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Comparing regional breast density using Full-Field Digital Mammograms and Magnetic Resonance Imaging

A preliminary study
 
: Garcia, E.; Oliver, A.; Diez, Y.; Diaz, O.; Georgii, J.; Gubern-Merida, A.; Marti, J.; Marti, R.

Harz, M. (Ed.); Mertzanidou, T. (Ed.); Hipwell, J. (Ed.) ; International Society of Medical Image Computing and Computer-Assisted Intervention -MICCAI-:
MICCAI-BIA 2015, Proceedings of the 3rd MICCAI Workshop on Breast Image Analysis : Munich, Germany, 2015
München, 2015
S.33-40
Workshop on Breast Image Analysis (MICCAI-BIA) <3, 2015, Munich>
Englisch
Konferenzbeitrag
Fraunhofer MEVIS ()

Abstract
Breast density is well established as an important risk factor for the development of breast cancer. Therefore, its objective estimation has been the focus of research in the past decades. In addition to global volumetric measures, the local distribution and patterns of this density are currently being investigated to determine whether they can provide complementary information for risk assessment. This paper proposes a framework to evaluate the correlation between local spatial distribution of dense tissue in full-field digital mammograms (FFDM) using a density estimation software (VolparaTM) and magnetic resonance imaging (MRI). Initial results with 51 patients (204 images) showed a significant correlation using several local measures, the largest being 0.81. This indicates that local density patterns estimated in FFDM correlate well with those in MRI. However, pixelwise measures failed to yield the same degree of correlation. This may indicate that the areas where tissue densities are located in both approaches are comparable, but small variations in pixelwise tissue distribution between both approaches exist.

: http://publica.fraunhofer.de/dokumente/N-496972.html