Landmarking the Brain for Geometric Morphometric Analysis: An Error Study
Landmarking the Brain for Geometric Morphometric Analysis: An Error Study
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DOI：
10.1371/journal.pone.0086005
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发表时间：
2014-01-28
期刊：
影响因子：
3.7
通讯作者：
DeLeon, Valerie B.
中科院分区：
文献类型：
--
作者：
Chollet, Madeleine B.;Aldridge, Kristina;DeLeon, Valerie B.
神经解剖表型通常使用体积分析进行评估。尽管这种方法功能强大且用途广泛，但它的局限性在于它无法量化形状的变化，无法描述区域之间的相互关系，也无法确定大小的变化是全局的还是局部的。统计形状分析使用坐标数据从生物学相关的标志是测试这些方面的表型的首选方法。到目前为止，大约有50个地标被用于研究大脑形状。在使用基于地标的大脑统计形状分析的研究中，大多数都没有发表地标识别的协议或这些地标的可靠性研究结果。本研究的主要目的有两个：(1)合作开发一组大脑地标的详细数据收集协议；(2)完成一组地标的观察者内部和观察者之间的验证研究。使用10名12岁男孩的样本，制定了29个皮质和皮质下地标的详细方案。最终标记组的平均观察者内误差为1.9 mm，范围为0.72 mm-5.6 mm。平均观察者间误差为1.1 mm，误差范围为0.40 mm-3.4 mm。这项研究成功地建立了具有里程碑意义的协议与最小的误差水平，可用于其他研究人员在评估神经解剖表型。
Neuroanatomic phenotypes are often assessed using volumetric analysis. Although powerful and versatile, this approach is limited in that it is unable to quantify changes in shape, to describe how regions are interrelated, or to determine whether changes in size are global or local. Statistical shape analysis using coordinate data from biologically relevant landmarks is the preferred method for testing these aspects of phenotype. To date, approximately fifty landmarks have been used to study brain shape. Of the studies that have used landmark-based statistical shape analysis of the brain, most have not published protocols for landmark identification or the results of reliability studies on these landmarks. The primary aims of this study were two-fold: (1) to collaboratively develop detailed data collection protocols for a set of brain landmarks, and (2) to complete an intra-and inter-observer validation study of the set of landmarks. Detailed protocols were developed for 29 cortical and subcortical landmarks using a sample of 10 boys aged 12 years old. Average intra-observer error for the final set of landmarks was 1.9 mm with a range of 0.72 mm-5.6 mm. Average inter-observer error was 1.1 mm with a range of 0.40 mm-3.4 mm. This study successfully establishes landmark protocols with a minimal level of error that can be used by other researchers in the assessment of neuroanatomic phenotypes.