The Psychosis MRI Shared Data Resource (Psy-ShareD)

IF 3.3 2区 医学 Q1 NEUROIMAGING Human Brain Mapping Pub Date : 2025-02-21 DOI:10.1002/hbm.70165
Paul Allen, Mariana Zurita, Rubaida Easmin, Sara Bucci, Matthew J. Kempton, Jack Rogers, Urvakhsh M. Mehta, Philip K. McGuire, Stephen M. Lawrie, Heather Whalley, Ary Gadelha, Graham K. Murray, Jane R. Garrison, Sophia Frangou, Rachel Upthegrove, Simon L. Evans, Veena Kumari, the Psy-ShareD Partnership
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Abstract

Neuroimaging research in the field of schizophrenia and other psychotic disorders has sought to investigate neuroanatomical markers, relative to healthy control groups. In recent decades, a large number of structural magnetic resonance imaging (MRI) studies have been funded and undertaken, but their small sample sizes and heterogeneous methods have led to inconsistencies across findings. To tackle this, efforts have been made to combine datasets across studies and sites. While notable recent multicentre initiatives and the resulting meta- and mega-analytical outputs have progressed the field, efforts have generally been restricted to MRI scans in one or two illness stages, often overlook patient heterogeneity, and study populations have rarely been globally representative of the diversity of patients who experience psychosis. Furthermore, access to these datasets is often restricted to consortia members who can contribute data, likely from research institutions located in high-income countries. The Psychosis MRI Shared Data Resource (Psy-ShareD) is a new open access structural MRI data sharing partnership that will host pre-existing structural T1-weighted MRI data collected across multiple sites worldwide, including the Global South. MRI T1 data included in Psy-ShareD will be available in image and feature-level formats, having been harmonised using state-of-the-art approaches. All T1 data will be linked to demographic and illness-related (diagnosis, symptoms, medication status) measures, and in a number of datasets, IQ and cognitive data, and medication history will also be available, allowing subgroup and dimensional analyses. Psy-ShareD will be free-to-access for all researchers. Importantly, comprehensive data catalogues, scientific support and training resources will be available to facilitate use by early career researchers and build capacity in the field. We are actively seeking new collaborators to contribute further T1 data. Collaborators will benefit in terms of authorships, as all publications arising from Psy-ShareD will include data contributors as authors.

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精神病MRI共享数据资源(psyp - Shared)
精神分裂症和其他精神疾病领域的神经影像学研究试图调查相对于健康对照组的神经解剖学标记。近几十年来,大量的结构磁共振成像(MRI)研究得到了资助和开展,但它们的小样本量和不同的方法导致了研究结果的不一致。为了解决这个问题,人们努力将不同研究和地点的数据集结合起来。虽然最近值得注意的多中心倡议以及由此产生的元分析和大分析结果在该领域取得了进展,但努力通常仅限于一两个疾病阶段的MRI扫描,往往忽略了患者的异质性,并且研究人群很少能在全球范围内代表精神病患者的多样性。此外,对这些数据集的访问通常仅限于能够提供数据的联盟成员,这些成员可能来自高收入国家的研究机构。精神病MRI共享数据资源(Psy-ShareD)是一个新的开放获取结构MRI数据共享合作伙伴关系,将托管从全球多个站点收集的预先存在的结构t1加权MRI数据,包括全球南方。psyshared中包含的MRI T1数据将以图像和特征级格式提供,并使用最先进的方法进行协调。所有T1数据将与人口统计和疾病相关(诊断、症状、用药状况)措施相关联,并且在许多数据集中,IQ和认知数据以及用药史也将可用,从而允许进行亚组和维度分析。Psy-ShareD将对所有研究人员免费开放。重要的是,将提供全面的数据目录、科学支持和培训资源,以促进早期职业研究人员的使用,并在该领域建立能力。我们正在积极寻找新的合作者来提供进一步的T1数据。合作者将在作者身份方面受益,因为所有来自Psy-ShareD的出版物将包括数据贡献者作为作者。
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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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