Recent developments in elastography suggest it is possible to image linear and nonlinear elastic parameters of breast tissues as well as shear wave propagation velocity and strains, and these parameters might be useful in non-invasively differentiating benign tumors from breast cancers. However, some commercial elastographic systems have not lived up to their high expectations. Our objectives of this proposal are twofold: 1) to build a virtual breast ultrasound simulation platform to accelerate development of UEI systems;and 2) to investigate mechanistic links between tissue microstructure and corresponding macroscopic mechanical properties of the tissue by using this novel ultrasound simulation infrastructure. The immediate outcome of this research includes a virtual open source software infrastructure for multi-scale biomechanical modeling of female breasts and subsequent ultrasound simulations. In addition to exposing undergraduate students to advanced cancer imaging research, impacts of this research include: 1)improving our understanding of resolution and contrast limits of elastographic systems in a complex but controllable virtual environment;and 2)enhancing our capability to infer micro-structural changes of ECM under image guidance. The latter will open new avenues for breast cancer diagnosis and therapy. Preliminary data demonstrate our research methodology is feasible. This AREA award will provide the Michigan Tech team with resources to train undergraduate and graduate students, obtain data for future NIH funding, and build a sustainable undergraduate research program in breast cancer imaging.
This is a pilot proposal to build a shared virtual ultrasound simulation resource in the public domain for ultrasound-based breast elastography which is becoming a standard imaging modality. New knowledge generated from sophisticated simulations of this kind will shed new light on new imaging mechanisms for breast elastography, thereby opening new avenues for breast cancer diagnosis and therapy.
|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|
|Rosen, David; Jiang, Jingfeng (2018) Fourier-Domain Shift Matching: A Robust Time-of-Flight Approach for Shear Wave Speed Estimation. IEEE Trans Ultrason Ferroelectr Freq Control 65:729-740|
|Peng, Bo; Wang, Yuqi; Hall, Timothy J et al. (2017) A GPU-Accelerated 3-D Coupled Subsample Estimation Algorithm for Volumetric Breast Strain Elastography. IEEE Trans Ultrason Ferroelectr Freq Control 64:694-705|
|Wang, Yu; Peng, Bo; Jiang, Jingfeng (2017) Building an open-source simulation platform of acoustic radiation force-based breast elastography. Phys Med Biol 62:1949-1968|
|Wang, Yu; Wang, Min; Jiang, Jingfeng (2017) An analysis of intrinsic variations of low-frequency shear wave speed in a stochastic tissue model: the first application for staging liver fibrosis. Phys Med Biol 62:1149-1171|
|Rosen, David; Wang, Yu; Jiang, Jingfeng (2017) Virtual Breast Quasi-static Elastography (VBQE). Ultrason Imaging 39:108-125|
|Narkar, Ameya R; Barker, Brett; Clisch, Matthew et al. (2016) pH Responsive and Oxidation Resistant Wet Adhesive based on Reversible Catechol-Boronate Complexation. Chem Mater 28:5432-5439|
|Peng, Bo; Wang, Yu; Yang, Wenjun et al. (2016) Relative Elastic Modulus Imaging Using Sector Ultrasound Data for Abdominal Applications: An Evaluation of Strategies and Feasibility. IEEE Trans Ultrason Ferroelectr Freq Control 63:1432-40|
|Jiang, Jingfeng; Hall, Timothy J (2015) A coupled subsample displacement estimation method for ultrasound-based strain elastography. Phys Med Biol 60:8347-64|
|Guo, Li; Xu, Yan; Xu, Zhengfu et al. (2015) A PDE-Based Regularization Algorithm Toward Reducing Speckle Tracking Noise: A Feasibility Study for Ultrasound Breast Elastography. Ultrason Imaging 37:277-93|
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