Performance of Magnetic Resonance Imaging-based Permeability Indices for Preoperative Glioma Grading.

Introduction: Due to the inherent limitations of histopathology as the gold standard method for glioma grading, in recent years, alternative methods, including methods based on imaging data, have been proposed for better glioma grading. This study aimed to determine the performance of permeability p...

Full description

Bibliographic Details
Published in:Journal of Basic Research in Medical Sciences Vol. 13; no. 1; pp. 34 - 43
Main Authors: Alikhani, Sina, Zakariaee, Seyed Salman
Format: diagnostic images equations & formulas research tables/charts Journal Article
Published: Ilam University of Medical Sciences 2026
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194361504&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 194361504
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        23830506
        N1MR
      jtl: Journal of Basic Research in Medical Sciences
      issn: 23830506
      maglogo: N
    pubinfo:
      dt: 2026
      vid: 13
      iid: 1
      pid: 63388
      pub: Ilam University of Medical Sciences
    artinfo:
      ui:
        194361504
        194361504
        194361504
        194361504
      ppf: 34
      ppct: 9
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: Performance of Magnetic Resonance Imaging-based Permeability Indices for Preoperative Glioma Grading.
      aug:
        au:
          Alikhani, Sina
          Zakariaee, Seyed Salman
        affil: Faculty of Medicine, Ilam University of Medical Sciences, Ilam, Iran
      sug:
        subj:
          Glioma Classification
          Neoplasm Staging
          Preoperative Period
          Magnetic Resonance Imaging Methods
          Sensitivity and Specificity
          Permeability
          Human
          Funding Source
          Male
          Female
          Adult
          Middle Age
          Retrospective Design
          Record Review
          Cross Sectional Studies
          Descriptive Statistics
          Data Analysis Software
          Mann-Whitney U Test
          ROC Curve
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Male
          Female
      ab: Introduction: Due to the inherent limitations of histopathology as the gold standard method for glioma grading, in recent years, alternative methods, including methods based on imaging data, have been proposed for better glioma grading. This study aimed to determine the performance of permeability parameters (Ktrans, Kep, Ve, and Vp) quantified using the dynamic contrast-enhanced MRI (DCE-MRI) method for preoperative glioma grading. Materials & Mediods: The radiological data of 31 patients with pathologically confirmed gliomas were retrospectively reviewed. The permeability parameters, including Ktrans, Kep, Ve, and Vp, were quantified using DCE-MRI data. The Mann-Whitney U test was used to assess the significance of differences in these parameters between different grades of glioma. The performance of the parameters for glioma grading was evaluated using receiver operating characteristic (ROC) curve analysis. Results: The mean age of the patients was 39.2 ± 14.1 years, and 18 of the participants were males (58.06%). Ktrans, Kep, and Vp parameters demonstrated a significant difference between different grades of glioma. The results showed that Ktrans yielded the best grading performance compared to other studied parameters (AUC>71%). Vp, Kep, and Ve parameters ranked next. Conclusion: DCE-MRI provides valuable quantitative parameters that can reliably differentiate between glioma grades. These noninvasive imaging biomarkers can serve as a powerful complement to the standard histopathological grading system, guiding better treatment planning and preventing unnecessary interventions.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N