The aim of our study involved the assessment of B-mode imaging and elastography with regard to their ability to predict mammographic density (MD) without X-rays. Women, who underwent routine mammography, were prospectively examined with additional B-mode ultrasound and elastography. MD was assessed quantitatively with a computer-assisted method (Madena). The B-mode and elastography images were assessed by histograms with equally sized gray-level intervals. Regression models were built and cross validated to examine the ability to predict MD. The results of this study showed that B-mode imaging and elastography were able to predict MD. B-mode seemed to give a more accurate prediction. R 2 for B-mode image and elastography were 0.67 and 0.44, respectively. Areas in the B-mode images that correlated with mammographic dense areas were either dark gray or of intermediate gray levels. Concerning elastography only the gray levels that represent extremely stiff tissue correlated positively with MD. In conclusion, ultrasound seems to be able to predict MD. Easy and cheap utilization of regular breast ultrasound machines encourages the use of ultrasound in larger case–control studies to validate this method as a breast cancer risk predictor. Furthermore, the application of ultrasound for breast tissue characterization could enable comprehensive research concerning breast cancer risk and breast density in young and pregnant women.
aDepartment of Gynecolgoy and Obstetrics, University Breast Center Franconia
bUniversity Breast Center Franconia, Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University
cComprehensive Cancer Center, Erlangen-Nuremberg
dFraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany
eDepartment of Medicine, Division of Hematology and Oncology, Dafid Geffen School of Medicine, University of California, Los Angeles, California, USA
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Correspondence to Sebastian Michael Jud, MD, Department of Gynecology and Obstetrics, University Breast Center Franconia, University Hospital Erlangen of the Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center, Erlangen Nuremberg, Germany Tel: +49 9131 85 33 553; fax: +49 9131 85 33 938; e-mail: email@example.com Sebastian Michael Jud and Lothar Häberle contributed equally to this study.
Received September 7, 2011
Accepted October 16, 2011