Université Clermont Auvergne, Clermont Auvergne INP, CHU Clermont-Ferrand, CNRS, Institut Pascal, F-63000, Clermont-Ferrand, France.
Université Clermont Auvergne, Clermont Auvergne INP, CNRS, Institut Pascal, F-63000, Clermont-Ferrand, France.
Sci Data. 2024 Nov 1;11(1):1189. doi: 10.1038/s41597-024-04053-x.
Understanding the architecture of the human deep brain is especially challenging because of the complex organization of the nuclei and fascicles that support most sensorimotor and behaviour controls. There are scant dedicated tools to explore and analyse this region. Here we took a transdisciplinary approach to build a new deep-brain MRI architecture atlas drawing on advanced clinical experience of MRI-based deep brain mapping. This new tool comprises a young-male-adult MRI template spatially normalized to the ICBM152, containing T1, inversion-recovery, and diffusion MRI datasets (in vivo acquisition), and an MRI atlas of 118 labelled deep brain structures. It is open-source and gives users high resolution image datasets to describe nuclear-based and axonal architecture, combining pioneering and recent knowledge. It is a useful addition to current 3D atlases and clinical tools.
理解人类大脑深部结构特别具有挑战性,因为支持大多数感觉运动和行为控制的核团和束的组织非常复杂。几乎没有专门的工具来探索和分析这个区域。在这里,我们采取跨学科的方法,利用基于 MRI 的大脑深部映射的先进临床经验,构建了一个新的大脑深部 MRI 结构图谱。这个新工具包括一个年轻男性成年人 MRI 模板,空间标准化到 ICBM152,包含 T1、反转恢复和扩散 MRI 数据集(体内采集),以及 118 个标记的大脑深部结构的 MRI 图谱。它是开源的,为用户提供高分辨率的图像数据集,用于描述基于核和轴突的结构,结合了开创性和最新的知识。它是当前 3D 图谱和临床工具的有益补充。