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Quantitative analysis of in-vivo microbubble distribution in the human brain
Microbubbles (MB) are widely used as contrast agents to perform contrast-enhanced ultrasound (CEUS) imaging and as acoustic amplifiers of mechanical bioeffects incited by therapeutic-level ultrasound. The distribution of MBs in the brain is not yet fully understood, thereby limiting intra-operative...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175375/ https://www.ncbi.nlm.nih.gov/pubmed/34083642 http://dx.doi.org/10.1038/s41598-021-91252-w |
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author | Prada, Francesco Gennari, Antonio G. Linville, Ian M. Mutersbaugh, Michael E. Chen, Zhihang Sheybani, Natasha DiMeco, Francesco Padilla, Frederic Hossack, John A. |
author_facet | Prada, Francesco Gennari, Antonio G. Linville, Ian M. Mutersbaugh, Michael E. Chen, Zhihang Sheybani, Natasha DiMeco, Francesco Padilla, Frederic Hossack, John A. |
author_sort | Prada, Francesco |
collection | PubMed |
description | Microbubbles (MB) are widely used as contrast agents to perform contrast-enhanced ultrasound (CEUS) imaging and as acoustic amplifiers of mechanical bioeffects incited by therapeutic-level ultrasound. The distribution of MBs in the brain is not yet fully understood, thereby limiting intra-operative CEUS guidance or MB-based FUS treatments. In this paper we describe a robust platform for quantification of MB distribution in the human brain, allowing to quantitatively discriminate between tumoral and normal brain tissues and we provide new information regarding real-time cerebral MBs distribution. Intraoperative CEUS imaging was performed during surgical tumor resection using an ultrasound machine (MyLab Twice, Esaote, Italy) equipped with a multifrequency (3–11 MHz) linear array probe (LA332) and a specific low mechanical index (MI < 0.4) CEUS algorithm (CnTi, Esaote, Italy; section thickness, 0.245 cm) for non-destructive continuous MBs imaging. CEUS acquisition is started by enabling the CnTI PEN-M algorithm automatically setting the MI at 0.4 with a center frequency of 2.94 MHz–10 Hz frame rate at 80 mm—allowing for continuous non-destructive MBs imaging. 19 ultrasound image sets of adequate length were selected and retrospectively analyzed using a custom image processing software for quantitative analysis of echo power. Regions of interest (ROIs) were drawn on key structures (artery–tumor–white matter) by a blinded neurosurgeon, following which peak enhancement and time intensity curves (TICs) were quantified. CEUS images revealed clear qualitative differences in MB distribution: arteries showed the earliest and highest enhancement among all structures, followed by tumor and white matter regions, respectively. The custom software built for quantitative analysis effectively captured these differences. Quantified peak intensities showed regions containing artery, tumor or white matter structures having an average MB intensity of 0.584, 0.436 and 0.175 units, respectively. Moreover, the normalized area under TICs revealed the time of flight for MB to be significantly lower in brain tissue as compared with tumor tissue. Significant heterogeneities in TICs were also observed within different regions of the same brain lesion. In this study, we provide the most comprehensive strategy for accurate quantitative analysis of MBs distribution in the human brain by means of CEUS intraoperative imaging. Furthermore our results demonstrate that CEUS imaging quantitative analysis enables discernment between different types of brain tumors as well as regions and structures within the brain. Similar considerations will be important for the planning and implementation of MB-based imaging or treatments in the future. |
format | Online Article Text |
id | pubmed-8175375 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81753752021-06-04 Quantitative analysis of in-vivo microbubble distribution in the human brain Prada, Francesco Gennari, Antonio G. Linville, Ian M. Mutersbaugh, Michael E. Chen, Zhihang Sheybani, Natasha DiMeco, Francesco Padilla, Frederic Hossack, John A. Sci Rep Article Microbubbles (MB) are widely used as contrast agents to perform contrast-enhanced ultrasound (CEUS) imaging and as acoustic amplifiers of mechanical bioeffects incited by therapeutic-level ultrasound. The distribution of MBs in the brain is not yet fully understood, thereby limiting intra-operative CEUS guidance or MB-based FUS treatments. In this paper we describe a robust platform for quantification of MB distribution in the human brain, allowing to quantitatively discriminate between tumoral and normal brain tissues and we provide new information regarding real-time cerebral MBs distribution. Intraoperative CEUS imaging was performed during surgical tumor resection using an ultrasound machine (MyLab Twice, Esaote, Italy) equipped with a multifrequency (3–11 MHz) linear array probe (LA332) and a specific low mechanical index (MI < 0.4) CEUS algorithm (CnTi, Esaote, Italy; section thickness, 0.245 cm) for non-destructive continuous MBs imaging. CEUS acquisition is started by enabling the CnTI PEN-M algorithm automatically setting the MI at 0.4 with a center frequency of 2.94 MHz–10 Hz frame rate at 80 mm—allowing for continuous non-destructive MBs imaging. 19 ultrasound image sets of adequate length were selected and retrospectively analyzed using a custom image processing software for quantitative analysis of echo power. Regions of interest (ROIs) were drawn on key structures (artery–tumor–white matter) by a blinded neurosurgeon, following which peak enhancement and time intensity curves (TICs) were quantified. CEUS images revealed clear qualitative differences in MB distribution: arteries showed the earliest and highest enhancement among all structures, followed by tumor and white matter regions, respectively. The custom software built for quantitative analysis effectively captured these differences. Quantified peak intensities showed regions containing artery, tumor or white matter structures having an average MB intensity of 0.584, 0.436 and 0.175 units, respectively. Moreover, the normalized area under TICs revealed the time of flight for MB to be significantly lower in brain tissue as compared with tumor tissue. Significant heterogeneities in TICs were also observed within different regions of the same brain lesion. In this study, we provide the most comprehensive strategy for accurate quantitative analysis of MBs distribution in the human brain by means of CEUS intraoperative imaging. Furthermore our results demonstrate that CEUS imaging quantitative analysis enables discernment between different types of brain tumors as well as regions and structures within the brain. Similar considerations will be important for the planning and implementation of MB-based imaging or treatments in the future. Nature Publishing Group UK 2021-06-03 /pmc/articles/PMC8175375/ /pubmed/34083642 http://dx.doi.org/10.1038/s41598-021-91252-w Text en © The Author(s) 2021 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Prada, Francesco Gennari, Antonio G. Linville, Ian M. Mutersbaugh, Michael E. Chen, Zhihang Sheybani, Natasha DiMeco, Francesco Padilla, Frederic Hossack, John A. Quantitative analysis of in-vivo microbubble distribution in the human brain |
title | Quantitative analysis of in-vivo microbubble distribution in the human brain |
title_full | Quantitative analysis of in-vivo microbubble distribution in the human brain |
title_fullStr | Quantitative analysis of in-vivo microbubble distribution in the human brain |
title_full_unstemmed | Quantitative analysis of in-vivo microbubble distribution in the human brain |
title_short | Quantitative analysis of in-vivo microbubble distribution in the human brain |
title_sort | quantitative analysis of in-vivo microbubble distribution in the human brain |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8175375/ https://www.ncbi.nlm.nih.gov/pubmed/34083642 http://dx.doi.org/10.1038/s41598-021-91252-w |
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