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Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments
Solid tumors are typically supplied nutrients by a network of irregular blood vessels. By targeting these vascular networks, it might be possible to hinder cancer growth and metastasis. Vascular disrupting agents induce intertumoral hemorrhaging, making photoacoustic (PA) imaging well positioned to...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Photo-Optical Instrumentation Engineers
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003142/ https://www.ncbi.nlm.nih.gov/pubmed/31707772 http://dx.doi.org/10.1117/1.JBO.24.11.116001 |
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author | Fadhel, Muhannad N. Hysi, Eno Zalev, Jason Kolios, Michael C. |
author_facet | Fadhel, Muhannad N. Hysi, Eno Zalev, Jason Kolios, Michael C. |
author_sort | Fadhel, Muhannad N. |
collection | PubMed |
description | Solid tumors are typically supplied nutrients by a network of irregular blood vessels. By targeting these vascular networks, it might be possible to hinder cancer growth and metastasis. Vascular disrupting agents induce intertumoral hemorrhaging, making photoacoustic (PA) imaging well positioned to detect bleeding due to its sensitivity to hemoglobin and its various states. We introduce a fractal-based numerical model of intertumoral hemorrhaging to simulate the PA signals from disrupted tumor blood vessels. The fractal model uses bifurcated cylinders to represent vascular trees. To mimic bleeding from blood vessels, hemoglobin diffusion from microvessels was simulated. In the simulations, the PA signals were detected by a linear array transducer (30 MHz center frequency) of four different vascular trees. The power spectrum of each beamformed PA signal was computed and fitted to a straight line within the [Formula: see text] bandwidth of the receiving transducer. The spectral slope and midband fit (MBF) based on the fit decreased by [Formula: see text] and 2.12 dB, respectively, 1 h post bleeding, while the [Formula: see text]-intercept increased by 1.21 dB. The results suggest that spectral PA analysis can be used to measure changes in the concentration and spatial distribution of hemoglobin in tissue without the need to resolve individual vessels. The simulations support the feasibility of using PA imaging and spectral analysis in cancer treatment monitoring by detecting microvessel disruption. |
format | Online Article Text |
id | pubmed-7003142 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Society of Photo-Optical Instrumentation Engineers |
record_format | MEDLINE/PubMed |
spelling | pubmed-70031422020-02-14 Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments Fadhel, Muhannad N. Hysi, Eno Zalev, Jason Kolios, Michael C. J Biomed Opt Imaging Solid tumors are typically supplied nutrients by a network of irregular blood vessels. By targeting these vascular networks, it might be possible to hinder cancer growth and metastasis. Vascular disrupting agents induce intertumoral hemorrhaging, making photoacoustic (PA) imaging well positioned to detect bleeding due to its sensitivity to hemoglobin and its various states. We introduce a fractal-based numerical model of intertumoral hemorrhaging to simulate the PA signals from disrupted tumor blood vessels. The fractal model uses bifurcated cylinders to represent vascular trees. To mimic bleeding from blood vessels, hemoglobin diffusion from microvessels was simulated. In the simulations, the PA signals were detected by a linear array transducer (30 MHz center frequency) of four different vascular trees. The power spectrum of each beamformed PA signal was computed and fitted to a straight line within the [Formula: see text] bandwidth of the receiving transducer. The spectral slope and midband fit (MBF) based on the fit decreased by [Formula: see text] and 2.12 dB, respectively, 1 h post bleeding, while the [Formula: see text]-intercept increased by 1.21 dB. The results suggest that spectral PA analysis can be used to measure changes in the concentration and spatial distribution of hemoglobin in tissue without the need to resolve individual vessels. The simulations support the feasibility of using PA imaging and spectral analysis in cancer treatment monitoring by detecting microvessel disruption. Society of Photo-Optical Instrumentation Engineers 2019-11-09 2019-11 /pmc/articles/PMC7003142/ /pubmed/31707772 http://dx.doi.org/10.1117/1.JBO.24.11.116001 Text en © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. |
spellingShingle | Imaging Fadhel, Muhannad N. Hysi, Eno Zalev, Jason Kolios, Michael C. Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments |
title | Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments |
title_full | Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments |
title_fullStr | Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments |
title_full_unstemmed | Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments |
title_short | Photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments |
title_sort | photoacoustic simulations of microvascular bleeding: spectral analysis and its application for monitoring vascular-targeted treatments |
topic | Imaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003142/ https://www.ncbi.nlm.nih.gov/pubmed/31707772 http://dx.doi.org/10.1117/1.JBO.24.11.116001 |
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