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Proceedings Paper

Detection and characterization of breast masses with ultrasound tomography: clinical results
Author(s): Neb Duric; Peter Littrup; Cuiping Li; Olsi Rama; Lisa Bey-Knight; Steven Schmidt; Jessica Lupinacci
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Paper Abstract

We report on a continuing assessment of the in-vivo performance of an operator independent breast imaging device based on the principles of acoustic tomography. This study highlights the feasibility of mass characterization using criteria derived from reflection, sound speed and attenuation imaging. The data were collected with a clinical prototype at the Karmanos Cancer Institute in Detroit MI from patients recruited at our breast center. Tomographic sets of images were constructed from the data and used to form 3-D image stacks corresponding to the volume of the breast. Masses were identified independently by either ultrasound or biopsy and their locations determined from conventional mammography and ultrasound exams. The nature of the mass and its location were used to assess the feasibility of our prototype to detect and characterize masses in a case-following scenario. Our techniques generated whole breast reflection images as well as images of the acoustic parameters of sound speed and attenuation. The combination of these images reveals major breast anatomy, including fat, parenchyma, fibrous stroma and masses. The three types of images are intrinsically co-registered because the reconstructions are performed using a common data set acquired by the prototype. Fusion imaging, utilizing thresholding, is shown to visualize mass characterization and facilitates separation of cancer from benign masses. These initial results indicate that operatorindependent whole-breast imaging and the detection and a characterization of cancerous breast masses are feasible using acoustic tomography techniques.

Paper Details

Date Published: 21 March 2009
PDF: 8 pages
Proc. SPIE 7265, Medical Imaging 2009: Ultrasonic Imaging and Signal Processing, 72651G (21 March 2009); doi: 10.1117/12.812994
Show Author Affiliations
Neb Duric, Karmanos Cancer Institute, Wayne State Univ. (United States)
Peter Littrup, Karmanos Cancer Institute, Wayne State Univ. (United States)
Cuiping Li, Karmanos Cancer Institute, Wayne State Univ. (United States)
Olsi Rama, Karmanos Cancer Institute, Wayne State Univ. (United States)
Lisa Bey-Knight, Karmanos Cancer Institute, Wayne State Univ. (United States)
Steven Schmidt, Karmanos Cancer Institute, Wayne State Univ. (United States)
Jessica Lupinacci, Karmanos Cancer Institute, Wayne State Univ. (United States)


Published in SPIE Proceedings Vol. 7265:
Medical Imaging 2009: Ultrasonic Imaging and Signal Processing
Stephen A. McAleavey; Jan D'hooge, Editor(s)

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