Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA.
Saint Louis University, School of Medicine, St Louis, MO, USA.
J Alzheimers Dis. 2023;96(4):1441-1451. doi: 10.3233/JAD-230738.
Given the advent of large-scale neuroimaging data-driven endeavors for Alzheimer's disease, there is a burgeoning need for well-characterized neuroimaging databases of healthy individuals. With the rise of initiatives around the globe for the rapid and unrestricted sharing of data resources, there is now an abundance of open-source neuroimaging datasets available to the research community. However, there is not yet a systematic review that fully details the demographic information and modalities actually available in all open access neuroimaging databases around the globe.
This systematic review aims to provide compile a list of MR structural imaging databases encompassing healthy individuals across the lifespan.
In this systematic review, we searched EMBASE and PubMed until May 2022 for open-access neuroimaging databases containing healthy control participants of any age, race, with normal development and cognition having at least one structural T1-weighted neuroimaging scan.
A total of 403 databases were included, for up to total of 48,268 participants with all available demographic information and imaging modalities detailed in Supplementary Table 1. There were significant trends noted when compiling normative databases for this systematic review, notably that 11.7% of databases included reported ethnicity in their participants, with underrepresentation of many socioeconomic groups globally.
As efforts to improve primary prevention of AD may require a broader perspective including increased relevance of earlier stages in life, and strategies in addressing modifiable risk factors may be individualized to specific demographics, improving data characterization to be richer and more rigorous will greatly enhance these efforts.
随着大规模神经影像学数据驱动的阿尔茨海默病研究的出现,人们对健康个体的神经影像学数据库的需求也日益增长。随着全球范围内快速和不受限制的数据资源共享倡议的兴起,现在有大量开源神经影像学数据集可供研究社区使用。然而,还没有一个系统的综述详细描述全球所有开放获取神经影像学数据库中的实际人口统计学信息和模态。
本系统综述旨在编制一份涵盖健康个体整个生命周期的磁共振结构成像数据库列表。
在本系统综述中,我们搜索了 EMBASE 和 PubMed,截至 2022 年 5 月,以获取包含任何年龄、种族、正常发育和认知的健康对照参与者的开放获取神经影像学数据库,这些参与者至少有一次结构 T1 加权神经影像学扫描。
共纳入了 403 个数据库,共计 48268 名参与者,所有可用的人口统计学信息和成像方式都在补充表 1 中详细列出。在为本次系统综述编制规范数据库时,我们注意到了一些显著的趋势,即 11.7%的数据库报告了参与者的种族,全球许多社会经济群体的代表性不足。
由于改善 AD 的一级预防的努力可能需要更广泛的视角,包括增加生命早期的相关性,并且针对可改变的风险因素的策略可能会针对特定的人口统计学特征进行个体化,因此改善数据特征使其更加丰富和严格将极大地促进这些努力。