Skip to content
Frontiers
Search

Original Research

Frontiers in Acoustics ·

Volume 4 - 2026 | Issue Ultrasound Technologies | https://doi.org/10.3389/facou.2026.1897567

Focused ultrasound increases Lucifer Yellow transport across hCMEC/D3 endothelial monolayers

  • 1. Faculty of Engineering and Health, HAWK University of Applied Sciences and Arts Hildesheim/Holzminden/Göttingen, Göttingen, Germany.
  • 2. Institute of Clinical Pharmacology, University Medical Center Göttingen, Göttingen, Germany.
  • 3. Medical Laser Center Lübeck, Lübeck, Germany.
  • 4. Institute of Biomedical Optics, University of Lübeck, Lübeck, Germany.
Article metrics100 viewsView details
PDFCiteMetrics

Abstract

Focused ultrasound (FUS) is being investigated as a non-invasive technique to modulate vascular barriers and improve therapeutic delivery to protected tissues, including the central nervous system. This study examined Lucifer Yellow transport across human cerebral microvascular endothelial hCMEC/D3 monolayers cultured on ThinCert inserts during and after a 60-second continuous-wave FUS exposure at 1.2 MHz and 80 Vpp, without added microbubbles.

The acoustic field was characterized using hydrophone measurements, and tracer accumulation was quantified before exposure, immediately afterward, and nine minutes later in eight independent paired experiments. During the exposure interval, FUS produced a mean control-adjusted increase in Lucifer Yellow transport of 0.283 nmol, with a 95% confidence interval of 0.185–0.380 nmol. All eight experiments showed an increase in the same direction. During the subsequent nine-minute interval, the additional control-adjusted accumulation was 0.035 nmol, which was not statistically significant.

Exploratory cell-free measurements and acute live/dead fluorescence imaging did not establish a consistent ultrasound-associated effect in those assessments. The findings demonstrate an increase in Lucifer Yellow transport during FUS exposure in the investigated endothelial monolayer–insert system. Further studies are needed to clarify the underlying acoustic mechanisms, characterize barrier recovery, and assess the applicability of these results to other vascular barrier models.

1. Introduction

Neurovascular endothelial barriers regulate molecular exchange between the circulation and neural tissues. The blood–brain barrier and blood–retinal barrier protect neural environments while limiting the penetration of many therapeutic agents. Focused ultrasound has emerged as a promising non-invasive approach for spatially controlled vascular barrier modulation. Human cerebral microvascular endothelial cells, particularly the hCMEC/D3 model, provide a controlled experimental system for investigating endothelial transport and permeability. However, this model does not fully reproduce the complexity of the in vivo blood–brain barrier or the blood–retinal barrier. This study investigates the temporal relationship between focused ultrasound exposure and Lucifer Yellow transport across hCMEC/D3 endothelial monolayers.

2. Materials and methods

Human cerebral microvascular endothelial hCMEC/D3 cells were cultured on permeable ThinCert inserts and used in paired focused-ultrasound and unexposed-control experiments. The membranes were coated with Matrigel, and the cellular inserts were cultured for six days with daily medium changes. Focused ultrasound was delivered as a 60-second continuous-wave exposure at 1.2 MHz and 80 Vpp, without added microbubbles. Hydrophone measurements were used to characterize the acoustic field and estimate the peak rarefactional focal pressure. Lucifer Yellow transport was quantified before exposure, immediately after the exposure interval, and nine minutes later, using sampling- and volume-corrected receiver amounts. Eight independent paired experiments were included in the cellular transport series. Additional exploratory cell-free measurements and separate live/dead fluorescence imaging experiments were performed to assess membrane transport and acute cellular responses.

