Sadil Patrick, Lindquist Martin A
Johns Hopkins Bloomberg School of Public Health.
bioRxiv. 2024 Jul 1:2024.03.07.583900. doi: 10.1101/2024.03.07.583900.
Subcortical volumes are a promising source of biomarkers and features in biosignatures, and automated methods facilitate extracting them in large, phenotypically rich datasets. However, while extensive research has verified that the automated methods produce volumes that are similar to those generated by expert annotation, the consistency of methods with each other is understudied. Using data from the UK Biobank, we compare the estimates of subcortical volumes produced by two popular software suites: FSL and FreeSurfer. Although most subcortical volumes exhibit good to excellent consistency across the methods, the tools produce diverging estimates of amygdalar volume. Through simulation, we show that this poor consistency can lead to conflicting results, where one but not the other tool suggests statistical significance, or where both tools suggest a significant relationship but in opposite directions. Considering these issues, we discuss several ways in which care should be taken when reporting on relationships involving amygdalar volume.
皮质下体积是生物标志物和生物特征中很有前景的来源，自动化方法有助于在大规模、表型丰富的数据集中提取它们。然而，尽管广泛的研究已经证实自动化方法生成的体积与专家注释生成的体积相似，但方法之间的一致性却未得到充分研究。利用英国生物银行的数据，我们比较了两个流行软件套件FSL和FreeSurfer生成的皮质下体积估计值。尽管大多数皮质下体积在不同方法之间表现出良好到极好的一致性，但这些工具对杏仁核体积的估计却存在差异。通过模拟，我们表明这种较差的一致性可能导致相互矛盾的结果，即一个工具表明有统计学意义而另一个工具则不然，或者两个工具都表明存在显著关系但方向相反。考虑到这些问题，我们讨论了在报告涉及杏仁核体积的关系时应注意的几种方法。
