Abstract
Ultrasound attenuation is caused by absorption and scattering in tissue and is thus a function of tissue composition, hence its imaging offers great potential for screening and differential diagnosis. In this paper we propose a novel method that allows to reconstruct spatial attenuation distribution in tissue based on computed tomography, using reflections from a passive acoustic reflector. This requires a standard ultrasound transducer operating in pulse-echo mode, thus it can be implemented on conventional ultrasound systems with minor modifications. We use calibration with water measurements in order to normalize measurements for quantitative imaging of attenuation. In contrast to earlier techniques, we herein show that attenuation reconstructions are possible without any geometric prior on the inclusion location or shape. We present a quantitative evaluation of reconstructions based on simulations, gelatin phantoms, and ex-vivo bovine skeletal muscle tissue, achieving contrast-to-noise ratio of up to 2.3 for an inclusion in ex-vivo tissue.
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References
Bamber, J.C., Hill, C.R.: Ultrasonic attenuation and propagation speed in mammalian tissues as a function of temperature. Ultras. Med. Biol. 5(2), 149–157 (1979)
Bamber, J.C., Hill, C.R., King, J.A.: Acoustic properties of normal and cancerous human liver: dependence on tissue structure. Ultras. Med. Biol. 7(2), 135–144 (1981)
Chang, C.H., Huang, S.W., Yang, H.C., Chou, Y.H., Li, P.C.: Reconstruction of ultrasonic sound velocity and attenuation coefficient using linear arrays: clinical assessment. Ultras. Med. Biol. 33(11), 1681–1687 (2007)
Duric, N., et al.: Detection of breast cancer with ultrasound tomography: first results with the Computed Ultrasound Risk Evaluation (CURE) prototype. Med. Phys. 34(2), 773–785 (2007)
Eby, S.F., Song, P., Chen, S., Chen, Q., Greenleaf, J.F., An, K.N.: Validation of shear wave elastography in skeletal muscle. J. Biomech. 46(14), 2381–2387 (2013)
Glozman, T., Azhari, H.: A method for characterization of tissue elastic properties combining ultrasonic computed tomography with elastography. J. Ultras. Med. 29(3), 387–398 (2010)
Goss, S.A., Johnston, R.L., Dunn, F.: Comprehensive compilation of empirical ultrasonic properties of mammalian tissues. J. Acoust. Soc. Am. 64, 423–457 (1978)
Goss, S.A., Johnston, R.L., Dunn, F.: Compilation of empirical ultrasonic properties of mammalian tissues. II. J. Acoust. Soc. Am. 68(1), 93–108 (1980)
Huang, S.W., Li, P.C.: Ultrasonic computed tomography reconstruction of the attenuation coefficient using a linear array. IEEE Trans. Ultras. Ferr. Freq. Control 52(11), 2011–2022 (2005)
Li, C., Sandhu, G.Y., Boone, M., Duric, N.: Breast imaging using waveform attenuation tomography. In: Procs SPIE Med Imaging, vol. 10139, p. 101390A (2017)
Sanabria, S.J., Rominger, M.B., Goksel, O.: Speed-of-sound imaging based on reflector delineation. IEEE Trans. Biomed. Eng. 66(7), 1949–1962 (2019)
Sanabria, S., et al.: Speed of sound ultrasound: a novel technique to identify muscle loss in seniors. Eur. Radiol. 29(1), 3–12 (2019)
Sanabria, S.J., Goksel, O.: Hand-held sound-speed imaging based on ultrasound reflector delineation. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9900, pp. 568–576. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46720-7_66
Sanabria, S.J., et al.: Breast-density assessment with handheld ultrasound: a novel biomarker to assess breast cancer risk and to tailor screening? Eur. Radiol. 28(8), 3165–3175 (2018)
Sanabria, S.J., Ozkan, E., Rominger, M., Goksel, O.: Spatial domain reconstruction for imaging speed-of-sound with pulse-echo ultrasound: simulation and in vivo study. Phys. Med. Biol. 63(21), 215015 (2018)
Sandrin, L., Tanter, M., Catheline, S., Fink, M.: Shear modulus imaging with 2-D transient elastography. IEEE Trans. Ultras. Ferr. Freq. Control 49(4), 426–435 (2002)
Smith, N.B., Webb, A.G.: Introduction to Medical Imaging: Physics, Engineering, and Clinical Applications. Cambridge University Press, Cambridge (2011)
Treeby, B.E., Cox, B.T.: k-Wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave fields. J. Biomed. Opt. 15(2), 021314 (2010)
Vishnevskiy, V., Rau, R., Goksel, O.: Deep variational networks with exponential weighting for learning computed tomography. In: MICCAI (2019, accepted). arXiv:1906.05528
Vishnevskiy, V., Sanabria, S.J., Goksel, O.: Image reconstruction via variational network for real-time hand-held sound-speed imaging. In: Knoll, F., Maier, A., Rueckert, D. (eds.) MLMIR 2018. LNCS, vol. 11074, pp. 120–128. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00129-2_14
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It was provided by the Swiss National Science Foundation and Innosuisse.
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Rau, R., Unal, O., Schweizer, D., Vishnevskiy, V., Goksel, O. (2019). Attenuation Imaging with Pulse-Echo Ultrasound Based on an Acoustic Reflector. In: Shen, D., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science(), vol 11768. Springer, Cham. https://doi.org/10.1007/978-3-030-32254-0_67
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DOI: https://doi.org/10.1007/978-3-030-32254-0_67
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