Development of a dynamic 4D anthropomorphic breast phantom for contrast-based breast imaging


Conference Paper

Mammography is currently the most widely accepted tool for detection and diagnosis of breast cancer. However, the sensitivity of mammography is reduced in women with dense breast tissue due to tissue overlap, which may obscure lesions. Digital breast tomosynthesis with contrast enhancement reduces tissue overlap and provides additional functional information about lesions (i.e. morphology and kinetics), which in turn may improve lesion characterization. The performance of such techniques is highly dependent on the structural composition of the breast, which varies significantly across patients. Therefore, optimization of breast imaging systems should be done with respect to this patient versatility. Furthermore, imaging techniques that employ contrast require the inclusion of a temporally varying breast composition with respect to the contrast agent kinetics to enable the optimization of the system. To these ends, we have developed a dynamic 4D anthropomorphic breast phantom, which can be used for optimizing a breast imaging system by incorporating material characteristics. The presented dynamic phantom is based on two recently developed anthropomorphic breast phantoms, which can be representative of a whole population through their randomized anatomical feature generation and various compression levels. The 4D dynamic phantom is incorporated with the kinetics of contrast agent uptake in different tissues and can realistically model benign and malignant lesions. To demonstrate the utility of the proposed dynamic phantom, contrast-enhanced digital mammography and breast tomosynthesis were simulated where a ray-tracing algorithm emulated the projections, a filtered back projection algorithm was used for reconstruction, and dual-energy and temporal subtractions were performed and compared. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Full Text

Duke Authors

Cited Authors

  • Kiarashi, N; Lin, Y; Segars, WP; Ghate, SV; Ikejimba, L; Chen, B; Lo, JY; Dobbins, JT; Nolte, LW; Samei, E

Published Date

  • May 4, 2012

Published In

Volume / Issue

  • 8313 /

International Standard Serial Number (ISSN)

  • 1605-7422

International Standard Book Number 13 (ISBN-13)

  • 9780819489623

Digital Object Identifier (DOI)

  • 10.1117/12.913332

Citation Source

  • Scopus