比较皮层下体积自动估算方法;FSL 和 FreeSurfer 估算的杏仁核体积一致性较差

IF 3.5 2区 医学 Q1 NEUROIMAGING Human Brain Mapping Pub Date : 2024-11-26 DOI:10.1002/hbm.70027
Patrick Sadil, Martin A. Lindquist
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引用次数: 0

摘要

皮层下体积是生物标志物和生物特征的重要来源,自动化方法有助于在表型丰富的大型数据集中提取这些特征。然而,尽管大量研究已经证实,自动方法产生的体积与专家注释产生的体积相似,但这些方法之间的一致性却未得到充分研究。利用英国生物库的数据,我们比较了两套流行软件对皮层下体积的估计:FSL 和 FreeSurfer。虽然大多数皮层下体积在不同方法中表现出良好甚至极佳的一致性,但这两种工具对杏仁体积的估计却存在差异。通过模拟实验,我们发现这种一致性差可能会导致相互矛盾的结果,即一种工具显示出统计学意义,而另一种工具却没有,或者两种工具都显示出显著关系,但方向却相反。考虑到这些问题,我们讨论了在报告涉及杏仁体量的关系时应注意的几种方法。
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Comparing automated subcortical volume estimation methods; amygdala volumes estimated by FSL and FreeSurfer have poor consistency

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.

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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
期刊最新文献
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