3. Results

Focused ultrasound was associated with a consistent increase in Lucifer Yellow transport during the 60-second exposure interval. The mean control-adjusted increase was 0.283 nmol, with a 95% confidence interval of 0.185–0.380 nmol, and all eight independent paired experiments showed the same direction of effect. During the subsequent nine-minute interval, the additional control-adjusted accumulation was 0.035 nmol, with a 95% confidence interval of −0.100 to 0.171 nmol; this difference was not statistically significant. Preliminary cell-free experiments did not reproduce the consistent positive exposure-interval response observed in the cellular experiments. Acute live/dead fluorescence metrics across five paired experiments showed mixed differences without a reproducible ultrasound-associated direction.

4. Discussion

The findings indicate that the increase in Lucifer Yellow transport occurred predominantly during focused ultrasound exposure in the hCMEC/D3 monolayer–insert system. The absence of a statistically detectable additional differential accumulation during the subsequent observation period does not establish complete recovery of endothelial barrier function. The cell-free experiments and fluorescence measurements were exploratory and do not establish a definitive mechanism or demonstrate safety. The local acoustic field at the endothelial monolayer, temperature changes, cavitation activity, and acoustic streaming were not directly characterized. Future investigations should examine these mechanisms and assess the findings in additional endothelial barrier models, including retinal endothelial systems.

5. Conclusions

A 60-second continuous-wave focused ultrasound exposure was associated with a consistent increase in Lucifer Yellow transport across hCMEC/D3 endothelial monolayers during the exposure interval. No statistically detectable additional differential accumulation was observed during the following nine minutes, although complete barrier recovery was not established. Exploratory live/dead imaging did not show a reproducible ultrasound-associated pattern. These results provide a controlled in vitro framework for investigating the timing of ultrasound-associated transport and support further studies of its mechanisms, limitations, and applicability to other vascular barrier models.

Statements

Conflict of interest

Gerrit Meußler and Ralf Brinkmann were employed by Medical Laser Center Lübeck. The remaining authors declared that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Jürgen Brockmöller declared that he was an editorial board member of Frontiers at the time of submission; this had no impact on the peer review process or the final decision.

Funding

This work was supported by the German Federal Ministry of Research, Technology and Space (BMFTR) under grant 13N16466.

Data availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics approval

Ethical approval was not required for the studies on humans in accordance with the local legislation and institutional requirements because only commercially available established cell lines were used.

Author contributions

Sam Bleker: Investigation, writing – original draft, conceptualization, writing – review and editing, methodology, visualization, and formal analysis.

Kyra-Elisa M. Redeker: Writing – review and editing, investigation, conceptualization, and methodology.

Gerrit Meußler: Writing – review and editing and methodology.

Ralf Brinkmann: Funding acquisition, writing – review and editing, and supervision.

Jürgen Brockmöller: Writing – review and editing, supervision, methodology, conceptualization, and resources.

Christoph Russmann: Funding acquisition, project administration, writing – review and editing, supervision, and conceptualization.

