Kalinowska-Lyszczarz A, Pawlak M A, Pietrzak A, Pawlak-Bus K, Leszczynski P, Puszczewicz M, Paprzycki W, Kozubski W, Michalak S
1 Division of Neurochemistry and Neuropathology, Department of Neurology, Poznan University of Medical Sciences, Poznan, Poland.
2 Department of Neurology and Cerebrovascular Disorders, Poznan University of Medical Sciences, Poznan, Poland.
Lupus. 2018 Sep;27(10):1624-1635. doi: 10.1177/0961203318781004. Epub 2018 Jun 27.
Differentiation of systemic lupus erythematosus (SLE) from multiple sclerosis (MS) can be challenging, especially when neuropsychiatric (NP) symptoms are accompanied by white matter lesions in the brain. Given the lack of discriminative power of currently applied tools for their differentiation, there is an unmet need for other measures that can aid in distinguishing between the two autoimmune disorders. In this study we aimed at exploring whether brain atrophy measures could serve as markers differentiating MS and SLE. Thirty-seven relapsing-remitting MS and 38 SLE patients with nervous system manifestations, matched according to age and disease duration, underwent 1.5 Tesla magnetic resonance imaging (MRI), including volumetric sequences, and clinical assessment. Voxelwise analysis was performed using ANTS-SyN elastic registration protocol, FSL Randomise and Gamma methods. Cortical and subcortical segmentation was performed with Freesurfer 5.3 pipeline using T1-weighted MPRAGE sequence data. Using MRI volumetric markers of general and subcortical gray matter atrophy and clinical variables, we built a stepwise multivariable logistic diagnostic model to identify MRI parameters that best differentiate MS and SLE patients. We found that the best volumetric predictors to distinguish them were: fourth ventricle volume (sensitivity 0.86, specificity 0.57, area under the curve, AUC 0.77), posterior corpus callosum (sensitivity 0.81, specificity 0.57, AUC 0.68), and third ventricle to thalamus ratio (sensitivity 0.42, specificity 0.84, AUC 0.65). The same classifiers were identified in a subgroup analysis that included patients with a short disease duration. In MS brain atrophy and lesion load correlated with clinical disability, while in SLE age was the main determinant of brain volume. This study proposes new imaging parameters for differential diagnosis of MS and SLE with central nervous system involvement. We show there is a different pattern of atrophy in MS and SLE, and the key structural volumes that are differentially affected include fourth ventricle and posterior section of corpus callosum, followed by third ventricle to thalamus ratio. Different correlation patterns between volumetric and clinical data may suggest that while in MS atrophy is driven mainly by disease activity, in SLE it is mostly associated with age. However, these results need further replication in a larger cohort.
将系统性红斑狼疮(SLE)与多发性硬化症(MS)区分开来可能具有挑战性,尤其是当神经精神(NP)症状伴有脑部白质病变时。鉴于目前用于区分它们的工具缺乏鉴别力,因此迫切需要其他有助于区分这两种自身免疫性疾病的措施。在本研究中,我们旨在探讨脑萎缩测量是否可以作为区分MS和SLE的标志物。37例复发缓解型MS患者和38例有神经系统表现的SLE患者,根据年龄和病程进行匹配,接受了1.5特斯拉磁共振成像(MRI)检查,包括容积序列检查和临床评估。使用ANTS-SyN弹性配准协议、FSL Randomise和Gamma方法进行体素分析。使用Freesurfer 5.3流程,利用T1加权MPRAGE序列数据进行皮质和皮质下分割。利用一般和皮质下灰质萎缩的MRI容积标志物以及临床变量,我们建立了一个逐步多变量逻辑诊断模型,以确定最能区分MS和SLE患者的MRI参数。我们发现,区分它们的最佳容积预测指标是:第四脑室容积(敏感性0.86,特异性0.57,曲线下面积,AUC 0.7)、胼胝体后部(敏感性0.81,特异性0.57,AUC 0.68)以及第三脑室与丘脑比值(敏感性0.42,特异性0.84,AUC 0.65)。在一项包括病程较短患者的亚组分析中也确定了相同的分类器。在MS中,脑萎缩和病变负荷与临床残疾相关,而在SLE中,年龄是脑容量的主要决定因素。本研究提出了用于鉴别诊断伴有中枢神经系统受累的MS和SLE的新成像参数。我们表明,MS和SLE存在不同的萎缩模式,受不同影响的关键结构容积包括第四脑室和胼胝体后部,其次是第三脑室与丘脑比值。容积数据和临床数据之间不同的相关模式可能表明,在MS中,萎缩主要由疾病活动驱动,而在SLE中,萎缩大多与年龄相关。然而,这些结果需要在更大的队列中进一步验证。