A cytoarchitecture-driven myelin model reveals area-specific signatures in human primary and secondary areas using ultra-high resolution in-vivo brain MRI
A cytoarchitecture-driven myelin model reveals area-specific signatures in human primary and secondary areas using ultra-high resolution in-vivo brain MRI
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DOI：
10.1016/j.neuroimage.2015.04.023
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发表时间：
2015-07-01
期刊：
影响因子：
5.7
通讯作者：
Bazin, P. -L.
中科院分区：
文献类型：
--
作者：
Dinse, J.;Haertwich, N.;Bazin, P. -L.
这项工作提出了一种新的方法，在已知细胞结构的基础上，在大脑磁共振图像中模拟人类皮层的层状髓磷脂模式。首次有可能在定量超高分辨率MR图像中估计特定原发和继发细胞结构区域的皮质内对比度。所提出的技术揭示了不同的区域特异性特征，这可能有助于研究皮质T-1值的空间分布和皮质髓磷脂的总体分布。鉴于缺乏这种一致性图谱，这可能会导致关于细胞和骨髓结构边界一致性的新讨论。将模拟的髓磷脂模式与人类超高分辨率体内7t脑MR图像（9名受试者）的数据进行定量比较。在验证中，将结果与一个死后脑样本及其离体MRI和组织学数据进行比较。提供了分析管道的详细信息。在对大脑分割和皮质结构研究的先进方法越来越感兴趣的背景下，所提出的模型有助于弥合经典组织学揭示的微观解剖与MRI可见的宏观解剖之间的差距。(C) 2015年作者。Elsevier Inc.出版。
This work presents a novel approach for modelling laminar myelin patterns in the human cortex in brain MR images on the basis of known cytoarchitecture. For the first time, it is possible to estimate intracortical contrast visible in quantitative ultra-high resolution MR images in specific primary and secondary cytoarchitectonic areas. The presented technique reveals different area-specific signatures which may help to study the spatial distribution of cortical T-1 values and the distribution of cortical myelin in general. It may lead to a new discussion on the concordance of cyto- and myeloarchitectonic boundaries, given the absence of such concordance atlases. The modelled myelin patterns are quantitatively compared with data from human ultra-high resolution in-vivo 7 T brain MR images (9 subjects). In the validation, the results are compared to one post-mortem brain sample and its ex-vivo MRI and histological data. Details of the analysis pipeline are provided. In the context of the increasing interest in advanced methods in brain segmentation and cortical architectural studies, the presented model helps to bridge the gap between the microanatomy revealed by classical histology and the macroanatomy visible in MRI. (C) 2015 The Authors. Published by Elsevier Inc.