Holograms to Focus Arbitrary Ultrasonic Fields through the Skull

[EN] We report 3D-printed acoustic holographic lenses for the formation of ultrasonic fields of complex spatial distribution inside the skull. Using holographic lenses, we experimentally, numerically and theoretically produce acoustic beams whose spatial distribution matches target structures of the central nervous system. In particular, we produce three types of targets of increasing complexity. First, a set of points are selected at the center of both right and left human hippocampi. Experiments using a skull phantom and 3D printed acoustic holographic lenses show that the corresponding bi-focal lens simultaneously focuses acoustic energy at the target foci, with good agreement between theory and simulations. Second, an arbitrary curve is set as the target inside the skull phantom. Using time-reversal methods the holographic beam bends following the target path, in a similar way as self-bending beams do in free space. Finally, the right human hippocampus is selected as a target volume. The focus of the corresponding holographic lens overlaps with the target volume in excellent agreement between theory in free-media, and experiments and simulations including the skull phantom. The precise control of focused ultrasound into the central nervous system is mainly limited due to the strong phase aberrations produced by refraction and attenuation of the skull. Using the present method, the ultrasonic beam can be focused not only at a single point but overlapping one or various target structures simultaneously using low-cost 3D-printed acoustic holographic lens. The results open new paths to spread incoming biomedical ultrasound applications including blood-brain barrier opening and neuromodulation.This work is supported by the Spanish Ministry of Economy and Innovation (MINECO) through Project No. TEC2016-80976-R. N.J. and S.J. acknowledge financial support from Generalitat Valenciana through Grants No. APOSTD/2017/042, No. ACIF/2017/045, and No. GV/2018/11. F.C. acknowledges financial support from Agencia Valenciana de la Innovacio through Grant No. INNCON00/18/9 and European Regional Development Fund (Grant No. IDIFEDER/2018/022).Jiménez-Gambín, S.; Jimenez, N.; Benlloch Baviera, JM.; Camarena Femenia, F. (2019). Holograms to Focus Arbitrary Ultrasonic Fields through the Skull. Physical Review Applied. 12(1):014016-1-014016-14. https://doi.org/10.1103/PhysRevApplied.12.014016S014016-1014016-14121GABOR, D. (1948). A New Microscopic Principle. Nature, 161(4098), 777-778. doi:10.1038/161777a0Microscopy by reconstructed wave-fronts. (1949). Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 197(1051), 454-487. doi:10.1098/rspa.1949.0075Leith, E. N., & Upatnieks, J. (1962). Reconstructed Wavefronts and Communication Theory*. Journal of the Optical Society of America, 52(10), 1123. doi:10.1364/josa.52.001123Ni, X., Kildishev, A. V., & Shalaev, V. M. (2013). Metasurface holograms for visible light. Nature Communications, 4(1). doi:10.1038/ncomms3807Huang, L., Chen, X., Mühlenbernd, H., Zhang, H., Chen, S., Bai, B., … Zhang, S. (2013). Three-dimensional optical holography using a plasmonic metasurface. Nature Communications, 4(1). doi:10.1038/ncomms3808Ma, G., & Sheng, P. (2016). Acoustic metamaterials: From local resonances to broad horizons. Science Advances, 2(2), e1501595. doi:10.1126/sciadv.1501595Cummer, S. A., Christensen, J., & Alù, A. (2016). Controlling sound with acoustic metamaterials. Nature