2D Shear Wave Imaging in Gaussian Noise and Reflection Media

Tran Quang Huy, Pham Thi Thu Ha, Tran Binh Duong, Nguyen Quang Vinh, Nguyen Thi Hoang Yen, Tran Duc Tan

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Published Dec 8, 2021
DOI: https://doi.org/10.25073/2588-1124/vnumap.4631

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QUANG HUY, Tran et al. 2D Shear Wave Imaging in Gaussian Noise and Reflection Media. VNU Journal of Science: Mathematics - Physics, [S.l.], v. 37, n. 4, dec. 2021. ISSN 2588-1124. Available at: <https://js.vnu.edu.vn/MaP/article/view/4631>. Date accessed: 27 dec. 2024. doi: https://doi.org/10.25073/2588-1124/vnumap.4631.
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Vol 37 No 4
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Original Articles

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Abstract

Shear wave imaging (SWI) is a rapid and convenient method of collecting images of tissues in the region of interest. SWI is based on the mechanical properties of soft tissues named the complex shear modulus (CSM). The complex shear modulus consisting of the elasticity and the viscosity, is useful for diagnosing pathological tissue conditions. Previous studies have not fully exploited the estimation of CSM in the medium containing Gaussian noise and the shear wave's reflection phenomenon. In this study, we focused on the model of shear wave propagation in the 2D environment by the time domain finite difference method (FDTD), taking into account the effect of Gaussian noise and reflected shear wave. We then reduced the noise of the measured particle velocity using a designed least mean square filter. Finally, for direct estimation of CSM, Helmholtz algebraic inverse transformation algorithm was used. Reflected waves significantly affect the estimation of CSM, especially the tissue's viscosity, which is demonstrated by numerical simulation results.


 

Keywords: hear wave, CSM, Gaussian noise, reflection, FDTD.

References

[1] A. P. Sarvazyan, O. V. Rudenko, S. D. Swanson, J. B. Fowlkes, S. Y. Emelianov, Shear Wave Elasticity Imaging: A New Ultrasonic Technology of Medical Diagnostics, Ultrasound in Medicine & Biology, Vol. 24, No. 9, 1998, pp. 1419-1435, https://doi.org/10.1016/S0301-5629(98)00110-0.
[2] S. Chen, M. W. Urban, C. Pislaru, R. Kinnick, Y. Zheng, A. Yao, J. F. Greenleaf, Shearwave Dispersion Ultrasound Vibrometry (SDUV) for Measuring Tissue Elasticity and Viscosity. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol.56, No.1, 2009, pp. 55-62, https://doi.org/10.1109/TUFFC.2009.1005.
[3] M. Orescanin, M. F. Insana, Model-Based Complex Shear Modulus Reconstruction: A Bayesian Approach, IEEE International Ultrasonics Symposium, IEEE, 2010, pp. 61-64.
[4] S. W. Hou, A. N. Merkle, J. S. Babb, R. McCabe, S. Gyftopoulos, R. S. Adler, Shear Wave Ultrasound Elastographic Evaluation of the Rotator Cuff Tendon, Journal of Ultrasound in Medicine, Vol. 36, No. 1, 2017, pp. 95-106, https://doi.org/10.7863/ultra.15.07041.
[5] J. A. Sande, S. Verjee, S. Vinayak, F. Amersi, M. Ghesani, Ultrasound Shear Wave Elastography and Liver Fibrosis: A Prospective Multicenter Study, World Journal of Hepatology, Vol. 9, No. 1, 2017, pp. 38-47, https://doi.org/10.4254/wjh.v9.i1.38.
[6] D. T. Tran, Y. Wang, L. T. Nguyen, M. N. Do, M. F. Insana, Complex Shear Modulus Estimation Using Maximum Likelihood Ensemble Filters, 4th International Conference on Biomedical Engineering in Vietnam, Springer, 2013, pp. 313-316.
[7] M. Orescanin, Y. Wang, M. F. Insana, 3-D FDTD Simulation of Shear Waves for Evaluation of Complex Modulus Imaging, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 58, No. 2, 2011, pp. 389-398, https://doi.org/10.1109/TUFFC.2011.1816.
[8] S. Papazoglou, U. Hamhaber, J. Braun, I. Sack, Algebraic Helmholtz Inversion in Planar Magnetic Resonance Elastography, Physics in Medicine & Biology, Vol. 53, No. 12, 2008, pp. 31-47, https://doi.org/10.1088/0031-9155/53/12/005.
[9] L. Q. Hai, D. T. Tran, N. L. Trung, H. T. Huynh, M. N. Do, Simulation Study of 2D Viscoelastic Imaging of Soft Tissues Using the Extended Kalman Filter for Tumor Detection, SIMULATION: Transactions of The Society for Modeling and Simulation International, Vol. 96, No. 5, pp. 435-447, https://doi.org/10.1177/0037549719873381.
[10] P. T. T. Ha, Q. H. Luong, V. D. Nguyen, D. T. Tran, H. T. Huynh, Two-Dimensional Complex Shear Modulus Imaging of Soft Tissues by Integration of Algebraic Helmoltz Inversion and LMS Filter Into Dealing with Noisy Data: A Simulation Study, Mathematical Biosciences and Engineering, 2020, Vol. 17, No. 1, pp. 404-417, https://doi.org/10.3934/mbe.2020022.
[11] H. Duan, P. Chaemsaithong, X. Ju, S. Y. S. Ho, Q. Sun, Y. Y. Tai, Y. L. Tak, L. C. Poon, Shear-wave Sonoelastographic Assessment of Cervix in Pregnancy, Acta Obstetricia Et Gynecologica Scandinavica, Vol. 99, No. 11, 2020, pp. 1458-1468, https://doi.org/10.1111/aogs.13874.
[12] V. J. Schrier, J. Lin, A. Gregory, A. R. Thoreson, A. Alizad, P. C. Amadio, M. Fatemi, Shear Wave Elastography of the Median Nerve: A Mechanical Study, Muscle & Nerve, Vol. 61, No. 6, 2020, pp. 826-833, https://doi.org/10.1002/mus.26863.