The Cerebral Blood Flow Biomedical Informatics Research Network (CBFBIRN) database and analysis pipeline for arterial spin labeling MRI data.
The Cerebral Blood Flow Biomedical Informatics Research Network (CBFBIRN) database and analysis pipeline for arterial spin labeling MRI data.
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DOI：
10.3389/fninf.2013.00021
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发表时间：
2013
影响因子：
3.5
通讯作者：
Liu TT
中科院分区：
文献类型：
--
作者：
Shin DD;Ozyurt IB;Liu TT
动脉自旋标记（ASL）是一种磁共振成像技术，提供了一个非侵入性和定量测量脑血流量（CBF）。经过十多年的积极研究，ASL现在正在成为一种强大而可靠的CBF测量技术，具有更高的可用性和易用性。越来越多的研究和临床机构将ASL用于神经科学研究和临床护理。在本文中，我们提出了一个在线CBF数据库和分析管道，统称为脑血流生物医学信息学研究网络（CBFBIRN），允许研究人员上传和共享ASL和临床数据。除了作为中央数据存储库之外，CBFBIRN还为CBF定量和组分析提供了简化的数据处理基础设施，这有可能加速新的科学和临床知识的发现。CBFBIRN内置的所有功能和特性都可以通过安全登录使用Web浏览器在线访问。在这项工作中，我们开始的CBFBIRN系统的数据模型和它的体系结构的一般描述，然后致力于CBFBIRN功能的论文的其余部分。后半部分的工作分为两个处理模块：（1）数据上传和CBF量化模块;（2）组分析模块，支持神经科学研究中常用的三种分析类型。迄今为止，CBFBIRN托管了来自1,300多名个体受试者的CBF地图和相关临床数据。这些数据来自20多项不同的研究，调查了各种条件对CBF的影响，包括阿尔茨海默氏症，精神分裂症，双相情感障碍，抑郁症，创伤性脑损伤，HIV，咖啡因使用和甲基苯丙胺滥用。几个例子的结果，产生的CBFBIRN处理模块，提出。最后，我们总结了CBFBIRN实施和部署过程中的经验教训以及我们在促进数据共享方面的经验。
Arterial spin labeling (ASL) is a magnetic resonance imaging technique that provides a non-invasive and quantitative measure of cerebral blood flow (CBF). After more than a decade of active research, ASL is now emerging as a robust and reliable CBF measurement technique with increased availability and ease of use. There is a growing number of research and clinical sites using ASL for neuroscience research and clinical care. In this paper, we present an online CBF Database and Analysis Pipeline, collectively called the Cerebral Blood Flow Biomedical Informatics Research Network (CBFBIRN) that allows researchers to upload and share ASL and clinical data. In addition to serving the role as a central data repository, the CBFBIRN provides a streamlined data processing infrastructure for CBF quantification and group analysis, which has the potential to accelerate the discovery of new scientific and clinical knowledge. All capabilities and features built into the CBFBIRN are accessed online using a web browser through a secure login. In this work, we begin with a general description of the CBFBIRN system data model and its architecture, then devote the remainder of the paper to the CBFBIRN capabilities. The latter part of our work is divided into two processing modules: (1) Data Upload and CBF Quantification Module; (2) Group Analysis Module that supports three types of analysis commonly used in neuroscience research. To date, the CBFBIRN hosts CBF maps and associated clinical data from more than 1,300 individual subjects. The data have been contributed by more than 20 different research studies, investigating the effect of various conditions on CBF including Alzheimer’s, schizophrenia, bipolar disorder, depression, traumatic brain injury, HIV, caffeine usage, and methamphetamine abuse. Several example results, generated by the CBFBIRN processing modules, are presented. We conclude with the lessons learned during implementation and deployment of the CBFBIRN and our experience in promoting data sharing.
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DOI：
10.1016/j.jaac.2013.07.008
发表时间：
2013-10
影响因子：
13.3
作者：
Ho TC;Wu J;Shin DD;Liu TT;Tapert SF;Yang G;Connolly CG;Frank GK;Max JE;Wolkowitz O;Eisendrath S;Hoeft F;Banerjee D;Hood K;Hendren RL;Paulus MP;Simmons AN;Yang TT
通讯作者：
Yang TT
影响因子：
3.5
作者：
Poline JB;Breeze JL;Ghosh S;Gorgolewski K;Halchenko YO;Hanke M;Haselgrove C;Helmer KG;Keator DB;Marcus DS;Poldrack RA;Schwartz Y;Ashburner J;Kennedy DN
通讯作者：
Kennedy DN
影响因子：
3.3
作者：
DETRE, JA;LEIGH, JS;KORETSKY, AP
通讯作者：
KORETSKY, AP
DOI：
10.1097/00004647-199611000-00019
发表时间：
1996-11-01
影响因子：
6.3
作者：
Alsop, DC;Detre, JA
通讯作者：
Detre, JA
影响因子：
6.6
作者：
Ford, Judith M.;Roach, Brian J.;Mathalon, Daniel H.
通讯作者：
Mathalon, Daniel H.