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Compositional breast imaging using a dual‐energy mammography protocol
Author(s) -
Laidevant Aurelie D.,
Malkov Serghei,
Flowers Chris I.,
Kerlikowske Karla,
Shepherd John A.
Publication year - 2010
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3259715
Subject(s) - mammography , repeatability , attenuation , digital mammography , nuclear medicine , breast imaging , biomedical engineering , materials science , medicine , breast cancer , radiology , mathematics , optics , physics , cancer , statistics
Purpose Mammography has a low sensitivity in dense breasts due to low contrast between malignant and normal tissue confounded by the predominant water density of the breast. Water is found in both adipose and fibroglandular tissue and constitutes most of the mass of a breast. However, significant protein mass is mainly found in the fibroglandular tissue where most cancers originate. If the protein compartment in a mammogram could be imaged without the influence of water, the sensitivity and specificity of the mammogram may be improved. This article describes a novel approach to dual‐energy mammography, full‐field digital compositional mammography (FFDCM), which can independently image the three compositional components of breast tissue: water, lipid, and protein. Methods Dual‐energy attenuation and breast shape measures are used together to solve for the three compositional thicknesses. Dual‐energy measurements were performed on breast‐mimicking phantoms using a full‐field digital mammography unit. The phantoms were made of materials shown to have similar x‐ray attenuation properties of the compositional compartments. They were made of two main stacks of thicknesses around 2 and 4 cm. Twenty‐six thickness and composition combinations were used to derive the compositional calibration using a least‐squares fitting approach. Results Very high accuracy was achieved with a simple cubic fitting function with root mean square errors of 0.023, 0.011, and 0.012 cm for the water, lipid, and protein thicknesses, respectively. The repeatability (percent coefficient of variation) of these measures was tested using sequential images and was found to be 0.5%, 0.5%, and 3.3% for water, lipid, and protein, respectively. However, swapping the location of the two stacks of the phantom on the imaging plate introduced further errors showing the need for more complete system uniformity corrections. Finally, a preliminary breast image is presented of each of the compositional compartments separately. Conclusions FFDCM has been derived and exhibited good compositional thickness accuracy on phantoms. Preliminary breast images demonstrated the feasibility of creating individual compositional diagnostic images in a clinical environment.