Current Perspectives on In Vivo Noninvasive Tracking of Extracellular Vesicles with Molecular Imaging
Clinical and preclinical in vivo tracking of extracellular vesicles (EVs) are a crucial tool for the development and optimization of EV-based diagnosis and treatment. EVs have gained interest due to their unique properties that make them excellent candidates for biological applications. Noninvasive...
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Online Access: | http://dx.doi.org/10.1155/2017/9158319 |
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doaj-193ff222b2814d9fa28d2a321d16316d2020-11-25T01:02:11ZengHindawi LimitedBioMed Research International2314-61332314-61412017-01-01201710.1155/2017/91583199158319Current Perspectives on In Vivo Noninvasive Tracking of Extracellular Vesicles with Molecular ImagingPrakash Gangadaran0Chae Moon Hong1Byeong-Cheol Ahn2Department of Nuclear Medicine, Kyungpook National University School of Medicine and Hospital, Daegu 700-721, Republic of KoreaDepartment of Nuclear Medicine, Kyungpook National University School of Medicine and Hospital, Daegu 700-721, Republic of KoreaDepartment of Nuclear Medicine, Kyungpook National University School of Medicine and Hospital, Daegu 700-721, Republic of KoreaClinical and preclinical in vivo tracking of extracellular vesicles (EVs) are a crucial tool for the development and optimization of EV-based diagnosis and treatment. EVs have gained interest due to their unique properties that make them excellent candidates for biological applications. Noninvasive in vivo EV tracking has allowed marked progress towards elucidating the mechanisms and functions of EVs in real time in preclinical and clinical studies. In this review, we summarize several molecular imaging methods that deal with EVs derived from different cells, which have allowed investigations of EV biodistribution, as well as their tracking, delivery, and tumor targeting, to determine their physiological functions and to exploit imaging-derived information for EV-based theranostics.http://dx.doi.org/10.1155/2017/9158319 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Prakash Gangadaran Chae Moon Hong Byeong-Cheol Ahn |
spellingShingle |
Prakash Gangadaran Chae Moon Hong Byeong-Cheol Ahn Current Perspectives on In Vivo Noninvasive Tracking of Extracellular Vesicles with Molecular Imaging BioMed Research International |
author_facet |
Prakash Gangadaran Chae Moon Hong Byeong-Cheol Ahn |
author_sort |
Prakash Gangadaran |
title |
Current Perspectives on In Vivo Noninvasive Tracking of Extracellular Vesicles with Molecular Imaging |
title_short |
Current Perspectives on In Vivo Noninvasive Tracking of Extracellular Vesicles with Molecular Imaging |
title_full |
Current Perspectives on In Vivo Noninvasive Tracking of Extracellular Vesicles with Molecular Imaging |
title_fullStr |
Current Perspectives on In Vivo Noninvasive Tracking of Extracellular Vesicles with Molecular Imaging |
title_full_unstemmed |
Current Perspectives on In Vivo Noninvasive Tracking of Extracellular Vesicles with Molecular Imaging |
title_sort |
current perspectives on in vivo noninvasive tracking of extracellular vesicles with molecular imaging |
publisher |
Hindawi Limited |
series |
BioMed Research International |
issn |
2314-6133 2314-6141 |
publishDate |
2017-01-01 |
description |
Clinical and preclinical in vivo tracking of extracellular vesicles (EVs) are a crucial tool for the development and optimization of EV-based diagnosis and treatment. EVs have gained interest due to their unique properties that make them excellent candidates for biological applications. Noninvasive in vivo EV tracking has allowed marked progress towards elucidating the mechanisms and functions of EVs in real time in preclinical and clinical studies. In this review, we summarize several molecular imaging methods that deal with EVs derived from different cells, which have allowed investigations of EV biodistribution, as well as their tracking, delivery, and tumor targeting, to determine their physiological functions and to exploit imaging-derived information for EV-based theranostics. |
url |
http://dx.doi.org/10.1155/2017/9158319 |
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_version_ |
1725206194831753216 |