A calibration approach to glandular tissue composition estimation in digital mammography.
The healthy breast is almost entirely composed of a mixture of fatty, epithelial, and stromal tissues which can be grouped into two distinctly attenuating tissue types: fatty and glandular. Further, the amount of glandular tissue is linked to breast cancer risk, so an objective quantitative analysis of glandular tissue can aid in risk estimation. Highnam and Brady have measured glandular tissue composition objectively. However, they argue that their work should only be used for "relative" tissue measurements unless a careful calibration has been performed. In this work, we perform such a "careful calibration" on a digital mammography system and use it to estimate breast tissue composition of patient breasts. We imaged 0%, 50%, and 100% glandular-equivalent phantoms of varying thicknesses for a number of clinically relevant x-ray techniques on a digital mammography system. From these images, we extracted mean signal and noise levels and computed calibration curves that can be used for quantitative tissue composition estimation. In this way, we calculate the percent glandular composition of a patient breast on a pixelwise basis. This tissue composition estimation method was applied to 23 digital mammograms. We estimated the quantitative impact of different error sources on the estimates of tissue composition. These error sources include compressed breast height estimation error, residual scattered radiation, quantum noise, and beam hardening. Errors in the compressed breast height estimate contribute the most error in tissue composition--on the order of +/-7% for a 4 cm compressed breast height: The spatially varying scattered radiation will contribute quantitatively less error overall, but may be significant in regions near the skinline. It is calculated that for a 4 cm compressed breast height, a residual scatter signal error is mitigated by approximately sixfold in the composition estimate. The error in composition due to the quantum noise, which is the limiting noise source in the system, is shown to be less than 1% glandular for most breasts.
Kaufhold
J
J
General Electric Global Research Center, Niskayuna, New York 12309, USA. kaufhold@crd.ge.com
Thomas
J A
JA
Eberhard
J W
JW
Galbo
C E
CE
Trotter
D E González
DE
D000273:Adipose Tissue / Q000000981:diagnostic imaging*; D002138:Calibration; D005260:Female; D006801:Humans; D008327:Mammography / Q000295:instrumentation / Q000379:methods*; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000295:instrumentation / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012542:Scattering, Radiation; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes