? Breast cancer is the second-leading cause of cancer deaths in women. Over 200,000 new cases of invasive breast cancer are expected in the USA this year alone. It is anticipated that nearly 40,000 women in the USA would die of breast cancer in 2002. Breast self examination and clinical breast examination (palpation) are the most frequently used diagnostic tools for detecting breast abnormalities, and most breast abnormalities are detected with palpation. The overall goal of this project is the development of tools that will improve the classification of breast lesions, particularly in mammographically-dense breasts using elasticity imaging. The basis of the proposed work is our successful real-time implementation of elasticity imaging on a commercially available ultrasound scanner and initial in vivo results on patients with breast disease. Measurements of the bulk elastic properties of in vitro tissues showed that most breast tissues have non-linear stress-strain relationships, but the non-linearity was highest in cancers. We have observed relative non-linearity in mechanical strain among in vivo breast tissue in our preliminary studies. To enhance and extend that work, we propose the following specific aims: 1) significantly improve the quality of strain image sequences through improved motion tracking and error detection and correction; 2) improve the data acquisition and computational capacity and flexibility of the clinical system by porting the application to a new platform (the Siemens Antares); 3) interface a pressure sensor array to the clinical sonography system to provide data acquisition feedback and encode and display the nonlinearity in the stress-strain relationship of tissues; 4) test these methods with simulated data and experiments with phantoms and human subjects; 5) develop tools to teach clinicians the standard measurement techniques for estimating bulk material properties, such as Young's modulus, how to adapt those techniques to scanning the human body. The result of this effort will be a clinically useful tool for examining the mechanical response of human tissues, and a set of training tools to allow the skilled ultrasound clinician to efficiently learn to use these new tools. ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA100373-01A1
Application #
6729336
Study Section
Diagnostic Imaging Study Section (DMG)
Program Officer
Croft, Barbara
Project Start
2004-04-01
Project End
2009-03-31
Budget Start
2004-04-01
Budget End
2005-03-31
Support Year
1
Fiscal Year
2004
Total Cost
$290,546
Indirect Cost
Name
University of Wisconsin Madison
Department
Physics
Type
Schools of Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Jiang, Jingfeng; Peng, Bo (2018) A Normalized Shear Deformation Indicator for Ultrasound Strain Elastography in Breast Tissues: An In Vivo Feasibility Study. Biomed Res Int 2018:2053612
Vajihi, Zara; Rosado-Mendez, Ivan M; Hall, Timothy J et al. (2018) Low Variance Estimation of Backscatter Quantitative Ultrasound Parameters Using Dynamic Programming. IEEE Trans Ultrason Ferroelectr Freq Control 65:2042-2053
Tyagi, Mohit; Wang, Yuqi; Hall, Timothy J et al. (2017) Improving three-dimensional mechanical imaging of breast lesions with principal component analysis. Med Phys 44:4194-4203
Liu, Tengxiao; Hall, Timothy J; Barbone, Paul E et al. (2017) Inferring spatial variations of microstructural properties from macroscopic mechanical response. Biomech Model Mechanobiol 16:479-496
Liu, Tengxiao; Babaniyi, Olalekan A; Hall, Timothy J et al. (2015) Noninvasive In-Vivo Quantification of Mechanical Heterogeneity of Invasive Breast Carcinomas. PLoS One 10:e0130258
Goenezen, Sevan; Dord, Jean-Francois; Sink, Zac et al. (2012) Linear and nonlinear elastic modulus imaging: an application to breast cancer diagnosis. IEEE Trans Med Imaging 31:1628-37
Pavan, Theo Z; Madsen, Ernest L; Frank, Gary R et al. (2012) A nonlinear elasticity phantom containing spherical inclusions. Phys Med Biol 57:4787-804
Xu, Haiyan; Varghese, Tomy; Jiang, Jingfeng et al. (2012) In vivo classification of breast masses using features derived from axial-strain and axial-shear images. Ultrason Imaging 34:222-36
Hall, Timothy J; Barbone, Paul; Oberai, Assad A et al. (2011) Recent results in nonlinear strain and modulus imaging. Curr Med Imaging Rev 7:313-327
Herd, Maria-Teresa; Hall, Timothy J; Jiang, Jingfeng et al. (2011) Improving the statistics of quantitative ultrasound techniques with deformation compounding: an experimental study. Ultrasound Med Biol 37:2066-74

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