References

  1. 1. Ahmad, M. S., Suardi, N., Shukri, A., Mohammad, H., Oglat, A. A., Alarab, A., et al. (2020). Chemical characteristics, motivation and strategies in choice of materials used as liver phantom: a literature review. J. Med. Ultrasound 28, 7–16. doi: 10.4103/JMU.JMU_4_19
  2. 2. Bisht, S. R., Marri, B. P., Karmakar, J., and Mercado-Shekhar, K. P. (2024a). Viscoelastic characterization of phantoms for ultrasound elastography created using low- and high-viscosity poly(vinyl alcohol) with EG as the cryoprotectant. ACS Omega 9, 8352–8361. doi: 10.1021/acsomega.3c09224
  3. 3. Bisht, S. R., Paul, A., Patel, P., Thareja, P., and Mercado-Shekhar, K. P. (2024b). Systematic quantification of differences in shear wave elastography estimates between linear-elastic and viscoelastic material assumptions. J. Acoust. Soc. Am. 155, 2025–2036. doi: 10.1121/10.0025291
  4. 4. Cao, Y., Li, G.-Y., Zhang, X., and Liu, Y.-L. (2017). Tissue-mimicking materials for elastography phantoms: a review. Extreme Mech. Lett. 17, 62–70. doi: 10.1016/j.eml.2017.09.009
  5. 5. Chandra, A., Bezabh, M. W., and Mercado-Shekhar, K. P. (2025). Quantifying the effect of fiber pennation angle on shear wave viscoelastography estimates: in silico and phantom studies. J. Acoust. Soc. Am. 157, 993–1003. doi: 10.1121/10.0035788
  6. 6. Chatelin, S., Bernal, M., Deffieux, T., Papadacci, C., Flaud, P., Nahas, A., et al. (2014). Anisotropic polyvinyl alcohol hydrogel phantom for shear wave elastography in fibrous biological soft tissue: a multimodality characterization. Phys. Med. Biol. 59, 6923–6940. doi: 10.1088/0031-9155/59/22/6923
  7. 7. Chen, S., Sanchez, W., Callstrom, M. R., Gorman, B., Lewis, J. T., Sanderson, S. O., et al. (2013). Assessment of liver viscoelasticity by using shear waves induced by ultrasound radiation force. Radiology 266, 964–970. doi: 10.1148/radiol.12120837
  8. 8. Chintada, B. R., Rau, R., and Goksel, O. (2022). Spectral ultrasound imaging of speed-of-sound and attenuation using an acoustic mirror. Front. Phys. 10, 860725. doi: 10.3389/fphy.2022.860725
  9. 9. Chmarra, M. K., Hansen, R., Mårvik, R., and Langø, T. (2013). Multimodal phantom of liver tissue. PLoS ONE 8, e64180. doi: 10.1371/journal.pone.0064180
  10. 10. Christie, L. B., Zheng, W., Johnson, W., Marecki, E. K., Heidrich, J., Xia, J., et al. (2023). Review of imaging test phantoms. J. Biomed. Opt. 28, 080903. doi: 10.1117/1.JBO.28.8.080903
  11. 11. Cournane, S., Fagan, A. J., and Browne, J. E. (2012). Review of ultrasound elastography quality control and training test phantoms. Ultrasound 20, 16–23. doi: 10.1258/ult.2011.011033
  12. 12. Culjat, M. O., Goldenberg, D., Tewari, P., and Singh, R. S. (2010). A review of tissue substitutes for ultrasound imaging. Ultrasound Med. Biol. 36, 861–873. doi: 10.1016/j.ultrasmedbio.2010.02.012
  13. 13. Das Mahanta, D., Brown, D. R., Pezzotti, S., Han, S., Schwaab, G., Shell, M. S., et al. (2023). Local solvation structures govern the mixing thermodynamics of glycerol-water solutions. Chem. Sci. 14, 7381–7392. doi: 10.1039/d3sc00517h
  14. 14. Dineley, J., Meagher, S., Poepping, T. L., McDicken, W. N., and Hoskins, P. R. (2006). Design and characterisation of a wall motion phantom. Ultrasound Med. Biol. 32, 1349–1357. doi: 10.1016/j.ultrasmedbio.2006.05.033
  15. 15. Elvira, L., Durán, C., Higuti, R. T., Tiago, M. M., Ibáñez, A., Parrilla, M., et al. (2019). Development and characterization of medical phantoms for ultrasound imaging based on customizable and mouldable polyvinyl alcohol cryogel-based materials and 3-D printing: application to high-frequency cranial ultrasonography in infants. Ultrasound Med. Biol. 45, 2226–2241. doi: 10.1016/j.ultrasmedbio.2019.04.030
  16. 16. Fong, R. J., Robertson, A., Mallon, P. E., and Thompson, R. L. (2018). The impact of plasticizer and degree of hydrolysis on free volume of poly(vinyl alcohol) films. Polymers 10, 1036. doi: 10.3390/polym10091036
  17. 17. Franks, F., and Ives, D. J. G. (1966). The structural properties of alcohol-water mixtures. Q. Rev. Chem. Soc. 20, 1–44. doi: 10.1039/qr9662000001
