Learning objectives
To illustrate what volumetric breast density is and how it can be estimated from digital mammograms.
To show the results of quantitative breast density measurements on mammography images of 527 patients.
To describe potential applications of volumetric breast density in clinical practice.
Background
Mammography (MG) is used for the screening and diagnosis of breast cancer.
However,
breasts can have a wide range of appearance on mammography,
associated with differences in tissue composition.
In terms of X-ray absorption,
the breast consists mainly of two components: fibroglandular tissue and fat.
Fibroglandular tissue attenuates X-rays more than fat,
and,
as such,
is brighter on a radiograph of the breast,
while fat is darker.
Bright image regions are associated with fibroglandular tissue and the amount of “brightness” on breast images is referred...
Imaging findings OR Procedure details
2240 mammography images from 527 women acquired by two GE digital systems (a Senographe DS and a Senographe Essential) were processed by Volpara.
Patient age distribution was between 32 and 86 years,
median 51 y (Figure 7).
Breast thickness values were normally distributed (Figure 8) while breast volume and breast density showed log-normal distribution (Figures 9 and 10).
It can be noticed that all the analyzed breasts showed density value below 50%,
for long time considered the “typical value” for most breasts [7].
Breast density...
Conclusion
Volumetric breast density software allows the extraction of objective data on breast density from digital mammograms,
which have potential to become helpful in tailoring patient workups [9-10],
in order to overcome mammography diagnostic limitations for highly dense breasts.
References
MJ Yaffe (2008),
Review mammographic density: Measurement of mammographic density,
Breast Cancer Research 10:209-219.
NF Boyd,
H Guo,
LJ Martin et al (2007),
Mammographic density and risk and detection of breast cancer,
N Engl J Med 356:227-236.
AI Phipps,
DSM Buist,
KE Malone et al (2012),
Breast density,
body mass index,
and risk of tumor marker-defined subtypes of breast cancer,
Ann Epidemiol 22:340-348.
American College of Radiology (ACR),
Breast Imaging Reporting and Data System (BI-RADS),
Reston,
Va: American College of Radiology 2003.
R Highnam,
M...
Personal Information
Gisella Gennaro,
Radiology Unit,
Veneto Institute of Oncology (IOV),
IRCCS,
Padua,
Italy.
Email:
[email protected]
Ralph Highnam,
Matakina International Ltd.
Email:
[email protected]