Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA.
Department of Neurobiology and Behavior, University of California, Irvine, CA, USA.
Sci Rep. 2024 Apr 17;14(1):8848. doi: 10.1038/s41598-024-59440-6.
UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem. This includes previously established cortical and subcortical measurements defined, in part, based on the Desikan-Killiany-Tourville atlas. Also included are morphological measurements from two recent developments: medial temporal lobe parcellation of hippocampal and extra-hippocampal regions in addition to cerebellum parcellation and thickness based on the Schmahmann anatomical labeling. Through predictive modeling, we assess the clinical utility of these IDP measurements, individually and in combination, using commonly studied phenotypic correlates including age, fluid intelligence, numeric memory, and several other sociodemographic variables. The predictive accuracy of these IDP-based models, in terms of root-mean-squared-error or area-under-the-curve for continuous and categorical variables, respectively, provides comparative insights between software libraries as well as potential clinical interpretability. Results demonstrate varied performance between package-based IDP sets and their combination, emphasizing the need for careful consideration in their selection and utilization.
英国生物银行是一个大型的流行病学资源,用于研究各种生活方式、环境和遗传因素与健康和疾病进展之间的前瞻性相关性。除了通过调查和体检获得的个体主体信息外,一个由多种模式组成的综合神经影像学电池提供了成像衍生的表型(IDP),可以作为神经科学研究中的生物标志物。在这项研究中,我们通过先进的归一化工具生态系统,增加了现有的英国生物银行神经影像学结构 IDP 集,这些 IDP 来自于 FSL 和 FreeSurfer 等成熟的软件库,还包括通过该生态系统获得的相关测量值。这包括以前基于 Desikan-Killiany-Tourville 图谱定义的皮质和皮质下测量值。还包括两个最新进展的形态学测量值:海马和海马外区域的内侧颞叶分割以及基于 Schmahmann 解剖学标签的小脑分割和厚度。通过预测模型,我们使用包括年龄、流体智力、数字记忆和其他几个社会人口统计学变量在内的常见研究表型相关性,单独和组合评估这些 IDP 测量值的临床实用性。就连续和分类变量的均方根误差或曲线下面积而言,这些基于 IDP 的模型的预测准确性提供了软件库之间的比较见解以及潜在的临床可解释性。结果表明,基于软件包的 IDP 集及其组合之间的性能存在差异,这强调了在选择和使用时需要仔细考虑。