Glioma grade discrimination with MR diffusion kurtosis imaging: A meta-Analysis of diagnostic accuracy

Research output: Contribution to journalArticle

Abstract

Purpose: To assess the diagnostic test accuracy and sources of heterogeneity for the discriminative potential of diffusion kurtosis imaging (DKI) to differentiate low-grade glioma (LGG) (World Health Organization [WHO] grade II) from high-grade glioma (HGG) (WHO grade III or IV). Materials and Methods: The Cochrane Library, Embase, Medline, and the Web of Science Core Collection were systematically searched by two librarians. Retrieved hits were screened for inclusion and were evaluated with the revised tool for quality assessment for diagnostic accuracy studies (commonly known as QUADAS-2) by two researchers. Statistical analysis comprised a random-effects model with associated heterogeneity analysis for mean differences in mean kurtosis (MK) in patients with LGG or HGG. A bivariate restricted maximum likelihood estimation method was used to describe the summary receiver operating characteristics curve and bivariate meta-regression. Results: Ten studies involving 430 patients were included. The mean difference in MK between LGG and HGG was 0.17 (95% confidence interval [CI]: 0.11, 0.22) with a z score equal to 5.86 (P < .001). The statistical heterogeneity was explained by glioma subtype, echo time, and the proportion of recurrent glioma versus primary glioma. The pooled area under the curve was 0.94 for discrimination of HGG from LGG, with 0.85 (95% CI: 0.74, 0.92) sensitivity and 0.92 (95% CI: 0.81, 0.96) specificity. Heterogeneity was driven by neuropathologic subtype and DKI technique. Conclusion: MK shows high diagnostic accuracy in the discrimination of LGG from HGG.

Details

Authors
Organisations
External organisations
  • Karolinska Institutet
  • Karolinska University Hospital
  • Uppsala University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Radiology, Nuclear Medicine and Medical Imaging
Original languageEnglish
Pages (from-to)119-127
Number of pages9
JournalRadiology
Volume287
Issue number1
Publication statusPublished - 2018 Apr 1
Publication categoryResearch
Peer-reviewedYes