  18. 18. Fromageau, J., Brusseau, E., Vray, D., Gimenez, G., and Delachartre, P. (2003). Characterization of PVA cryogel for intravascular ultrasound elasticity imaging. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 50, 1318–1324. doi: 10.1109/TUFFC.2003.1244748
  19. 19. Greenspan, M., and Tschiegg, C. E. (1957). Speed of sound in water by a direct method. J. Res. Natl. Bur. Stand. 59, 249–254. doi: 10.6028/jres.059.028
  20. 20. Gun’ko, V. M., Savina, I. N., and Mikhalovsky, S. V. (2017). Properties of water bound in hydrogels. Gels 3, 37. doi: 10.3390/gels3040037
  21. 21. Hughes, S. W. (2005). Archimedes revisited: a faster, better, cheaper method of accurately measuring the volume of small objects. Phys. Educ. 40, 468–474. doi: 10.1088/0031-9120/40/5/008
  22. 22. Huntzicker, S., Nayak, R., and Doyley, M. M. (2014). Quantitative sparse array vascular elastography: the impact of tissue attenuation and modulus contrast on performance. J. Med. Imaging 1, 027001. doi: 10.1117/1.JMI.1.2.027001
  23. 23. Kaiser, A., Ritter, M., Nazmutdinov, R., and Probst, M. (2016). Hydrogen bonding and dielectric spectra of EG-water mixtures from molecular dynamics simulations. J. Phys. Chem. B 120, 10515–10523. doi: 10.1021/acs.jpcb.6b05236
  24. 24. Kallweit, C. M., Chee, A. J. Y., Yiu, B. Y. S., Peterson, S. D., and Yu, A. C. H. (2025). Dual-modality flow phantom for ultrasound and optical flow measurements. Phys. Med. Biol. 70, 035012. doi: 10.1088/1361-6560/ada5a3
  25. 25. Khan, S., Goswami, S., Feng, F., Hollenbach, S., Doyley, M. M., and McAleavey, S. A. (2024). Probing tissue viscoelasticity with STL ultrasound shearwave spectroscopy using cole–cole diagrams. IEEE Trans. Biomed. Eng. 71, 916–928. doi: 10.1109/TBME.2023.3322420
  26. 26. Kumar, V., Denis, M., Gregory, A., Bayat, M., Mehrmohammadi, M., Fazzio, R., et al. (2018). Viscoelastic parameters as discriminators of breast masses: initial human study results. PLoS ONE 13, e0205717. doi: 10.1371/journal.pone.0205717
  27. 27. Lim, W. T. H., Ooi, E. H., Foo, J. J., Ng, K. H., Wong, J. H. D., and Leong, S. S. (2023). The role of shear viscosity as a biomarker for improving chronic kidney disease detection using shear wave elastography: a computational study using a validated finite element model. Ultrasonics 133, 107046. doi: 10.1016/j.ultras.2023.107046
  28. 28. Liu, C., Xue, C., Zhang, B., Zhang, G., and He, C. (2018). The application of an ultrasound tomography algorithm in a novel ring 3D ultrasound imaging system. Sensors 18, 1332. doi: 10.3390/s18051332
  29. 29. Loupas, T., Powers, J. T., and Gill, R. W. (1995). An axial velocity estimator for ultrasound blood flow imaging, based on a full evaluation of the doppler equation by means of a two-dimensional autocorrelation approach. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 42, 672–688. doi: 10.1109/58.393110
  30. 30. Maksuti, E., Widman, E., Larsson, D., Urban, M. W., Larsson, M., and Bjallmark, A. (2016). Arterial stiffness estimation by shear wave elastography: validation in phantoms with mechanical testing. Ultrasound Med. Biol. 42, 308–321. doi: 10.1016/j.ultrasmedbio.2015.08.012
  31. 31. Mercado-Shekhar, K. P., Kleven, R. T., Aponte Rivera, H., Lewis, R., Karani, K. B., Vos, H. J., et al. (2018). Effect of clot stiffness on recombinant tissue plasminogen activator lytic susceptibility in vitro. Ultrasound Med. Biol. 44, 2710–2727. doi: 10.1016/j.ultrasmedbio.2018.08.005
  32. 32. Nahirnyak, V. M., Yoon, S. W., and Holland, C. K. (2005). Acousto-mechanical and thermal properties of clotted blood. J. Acoust. Soc. Am. 117, 2413. doi: 10.1121/1.4786299
  33. 33. Ormachea, J., Lavarello, R. J., McAleavey, S. A., Parker, K. J., and Castaneda, B. (2016). Shear wave speed measurements using crawling wave sonoelastography and single tracking location shear wave elasticity imaging for tissue characterization. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 63, 1351–1360. doi: 10.1109/TUFFC.2016.2576962
  34. 34. Ormachea, J., and Parker, K. J. (2020). Comprehensive viscoelastic characterization of tissues and the inter-relationship of shear wave (group and phase) velocity, attenuation and dispersion. Ultrasound Med. Biol. 46, 3448–3459. doi: 10.1016/j.ultrasmedbio.2020.08.023
