Computational Feasibility Study of a Torsional Wave Transducer for Tissue Stiffness Monitoring

A torsional piezoelectric ultrasonic transducer design
is proposed to measure shear moduli in soft tissue with direct
access availability, using shear wave elastography technique. The
measurement of shear moduli of tissues is a challenging problem,
mainly derived from a) the difficulty of isolating a pure shear wave,
given the interference of multiple waves of different types (P, S,
even guided) emitted by the transducers and reflected in geometric
boundaries, and b) the highly attenuating nature of soft tissular
materials. An immediate application, overcoming these drawbacks,
is the measurement of changes in cervix stiffness to estimate the
gestational age at delivery. The design has been optimized using
a finite element model (FEM) and a semi-analytical estimator of
the probability of detection (POD) to determine a suitable geometry,
materials and generated waves. The technique is based on the time
of flight measurement between emitter and receiver, to infer shear
wave velocity. Current research is centered in prototype testing and
validation. The geometric optimization of the transducer was able
to annihilate the compressional wave emission, generating a quite
pure shear torsional wave. Currently, mechanical and electromagnetic
coupling between emitter and receiver signals are being the research
focus. Conclusions: the design overcomes the main described
problems. The almost pure shear torsional wave along with the short
time of flight avoids the possibility of multiple wave interference.
This short propagation distance reduce the effect of attenuation, and
allow the emission of very low energies assuring a good biological
security for human use.




References:
[1] S. Van Kervel and J. Thijssen, “A calculation scheme for the optimum
design of ultrasonic transducers,” Ultrasonics, vol. 21, no. 3, pp.
134–140, 1983.
[2] D. Bader and P. Bowker, “Mechanical characteristics of skin and
underlying tissues in vivo,” Biomaterials, vol. 4, no. 4, pp. 305–308,
1983.
[3] A. S. Ahuja, “Tissue as a voigt body for propagation of ultrasound,”
Ultrasonic Imaging, vol. 1, no. 2, pp. 136–143, 1979.
[4] J. Pereira, J. Mansour, and B. Davis, “Dynamic measurement of the
viscoelastic properties of skin,” Journal of Biomechanics, vol. 24, no. 2,
pp. 157–162, 1991.
[5] T. Bigelow, B. McFarlin, W. O’Brien Jr., and M. Oelze, “In vivo
ultrasonic attenuation slope estimates for detecting cervical ripening in
rats: Preliminary results,” Journal of the Acoustical Society of America,
vol. 123, no. 3, pp. 1794–1800, 2008, cited By (since 1996) 0.
[6] J. Melchor and G. Rus, “Torsional ultrsonic transducer computational
design optimization,” Ultrasonics, vol. 50, no. 7, pp. 1950–1962, 2014.
[7] B. L. McFarlin, W. D. O’brien, Jr., M. L. Oelze, J. F. Zachary, and
R. White-Traut, “Ultrasound insertion loss of the rat cervix,” American
Journal of Obstetrics and Gynecology, vol. 193, no. 6, Supplement
1, pp. S154–S154, 2005, 26th Annual Meeting of the Society for
Maternal-Fetal Medicine - The Pregnancy Meeting.
[8] B. L. McFarlin, W. D. O’Brien, M. L. Oelze, J. F. Zachary, and R. C.
White-Traut, “Quantitative ultrasound assessment of the rat cervix,”
Journal of ultrasound in medicine, vol. 25, no. 8, pp. 1031–1040, 2006.
[9] M. Lebertre, F. Ossant, L. Vaillant, S. Diridollou, and F. Patat, “Spatial
variation of acoustic parameters in human skin: an in vitro study between
22 and 45 mhz,” Ultrasound in medicine & biology, vol. 28, no. 5, pp.
599–615, 2002.
[10] F. Sebag, J. Vaillant-Lombard, J. Berbis, V. Griset, J. Henry, P. Petit, and
C. Oliver, “Shear wave elastography: a new ultrasound imaging mode
for the differential diagnosis of benign and malignant thyroid nodules,”
Journal of Clinical Endocrinology & Metabolism, vol. 95, no. 12, pp.
5281–5288, 2010.
[11] J. M. Chang, W. K. Moon, N. Cho, A. Yi, H. R. Koo, W. Han, D.-Y.
Noh, H.-G. Moon, and S. J. Kim, “Clinical application of shear wave
elastography (swe) in the diagnosis of benign and malignant breast
diseases,” Breast cancer research and treatment, vol. 129, no. 1, pp.
89–97, 2011.
[12] G. Rus, S. Y. Lee, S. Y. Chang, and S. C. Wooh, “Optimized damage
detection of steel plates from noisy impact test,” International Journal
for Numerical Methods in Engineering, vol. 68, pp. 707–727, 2006.
[13] L. Rade and B. Westergren, Mathematics Handbook for Science and
Engineering. Springer, 1999.
[14] D. Goldberg, Genetic algorithms in search, optimization and machine
learning. Addison-Wesley Publ, Reading, Massachussets, etc., 1989.
[15] R. Gallego and G. Rus, “Identification of cracks and cavities using
the topological sensitivity boundary integral equation,” Computational
Mechanics, vol. 33, pp. 154–163, 2004.