FMRI Dynamic Phantom for Improved Detection of Resting-State Brain Networks

FMRI 动态体模可改善静息态大脑网络的检测

• 批准号: 9255129
• 负责人: ALAN KRIEGSTEIN
• 金额: $ 22.5万
• 依托单位: ALA SCIENTIFIC INSTRUMENTS, INC.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9255129
• 关键词: Address; Adolescent; Age; Algorithms; Area; Autistic Disorder; BRAIN initiative; Base of the Brain; Big Data; Biological Markers; Brain; Brain Injuries; Brain region; Calibration; Clinical; Cognitive; Complex; Computer software; Data; Data Quality; Data Set; Detection; Development; Devices; Diagnostic; Doctor of Philosophy; Documentation; Engineering; Ensure; Feedback; Friction; Functional Imaging; Functional Magnetic Resonance Imaging; General Hospitals; Generations; Human; International; International Unit; Investments; Lead; Learning; Legal patent; Magnetic Resonance Imaging; Maps; Massachusetts; Measurement; Measures; Mental Depression; Methods; Modeling; Modernization; Morphologic artifacts; National Institute of Drug Abuse; Neurologic; Neurosciences Research; Noise; Nonlinear Dynamics; Patients; Phase; Physiologic pulse; Production; Protocols documentation; Proxy; PubMed; Publishing; Quality Control; Reproducibility; Research; Rest; Series; Signal Transduction; Site; Technology; Testing; Thinking; Time; TimeLine; United States National Institutes of Health; Universities; Validation; addiction; analytical method; analytical tool; base; biobank; clinical application; clinically relevant; cognitive development; commercialization; connectome; cost effectiveness; data integration; design; experimental study; field study; human data; imaging study; improved; instrument; interest; medical schools; neuroimaging; neuropsychopharmacology; prototype; quality assurance; research study; tool

Abstract Functional magnetic resonance imaging (fMRI) has rapidly become the dominant tool in human neuroscience research, and is poised to become a transformative technology in the areas of psychiatric and neurological diagnostics. In recent years, large-scale ($150M-$1.2B USD) and long-term (10-12 year) international investments (e.g., NIDA Adolescent Brain Cognitive Development Study, NIH Human Connectome Project, White House BRAIN Initiative, UK Biobank, EU Human Brain Project) have expanded the reach of human fMRI to include faster pulse sequences and more complex analytic tools, higher (≥7T) field strength, integration with multi-scale experiments and modeling, and an emphasis on integration of data across multiple scanner/study sites. This generation of fMRI studies goes beyond the original simplistic models that focused upon “activation maps,” to investigate connections, networks, and dynamic nonlinear circuits in the brain. New ways of thinking are being applied to some of our highest-impact areas of societal interest, ranging from addiction, depression, autism, and brain injury, to age-based cognitive degeneration. However, while fMRI research dramatically accelerates, quality assurance protocols for the MRI machines needed to generate these findings have lagged far behind. Thus, today's neuroimaging centers typically use outdated static phantom protocols that are now incapable of targeting quality control issues relevant to current and emerging applications. The Stony Brook Dynamic Phantom is designed to address this urgent need. Building upon a 1st generation working prototype of the phantom (patent pending), as well as engineering improvements in the 2nd generation prototype designed to increase its durability and reliability, here we focus on the next logical steps to commercialization. Phase I focuses on quality control and establishing added value to the market, by showing that our phantom's measure of dynamic fidelity provides a uniquely informative measure of data quality with direct and concrete implications for the interpretation of human data. Incorporating feedback provided by our Senior Advisory Board, Phase II then proceeds towards commercialization in three steps. First, ALA Scientific Instruments will adapt the engineering for mass production. Second, the academic teams at Stony Brook University and Massachusetts General Hospital/Harvard Medical School will develop algorithms that use characterization of scanner noise to clean data of associated artifact, for both single-subject (clinical) applications as well as normalization across scanners for multi-site research. Finally, hardware and software will be then integrated into one product, which will be field-tested by 15 international leaders in the neuroimaging field. Feedback from this group, identifying potential friction points in terms of the initial learning curve and/or day-to-day usage of the phantom, will be implemented in the final design, to ensure that our final manufacturing for the hardware, software, and documentation make the phantom as pleasant to operate and practically useful as possible. At this point, our device will be ready for commercial distribution.

摘要 功能磁共振成像（fMRI）已迅速成为人类神经科学的主导工具 研究，并有望成为精神病学和神经病学领域的变革性技术 诊断近年来，大规模（1.5亿美元至12亿美元）和长期（10-12年）国际 投资（例如，NIDA青少年大脑认知发展研究，NIH人类连接组项目， 白宫大脑计划、英国生物银行、欧盟人脑计划）已经扩大了人类功能磁共振成像的范围 包括更快的脉冲序列和更复杂的分析工具，更高（≥ 7 T）的场强，与 多尺度实验和建模，并强调跨多个扫描仪/研究的数据集成 网站.这一代功能磁共振成像研究超越了最初的简单模型，集中在“激活” 地图，”研究连接，网络和动态非线性电路在大脑中。新的思维方式 正被应用于一些对社会影响最大的领域，从成瘾，抑郁， 自闭症和脑损伤，以及基于年龄的认知退化。然而，虽然功能磁共振成像研究显着 加速，质量保证协议的MRI机器需要产生这些结果已经落后 远远落后。因此，今天的神经成像中心通常使用过时的静态体模协议， 无法针对与当前和新兴应用相关的质量控制问题。斯托尼布鲁克 Dynamic Phantom旨在满足这一迫切需求。基于第一代工作原型 幻影（专利申请中），以及第二代原型的工程改进 旨在提高其耐用性和可靠性，在这里，我们专注于商业化的下一个逻辑步骤。 第一阶段的重点是质量控制和建立附加值的市场，通过显示我们的幻影的 动态保真度的测量提供了一个独特的数据质量的信息测量， 对人类数据解释的影响。验证高级顾问提供的反馈 董事会，第二阶段，然后进行商业化的三个步骤。首先，ALA科学仪器将 使工程适应大规模生产。其次，斯托尼布鲁克大学的学术团队和 马萨诸塞州总医院/哈佛医学院将开发算法， 扫描仪噪声，以清除相关伪影的数据，用于单个受试者（临床）应用以及 跨扫描仪的标准化，用于多站点研究。最后，硬件和软件将被整合 这将由15位神经影像领域的国际领导者进行现场测试。反馈 从这一组中，确定初始学习曲线和/或日常使用方面的潜在摩擦点 将在最终设计中实施，以确保我们最终的硬件制造， 软件和文档使体模操作起来尽可能舒适和实用。在 至此，我们的设备就可以进行商业销售了。