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Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis
No clear conclusions have yet been reached regarding the accuracy of magnetic resonance imaging (MRI) radiomics in distinguishing high-grade glioma (HGG) from low-grade glioma (LGG). In the present study, a meta-analysis was conducted to determine the diagnostic value of MRI radiomics in differentia...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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D.A. Spandidos
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10472021/ https://www.ncbi.nlm.nih.gov/pubmed/37664663 http://dx.doi.org/10.3892/ol.2023.14023 |
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author | Wang, Jiefang Chen, Zhichao Chen, Jieyun |
author_facet | Wang, Jiefang Chen, Zhichao Chen, Jieyun |
author_sort | Wang, Jiefang |
collection | PubMed |
description | No clear conclusions have yet been reached regarding the accuracy of magnetic resonance imaging (MRI) radiomics in distinguishing high-grade glioma (HGG) from low-grade glioma (LGG). In the present study, a meta-analysis was conducted to determine the diagnostic value of MRI radiomics in differentiating between HGG and LGG, in order to guide their clinical diagnosis. PubMed, Embase and the Cochrane Library databases were searched up to November 2022. The search included studies in which true positive, false positive, true negative and false negative values for the differentiation of HGG from LGG were reported or could be calculated by retrograde extrapolation. Duplicate publications, research without full text, studies with incomplete information or unextractable data, animal studies, reviews and systematic reviews were excluded. STATA 15.1 was used to analyze the data. The meta-analysis included 15 studies, which comprised a total of 1,124 patients, of which 701 had HGG and 423 had LGG. The pooled sensitivity and specificity of the studies overall were 0.92 (95% CI: 0.89–0.95) and 0.89 (95% CI: 0.85–0.92), respectively. The positive and negative likelihood ratios of the studies overall were 7.89 (95% CI: 6.01–10.37) and 0.09 (95% CI: 0.07–0.12), respectively. The pooled diagnostic odds ratio of the studies was 85.20 (95% CI: 54.52–133.14). The area under the summary receiver operating characteristic curve was 0.91. These findings indicate that radiomics may be an accurate tool for the differentiation of glioma grades. However, further research is needed to verify the most appropriate of these technologies. |
format | Online Article Text |
id | pubmed-10472021 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-104720212023-09-02 Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis Wang, Jiefang Chen, Zhichao Chen, Jieyun Oncol Lett Articles No clear conclusions have yet been reached regarding the accuracy of magnetic resonance imaging (MRI) radiomics in distinguishing high-grade glioma (HGG) from low-grade glioma (LGG). In the present study, a meta-analysis was conducted to determine the diagnostic value of MRI radiomics in differentiating between HGG and LGG, in order to guide their clinical diagnosis. PubMed, Embase and the Cochrane Library databases were searched up to November 2022. The search included studies in which true positive, false positive, true negative and false negative values for the differentiation of HGG from LGG were reported or could be calculated by retrograde extrapolation. Duplicate publications, research without full text, studies with incomplete information or unextractable data, animal studies, reviews and systematic reviews were excluded. STATA 15.1 was used to analyze the data. The meta-analysis included 15 studies, which comprised a total of 1,124 patients, of which 701 had HGG and 423 had LGG. The pooled sensitivity and specificity of the studies overall were 0.92 (95% CI: 0.89–0.95) and 0.89 (95% CI: 0.85–0.92), respectively. The positive and negative likelihood ratios of the studies overall were 7.89 (95% CI: 6.01–10.37) and 0.09 (95% CI: 0.07–0.12), respectively. The pooled diagnostic odds ratio of the studies was 85.20 (95% CI: 54.52–133.14). The area under the summary receiver operating characteristic curve was 0.91. These findings indicate that radiomics may be an accurate tool for the differentiation of glioma grades. However, further research is needed to verify the most appropriate of these technologies. D.A. Spandidos 2023-08-23 /pmc/articles/PMC10472021/ /pubmed/37664663 http://dx.doi.org/10.3892/ol.2023.14023 Text en Copyright: © Wang et al. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Wang, Jiefang Chen, Zhichao Chen, Jieyun Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis |
title | Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis |
title_full | Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis |
title_fullStr | Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis |
title_full_unstemmed | Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis |
title_short | Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis |
title_sort | diagnostic value of mri radiomics in differentiating high‑grade glioma from low‑grade glioma: a meta‑analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10472021/ https://www.ncbi.nlm.nih.gov/pubmed/37664663 http://dx.doi.org/10.3892/ol.2023.14023 |
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