Reviews Materials, 1(3). doi:10.1038/natrevmats.2016.1Liu, Z. (2000). Locally Resonant Sonic Materials. Science, 289(5485), 1734-1736. doi:10.1126/science.289.5485.1734Fang, N., Xi, D., Xu, J., Ambati, M., Srituravanich, W., Sun, C., & Zhang, X. (2006). Ultrasonic metamaterials with negative modulus. Nature Materials, 5(6), 452-456. doi:10.1038/nmat1644Yang, M., Ma, G., Yang, Z., & Sheng, P. (2013). Coupled Membranes with Doubly Negative Mass Density and Bulk Modulus. Physical Review Letters, 110(13). doi:10.1103/physrevlett.110.134301Li, Y., Liang, B., Gu, Z., Zou, X., & Cheng, J. (2013). Reflected wavefront manipulation based on ultrathin planar acoustic metasurfaces. Scientific Reports, 3(1). doi:10.1038/srep02546Xie, Y., Wang, W., Chen, H., Konneker, A., Popa, B.-I., & Cummer, S. A. (2014). Wavefront modulation and subwavelength diffractive acoustics with an acoustic metasurface. Nature Communications, 5(1). doi:10.1038/ncomms6553Jiménez, N., Cox, T. J., Romero-García, V., & Groby, J.-P. (2017). Metadiffusers: Deep-subwavelength sound diffusers. Scientific Reports, 7(1). doi:10.1038/s41598-017-05710-5Jiménez, N., Romero-García, V., Pagneux, V., & Groby, J.-P. (2017). Rainbow-trapping absorbers: Broadband, perfect and asymmetric sound absorption by subwavelength panels for transmission problems. Scientific Reports, 7(1). doi:10.1038/s41598-017-13706-4Qi, S., Li, Y., & Assouar, B. (2017). Acoustic Focusing and Energy Confinement Based on Multilateral Metasurfaces. Physical Review Applied, 7(5). doi:10.1103/physrevapplied.7.054006Bok, E., Park, J. J., Choi, H., Han, C. K., Wright, O. B., & Lee, S. H. (2018). Metasurface for Water-to-Air Sound Transmission. Physical Review Letters, 120(4). doi:10.1103/physrevlett.120.044302Li, Y., Jiang, X., Liang, B., Cheng, J., & Zhang, L. (2015). Metascreen-Based Acoustic Passive Phased Array. Physical Review Applied, 4(2). doi:10.1103/physrevapplied.4.024003Li, Y., & Assouar, M. B. (2015). Three-dimensional collimated self-accelerating beam through acoustic metascreen. Scientific Reports, 5(1). doi:10.1038/srep17612Kaina, N., Lemoult, F., Fink, M., & Lerosey, G. (2015). Negative refractive index and acoustic superlens from multiple scattering in single negative metamaterials. Nature, 525(7567), 77-81. doi:10.1038/nature14678Li, J., Fok, L., Yin, X., Bartal, G., & Zhang, X. (2009). Experimental demonstration of an acoustic magnifying hyperlens. Nature Materials, 8(12), 931-934. doi:10.1038/nmat2561Melde, K., Mark, A. G., Qiu, T., & Fischer, P. (2016). Holograms for acoustics. Nature, 537(7621), 518-522. doi:10.1038/nature19755Xie, Y., Shen, C., Wang, W., Li, J., Suo, D., Popa, B.-I., … Cummer, S. A. (2016). Acoustic Holographic Rendering with Two-dimensional Metamaterial-based Passive Phased Array. Scientific Reports, 6(1). doi:10.1038/srep35437Zhu, Y., Hu, J., Fan, X., Yang, J., Liang, B., Zhu, X., & Cheng, J. (2018). Fine manipulation of sound via lossy metamaterials with independent and arbitrary reflection amplitude and phase. Nature Communications, 9(1). doi:10.1038/s41467-018-04103-0Memoli, G., Caleap, M., Asakawa, M., Sahoo, D. R., Drinkwater, B. W., & Subramanian, S. (2017). Metamaterial bricks and quantization of meta-surfaces. Nature Communications, 8(1). doi:10.1038/ncomms14608Brown, M. D., Cox, B. T., & Treeby, B. E. (2017). Design of multi-frequency acoustic kinoforms. Applied Physics Letters, 111(24), 244101. doi:10.1063/1.5004040Hertzberg, Y., & Navon, G. (2011). Bypassing absorbing objects in focused ultrasound