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Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance
Rapid diagnosis and therapeutic monitoring of aggressive diseases such as glioblastoma can improve patient survival by providing physicians the time to optimally deliver treatment. This research tested whether metabolic imaging with hyperpolarized MRI could detect changes in tumor progression faster...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534002/ https://www.ncbi.nlm.nih.gov/pubmed/34685601 http://dx.doi.org/10.3390/cells10102621 |
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author | Salzillo, Travis C. Mawoneke, Vimbai Weygand, Joseph Shetty, Akaanksh Gumin, Joy Zacharias, Niki M. Gammon, Seth T. Piwnica-Worms, David Fuller, Gregory N. Logothetis, Christopher J. Lang, Frederick F. Bhattacharya, Pratip K. |
author_facet | Salzillo, Travis C. Mawoneke, Vimbai Weygand, Joseph Shetty, Akaanksh Gumin, Joy Zacharias, Niki M. Gammon, Seth T. Piwnica-Worms, David Fuller, Gregory N. Logothetis, Christopher J. Lang, Frederick F. Bhattacharya, Pratip K. |
author_sort | Salzillo, Travis C. |
collection | PubMed |
description | Rapid diagnosis and therapeutic monitoring of aggressive diseases such as glioblastoma can improve patient survival by providing physicians the time to optimally deliver treatment. This research tested whether metabolic imaging with hyperpolarized MRI could detect changes in tumor progression faster than conventional anatomic MRI in patient-derived glioblastoma murine models. To capture the dynamic nature of cancer metabolism, hyperpolarized MRI, NMR spectroscopy, and immunohistochemistry were performed at several time-points during tumor development, regression, and recurrence. Hyperpolarized MRI detected significant changes of metabolism throughout tumor progression whereas conventional MRI was less sensitive. This was accompanied by aberrations in amino acid and phospholipid lipid metabolism and MCT1 expression. Hyperpolarized MRI can help address clinical challenges such as identifying malignant disease prior to aggressive growth, differentiating pseudoprogression from true progression, and predicting relapse. The individual evolution of these metabolic assays as well as their correlations with one another provides context for further academic research. |
format | Online Article Text |
id | pubmed-8534002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-85340022021-10-23 Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance Salzillo, Travis C. Mawoneke, Vimbai Weygand, Joseph Shetty, Akaanksh Gumin, Joy Zacharias, Niki M. Gammon, Seth T. Piwnica-Worms, David Fuller, Gregory N. Logothetis, Christopher J. Lang, Frederick F. Bhattacharya, Pratip K. Cells Article Rapid diagnosis and therapeutic monitoring of aggressive diseases such as glioblastoma can improve patient survival by providing physicians the time to optimally deliver treatment. This research tested whether metabolic imaging with hyperpolarized MRI could detect changes in tumor progression faster than conventional anatomic MRI in patient-derived glioblastoma murine models. To capture the dynamic nature of cancer metabolism, hyperpolarized MRI, NMR spectroscopy, and immunohistochemistry were performed at several time-points during tumor development, regression, and recurrence. Hyperpolarized MRI detected significant changes of metabolism throughout tumor progression whereas conventional MRI was less sensitive. This was accompanied by aberrations in amino acid and phospholipid lipid metabolism and MCT1 expression. Hyperpolarized MRI can help address clinical challenges such as identifying malignant disease prior to aggressive growth, differentiating pseudoprogression from true progression, and predicting relapse. The individual evolution of these metabolic assays as well as their correlations with one another provides context for further academic research. MDPI 2021-10-01 /pmc/articles/PMC8534002/ /pubmed/34685601 http://dx.doi.org/10.3390/cells10102621 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Salzillo, Travis C. Mawoneke, Vimbai Weygand, Joseph Shetty, Akaanksh Gumin, Joy Zacharias, Niki M. Gammon, Seth T. Piwnica-Worms, David Fuller, Gregory N. Logothetis, Christopher J. Lang, Frederick F. Bhattacharya, Pratip K. Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance |
title | Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance |
title_full | Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance |
title_fullStr | Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance |
title_full_unstemmed | Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance |
title_short | Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance |
title_sort | measuring the metabolic evolution of glioblastoma throughout tumor development, regression, and recurrence with hyperpolarized magnetic resonance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534002/ https://www.ncbi.nlm.nih.gov/pubmed/34685601 http://dx.doi.org/10.3390/cells10102621 |
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