Tranfa Mario, Petracca Maria, Moccia Marcello, Scaravilli Alessandra, Barkhof Frederik, Brescia Morra Vincenzo, Carotenuto Antonio, Collorone Sara, Elefante Andrea, Falco Fabrizia, Lanzillo Roberta, Lorenzini Luigi, Schoonheim Menno M, Toosy Ahmed T, Brunetti Arturo, Cocozza Sirio, Quarantelli Mario, Pontillo Giuseppe
Department of Advanced Biomedical Sciences, University "Federico II," Naples, Italy.
Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands.
Neurology. 2025 Feb 25;104(4):e213349. doi: 10.1212/WNL.0000000000213349. Epub 2025 Jan 23.
Although multiple sclerosis (MS) can be conceptualized as a network disorder, brain network analyses typically require advanced MRI sequences not commonly acquired in clinical practice. Using conventional MRI, we assessed cross-sectional and longitudinal structural disconnection and morphometric similarity networks in people with MS (pwMS), along with their relationship with clinical disability.
In this longitudinal monocentric study, 3T structural MRI of pwMS and healthy controls (HC) was retrospectively analyzed. Physical and cognitive disabilities were assessed with the expanded disability status scale (EDSS) and the symbol digit modalities test (SDMT), respectively. Demyelinating lesions were automatically segmented, and the corresponding masks were used to assess pairwise structural disconnection between atlas-defined brain regions based on normative tractography data. Using the Morphometric Inverse Divergence method, we computed morphometric similarity between cortical regions based on FreeSurfer surface reconstruction. Using network-based statistics (NBS) and its extension NBS-predict, we tested whether subject-level connectomes were associated with disease status, progression, clinical disability, and long-term confirmed disability progression (CDP), independently from global lesion burden and atrophy.
We studied 461 pwMS (age = 37.2 ± 10.6 years, F/M = 324/137), corresponding to 1,235 visits (mean follow-up time = 1.9 ± 2.0 years, range = 0.1-13.3 years), and 55 HC (age = 42.4 ± 15.7 years; F/M = 25/30). Long-term clinical follow-up was available for 285 pwMS (mean follow-up time = 12.4 ± 2.8 years), 127 of whom (44.6%) exhibited CDP. At baseline, structural disconnection in pwMS was mostly centered around the thalami and cortical sensory and association hubs, while morphometric similarity was extensively disrupted ( < 0.01). EDSS was related to frontothalamic disconnection ( < 0.01) and disrupted morphometric similarity around the left perisylvian cortex ( = 0.02), while SDMT was associated with cortico-subcortical disconnection in the left hemisphere ( < 0.01). Longitudinally, both structural disconnection and morphometric similarity disruption significantly progressed ( = 0.04 and < 0.01), correlating with EDSS increase (ρ = 0.07, = 0.02 and ρ = 0.11, < 0.001), while baseline disconnection predicted long-term CDP (accuracy = 59% [58-60], = 0.03).
Structural disconnection and morphometric similarity networks, as assessed through conventional MRI, are sensitive to MS-related brain damage and its progression. They explain disease-related clinical disability and predict its long-term evolution independently from global lesion burden and atrophy, potentially adding to established MRI measures as network-based biomarkers of disease severity and progression.
尽管多发性硬化症(MS)可被视为一种网络疾病,但脑网络分析通常需要先进的MRI序列,而这些序列在临床实践中并不常用。我们使用传统MRI评估了MS患者(pwMS)的横断面和纵向结构断开以及形态相似性网络,及其与临床残疾的关系。
在这项纵向单中心研究中,我们对pwMS和健康对照(HC)的3T结构MRI进行了回顾性分析。分别使用扩展残疾状态量表(EDSS)和符号数字模态测验(SDMT)评估身体和认知残疾。对脱髓鞘病变进行自动分割,并使用相应的掩码基于标准化纤维束成像数据评估图谱定义的脑区之间的成对结构断开。使用形态计量逆散度方法,我们基于FreeSurfer表面重建计算了皮质区域之间的形态计量相似性。使用基于网络的统计方法(NBS)及其扩展NBS-predict,我们测试了个体水平的连接组是否与疾病状态、进展、临床残疾和长期确诊的残疾进展(CDP)相关,且独立于整体病变负担和萎缩情况。
我们研究了461例pwMS(年龄 = 37.2 ± 10.6岁,女性/男性 = 324/137),共1235次随访(平均随访时间 = 1.9 ± 2.0年,范围 = 0.1 - 13.3年),以及55例HC(年龄 = 42.4 ± 15.7岁;女性/男性 = 25/30)。对285例pwMS进行了长期临床随访(平均随访时间 = 12.4 ± 2.8年),其中127例(44.6%)出现了CDP。在基线时,pwMS的结构断开主要集中在丘脑以及皮质感觉和联合枢纽周围,而形态计量相似性则受到广泛破坏(P < 0.01)。EDSS与额丘脑断开相关(P < 0.01),且左侧颞周皮质周围的形态计量相似性受到破坏(P = 0.02),而SDMT与左半球皮质 - 皮质下断开相关(P < 0.01)。纵向来看,结构断开和形态计量相似性破坏均显著进展(P = 0.04和P < 0.01),与EDSS增加相关(ρ = 0.07,P = 0.02和ρ = 0.11,P < 0.001),而基线断开可预测长期CDP(准确率 = 59% [58 - 60],P = 0.03)。
通过传统MRI评估的结构断开和形态计量相似性网络对与MS相关的脑损伤及其进展敏感。它们解释了与疾病相关的临床残疾,并独立于整体病变负担和萎缩情况预测其长期演变,可能作为基于网络的疾病严重程度和进展的生物标志物,补充现有的MRI测量方法。