Takla Taylor N, Feldpausch Jennie, Edwards Erin M, Han Shuo, Calabresi Peter A, Prince Jerry, Zackowski Kathleen M, Fritz Nora E
Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA.
Department of Health Care Sciences, Wayne State University, Detroit, MI 48201, USA.
Brain Sci. 2025 Jan 16;15(1):77. doi: 10.3390/brainsci15010077.
The cerebellum is a common lesion site in persons with multiple sclerosis (PwMS). Physiologic and anatomic studies have identified a topographic organization of the cerebellum including functionally distinct motor and cognitive areas. In this study, a recent parcellation algorithm was applied to a sample of PwMS and healthy controls to examine the relationships among specific cerebellar regions, fall status, and common clinical measures of motor and cognitive functions.
Thirty-one PwMS and twenty-nine age- and sex-matched controls underwent an MRI scan and motor and cognitive testing. The parcellation algorithm was applied to all images and divided the cerebellum into 28 regions. Mann-Whitney U tests were used to compare cerebellar volumes among PwMS and controls, and MS fallers and MS non-fallers. Relationships between cerebellar volumes and motor and cognitive function were evaluated using Spearman correlations.
PwMS performed significantly worse on functional measures compared to controls. We found significant differences in volumetric measures between PwMS and controls in the corpus medullare, lobules I-III, and lobule V. Volumetric differences seen between the PwMS and controls were primarily driven by the MS fallers. Finally, functional performance on motor and cognitive tasks was associated with cerebellar volumes.
Using the parcellation tool, our results showed that the volumes of motor and cognitive lobules impact both motor and cognitive performance, and that functional performance and cerebellar volumes distinguishes the MS fallers from non-fallers. Future studies should explore the potential of cerebellar imaging to predict falls in PwMS.
小脑是多发性硬化症患者（PwMS）常见的病变部位。生理和解剖学研究已确定小脑存在一种拓扑组织，包括功能上不同的运动和认知区域。在本研究中，一种最新的脑区划分算法被应用于PwMS样本和健康对照，以研究特定小脑区域、跌倒状态以及运动和认知功能的常见临床指标之间的关系。
31名PwMS患者和29名年龄及性别匹配的对照者接受了MRI扫描以及运动和认知测试。脑区划分算法应用于所有图像，将小脑分为28个区域。采用曼-惠特尼U检验比较PwMS患者与对照者、PwMS跌倒者与非跌倒者之间的小脑体积。使用斯皮尔曼相关性评估小脑体积与运动和认知功能之间的关系。
与对照者相比，PwMS患者在功能指标上表现明显更差。我们发现PwMS患者与对照者在延髓、小叶I - III和小叶V的体积测量上存在显著差异。PwMS患者与对照者之间的体积差异主要由跌倒的PwMS患者驱动。最后，运动和认知任务的功能表现与小脑体积相关。
使用脑区划分工具，我们的结果表明运动和认知小叶的体积会影响运动和认知表现，并且功能表现和小脑体积可区分跌倒的PwMS患者与非跌倒者。未来的研究应探索小脑成像预测PwMS患者跌倒的潜力。
