Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.
Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.
Eur J Neurol. 2017 Feb;24(2):292-301. doi: 10.1111/ene.13200. Epub 2016 Nov 22.
While impaired cognitive performance is common in multiple sclerosis (MS), it has been largely underdiagnosed. Here a magnetic resonance imaging (MRI) screening algorithm is proposed to identify patients at highest risk of cognitive impairment. The objective was to examine whether assessment of lesion burden together with whole brain atrophy on MRI improves our ability to identify cognitively impaired MS patients.
Of the 1253 patients enrolled in the study, 1052 patients with all cognitive, volumetric MRI and clinical data available were included in the analysis. Brain MRI and neuropsychological assessment with the Brief International Cognitive Assessment for Multiple Sclerosis were performed. Multivariable logistic regression and individual prediction analysis were used to investigate the associations between MRI markers and cognitive impairment. The results of the primary analysis were validated at two subsequent time points (months 12 and 24).
The prevalence of cognitive impairment was greater in patients with low brain parenchymal fraction (BPF) (<0.85) and high T2 lesion volume (T2-LV) (>3.5 ml) than in patients with high BPF (>0.85) and low T2-LV (<3.5 ml), with an odds ratio (OR) of 6.5 (95% CI 4.4-9.5). Low BPF together with high T2-LV identified in 270 (25.7%) patients predicted cognitive impairment with 83% specificity, 82% negative predictive value, 51% sensitivity and 75% overall accuracy. The risk of confirmed cognitive decline over the follow-up was greater in patients with high T2-LV (OR 2.1; 95% CI 1.1-3.8) and low BPF (OR 2.6; 95% CI 1.4-4.7).
The integrated MRI assessment of lesion burden and brain atrophy may improve the stratification of MS patients who may benefit from cognitive assessment.
认知功能障碍在多发性硬化症(MS)中较为常见,但很大程度上被漏诊。本研究提出一种磁共振成像(MRI)筛查算法,以识别认知功能障碍风险最高的患者。本研究旨在探讨评估病灶负荷与脑萎缩是否能提高识别认知障碍 MS 患者的能力。
在纳入的 1253 例患者中,1052 例具有完整认知、容积 MRI 和临床数据的患者纳入分析。进行脑 MRI 和神经心理学评估,采用简短国际认知评估多发性硬化量表。采用多变量逻辑回归和个体预测分析,探讨 MRI 标志物与认知障碍的相关性。主要分析结果在随后的两个时间点(12 个月和 24 个月)进行验证。
脑实质分数(BPF)较低(<0.85)和 T2 病灶体积(T2-LV)较高(>3.5 ml)的患者认知障碍发生率高于 BPF 较高(>0.85)和 T2-LV 较低(<3.5 ml)的患者,比值比(OR)为 6.5(95%可信区间 4.4-9.5)。270 例(25.7%)患者同时存在低 BPF 和高 T2-LV,可预测认知障碍,特异性为 83%,阴性预测值为 82%,敏感性为 51%,总准确率为 75%。在随访期间,T2-LV 较高(OR 2.1;95%可信区间 1.1-3.8)和 BPF 较低(OR 2.6;95%可信区间 1.4-4.7)的患者发生确诊认知下降的风险更大。
病灶负荷和脑萎缩的综合 MRI 评估可能改善 MS 患者的分层,这些患者可能受益于认知评估。