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Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI
OBJECTIVES: To investigate whether glioma isocitrate dehydrogenase (IDH) 1 mutation and vascular endothelial growth factor (VEGF) expression can be estimated by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: Chinese Glioma Genome Atlas (CGGA) database...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793903/ https://www.ncbi.nlm.nih.gov/pubmed/33425744 http://dx.doi.org/10.3389/fonc.2020.593102 |
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author | Hu, Yue Chen, Yue Wang, Jie Kang, Jin Juan Shen, Dan Dan Jia, Zhong Zheng |
author_facet | Hu, Yue Chen, Yue Wang, Jie Kang, Jin Juan Shen, Dan Dan Jia, Zhong Zheng |
author_sort | Hu, Yue |
collection | PubMed |
description | OBJECTIVES: To investigate whether glioma isocitrate dehydrogenase (IDH) 1 mutation and vascular endothelial growth factor (VEGF) expression can be estimated by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: Chinese Glioma Genome Atlas (CGGA) database was wined for differential expression of VEGF in gliomas with different IDH genotypes. The VEGF expression and IDH1 genotypes of 56 glioma samples in our hospital were assessed by immunohistochemistry. Preoperative DCE-MRI data of glioma samples were reviewed. Regions of interest (ROIs) covering tumor parenchyma were delineated. Histogram parameters of volume transfer constant (K(trans)) and volume of extravascular extracellular space per unit volume of tissue (V(e)) derived from DCE-MRI were obtained. Histogram parameters of K(trans), V(e) and VEGF expression of IDH1 mutant type (IDH1(mut)) gliomas were compared with the IDH1 wildtype (IDH1(wt)) gliomas. Receiver operating characteristic (ROC) curve analysis was performed to differentiate IDH1(mut) from IDH1(wt) gliomas. The correlation coefficients were determined between histogram parameters of K(trans), V(e) and VEGF expression in gliomas. RESULTS: In CGGA database, VEGF expression in IDH(mut) gliomas was lower as compared to wildtype counterpart. The immunohistochemistry of glioma samples in our hospital also confirmed the results. Comparisons demonstrated statistically significant differences in histogram parameters of K(trans)and V(e) [mean, standard deviation (SD), 50th, 75th, 90th. and 95th percentile] between IDH1(mut)and IDH1(wt)gliomas (P < 0.05, respectively). ROC curve analysis revealed that 50th percentile of K(trans) (0.019 min(−1)) and V(e) (0.039) provided the perfect combination of sensitivity and specificity in differentiating gliomas with IDH1(mut)from IDH1(wt). Irrespective of IDH1 mutation, histogram parameters of K(trans)and V(e) were correlated with VEGF expression in gliomas (P < 0.05, respectively). CONCLUSIONS: VEGF expression is significantly lower in IDH1(mut) gliomas as compared to the wildtype counterpart, and it is non-invasively predictable with histogram analysis of DCE-MRI. |
format | Online Article Text |
id | pubmed-7793903 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77939032021-01-09 Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI Hu, Yue Chen, Yue Wang, Jie Kang, Jin Juan Shen, Dan Dan Jia, Zhong Zheng Front Oncol Oncology OBJECTIVES: To investigate whether glioma isocitrate dehydrogenase (IDH) 1 mutation and vascular endothelial growth factor (VEGF) expression can be estimated by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: Chinese Glioma Genome Atlas (CGGA) database was wined for differential expression of VEGF in gliomas with different IDH genotypes. The VEGF expression and IDH1 genotypes of 56 glioma samples in our hospital were assessed by immunohistochemistry. Preoperative DCE-MRI data of glioma samples were reviewed. Regions of interest (ROIs) covering tumor parenchyma were delineated. Histogram parameters of volume transfer constant (K(trans)) and volume of extravascular extracellular space per unit volume of tissue (V(e)) derived from DCE-MRI were obtained. Histogram parameters of K(trans), V(e) and VEGF expression of IDH1 mutant type (IDH1(mut)) gliomas were compared with the IDH1 wildtype (IDH1(wt)) gliomas. Receiver operating characteristic (ROC) curve analysis was performed to differentiate IDH1(mut) from IDH1(wt) gliomas. The correlation coefficients were determined between histogram parameters of K(trans), V(e) and VEGF expression in gliomas. RESULTS: In CGGA database, VEGF expression in IDH(mut) gliomas was lower as compared to wildtype counterpart. The immunohistochemistry of glioma samples in our hospital also confirmed the results. Comparisons demonstrated statistically significant differences in histogram parameters of K(trans)and V(e) [mean, standard deviation (SD), 50th, 75th, 90th. and 95th percentile] between IDH1(mut)and IDH1(wt)gliomas (P < 0.05, respectively). ROC curve analysis revealed that 50th percentile of K(trans) (0.019 min(−1)) and V(e) (0.039) provided the perfect combination of sensitivity and specificity in differentiating gliomas with IDH1(mut)from IDH1(wt). Irrespective of IDH1 mutation, histogram parameters of K(trans)and V(e) were correlated with VEGF expression in gliomas (P < 0.05, respectively). CONCLUSIONS: VEGF expression is significantly lower in IDH1(mut) gliomas as compared to the wildtype counterpart, and it is non-invasively predictable with histogram analysis of DCE-MRI. Frontiers Media S.A. 2020-12-08 /pmc/articles/PMC7793903/ /pubmed/33425744 http://dx.doi.org/10.3389/fonc.2020.593102 Text en Copyright © 2020 Hu, Chen, Wang, Kang, Shen and Jia http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Hu, Yue Chen, Yue Wang, Jie Kang, Jin Juan Shen, Dan Dan Jia, Zhong Zheng Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI |
title | Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI |
title_full | Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI |
title_fullStr | Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI |
title_full_unstemmed | Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI |
title_short | Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI |
title_sort | non-invasive estimation of glioma idh1 mutation and vegf expression by histogram analysis of dynamic contrast-enhanced mri |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793903/ https://www.ncbi.nlm.nih.gov/pubmed/33425744 http://dx.doi.org/10.3389/fonc.2020.593102 |
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