography. In: Tingberg, A., Lång, K., Timberg, P. (eds) Breast Imaging. IWDM 2016. Lecture Notes in Computer Science(), vol 9699. Springer, Cham. https://doi.org/10.1007/978-3-319-41546-8_47
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DOI: https://doi.org/10.1007/978-3-319-41546-8_47
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