using computer generated holographic technique. Medical Physics, 38(12), 6407-6415. doi:10.1118/1.3651464Zhang, P., Li, T., Zhu, J., Zhu, X., Yang, S., Wang, Y., … Zhang, X. (2014). Generation of acoustic self-bending and bottle beams by phase engineering. Nature Communications, 5(1). doi:10.1038/ncomms5316Marzo, A., Seah, S. A., Drinkwater, B. W., Sahoo, D. R., Long, B., & Subramanian, S. (2015). Holographic acoustic elements for manipulation of levitated objects. Nature Communications, 6(1). doi:10.1038/ncomms9661Ter Haar, >Gail, & Coussios, C. (2007). High intensity focused ultrasound: Physical principles and devices. International Journal of Hyperthermia, 23(2), 89-104. doi:10.1080/02656730601186138Gélat, P., ter Haar, G., & Saffari, N. (2014). A comparison of methods for focusing the field of a HIFU array transducer through human ribs. Physics in Medicine and Biology, 59(12), 3139-3171. doi:10.1088/0031-9155/59/12/3139Fry, F. J., & Barger, J. E. (1978). Acoustical properties of the human skull. The Journal of the Acoustical Society of America, 63(5), 1576-1590. doi:10.1121/1.381852Thomas, J.-L., & Fink, M. A. (1996). Ultrasonic beam focusing through tissue inhomogeneities with a time reversal mirror: application to transskull therapy. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 43(6), 1122-1129. doi:10.1109/58.542055Hynynen, K., & Jolesz, F. A. (1998). Demonstration of Potential Noninvasive Ultrasound Brain Therapy Through an Intact Skull. Ultrasound in Medicine & Biology, 24(2), 275-283. doi:10.1016/s0301-5629(97)00269-xSun, J., & Hynynen, K. (1998). Focusing of therapeutic ultrasound through a human skull: A numerical study. The Journal of the Acoustical Society of America, 104(3), 1705-1715. doi:10.1121/1.424383Aubry, J.-F., Tanter, M., Pernot, M., Thomas, J.-L., & Fink, M. (2003). Experimental demonstration of noninvasive transskull adaptive focusing based on prior computed tomography scans. The Journal of the Acoustical Society of America, 113(1), 84-93. doi:10.1121/1.1529663Tanter, M., Thomas, J.-L., & Fink, M. (1998). Focusing and steering through absorbing and aberrating layers: Application to ultrasonic propagation through the skull. The Journal of the Acoustical Society of America, 103(5), 2403-2410. doi:10.1121/1.422759Hertzberg, Y., Volovick, A., Zur, Y., Medan, Y., Vitek, S., & Navon, G. (2010). Ultrasound focusing using magnetic resonance acoustic radiation force imaging: Application to ultrasound transcranial therapy. Medical Physics, 37(6Part1), 2934-2942. doi:10.1118/1.3395553Jolesz, F. A. (Ed.). (2014). Intraoperative Imaging and Image-Guided Therapy. doi:10.1007/978-1-4614-7657-3Shen, C., Xu, J., Fang, N. X., & Jing, Y. (2014). Anisotropic Complementary Acoustic Metamaterial for Canceling out Aberrating Layers. Physical Review X, 4(4). doi:10.1103/physrevx.4.041033Maimbourg, G., Houdouin, A., Deffieux, T., Tanter, M., & Aubry, J.-F. (2018). 3D-printed adaptive acoustic lens as a disruptive technology for transcranial ultrasound therapy using single-element transducers. Physics in Medicine & Biology, 63(2), 025026. doi:10.1088/1361-6560/aaa037Ferri, M., Bravo, J. M., Redondo, J., & Sánchez-Pérez, J. V. (2019). Enhanced Numerical Method for the Design of 3-D-Printed Holographic Acoustic Lenses for Aberration Correction of Single-Element Transcranial Focused Ultrasound. Ultrasound in Medicine & Biology, 45(3), 867-884. doi:10.1016/j.ultrasmedbio.2018.10.022Hynynen, K., McDannold, N., Vykhodtseva, N., & Jolesz, F. A. (2001). Noninvasive