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Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization
Super-resolution imaging methods promote tissue characterization beyond the spatial resolution limits of the devices and bridge the gap between histopathological analysis and non-invasive imaging. Here, we introduce motion model ultrasound localization microscopy (mULM) as an easily applicable and r...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5906644/ https://www.ncbi.nlm.nih.gov/pubmed/29670096 http://dx.doi.org/10.1038/s41467-018-03973-8 |
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author | Opacic, Tatjana Dencks, Stefanie Theek, Benjamin Piepenbrock, Marion Ackermann, Dimitri Rix, Anne Lammers, Twan Stickeler, Elmar Delorme, Stefan Schmitz, Georg Kiessling, Fabian |
author_facet | Opacic, Tatjana Dencks, Stefanie Theek, Benjamin Piepenbrock, Marion Ackermann, Dimitri Rix, Anne Lammers, Twan Stickeler, Elmar Delorme, Stefan Schmitz, Georg Kiessling, Fabian |
author_sort | Opacic, Tatjana |
collection | PubMed |
description | Super-resolution imaging methods promote tissue characterization beyond the spatial resolution limits of the devices and bridge the gap between histopathological analysis and non-invasive imaging. Here, we introduce motion model ultrasound localization microscopy (mULM) as an easily applicable and robust new tool to morphologically and functionally characterize fine vascular networks in tumors at super-resolution. In tumor-bearing mice and for the first time in patients, we demonstrate that within less than 1 min scan time mULM can be realized using conventional preclinical and clinical ultrasound devices. In this context, next to highly detailed images of tumor microvascularization and the reliable quantification of relative blood volume and perfusion, mULM provides multiple new functional and morphological parameters that discriminate tumors with different vascular phenotypes. Furthermore, our initial patient data indicate that mULM can be applied in a clinical ultrasound setting opening avenues for the multiparametric characterization of tumors and the assessment of therapy response. |
format | Online Article Text |
id | pubmed-5906644 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-59066442018-04-20 Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization Opacic, Tatjana Dencks, Stefanie Theek, Benjamin Piepenbrock, Marion Ackermann, Dimitri Rix, Anne Lammers, Twan Stickeler, Elmar Delorme, Stefan Schmitz, Georg Kiessling, Fabian Nat Commun Article Super-resolution imaging methods promote tissue characterization beyond the spatial resolution limits of the devices and bridge the gap between histopathological analysis and non-invasive imaging. Here, we introduce motion model ultrasound localization microscopy (mULM) as an easily applicable and robust new tool to morphologically and functionally characterize fine vascular networks in tumors at super-resolution. In tumor-bearing mice and for the first time in patients, we demonstrate that within less than 1 min scan time mULM can be realized using conventional preclinical and clinical ultrasound devices. In this context, next to highly detailed images of tumor microvascularization and the reliable quantification of relative blood volume and perfusion, mULM provides multiple new functional and morphological parameters that discriminate tumors with different vascular phenotypes. Furthermore, our initial patient data indicate that mULM can be applied in a clinical ultrasound setting opening avenues for the multiparametric characterization of tumors and the assessment of therapy response. Nature Publishing Group UK 2018-04-18 /pmc/articles/PMC5906644/ /pubmed/29670096 http://dx.doi.org/10.1038/s41467-018-03973-8 Text en © The Author(s) 2018 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/. |
spellingShingle | Article Opacic, Tatjana Dencks, Stefanie Theek, Benjamin Piepenbrock, Marion Ackermann, Dimitri Rix, Anne Lammers, Twan Stickeler, Elmar Delorme, Stefan Schmitz, Georg Kiessling, Fabian Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization |
title | Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization |
title_full | Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization |
title_fullStr | Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization |
title_full_unstemmed | Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization |
title_short | Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization |
title_sort | motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5906644/ https://www.ncbi.nlm.nih.gov/pubmed/29670096 http://dx.doi.org/10.1038/s41467-018-03973-8 |
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