  35. 35. Parker, K. J., Szabo, T., and Holm, S. (2019). Towards a consensus on rheological models for elastography in soft tissues. Phys. Med. Biol. 64, 215012. doi: 10.1088/1361-6560/ab453d
  36. 36. Poul, S. S., and Parker, K. J. (2021). Fat and fibrosis as confounding cofactors in viscoelastic measurements of the liver. Phys. Med. Biol. 66, 045024. doi: 10.1088/1361-6560/abd593
  37. 37. Quarato, C. M. I., Lacedonia, D., Salvemini, M., Tuccari, G., Mastrodonato, G., Villani, R., et al. (2023). A review on biological effects of ultrasounds: key messages for clinicians. Diagnostics 13, 855. doi: 10.3390/diagnostics13050855
  38. 38. Rethy, A., Sæternes, J. O., Halgunset, J., Mårvik, R., Hofstad, E. F., Sánchez-Margallo, J. A., et al. (2017). Anthropomorphic liver phantom with flow for multimodal image-guided liver therapy research and training. Int. J. Comput. Assist. Radiol. Surg. 13, 61–72. doi: 10.1007/s11548-017-1669-3
  39. 39. Rhys, N. H., Gillams, R. J., Collins, L. E., Callear, S. K., Lawrence, M. J., and McLain, S. E. (2016). On the structure of an aqueous PG solution. J. Chem. Phys. 145, 224504. doi: 10.1063/1.4971208
  40. 40. RSNA-QIBA Ultrasound Shear Wave Speed Committee (2016). RSNA-QIBA ultrasound shear-wave-speed algorithms [source code]. GitHub. Available online at: https://github.com/orgs/RSNA-QIBA-US-SWS/ (Accessed February 15, 2026).
  41. 41. Rus, G., Faris, I. H., Torres, J., Callejas, A., and Melchor, J. (2020). Why are viscosity and nonlinearity bound to make an impact in clinical elastographic diagnosis? Sensors 20, 2379. doi: 10.3390/s20082379
  42. 42. Sharma, A., Marapureddy, S. G., Paul, A., Bisht, S. R., Kakkar, M., Thareja, P., et al. (2023). Characterizing viscoelastic polyvinyl alcohol phantoms for ultrasound elastography. Ultrasound Med. Biol. 49, 497–511. doi: 10.1016/j.ultrasmedbio.2022.09.019
  43. 43. Stojkov, G., Niyazov, Z., Picchioni, F., and Bose, R. K. (2021). Relationship between structure and rheology of hydrogels for various applications. Gels 7, 255. doi: 10.3390/gels7040255
  44. 44. Surry, K. J. M., Austin, H. J. B., Fenster, A., and Peters, T. M. (2004). Poly(vinyl alcohol) cryogel phantoms for use in ultrasound and MR imaging. Phys. Med. Biol. 49, 5529–5546. doi: 10.1088/0031-9155/49/24/009
  45. 45. Urban, M. W., and Greenleaf, J. F. (2009). A Kramers–Kronig-based quality factor for shear wave propagation in soft tissue. Phys. Med. Biol. 54, 5919–5933. doi: 10.1088/0031-9155/54/19/017
  46. 46. Virén, T., Saarakkala, S., Jurvelin, J. S., Pulkkinen, H. J., Tiitu, V., Valonen, P., et al. (2010). Quantitative evaluation of spontaneously and surgically repaired rabbit articular cartilage using intra-articular ultrasound method in situ. Ultrasound Med. Biol. 36, 833–839. doi: 10.1016/j.ultrasmedbio.2010.02.015
  47. 47. Wang, J., Xu, Y., Tian, C., Yu, Y., and Zou, C. (2024). Application of polyvinyl alcohol-EG hydrogel technology for removing animal glue in book restoration based on fluorescent labeling evaluation. Nanomaterials 14, 1878. doi: 10.3390/nano14231878
  48. 48. Widman, E., Maksuti, E., Larsson, D., Urban, M. W., Bjallmark, A., and Larsson, M. (2015). Shear wave elastography plaque characterization with mechanical testing validation: a phantom study. Phys. Med. Biol. 60, 3151–3174. doi: 10.1088/0031-9155/60/8/3151
  49. 49. Worch, J. C., Prydderch, H., Jimaja, S., Bexis, P., Becker, M. L., and Dove, A. P. (2019). Stereochemical enhancement of polymer properties. Nat. Rev. Chem. 3, 514–535. doi: 10.1038/s41570-019-0117-z
  50. 50. Yang, X., Dargaville, B. L., and Hutmacher, D. W. (2021). Elucidating the molecular mechanisms for the interaction of water with polyEG-based hydrogels: influence of ionic strength and gel network structure. Polymers 13, 845. doi: 10.3390/polym13060845
  51. 51. Zhou, B., and Zhang, X. (2018). Comparison of five viscoelastic models for estimating viscoelastic parameters using ultrasound shear wave elastography. J. Mech. Behav. Biomed. Mater. 85, 109–116. doi: 10.1016/j.jmbbm.2018.05.041
  52. 52. Zhu, Y., Zhang, X., Zheng, Y., Shen, Y., Lin, H., et al. (2014). Quantitative analysis of liver fibrosis in rats with shearwave dispersion ultrasound vibrometry: Comparison with dynamic mechanical analysis. Med. Eng. Phys. 36, 1401–1407. doi: 10.1016/j.medengphy.2014.04.002

