Dataset Information

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.

ABSTRACT: 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.

SUBMITTER: Abdalla G

PROVIDER: S-EPMC7311378 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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.

Abdalla Gehad G Dixon Luke L Sanverdi Eser E Machado Pedro M PM Kwong Joey S W JSW Panovska-Griffiths Jasmina J Rojas-Garcia Antonio A Yoneoka Daisuke D Veraart Jelle J Van Cauter Sofie S Abdel-Khalek Ahmed M AM Settein Magdy M Yousry Tarek T Bisdas Sotirios S

Neuroradiology 20200504 7

<h4>Purpose</h4>We aim to illustrate the diagnostic performance of diffusional kurtosis imaging (DKI) in the diagnosis of gliomas.<h4>Methods</h4>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 ...[more]

PMID: 32367349

Similar Datasets

Project description:INTRODUCTION:Central nervous system (CNS) gliomas are the most common primary intra-axial brain tumours and pose variable treatment response according to their grade, therefore, precise staging is mandatory. Histopathological analysis of surgical tumour samples is still deemed as the state-of-the-art staging technique for gliomas due to the moderate specificity of the available non-invasive imaging modalities. A recently evolved analysis of the tissue water diffusion properties, known as diffusional kurtosis imaging (DKI), is a dimensionless metric, which quantifies water molecules' degree of non-Gaussian diffusion, hence reflects tissue microenvironment's complexity by means of non-invasive diffusion-weighted MRI acquisitions. The objective of this systematic review and meta-analysis is to explore the performance of DKI in the presurgical grading of gliomas, both regarding the differentiation between high-grade and low-grade gliomas as well as the discrimination between gliomas and other intra-axial brain tumours. METHODS AND ANALYSIS:We will search PubMed, Medline via Ovid, Embase and Scopus in July 2018 for research studies published between January 1990 and June 2018 with no language restrictions, which have reported on the performance of DKI in diagnosing CNS gliomas. Robust inclusion/exclusion criteria will be applied for selection of eligible articles. Two authors will separately perform quality assessment according to the quality assessment of diagnostic accuracy studies-2 tool. Data will be extracted in a predesigned spreadsheet. A meta-analysis will be held using a random-effects model if substantial statistical heterogeneity is expected. The heterogeneity of studies will be evaluated, and sensitivity analyses will be conducted according to individual study quality. ETHICS AND DISSEMINATION:This work will be based on published studies; hence, it does not require institutional review board approval or ethics clearance. The results will be published in peer-reviewed journals. PROSPERO REGISTRATION NUMBER:CRD42018099192.

Project description:Background and purposeConventional MR imaging typically yields normal images of the brain or indicates lesions in areas of high aquaporin expression in patients with neuromyelitis optica. Diffusional kurtosis imaging was applied in patients with neuromyelitis optica to determine whether this technique could detect alterations in diffusion and diffusional kurtosis parameters in normal-appearing white matter and to explore the relationship between diffusional kurtosis imaging and DTI parameters.Materials and methodsThirteen patients with neuromyelitis optica and 13 healthy controls underwent MR imaging of the brain with conventional and diffusional kurtosis imaging sequences. Tract-based spatial statistics and region-of-interest-based analyses were conducted to identify differences between patients with neuromyelitis optica and controls through conventional DTI and diffusional kurtosis imaging parameters. The parameters were correlated to determine the potential relationship between them.ResultsCompared with healthy controls, several diffusional kurtosis imaging and DTI parameters were altered in various fiber tracts of patients with neuromyelitis optica (P < .05). A significant decrease (P < .05) in radial kurtosis was observed in the corpus callosum and anterior corona radiata and left optic radiation. Differences (P < .1) in mean kurtosis were found in patients with neuromyelitis optica. We found a negative correlation between diffusional kurtosis imaging (radial kurtosis, axial kurtosis, mean kurtosis) and the corresponding DTI parameters (radial diffusivity, axial diffusivity, mean diffusivity). Positive correlations were found for radial kurtosis and mean kurtosis with fractional anisotropy.ConclusionsThis study demonstrated differences in conventional diffusion and diffusional kurtosis parameters, especially radial kurtosis, in the normal-appearing white matter of patients with neuromyelitis optica compared with healthy controls. Larger studies of patients with neuromyelitis optica should be performed to assess the potential clinical impact of these findings.

Project description:Background and purposeDiffusional kurtosis imaging is an MR imaging technique that provides microstructural information in biologic systems. Its application in clinical studies, however, is hampered by long acquisition and postprocessing times. We evaluated a new and fast (2 minutes 46 seconds) diffusional kurtosis imaging method with regard to glioma grading, compared it with conventional diffusional kurtosis imaging, and compared the diagnostic accuracy of fast mean kurtosis (MK') to that of the widely used mean diffusivity.Materials and methodsMK' and mean diffusivity were measured in the contrast-enhancing tumor core, the perifocal hyperintensity (indicated on T2 FLAIR images), and the contralateral normal-appearing white and gray matter of 34 patients (22 with high-grade and 12 with low-grade gliomas). MK' and mean diffusivity in the different tumor grades were compared by using a Wilcoxon rank sum test. Receiver operating characteristic curves and the areas under the curve were calculated to determine the diagnostic accuracy of MK' and mean diffusivity.ResultsMK' in the tumor core, but not mean diffusivity, differentiated high-grade from low-grade gliomas, and MK' differentiated glioblastomas from the remaining gliomas with high accuracy (area under the curveMK' = 0.842; PMK' < .001). MK' and mean diffusivity identified glioblastomas in the group of high-grade gliomas with similar significance and accuracy (area under the curveMK' = 0.886; area under the curvemean diffusivity = 0.876; PMK' = .003; Pmean diffusivity = .004). The mean MK' in all tissue types was comparable to that obtained by conventional diffusional kurtosis imaging.ConclusionsThe diffusional kurtosis imaging approach used here is considerably faster than conventional diffusional kurtosis imaging methods but yields comparable results. It can be accommodated in clinical protocols and enables exploration of the role of MK' as a biomarker in determining glioma subtypes or response evaluation.

Dataset Information

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.

Publications

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.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets