von Gumberz Johanna, Mahmoudi Mina, Young Kim, Schippling Sven, Martin Roland, Heesen Christoph, Siemonsen Susanne, Stellmann Jan-Patrick
Institute of Neuroimmunology and MS (INIMS), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
PeerJ. 2016 Sep 20;4:e2442. doi: 10.7717/peerj.2442. eCollection 2016.
Magnetic resonance imaging (MRI) is the best biomarker of inflammatory disease activity in relapsing remitting Multiple Sclerosis (RRMS) so far but the association with disability is weak. Appearance of new MRI-lesions is used to evaluate response to immunotherapies in individual patients as well as being the most common primary outcome in phase-2 trials. Measurements of brain atrophy show promising outcomes in natural cohort studies and some phase-2 trials. From a theoretical perspective they might represent irreversible neurodegeneration and be more closely associated with disability. However, these atrophy measurements are not yet established as prognostic factors in real-life clinical routine. High field MRI has improved image quality and resolution and new methods to measure atrophy dynamics have become available.
To investigate the predictive value of MRI classification criteria in to high/low atrophy and inflammation groups, and to explore predictive capacity of two consecutive routine MRI scans for disability progression in RRMS in a real-life prospective cohort.
82 RRMS-patients (40 untreated, 42 treated with immunotherapies, mean age 40 years, median Expanded Disability Status Scale (EDSS) of 2, underwent two clinically indicated MRI scans (3 Tesla) within 5-14 months, and EDSS assessment after a mean of 3.0 (1.5-4.2) years. We investigated the predictive value of predefined classifications in low/high inflammatory and atrophy groups for EDSS progression (≥1.5 if baseline EDSS = 0, ≥1.0 if baseline EDSS <5, ≥0.5 for other) by chi-square tests and by analysis of variance (ANOVA). The classifications were based on current scientific or clinical recommendation (e.g., treatment response criteria). Brain atrophy was assessed with three different methods (SIENA, SIENAX, and FreeSurfer). Post-hoc analyses aimed to explore clinical data and dynamics of MRI outcomes as predictors in multivariate linear and logit models.
Progression was observed in 24% of patients and was independent from treatment status. None of the predefined classifications were predictive for progression. Explorative post-hoc analyses found lower baseline EDSS and higher grey matter atrophy (FreeSurfer) as best predictors (R (2) = 0.29) for EDSS progression and the accuracy was overall good (Area under the curve = 0.81).
Beside EDSS at baseline, short-term grey matter atrophy is predictive for EDSS progression in treated and untreated RRMS. The development of atrophy measurements for individual risk counselling and evaluation of treatment response seems possible, but needs further validation in larger cohorts. MRI-atrophy estimates from the FreeSurfer toolbox seem to be more reliable than older methods.
磁共振成像（MRI）是目前复发缓解型多发性硬化症（RRMS）中炎症性疾病活动的最佳生物标志物，但与残疾的关联较弱。新MRI病变的出现用于评估个体患者对免疫疗法的反应，也是2期试验中最常见的主要结局。脑萎缩测量在自然队列研究和一些2期试验中显示出有前景的结果。从理论角度来看，它们可能代表不可逆的神经退行性变，并且与残疾的关联更为密切。然而，这些萎缩测量在实际临床常规中尚未被确立为预后因素。高场MRI提高了图像质量和分辨率，并且出现了测量萎缩动态的新方法。
研究MRI分类标准对高/低萎缩和炎症组的预测价值，并在实际生活中的前瞻性队列中探索两次连续常规MRI扫描对RRMS患者残疾进展的预测能力。
82例RRMS患者（40例未治疗，42例接受免疫疗法治疗，平均年龄40岁，扩展残疾状态量表（EDSS）中位数为2）在5 - 14个月内接受了两次临床指征的MRI扫描（3特斯拉），并在平均3.0（1.5 - 4.2）年后进行了EDSS评估。我们通过卡方检验和方差分析（ANOVA）研究了低/高炎症和萎缩组中预定义分类对EDSS进展（如果基线EDSS = 0，则≥1.5；如果基线EDSS <5，则≥1.0；其他情况则≥0.5）的预测价值。这些分类基于当前的科学或临床建议（例如，治疗反应标准）。使用三种不同方法（SIENA、SIENAX和FreeSurfer）评估脑萎缩。事后分析旨在探索临床数据和MRI结果的动态变化，作为多变量线性和逻辑模型中的预测因素。
24%的患者出现了进展，且与治疗状态无关。没有一个预定义分类对进展具有预测性。探索性事后分析发现较低的基线EDSS和较高的灰质萎缩（FreeSurfer）是EDSS进展的最佳预测因素（R（2）= 0.29），总体准确性良好（曲线下面积 = 0.81）。
除了基线时的EDSS外，短期灰质萎缩可预测接受治疗和未接受治疗的RRMS患者的EDSS进展。开发用于个体风险咨询和治疗反应评估的萎缩测量方法似乎是可行的，但需要在更大的队列中进行进一步验证。FreeSurfer工具箱的MRI萎缩估计似乎比旧方法更可靠。