Citation

Germany., 1. F. o. E. a. H. H. U. o. A. S. a. A. H. G., et al. (2026). Focused ultrasound increases Lucifer Yellow transport across hCMEC/D3 endothelial monolayers. Frontiers in Acoustics, Volume 4. https://doi.org/
Received
Revised
Accepted
Published
Volume
4 - 2026

Edited by

John Sharer Allen

Reviewed by

  • Suwan Jayasinghe
  • Jean-Michel Escoffre

Copyright

© 2026 Bleker, Redeker, Meußler, Brinkmann, Brockmöller and Russmann. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).

License: CC BY 4.0

*Correspondence: Christoph Russmann

Article metrics

Views
100
Downloads
200
Citations
301
Shares
240

Related articles

Original ResearchFocused ultrasound increases Lucifer Yellow transport across hCMEC/D3 endothelial monolayersSam Bleker, Kyra-Elisa M. Redeker, Gerrit Meußler, Ralf Brinkmann, Jürgen Brockmöller, Christoph RussmannOriginal ResearchCharacterization of tissue-mimicking polyvinyl alcohol phantoms for shear wave viscoelastography: effects of aluminum oxide and cryoprotectant concentrationDevyani Gupta, Akash Chandra, Jagruti M. Patil, Karla P. Mercado-ShekharMethodsA computational framework based on immersed boundary-lattice Boltzmann coupling for ultrasound-excited encapsulated microbubblesMorteza Garousi, Michael L. Calvisi