Local mammographic density as a predictor of breast cancer

Mayu Otsuka, Elaine Harkness, Xin Chen, Emmanouil Moschidis, Megan Bydder, Soujanya Gadde, Yit Lim, Anthony J Maxwell, D Gareth Evans, Anthony Howell, Paula Stavrinos, Mary Wilson, Susan Astley

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


High overall mammographic density is associated with both an increased risk of developing breast cancer and the risk of cancer being masked. We compared local density at cancer sites in diagnostic images with corresponding previous screening mammograms (priors), and matched controls. VolparaTM density maps were obtained for 54 mammograms showing unilateral breast cancer and their priors which had been previously read as normal. These were each matched to 3 controls on age, menopausal status, hormone replacement therapy usage, body mass index and year of prior. Local percent density was computed in 15mm square regions at lesion sites and similar locations in the corresponding images. Conditional logistic regression was used to predict case-control status. In diagnostic and prior images, local density was increased at the lesion site compared with the opposite breast (medians 21.58%, 9.18%, p
Original languageEnglish
Title of host publicationMedical Imaging 2015: Computer-Aided Diagnosis
EditorsLubomir M Hadjiiski, Georgia D Tourassi
Place of PublicationUSA
Number of pages8
Publication statusPublished - 20 Mar 2015
EventSPIE Medical Imaging - Orlando, Florida
Duration: 15 Feb 201520 Feb 2015

Publication series

NameMedical Imaging 2015: Computer-Aided Diagnosis


ConferenceSPIE Medical Imaging
CityOrlando, Florida


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