Keywords:
Image verification, Cancer, Diagnostic procedure, Decision analysis, MR, Mammography, Oncology, Breast
Authors:
D. LA FORGIA1, R. Dentamaro2, V. Didonna2, A. Fanizzi3, L. Losurdo2, M. Raffaella2, P. Tamborra2, M. Telegrafo2, M. Moschetta2; 1BARI, BA/IT, 2BARI/IT, 3Bari, Italy/IT
DOI:
10.26044/ecr2019/C-3045
Aims and objectives
A new technology in mammography,
known as Contrast-Enhanced Spectral Mammography (CESM),
is affirming itself as a valide alternative to the breast Magnetic Resonance Imaging (MRI) since combines digital mammography (DM) with the benefits of contrast imaging [1,2].
This technique allows the acquisition of multiple views performed in dual-energy exposure after a single injection of a iodinated contrast medium (CM) [3].
In this way,
low- (LE) and high-energy (HE) images are obtained: the first images are the same properties os digital mammograms,
while the second ones are not visible on the monitor.
Indeed,
they cannot be consulted by radiologists since they are used to be recombined with the LE images by spectral subtraction; the so obtained recombined (RC) images are used for diagnosis purpose.
In both techniques,
it can happen that the normal tissue becomes impregnated by the CM depending on several factors as the vascularity and the permeability of the tissue,
and the effects of a endocrine therapy.
This breast activity is known as background parenchymal enhancement (BPE) and is qualitatively described by four categories: minimal,
mild,
moderate and marked [2,4].
The use of the contrast medium,
both in the MRI and in the CESM examination,
allows to evaluate the presence of abnormal vascularization correlated to the neoangiogenesis of breast carcer [5,6].
However,
these techniques show substantial differences about costs,
dependence from hormonal effects,
patient tollerability and possible delays in booking with postponement of diagnosis and clinical treatment [7-10].
The aim of this work is to study the limits and estimate the diagnostic performance of these two methods on a common dataset.