Abstract
Interest in measuring breast tissue density due to its association with breast cancer risk grows, though the majority of studies use qualitative density measures manually reported by radiologists, which are time-consuming and costly. The purpose of this study was to compare the accuracy of Hologic’s FDA-approved, commercially available automatic quantitative Quantra technique to a semi-automatic quantitative MRI-based Fuzzy C-Means technique in a screening population.
MRI and mammographic images were retrospectively analyzed from 123 women who had both types of exams within four years, a BIRADs diagnosis outcome of 1 or 2, and no history of breast cancer or surgery. Both techniques produced three measures: total breast volume, fibroglandular tissue volume, and percent fibroglandular tissue, which were compared.
Correlations between the three measures produced by the two techniques were mixed, with total volume having the highest correlation (R2=0.8909), percent fibroglandular density having moderate correlation (R2=0.5015), and fibroglandular tissue volume having the lowest correlation (R2=0.3853). Quantra results for percent fibroglandular density were significantly compressed in comparison with that of MRI, by about two-fold.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Shepherd, J.A., Kerlikowske, K., Ma, L., Duewer, F., Fan, B., Wang, J., Malkov, S., Vittinghoff, E., Cumming, S.: Volume of Mammographic Density and Risk of Breast Cancer. Cancer Epidemiol. Biomarkers Prev. 20, 1473–1482 (2011)
Klifa, C., Carballido-Gamio, J., Wilmes, L., Laprie, A., Lobo, C., DeMicco, E., Watkins, M., Shepherd, J., Gibbs, J., Hylton, N.: Quantification of Breast Tissue from MR data using Fuzzy Clustering. In: Proc. of 26th Annual International Conference of IEEE: Engineering in Medicine and Biology Society 2004, San Francisco, CA, vol. 1, pp. 1667–1670 (2004)
Hartman, K., Highnam, R., Warren, R., Jackson, V.: Volumetric Assessment of Breast Tissue Composition from FFDM Images. In: Krupinski, E.A. (ed.) IWDM 2008. LNCS, vol. 5116, pp. 33–39. Springer, Heidelberg (2008)
Kontos, D., Xing, Y., Bakic, P.R., Conant, E.F., Maidment, A.D.A.: A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: Results from a high-risk population. In: Karssemeijer, N., Summers, R. (eds.) Proc. of SPIE, Medical Imaging 2010: Computer-Aided Diagnosis, San Diego, CA, vol. 7624, p. 762409 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, J., Aziz, A., Newitt, D., Joe, B.N., Hylton, N., Shepherd, J.A. (2012). Comparison of Hologic’s Quantra Volumetric Assessment to MRI Breast Density. In: Maidment, A.D.A., Bakic, P.R., Gavenonis, S. (eds) Breast Imaging. IWDM 2012. Lecture Notes in Computer Science, vol 7361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31271-7_80
Download citation
DOI: https://doi.org/10.1007/978-3-642-31271-7_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31270-0
Online ISBN: 978-3-642-31271-7
eBook Packages: Computer ScienceComputer Science (R0)