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Magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma
Ultrasound in combination with the introduction of microbubbles into the vasculature effectively opens the blood brain barrier (BBB) to allow the passage of therapeutic agents. Increased permeability of the BBB is typically demonstrated with small-molecule agents (e.g., 1-nm gadolinium salts). Perme...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477799/ https://www.ncbi.nlm.nih.gov/pubmed/36109574 http://dx.doi.org/10.1038/s42003-022-03881-0 |
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author | Plaksin, Michael Bercovici, Tiran Sat Toltsis, Gabriella Gabi Grinfeld, Javier Shapira, Boaz Zur, Yuval de Picciotto, Rafi Zadicario, Eyal Siddeeq, Mustaffa Wohl, Anton Zibly, Zion Levy, Yoav Cohen, Zvi R. |
author_facet | Plaksin, Michael Bercovici, Tiran Sat Toltsis, Gabriella Gabi Grinfeld, Javier Shapira, Boaz Zur, Yuval de Picciotto, Rafi Zadicario, Eyal Siddeeq, Mustaffa Wohl, Anton Zibly, Zion Levy, Yoav Cohen, Zvi R. |
author_sort | Plaksin, Michael |
collection | PubMed |
description | Ultrasound in combination with the introduction of microbubbles into the vasculature effectively opens the blood brain barrier (BBB) to allow the passage of therapeutic agents. Increased permeability of the BBB is typically demonstrated with small-molecule agents (e.g., 1-nm gadolinium salts). Permeability to small-molecule agents, however, cannot reliably predict the transfer of remarkably larger molecules (e.g., monoclonal antibodies) required by numerous therapies. To overcome this issue, we developed a magnetic resonance imaging analysis based on the ΔR(2)* physical parameter that can be measured intraoperatively for efficient real-time treatment management. We demonstrate successful correlations between ΔR(2)* values and parenchymal concentrations of 3 differently sized (18 nm–44 nm) populations of liposomes in a rat model. Reaching an appropriate ΔR(2)* value during treatment can reflect the effective delivery of large therapeutic agents. This prediction power enables the achievement of desirable parenchymal drug concentrations, which is paramount to obtaining effective therapeutic outcomes. |
format | Online Article Text |
id | pubmed-9477799 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94777992022-09-17 Magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma Plaksin, Michael Bercovici, Tiran Sat Toltsis, Gabriella Gabi Grinfeld, Javier Shapira, Boaz Zur, Yuval de Picciotto, Rafi Zadicario, Eyal Siddeeq, Mustaffa Wohl, Anton Zibly, Zion Levy, Yoav Cohen, Zvi R. Commun Biol Article Ultrasound in combination with the introduction of microbubbles into the vasculature effectively opens the blood brain barrier (BBB) to allow the passage of therapeutic agents. Increased permeability of the BBB is typically demonstrated with small-molecule agents (e.g., 1-nm gadolinium salts). Permeability to small-molecule agents, however, cannot reliably predict the transfer of remarkably larger molecules (e.g., monoclonal antibodies) required by numerous therapies. To overcome this issue, we developed a magnetic resonance imaging analysis based on the ΔR(2)* physical parameter that can be measured intraoperatively for efficient real-time treatment management. We demonstrate successful correlations between ΔR(2)* values and parenchymal concentrations of 3 differently sized (18 nm–44 nm) populations of liposomes in a rat model. Reaching an appropriate ΔR(2)* value during treatment can reflect the effective delivery of large therapeutic agents. This prediction power enables the achievement of desirable parenchymal drug concentrations, which is paramount to obtaining effective therapeutic outcomes. Nature Publishing Group UK 2022-09-15 /pmc/articles/PMC9477799/ /pubmed/36109574 http://dx.doi.org/10.1038/s42003-022-03881-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Plaksin, Michael Bercovici, Tiran Sat Toltsis, Gabriella Gabi Grinfeld, Javier Shapira, Boaz Zur, Yuval de Picciotto, Rafi Zadicario, Eyal Siddeeq, Mustaffa Wohl, Anton Zibly, Zion Levy, Yoav Cohen, Zvi R. Magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma |
title | Magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma |
title_full | Magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma |
title_fullStr | Magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma |
title_full_unstemmed | Magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma |
title_short | Magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma |
title_sort | magnetic resonance imaging analysis predicts nanoparticle concentration delivered to the brain parenchyma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9477799/ https://www.ncbi.nlm.nih.gov/pubmed/36109574 http://dx.doi.org/10.1038/s42003-022-03881-0 |
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