MR Imaging–guided Focal Opening of the Blood-Brain Barrier in Rabbits. Radiology, 220(3), 640-646. doi:10.1148/radiol.2202001804Tyler, W. J., Tufail, Y., Finsterwald, M., Tauchmann, M. L., Olson, E. J., & Majestic, C. (2008). Remote Excitation of Neuronal Circuits Using Low-Intensity, Low-Frequency Ultrasound. PLoS ONE, 3(10), e3511. doi:10.1371/journal.pone.0003511Schneider, U., Pedroni, E., & Lomax, A. (1996). The calibration of CT Hounsfield units for radiotherapy treatment planning. Physics in Medicine and Biology, 41(1), 111-124. doi:10.1088/0031-9155/41/1/009Mast, T. D. (2000). Empirical relationships between acoustic parameters in human soft tissues. Acoustics Research Letters Online, 1(2), 37-42. doi:10.1121/1.1336896Mazziotta, J. C., Toga, A. W., Evans, A., Fox, P., & Lancaster, J. (1995). A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development. NeuroImage, 2(2), 89-101. doi:10.1006/nimg.1995.1012Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006). User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. NeuroImage, 31(3), 1116-1128. doi:10.1016/j.neuroimage.2006.01.015Treeby, B. E., & Cox, B. T. (2010). Modeling power law absorption and dispersion for acoustic propagation using the fractional Laplacian. The Journal of the Acoustical Society of America, 127(5), 2741-2748. doi:10.1121/1.3377056Treeby, B. E., Jaros, J., Rendell, A. P., & Cox, B. T. (2012). Modeling nonlinear ultrasound propagation in heterogeneous media with power law absorption using a k-space pseudospectral method. The Journal of the Acoustical Society of America, 131(6), 4324-4336. doi:10.1121/1.4712021Jiménez, N., Camarena, F., Redondo, J., Sánchez-Morcillo, V., Hou, Y., & Konofagou, E. E. (2016). Time-Domain Simulation of Ultrasound Propagation in a Tissue-Like Medium Based on the Resolution of the Nonlinear Acoustic Constitutive Relations. Acta Acustica united with Acustica, 102(5), 876-892. doi:10.3813/aaa.919002Jiménez, N., Romero-García, V., Pagneux, V., & Groby, J.-P. (2017). Quasiperfect absorption by subwavelength acoustic panels in transmission using accumulation of resonances due to slow sound. Physical Review B, 95(1). doi:10.1103/physrevb.95.014205Tsang, P. W. M., & Poon, T.-C. (2013). Novel method for converting digital Fresnel hologram to phase-only hologram based on bidirectional error diffusion. Optics Express, 21(20), 23680. doi:10.1364/oe.21.023680Lirette, R., & Mobley, J. (2017). Focal zone characteristics of stepped Fresnel and axicon acoustic lenses. doi:10.1121/2.0000703Gatto, M., Memoli, G., Shaw, A., Sadhoo, N., Gelat, P., & Harris, R. A. (2012). Three-Dimensional Printing (3DP) of neonatal head phantom for ultrasound: Thermocouple embedding and simulation of bone. Medical Engineering & Physics, 34(7), 929-937. doi:10.1016/j.medengphy.2011.10.012Robertson, J., Martin, E., Cox, B., & Treeby, B. E. (2017). Sensitivity of simulated transcranial ultrasound fields to acoustic medium property maps. Physics in Medicine and Biology, 62(7), 2559-2580. doi:10.1088/1361-6560/aa5e98Hill, C. R., Bamber, J. C., & ter Haar, G. R. (Eds.). (2004). Physical Principles of Medical Ultrasonics. doi:10.1002/0470093978O’Neil, H. T. (1949). Theory of Focusing Radiators. The Journal of the Acoustical Society of America, 21(5), 516-526. doi:10.1121/1.1906542Chen, D.-C., Zhu, X.-F., Wei, Q., Wu, D.-J., & Liu, X.-J. (2018). Broadband acoustic focusing by Airy-like beams based on acoustic metasurfaces. Journal of Applied Physics, 123(4), 044503. doi:10.1063/1.501070

