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建立并验证新生儿大脑功能成像头模型数据库。

Construction and validation of a database of head models for functional imaging of the neonatal brain.

机构信息

DOT-HUB, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.

Biomedical Optics Research Laboratory, Medical Physics and Biomedical Engineering, University College London, London, UK.

出版信息

Hum Brain Mapp. 2021 Feb 15;42(3):567-586. doi: 10.1002/hbm.25242. Epub 2020 Oct 17.

Abstract

The neonatal brain undergoes dramatic structural and functional changes over the last trimester of gestation. The accuracy of source localisation of brain activity recorded from the scalp therefore relies on accurate age-specific head models. Although an age-appropriate population-level atlas could be used, detail is lost in the construction of such atlases, in particular with regard to the smoothing of the cortical surface, and so such a model is not representative of anatomy at an individual level. In this work, we describe the construction of a database of individual structural priors of the neonatal head using 215 individual-level datasets at ages 29-44 weeks postmenstrual age from the Developing Human Connectome Project. We have validated a method to segment the extra-cerebral tissue against manual segmentation. We have also conducted a leave-one-out analysis to quantify the expected spatial error incurred with regard to localising functional activation when using a best-matching individual from the database in place of a subject-specific model; the median error was calculated to be 8.3 mm (median absolute deviation 3.8 mm). The database can be applied for any functional neuroimaging modality which requires structural data whereby the physical parameters associated with that modality vary with tissue type and is freely available at www.ucl.ac.uk/dot-hub.

摘要

胎儿大脑在妊娠最后三个月经历显著的结构和功能变化。因此,头皮记录的脑活动源定位的准确性依赖于准确的年龄特异性头部模型。尽管可以使用适合年龄的人群水平图谱,但在构建此类图谱时会丢失细节,特别是在皮质表面的平滑化方面,因此此类模型不能代表个体水平的解剖结构。在这项工作中,我们描述了使用来自发育人类连接组计划的 215 个个体水平数据集,在妊娠后 29-44 周的年龄范围内,构建个体新生儿头部结构先验数据库的方法。我们已经验证了一种针对大脑外组织进行分割的方法,以对抗手动分割。我们还进行了一次留一分析,以量化在使用数据库中最佳匹配的个体代替特定于个体的模型来定位功能激活时所涉及的预期空间误差;中位数误差计算为 8.3 毫米(中位数绝对偏差为 3.8 毫米)。该数据库可应用于任何需要结构数据的功能神经影像学模式,其中与该模式相关的物理参数随组织类型而变化,并可在 www.ucl.ac.uk/dot-hub 上免费获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/29b0/7814762/68df63496298/HBM-42-567-g001.jpg

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