Fillmore Paul T, Richards John E, Phillips-Meek Michelle C, Cryer Alison, Stevens Michael
Department of Communication Sciences and Disorders, University of South Carolina, Columbia, S.C., USA.
Dev Neurosci. 2015;37(6):515-32. doi: 10.1159/000438749. Epub 2015 Oct 7.
Accurate labeling of brain structures within an individual or group is a key issue in neuroimaging. Methods for labeling infant brains have depended on the labels done on adult brains or average magnetic resonance imaging (MRI) templates based on adult brains. However, the features of adult brains differ in several ways from infant brains, so the creation of a labeled stereotaxic atlas based on infants would be helpful. The current work builds on the recent creation of age-appropriate average MRI templates during the first year (3, 4.5, 6, 7.5, 9, and 12 months) by creating anatomical label sets for each template.
We created stereotaxic atlases for the age-specific average MRI templates. Manual delineation of cortical and subcortical areas was done on the average templates based on infants during the first year. We also applied a procedure for automatic computation of macroanatomical atlases for individual infant participants using two manually segmented adult atlases (Hammers, LONI Probabilistic Brain Atlas-LPBA40). To evaluate our methods, we did manual delineation of several cortical areas on selected individuals from each age. Linear and nonlinear registration of the individual and average template was used to transform the average atlas into the individual participant's space, and the average-transformed atlas was compared to the individual manually delineated brain areas. We also applied these methods to an external data set - not used in the atlas creation - to test generalizability of the atlases.
Age-appropriate manual atlases were the best fit to the individual manually delineated regions, with more error seen at greater age discrepancy. There was a close fit between the manually delineated and the automatically labeled regions for individual participants and for the age-appropriate template-based atlas transformed into participant space. There was close correspondence between automatic labeling of individual brain regions and those from the age-appropriate template. These relationships held even when tested on an external set of images.
We have created age-appropriate labeled templates for use in the study of infant development at 6 ages (3, 4.5, 6, 7.5, 9, and 12 months). Comparison with manual methods was quite good. We developed three stereotaxic atlases (one manual, two automatic) for each infant age, which should allow more fine-grained analysis of brain structure for these populations than was previously possible with existing tools. The template-based atlases constructed in the current study are available online (http://jerlab.psych.sc.edu/NeurodevelopmentalMRIDatabase).
准确标记个体或群体内的脑结构是神经影像学中的一个关键问题。标记婴儿大脑的方法一直依赖于对成人大脑所做的标记或基于成人大脑的平均磁共振成像(MRI)模板。然而,成人大脑的特征在几个方面与婴儿大脑不同,因此创建基于婴儿的标记立体定向图谱会有所帮助。当前的工作建立在最近创建的一岁以内(3、4.5、6、7.5、9和12个月)适合年龄的平均MRI模板基础上,为每个模板创建解剖学标签集。
我们为特定年龄的平均MRI模板创建了立体定向图谱。基于一岁以内婴儿的平均模板,手动勾勒皮质和皮质下区域。我们还使用两个手动分割的成人大脑图谱(哈默斯图谱、洛杉矶神经影像实验室概率性脑图谱-LPBA40),对个体婴儿参与者应用了一种自动计算大体解剖图谱的程序。为了评估我们的方法,我们对每个年龄组中选定个体的几个皮质区域进行了手动勾勒。使用个体与平均模板的线性和非线性配准,将平均图谱转换到个体参与者的空间,并将转换后的平均图谱与个体手动勾勒的脑区进行比较。我们还将这些方法应用于一个未用于图谱创建的外部数据集,以测试图谱的通用性。
适合年龄的手动图谱与个体手动勾勒的区域拟合度最佳,年龄差异越大,误差越大。对于个体参与者以及转换到参与者空间的基于适合年龄模板的图谱,手动勾勒区域与自动标记区域之间拟合度很高。个体脑区的自动标记与适合年龄模板的标记之间存在密切对应关系。即使在一组外部图像上进行测试,这些关系依然成立。
我们创建了适合6个年龄(3、4.5、6、7.5、9和12个月)用于婴儿发育研究的标记模板。与手动方法的比较结果相当不错。我们为每个婴儿年龄开发了三个立体定向图谱(一个手动图谱、两个自动图谱),这应该能让对这些人群的脑结构进行比现有工具以前所能做到的更精细的分析。本研究中构建的基于模板的图谱可在网上获取(http://jerlab.psych.sc.edu/NeurodevelopmentalMRIDatabase)。