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Proceedings Paper

Model-based estimation of breast percent density in raw and processed full-field digital mammography images from image-acquisition physics and patient-image characteristics
Author(s): Brad M. Keller; Diane L. Nathan; Emily F. Conant; Despina Kontos
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Paper Abstract

Breast percent density (PD%), as measured mammographically, is one of the strongest known risk factors for breast cancer. While the majority of studies to date have focused on PD% assessment from digitized film mammograms, digital mammography (DM) is becoming increasingly common, and allows for direct PD% assessment at the time of imaging. This work investigates the accuracy of a generalized linear model-based (GLM) estimation of PD% from raw and postprocessed digital mammograms, utilizing image acquisition physics, patient characteristics and gray-level intensity features of the specific image. The model is trained in a leave-one-woman-out fashion on a series of 81 cases for which bilateral, mediolateral-oblique DM images were available in both raw and post-processed format. Baseline continuous and categorical density estimates were provided by a trained breast-imaging radiologist. Regression analysis is performed and Pearson's correlation, r, and Cohen's kappa, κ, are computed. The GLM PD% estimation model performed well on both processed (r=0.89, p<0.001) and raw (r=0.75, p<0.001) images. Model agreement with radiologist assigned density categories was also high for processed (κ=0.79, p<0.001) and raw (κ=0.76, p<0.001) images. Model-based prediction of breast PD% could allow for a reproducible estimation of breast density, providing a rapid risk assessment tool for clinical practice.

Paper Details

Date Published: 2 March 2012
PDF: 6 pages
Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83130K (2 March 2012); doi: 10.1117/12.912368
Show Author Affiliations
Brad M. Keller, Univ. of Pennsylvania Perelman School of Medicine (United States)
Diane L. Nathan, Univ. of Pennsylvania Perelman School of Medicine (United States)
Emily F. Conant, Univ. of Pennsylvania Perelman School of Medicine (United States)
Despina Kontos, Univ. of Pennsylvania Perelman School of Medicine (United States)


Published in SPIE Proceedings Vol. 8313:
Medical Imaging 2012: Physics of Medical Imaging
Norbert J. Pelc; Robert M. Nishikawa; Bruce R. Whiting, Editor(s)

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