Currently, there is an urgent need for pre-biopsy assessment of thyroid nodules. Conventional ultrasound is quite sensitive for detection of thyroid nodules;however, low specificity of traditional ultrasound leads to a great number of unnecessary (i.e. benign) biopsies that causes a significant financial and physical burden to the patients. To overcome the present challenging dilemma, it is thus important to develop new low- cost and noninvasive techniques to evaluate thyroid nodules with high sensitivity and specificity. The purpose of our research is to advance, optimize and evaluate the efficacy of a new noninvasive method called Multispectral Imaging and Elasticity Assessment (MIEA), which is comprised of three ultrasound-based techniques: vibro-acoustography (VA), comb-push ultrasound shear wave elastography (CUSE), and shear wave dispersion ultrasound vibrometry (SDUV) for characterization of thyroid nodules. The term multispectral refers to the concept of evaluating thyroid tissue at multiple frequency bands to obtain maximum information. The MIEA method will provide additional information not available from diagnostic US imaging. VA is an imaging method that provides information about the nodule shape and the presence of microcalcifications in the nodules, CUSE is a method for 2D mapping of elasticity, and SDUV is a method for point measurement of elasticity and viscosity. Both elasticity and calcifications are important in diagnosis of malignant nodules and will evaluate the effects of viscosity in this differentiation. The long-term goal of this project is to develop a new tool for assessment of thyroid nodules. Our hypothesis is that the MIEA method improves the sensitivity and specificity of thyroid cancer detection. Hence by improving the selection of thyroid nodules for biopsy, this method reduces the number of unnecessary FNAB and the associated cost and burden to the patients. MIEA can be implemented on conventional ultrasound scanners, and measurements can be made under the guidance of B-mode ultrasound imaging using the same ultrasonic probe. The proposed MIEA method is fast, low cost, portable, and noninvasive, thus it can be available to a large patient population. This proposal focuses on two specific Aims.
Aim # 1: Prepare system for patient studies - Advance, optimize, and automate the MIEA method for human thyroid study;
Aim # 2: Human study - Assess diagnostic value of the MIEA method in differentiation of thyroid nodules by correlating the results to surgical pathology as the gold standard. Approach: VA, SDUV, and CUSE will be implemented on a programmable ultrasound system and their performance will be tested and optimized using thyroid-mimicking phantoms. The results will be validated using independent measurements. In the second Aim, we will conduct a human study on a group of patients who are scheduled to have clinically-indicated thyroid biopsy for suspected thyroid nodules. VA imaging, 2D elasticity mapping by CUSE, and viscoelasticity measurement by SDUV will be performed on these patients and the results will be correlated with the findings of surgical biopsy as reported by the pathologist. The results will be used to evaluate the sensitivity and specificity of MIEA for differentiation of thyroid nodules.

Public Health Relevance

It is known that cancerous nodules are harder than the benign ones. Therefore, scientists have been trying to develop new imaging tools that are sensitive to tissue stiffness. Also, presence of calcification in thyroid nodules is associated with cancer. Thi project is about developing and applying a new method called MIEA for accurate measurement of thyroid nodule stiffness, imaging, and detecting the presence of calcification. This new tool will help improving detection and differentiation of thyroid nodules, which will eventually help physicians in improving diagnosis of thyroid cancer.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB017213-01A1
Application #
8787587
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Liu, Christina
Project Start
2014-07-01
Project End
2018-06-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
City
Rochester
State
MN
Country
United States
Zip Code
55905
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
Mehrmohammadi, Mohammad; Song, Pengfei; Meixner, Duane D et al. (2015) Comb-push ultrasound shear elastography (CUSE) for evaluation of thyroid nodules: preliminary in vivo results. IEEE Trans Med Imaging 34:97-106
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