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扩散峰度成像在脑胶质瘤分级中的作用:一项系统评价与荟萃分析方案

Role of diffusional kurtosis imaging in grading of brain gliomas: a protocol for systematic review and meta-analysis.

作者信息

Abdalla Gehad, Sanverdi Eser, Machado Pedro M, Kwong Joey S W, Panovska-Griffiths Jasmina, Rojas-Garcia Antonio, Yoneoka Daisuke, Yousry Tarek, Bisdas Sotirios

机构信息

Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery UCL Hospitals NHS Trust, London, UK.

MRC Centre for Neuromuscular Diseases & Centre for Rheumatology, University College London, London, UK.

出版信息

BMJ Open. 2018 Dec 14;8(12):e025123. doi: 10.1136/bmjopen-2018-025123.

Abstract

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.

摘要

引言

中枢神经系统(CNS)胶质瘤是最常见的原发性脑内肿瘤,根据其分级表现出不同的治疗反应,因此,精确分期至关重要。由于现有非侵入性成像方式的特异性中等,手术肿瘤样本的组织病理学分析仍被视为胶质瘤的最先进分期技术。最近发展起来的对组织水扩散特性的分析,即扩散峰度成像(DKI),是一种无量纲指标,它量化水分子的非高斯扩散程度,从而通过非侵入性扩散加权磁共振成像采集反映组织微环境的复杂性。本系统评价和荟萃分析的目的是探讨DKI在胶质瘤术前分级中的表现,包括高级别和低级别胶质瘤的鉴别以及胶质瘤与其他脑内肿瘤的区分。

方法与分析

我们将于2018年7月在PubMed、通过Ovid的Medline、Embase和Scopus中检索1990年1月至2018年6月发表的研究,无语言限制,这些研究报告了DKI在诊断中枢神经系统胶质瘤中的表现。将应用严格的纳入/排除标准选择符合条件的文章。两位作者将根据诊断准确性研究质量评估-2工具分别进行质量评估。数据将在预先设计的电子表格中提取。如果预期存在实质性统计异质性,将使用随机效应模型进行荟萃分析。将评估研究的异质性,并根据个体研究质量进行敏感性分析。

伦理与传播

本研究将基于已发表的研究;因此,不需要机构审查委员会批准或伦理许可。研究结果将发表在同行评审期刊上。

PROSPERO注册号:CRD42018099192。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2002/6303635/188f40976a3a/bmjopen-2018-025123f01.jpg

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