MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc Polikliniek Neurologie, Attn. MS Center Amsterdam, P. O. Box 7057, 1007 MB, Amsterdam, The Netherlands.
MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
J Neurol. 2024 Sep;271(9):5958-5968. doi: 10.1007/s00415-024-12516-9. Epub 2024 Jul 15.
Digital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression.
To study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS.
In this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates.
In PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12.
Our results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools.
使用基于智能手机的监测工具对多发性硬化症（MS）患者进行数字监测是评估疾病活动和进展的一种很有前途的方法。
研究多发性硬化症患者主动和被动数字监测参数与 MRI 体积测量之间的横断面和纵向关联。
在这项前瞻性研究中，纳入了 92 名多发性硬化症患者。在基线（M0）和 12 个月随访（M12）时进行临床测试（扩展残疾状况量表（EDSS）、定时 25 英尺步行测试（T25FW）、9 孔钉测试（NHPT）和符号数字模态测试（SDMT））和结构 MRI 扫描。主动监测包括基于智能手机的符号数字模态测试（sSDMT）和 2 分钟步行测试（s2MWT），而被动监测则基于智能手机按键动力学（KD）。使用线性回归分析确定数字和临床结果与脑体积之间的横断面和纵向关系，以年龄、疾病持续时间和性别为协变量。
在多发性硬化症患者中，sSDMT 和 SDMT 均与丘脑体积和病变体积相关。KD 与脑、脑室、丘脑和病变体积相关。s2MWT 与 MRI 体积之间没有发现任何关系。NHPT 评分仅与病变体积相关，而 EDSS 和 T25FW 与 MRI 无关。在 M0 和 M12 之间，任何结果测量都没有发现任何纵向关联。
我们的结果表明，数字生物标志物与多发性硬化症患者的脑体积之间存在明显的横断面相关性，而这些相关性并非都存在于传统的临床结局中，这支持了数字监测工具的潜在附加价值。
