The diagnostic role of diffusional kurtosis imaging in glioma grading and differentiation of gliomas from other intra-axial brain tumours: a systematic review with critical appraisal and meta-analysis

Journal article

Purpose We aim to illustrate the diagnostic performance of diffusional kurtosis imaging (DKI) in the diagnosis of gliomas. Methods A review protocol was developed according to the (PRISMA-P) checklist, registered in the international prospective register of systematic reviews (PROSPERO) and published. A literature search in 4 databases was performed using the keywords ‘glioma’ and ‘diffusional kurtosis’. After applying a robust inclusion/exclusion criteria, included articles were independently evaluated according to the QUADAS-2 tool and data extraction was done. Reported sensitivities and specificities were used to construct 2 × 2 tables and paired forest plots using the Review Manager (RevMan®) software. A random-effect model was pursued using the hierarchical summary receiver operator characteristics. Results A total of 216 hits were retrieved. Considering duplicates and inclusion criteria, 23 articles were eligible for full-text reading. Ultimately, 19 studies were eligible for final inclusion. The quality assessment revealed 9 studies with low risk of bias in the 4 domains. Using a bivariate random-effect model for data synthesis, summary ROC curve showed a pooled area under the curve (AUC) of 0.92 and estimated sensitivity of 0.87 (95% CI 0.78–0.92) in high-/low-grade gliomas’ differentiation. A mean difference in mean kurtosis (MK) value between HGG and LGG of 0.22 (95% CI 0.25–0.19) was illustrated (p value = 0.0014) with moderate heterogeneity (I2 = 73.8%). Conclusion DKI shows good diagnostic accuracy in the differentiation of high- and low-grade gliomas further supporting its potential role in clinical practice. Further exploration of DKI in differentiating IDH status and in characterising non-glioma CNS tumours is however needed

Authors: Abdalla, G; Dixon, L; Sanverdi, E; Machado, PM; Kwong, JSW

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Journal: Neuroradiology
• Volume: 62
• Issue: 7
• Pages: 791-802
• Publication date: 2020-05-04
• DOI: 10.1007/s00234-020-02425-9
• EISSN: 1432-1920
• ISSN: 0028-3940
• Language: English
• Keywords: Grading (engineering); Statistics; Data extraction; Mathematics; Receiver operating characteristic; Pathology; Medical physics; Internal medicine; Kurtosis; Medicine; Critical appraisal; MEDLINE; Forest plot; Publication bias; Glioma; Meta-analysis