Ultrasonic characterization of ultrasound contrast agents

The main constituent of an ultrasound contrast agent (UCA) is gas-filled microbubbles. An average UCA contains billions per ml. These microbubbles are excellent ultrasound scatterers due to their high compressibility. In an ultrasound field they act as resonant systems, resulting in harmonic energy in the backscattered ultrasound signal, such as energy at the subharmonic, ultraharmonic and higher harmonic frequencies. This harmonic energy is exploited for contrast enhanced imaging to discriminate the contrast agent from surrounding tissue. The amount of harmonic energy that the contrast agent bubbles generate depends on the bubble characteristics in combination with the ultrasound field applied. This paper summarizes different strategies to characterize the UCAs. These strategies can be divided into acoustic and optical methods, which focus on the linear or nonlinear responses of the contrast agent bubbles. In addition, the characteristics of individual bubbles can be determined or the bubbles can be examined when they are part of a population. Recently, especially optical methods have proven their value to study individual bubbles. This paper concludes by showing some examples of optically observed typical behavior of contrast bubbles in ultrasound fields

On Distant Speech Recognition for Home Automation

The official version of this draft is available at Springer via http://dx.doi.org/10.1007/978-3-319-16226-3_7International audienceIn the framework of Ambient Assisted Living, home automation may be a solution for helping elderly people living alone at home. This study is part of the Sweet-Home project which aims at developing a new home automation system based on voice command to improve support and well-being of people in loss of autonomy. The goal of the study is vocal order recognition with a focus on two aspects: distance speech recognition and sentence spotting. Several ASR techniques were evaluated on a realistic corpus acquired in a 4-room flat equipped with microphones set in the ceiling. This distant speech French corpus was recorded with 21 speakers who acted scenarios of activities of daily living. Techniques acting at the decoding stage, such as our novel approach called Driven Decoding Algorithm (DDA), gave better speech recognition results than the baseline and other approaches. This solution which uses the two best SNR channels and a priori knowledge (voice commands and distress sentences) has demonstrated an increase in recognition rate without introducing false alarms

Recognition of aminoacyl-tRNA: a common molecular mechanism revealed by cryo-EM

The accuracy of ribosomal translation is achieved by an initial selection and a proofreading step, mediated by EF-Tu, which forms a ternary complex with aminoacyl(aa)-tRNA. To study the binding modes of different aa-tRNAs, we compared cryo-EM maps of the kirromycin-stalled ribosome bound with ternary complexes containing Phe-tRNAPhe, Trp-tRNATrp, or Leu-tRNALeuI. The three maps suggest a common binding manner of cognate aa-tRNAs in their specific binding with both the ribosome and EF-Tu. All three aa-tRNAs have the same ‘loaded spring' conformation with a kink and twist between the D-stem and anticodon stem. The three complexes are similarly integrated in an interaction network, extending from the anticodon loop through h44 and protein S12 to the EF-Tu-binding CCA end of aa-tRNA, proposed to signal cognate codon–anticodon interaction to the GTPase centre and tune the accuracy of aa-tRNA selection

Nucleation and crystallization in bio-based immiscible polyester blends

Bio-based thermoplastic polyesters are highly promising materials as they combine interesting thermal and physical properties and in many cases biodegradability. However, sometimes the best property balance can only be achieved by blending in order to improve barrier properties, biodegradability or mechanical properties. Nucleation, crystallization and morphology are key factors that can dominate all these properties in crystallizable biobased polyesters. Therefore, their understanding, prediction and tailoring is essential. In this work, after a brief introduction about immiscible polymer blends, we summarize the crystallization behavior of the most important bio-based (and immiscible) polyester blends, considering examples of double-crystalline components. Even though in some specific blends (e.g., polylactide/polycaprolactone) many efforts have been made to understand the influence of blending on the nucleation, crystallization and morphology of the parent components, there are still many points that have yet to be understood. In the case of other immiscible polyester blends systems, the literature is scarce, opening up opportunities in this environmentally important research topic.The authors would like to acknowledge funding by the BIODEST project ((RISE) H2020-MSCA-RISE-2017-778092