ABCD 扩散分数各向异性和皮质厚度的部位可靠性分析:扫描仪平台的影响

IF 3.5 2区 医学 Q1 NEUROIMAGING Human Brain Mapping Pub Date : 2024-11-11 DOI:10.1002/hbm.70070
Yezhi Pan, L. Elliot Hong, Ashley Acheson, Paul M. Thompson, Neda Jahanshad, Alyssa H. Zhu, Jiaao Yu, Chixiang Chen, Tianzhou Ma, Ho-Ling Liu, Jelle Veraart, Els Fieremans, Nicole R. Karcher, Peter Kochunov, Shuo Chen
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引用次数: 0

摘要

青少年大脑和认知发展(ABCD)项目是规模最大的青少年大脑发展研究。该项目采用标准化的多站点磁共振成像数据收集和分析协议,对 21 个站点的 11,868 名 9-10 岁参与者进行纵向追踪。虽然多研究地点和多扫描仪的研究设计提高了分析结果的稳健性和可推广性,但也可能带来非生物变异,包括扫描仪相关变异、受试者运动和偏离方案等。在大脑皮层厚度和脑白质完整性不断成熟的时期,ABCD 成像数据每两年收集一次。这些变化会使经典的测试-重复测试方法(如类内相关系数(ICC))产生偏差。我们开发了一种部位自适应 ICC (AICC),用于评估成像衍生表型的可靠性,同时考虑到正在进行的大脑发育。AICC 使用加权混合模型迭代估计群体水平上与年龄相关的大脑发育轨迹,并更新经年龄校正的按部位可信度,直至收敛。我们评估了各部位弥散张量成像的区域分数各向异性(FA)测量值和结构磁共振成像数据的皮层厚度(CT)的测试-重复可靠性。各研究点 20 个 FA 道的平均 AICC 为 0.61 ± 0.19,低于各研究点 34 个区域 CT 的平均 AICC(0.76 ± 0.12)。值得注意的是,与使用通用电气/飞利浦扫描仪的站点相比,使用西门子扫描仪的站点在 FA 方面的 AICC 值都明显更高(AICC = 0.71 ± 0.12 vs. 0.46 ± 0.17,p<0.05)。
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A Site-Wise Reliability Analysis of the ABCD Diffusion Fractional Anisotropy and Cortical Thickness: Impact of Scanner Platforms

The Adolescent Brain and Cognitive Development (ABCD) project is the largest study of adolescent brain development. ABCD longitudinally tracks 11,868 participants aged 9–10 years from 21 sites using standardized protocols for multi-site MRI data collection and analysis. While the multi-site and multi-scanner study design enhances the robustness and generalizability of analysis results, it may also introduce nonbiological variances including scanner-related variations, subject motion, and deviations from protocols. ABCD imaging data were collected biennially within a period of ongoing maturation in cortical thickness and integrity of cerebral white matter. These changes can bias the classical test–retest methodologies, such as intraclass correlation coefficients (ICC). We developed a site-wise adaptive ICC (AICC) to evaluate the reliability of imaging-derived phenotypes while accounting for ongoing brain development. AICC iteratively estimates the population-level age-related brain development trajectory using a weighted mixed model and updates age-corrected site-wise reliability until convergence. We evaluated the test–retest reliability of regional fractional anisotropy (FA) measures from diffusion tensor imaging and cortical thickness (CT) from structural MRI data for each site. The mean AICC for 20 FA tracts across sites was 0.61 ± 0.19, lower than the mean AICC for CT in 34 regions across sites, 0.76 ± 0.12. Remarkably, sites using Siemens scanners consistently showed significantly higher AICC values compared with those using GE/Philips scanners for both FA (AICC = 0.71 ± 0.12 vs. 0.46 ± 0.17, p < 0.001) and CT (AICC = 0.80 ± 0.10 vs. 0.69 ± 0.11, p < 0.001). These findings demonstrate site-and-scanner related variations in data quality and underscore the necessity for meticulous data curation in subsequent association analyses.

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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.
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