Biological Psychology, Department of Psychology, School of Medicine and Health Sciences, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
Cluster of Excellence "Hearing4all", Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
Sci Rep. 2020 Dec 17;10(1):22238. doi: 10.1038/s41598-020-79289-9.
The hypothalamus is a small, yet highly versatile structure mainly involved in bodily functions such as control of food intake and endocrine activity. Functional anatomy of different hypothalamic areas is mainly investigated using structural MRI, validated by ex-vivo histological studies. Based on diffusion-weighted imaging (DWI), recent automated clustering methods provide robust tools for parcellation. Using data of 100 healthy adults provided by the Human Connectome Project Database, we applied DWI-based automated clustering to the hypothalamus and related microstructural properties in these hypothalamic compartments to obesity. Our results suggest that the hypothalamus can be reliably partitioned into four clusters in each hemisphere using diffusion-based parcellation. These correspond to an anterior-superior, anterior-inferior, intermediate, and posterior cluster. Obesity was predicted by mean diffusivity of the anterior-superior cluster, suggesting altered inhibition of food intake. The proposed method provides an automated hypothalamic parcellation technique based on DWI data to explore anatomy and function of hypothalamic subunits in vivo in humans.
下丘脑是一个体积小但功能多样的结构，主要参与控制食物摄入和内分泌活动等身体功能。不同下丘脑区域的功能解剖结构主要通过结构磁共振成像（MRI）进行研究，并通过离体组织学研究进行验证。基于弥散加权成像（DWI），最近的自动聚类方法为分割提供了强大的工具。我们使用人类连接组计划数据库提供的 100 名健康成年人的数据，将基于 DWI 的自动聚类应用于下丘脑及其相关微结构特性与肥胖的关系。我们的研究结果表明，使用基于扩散的分割方法，可以在每个半球中将下丘脑可靠地分为四个簇。这些簇对应于前上、前下、中间和后簇。前上簇的平均扩散系数可以预测肥胖，提示食物摄入抑制的改变。本研究提出的方法提供了一种基于 DWI 数据的自动下丘脑分割技术，可在人体内探索下丘脑亚单位的解剖结构和功能。
