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Proceedings Paper

A novel ultrasonic method for measuring breast density and breast cancer risk
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Paper Abstract

Women with high mammographic breast density are at 4- to 6-fold increased risk of developing breast cancer compared to women with fatty breasts. However, current breast density estimations rely on mammography, which cannot provide accurate volumetric breast representation. Therefore, we explored two techniques of breast density evaluation via ultrasound tomography. A sample of 93 patients was imaged with our clinical prototype; each dataset contained 45-75 tomograms ranging from near the chest wall through the nipple. Whole breast acoustic velocity was determined by creating image stacks and evaluating the sound speed frequency distribution. Ultrasound percent density (USPD) was determined by segmenting high sound speed areas from each tomogram using k-means clustering, integrating over the entire breast, and dividing by total breast area. Both techniques were independently evaluated using two mammographic density measures: (1) qualitative, determined by a radiologist's visual assessment using BI-RADS Categories, and (2) quantitative, via semi-automatic segmentation to calculate mammographic percent density (MPD) for craniocaudal and medio-lateral oblique mammograms. ~140 m/s difference in acoustic velocity was observed between fatty and dense BI-RADS Categories. Increased sound speed was found with increased BI-RADS Category and quantitative MPD. Furthermore, strong positive associations between USPD, BI-RADS Category, and calculated MPD were observed. These results confirm that utilizing sound speed, both for whole-breast evaluation and segmenting locally, can be implemented to evaluate breast density.

Paper Details

Date Published: 13 March 2008
PDF: 7 pages
Proc. SPIE 6920, Medical Imaging 2008: Ultrasonic Imaging and Signal Processing, 69200Q (13 March 2008); doi: 10.1117/12.772365
Show Author Affiliations
Carri K. Glide-Hurst, William Beaumont Hospital (United States)
Neb Duric, Karmanos Cancer Institute (United States)
Peter J. Littrup, Karmanos Cancer Institute (United States)

Published in SPIE Proceedings Vol. 6920:
Medical Imaging 2008: Ultrasonic Imaging and Signal Processing
Stephen A. McAleavey; Jan D'hooge, Editor(s)

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