Development and application of a suite of 4-D virtual breast phantoms for optimization and evaluation of breast imaging systems.
Mammography is currently the most widely utilized tool for detection and diagnosis of breast cancer. However, in women with dense breast tissue, tissue overlap may obscure lesions. Digital breast tomosynthesis can reduce tissue overlap. Furthermore, imaging with contrast enhancement can provide additional functional information about lesions, such as morphology and kinetics, which in turn may improve lesion identification and characterization. The performance of these imaging techniques is strongly dependent on the structural composition of the breast, which varies significantly among patients. Therefore, imaging system and imaging technique optimization should take patient variability into consideration. Furthermore, optimization of imaging techniques that employ contrast agents should include the temporally varying breast composition with respect to the contrast agent uptake kinetics. To these ends, we have developed a suite of 4-D virtual breast phantoms, which are incorporated with the kinetics of contrast agent propagation in different tissues and can realistically model normal breast parenchyma as well as benign and malignant lesions. This development presents a new approach in performing simulation studies using truly anthropomorphic models. To demonstrate the utility of the proposed 4-D phantoms, we present a simplified example study to compare the performance of 14 imaging paradigms qualitatively and quantitatively.
Duke Scholars
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Related Subject Headings
- Signal-To-Noise Ratio
- Phantoms, Imaging
- Nuclear Medicine & Medical Imaging
- Mammography
- Imaging, Three-Dimensional
- Image Interpretation, Computer-Assisted
- Humans
- Female
- Contrast Media
- Breast Neoplasms
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Signal-To-Noise Ratio
- Phantoms, Imaging
- Nuclear Medicine & Medical Imaging
- Mammography
- Imaging, Three-Dimensional
- Image Interpretation, Computer-Assisted
- Humans
- Female
- Contrast Media
- Breast Neoplasms