Construction and validation of a database of head models for functional imaging of the neonatal brain,Human Brain Mapping

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Construction and validation of a database of head models for functional imaging of the neonatal brain
Human Brain Mapping ( IF 3.5 ) Pub Date : 2020-10-17 , DOI: 10.1002/hbm.25242
Liam H Collins-Jones _{1,

2} , Tomoki Arichi _{3,

4} , Tanya Poppe ₃ , Addison Billing _{1,

5} , Jiaxin Xiao ₃ , Lorenzo Fabrizi ₆ , Sabrina Brigadoi _{7,

8} , Jeremy C Hebden _{1,

2} , Clare E Elwell ₁ , Robert J Cooper _{1,

2}

Affiliation

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.

中文翻译：

新生儿脑功能成像头部模型数据库的构建和验证

新生儿的大脑在妊娠的最后三个月经历了剧烈的结构和功能变化。因此，从头皮记录的大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方面，因此这样的模型不能代表个体水平的解剖学。在这项工作中，我们使用来自开发中的人类连接组项目的 29-44 周月经后年龄的 215 个个体水平数据集描述了新生儿头部个体结构先验数据库的构建。我们已经验证了一种针对手动分割来分割脑外组织的方法。我们还进行了遗漏分析，以量化使用数据库中最匹配的个体代替特定主题模型时在定位功能激活方面产生的预期空间误差；中值误差计算为 8.3 毫米（中值绝对偏差 3.8 毫米）。该数据库可应用于任何需要结构数据的功能性神经成像模式，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 免费获得。

更新日期：2020-10-17

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