Early diagnosis of breast cancer is critical for favorable clinical outcomes. Many traditional imaging methods have suboptimal sensitivity for breast cancer detection, particularly in women with dense breasts. Methods with high sensitivity, such as magnetic resonance imaging (MRI), suffer from low specificity rates, resulting in unnecessary biopsies. In normal clinical practice, majority of biopsy cases turn out to be false positives, leading to unnecessary biopsies. Undergoing biopsy for benign disease can result in significant cost and great emotional distress. Any reduction in false positives can be significant in terms of patient care, and healthcare cost. It is, therefore, important to develop new low-cost breast imaging techniques with high sensitivity and specificity. The long-term goal of this project is to develop an ultrasound-based breast imaging technique to improve the diagnostic specificity in breast cancer. To improve the specificity, one needs to measure a parameter of tissue that is highly correlated to tissue pathology. One such parameter for breast is the shear elastic modulus. To date, several methods have been developed for mapping the shear elasticity of tissue. In almost all cases, these methods are based on the assumption of plane shear wave propagation in tissue. However, this assumption can be violated in the complex structure of biological soft tissues, leading to errors in elasticity estimation and image artifacts, which may produce false positives or false negatives. For this reason, developing an elasticity mapping technique that does not rely on this assumption is of significant value. The short-term goal of the proposed research is to develop a new method for viscoelasticity imaging of breast that can work with any type of wave, and not restricted to plane shear waves. The proposed method, called radiation force computed elastography (RFCE), produces quantitative map of tissue viscoelasticity. This method uses ultrasound radiation force (URF) to induce a vibration in tissue, and then measures the resulting motion. Such motion does not have to be a plane shear wave or any other particular wave mode. RFCE is anticipated to produce more reliable and accurate results than other viscoelasticity imaging methods that are based on the assumption of plane shear wave. RFCE treats viscoelasticity estimation as a stochastic problem, a robust approach when conditions are not well defined. Goal of this project are achieved in 3 Specific Aims: (1) Extension and implementation of a novel computational inverse problem framework to viscoelasticity mapping using URF, (2) Validation of the inverse problem framework using laboratory phantoms and tissue samples, and (3) Pilot Studies- Estimation of viscoelastic parameters of masses in human breast.
The first Aim i s focused on developing the computational method for estimating viscoelasticity map of the object from motion data.
The second aim optimizes RFCE on phantoms and tissue sample and prepares it for the human study in the third aim.
Aim 3 is focused on evaluating the performance of RFCE in identifying masses in breast in clinical settings. Successful completion of this project will have a significan impact in breast cancer imaging.
It has been established that cancerous masses are harder than noncancerous masses. Therefore, one way to diagnose cancer is to measure the stiffness of masses. Based on this idea, the goal of this project is to develop new tools for measuring the stiffness of tissue. The new tool, which is called RFCE, will be able to produce a map of breast stiffness, which a physician can use to identify cancerous and non-cancerous masses.
|Kumar, Viksit; Denis, Max; Gregory, Adriana et al. (2018) Viscoelastic parameters as discriminators of breast masses: Initial human study results. PLoS One 13:e0205717|
|Bayat, Mahdi; Nabavizadeh, Alireza; Kumar, Viksit et al. (2018) Automated In Vivo Sub-Hertz Analysis of Viscoelasticity (SAVE) for Evaluation of Breast Lesions. IEEE Trans Biomed Eng 65:2237-2247|
|Nayak, Rohit; Kumar, Viksit; Webb, Jeremy et al. (2018) Non-contrast agent based small vessel imaging of human thyroid using motion corrected power Doppler imaging. Sci Rep 8:15318|
|Gregory, Adriana; Bayat, Mahdi; Kumar, Viksit et al. (2018) Differentiation of Benign and Malignant Thyroid Nodules by Using Comb-push Ultrasound Shear Elastography: A Preliminary Two-plane View Study. Acad Radiol 25:1388-1397|
|Zou, Zilong; Aquino, Wilkins; Harari, Isaac (2017) Nitsche's Method For Helmholtz Problems with Embedded Interfaces. Int J Numer Methods Eng 110:618-636|
|Ghosh, Susanta; Zou, Zilong; Babaniyi, Olalekan et al. (2017) Modified error in constitutive equations (MECE) approach for ultrasound elastography. J Acoust Soc Am 142:2084|
|Nabavizadeh, Alireza; Kinnick, Randall R; Bayat, Mahdi et al. (2017) Automated Compression Device for Viscoelasticity Imaging. IEEE Trans Biomed Eng 64:1535-1546|
|Diaz, Manuel I; Aquino, Wilkins; Bonnet, Marc (2015) A Modified Error in Constitutive Equation Approach for Frequency-Domain Viscoelasticity Imaging Using Interior Data. Comput Methods Appl Mech Eng 296:129-149|
|Gregory, Adriana; Bayat, Mahdi; Denis, Max et al. (2015) An experimental phantom study on the effect of calcifications on ultrasound shear wave elastography. Conf Proc IEEE Eng Med Biol Soc 2015:3843-6|
|Denis, Max; Bayat, Mahdi; Mehrmohammadi, Mohammad et al. (2015) Update on Breast Cancer Detection Using Comb-Push Ultrasound Shear Elastography. IEEE Trans Ultrason Ferroelectr Freq Control 62:1644-50|