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Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis

  • Authors:
    • Jiefang Wang
    • Zhichao Chen
    • Jieyun Chen
  • View Affiliations / Copyright

    Affiliations: Department of Radiology, Quanzhou First Hospital Affiliated to Fujian Medical University, Quanzhou, Fujian 362000, P.R. China, Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian 362000, P.R. China
    Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 436
    |
    Published online on: August 23, 2023
       https://doi.org/10.3892/ol.2023.14023
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Abstract

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.
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Copy and paste a formatted citation
Spandidos Publications style
Wang J, Chen Z and Chen J: Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis. Oncol Lett 26: 436, 2023.
APA
Wang, J., Chen, Z., & Chen, J. (2023). Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis. Oncology Letters, 26, 436. https://doi.org/10.3892/ol.2023.14023
MLA
Wang, J., Chen, Z., Chen, J."Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis". Oncology Letters 26.4 (2023): 436.
Chicago
Wang, J., Chen, Z., Chen, J."Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis". Oncology Letters 26, no. 4 (2023): 436. https://doi.org/10.3892/ol.2023.14023
Copy and paste a formatted citation
x
Spandidos Publications style
Wang J, Chen Z and Chen J: Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis. Oncol Lett 26: 436, 2023.
APA
Wang, J., Chen, Z., & Chen, J. (2023). Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis. Oncology Letters, 26, 436. https://doi.org/10.3892/ol.2023.14023
MLA
Wang, J., Chen, Z., Chen, J."Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis". Oncology Letters 26.4 (2023): 436.
Chicago
Wang, J., Chen, Z., Chen, J."Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis". Oncology Letters 26, no. 4 (2023): 436. https://doi.org/10.3892/ol.2023.14023
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