Gupta A, Al-Dasuqi K, Xia F, Askin G, Zhao Y, Delgado D, Wang Y
From the Department of Radiology (A.G., K.A.-D., F.X., Y.W.)
Clinical and Translational Neuroscience Unit (A.G.), Feil Family Brain and Mind Research Institute.
AJNR Am J Neuroradiol. 2017 Jul;38(7):1317-1322. doi: 10.3174/ajnr.A5209. Epub 2017 May 18.
Concerns have arisen about the long-term health effects of repeat gadolinium injections in patients with multiple sclerosis and the incomplete characterization of MS lesion pathophysiology that results from relying on enhancement characteristics alone.
Our aim was to perform a systematic review and meta-analysis analyzing whether noncontrast MR imaging biomarkers can distinguish enhancing and nonenhancing brain MS lesions.
Our sources were Ovid MEDLINE, Ovid Embase, and the Cochrane data base from inception to August 2016.
We included 37 journal articles on 985 patients with MS who had MR imaging in which T1-weighted postcontrast sequences were compared with noncontrast sequences obtained during the same MR imaging examination by using ROI analysis of individual MS lesions.
We performed random-effects meta-analyses comparing the standard mean difference of each MR imaging metric taken from enhancing-versus-nonenhancing lesions.
DTI-based fractional anisotropy values are significantly different between enhancing and nonenhancing lesions ( = .02), with enhancing lesions showing decreased fractional anisotropy compared with nonenhancing lesions. Of the other most frequently studied MR imaging biomarkers (mean diffusivity, magnetization transfer ratio, or ADC), none were significantly different ( values of 0.30, 0.47, and 0.19. respectively) between enhancing and nonenhancing lesions. Of the limited studies providing diagnostic accuracy measures, gradient-echo-based quantitative susceptibility mapping had the best performance in discriminating enhancing and nonenhancing MS lesions.
MR imaging techniques and patient characteristics were variable across studies. Most studies did not provide diagnostic accuracy measures. All imaging metrics were not studied in all 37 studies.
Noncontrast MR imaging techniques, such as DTI-based FA, can assess MS lesion acuity without gadolinium.
对于多发性硬化症患者重复注射钆对比剂的长期健康影响以及仅依靠强化特征导致的多发性硬化症病变病理生理学特征描述不完整，人们已产生担忧。
我们的目的是进行一项系统评价和荟萃分析，分析非增强磁共振成像生物标志物是否能够区分强化和非强化的脑多发性硬化症病变。
我们的数据来源是从创刊至2016年8月的Ovid MEDLINE、Ovid Embase和Cochrane数据库。
我们纳入了37篇关于985例多发性硬化症患者的期刊文章，这些患者接受了磁共振成像检查，其中通过对单个多发性硬化症病变进行感兴趣区分析，将T1加权增强后序列与同一磁共振成像检查期间获得的非增强序列进行了比较。
我们进行了随机效应荟萃分析，比较了取自强化与非强化病变的每个磁共振成像指标的标准平均差异。
基于扩散张量成像的分数各向异性值在强化和非强化病变之间存在显著差异（P = 0.02），与非强化病变相比，强化病变的分数各向异性降低。在其他最常研究的磁共振成像生物标志物（平均扩散率、磁化传递率或表观扩散系数）中，强化和非强化病变之间均无显著差异（P值分别为0.30、0.47和0.19）。在提供诊断准确性测量的有限研究中，基于梯度回波的定量磁化率成像在区分强化和非强化的多发性硬化症病变方面表现最佳。
各研究中的磁共振成像技术和患者特征存在差异。大多数研究未提供诊断准确性测量。并非所有37项研究都对所有成像指标进行了研究。
非增强磁共振成像技术，如基于扩散张量成像的分数各向异性，可以在不使用钆对比剂的情况下评估多发性硬化症病变的严重程度。
