Breaking Spatiotemporal Barriers of MR Imaging Technologies to Study Human Brain Function and Neuroenergetics
Breaking Spatiotemporal Barriers of MR Imaging Technologies to Study Human Brain Function and Neuroenergetics
批准号:
9789873
负责人:
Wei Chen
金额:
$124.81万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-22 至 2023-06-30
关键词:
AddressBRAIN initiativeBlood flowBrainCeramicsCerebrumCommunitiesComputer SimulationCustomDatabasesDetectionDevelopmentEnergy MetabolismEngineeringFormulationFrequenciesFunctional Magnetic Resonance ImagingFundingGeometryGoalsGrantHeadHumanHuman bodyIllinoisImageImaging TechniquesImaging technologyInstitutionKnowledgeMagnetic ResonanceMagnetic Resonance ImagingMapsMetabolismMethodsMinnesotaModalityMolecularMonoclonal Antibody R24NeuronsNeurosciencesNeurotransmittersNoiseNuclearOxygenParentsPerformancePhasePilot ProjectsProcessProductionRegulationResearchResearch PersonnelResolutionRestSafetySignal TransductionStructureTechniquesTechnologyTemperatureTestingThalamic NucleiUnited States National Institutes of HealthUniversitiesWorkabsorptionbasebrain researchbrain tissueclinical Diagnosiscostcost effectivedielectric propertyfunctional improvementgray matterimaging approachimaging studyimprovedin vivoinnovationinterestmagnetic fieldmagnetic resonance spectroscopic imagingmetabolic ratemultimodalityneural circuitneuroimagingneurotechnologynext generationnoveloperationpersonalized medicineradio frequencyrelating to nervous systemresponseskillsspatiotemporalspectroscopic imagingsuccesstechnology development
中文摘要
项目总结:
了解神经网络电路如何工作,以及如何在介观(亚毫米)尺度上相互连接。
神经能量代谢系统和神经递质在休息和工作状态下支持大脑功能。
对脑科学研究和脑科学倡议至关重要。磁共振成像技术(MR)和成像技术(MRI),包括功能成像技术
磁共振成像(FMRI)和磁共振波谱成像(MRSI)是在活体内进行的,它是使人们能够从神经成像到神经成像的唯一的医学模式。
活动、功能和连接能力以及大脑结构在大脑皮层和柱状层水平,包括神经能量学和神经功能学。
神经递质存在于人类大脑中。然而,解决这一基础神经科学问题仍然是一项具有挑战性的任务。
目前还不存在需要更高灵敏度和更高时空分辨率的问题。
油田的实力一直是应对这一挑战的主流模式,然而,除了高昂的成本外,它还构成了一种挑战。
安全和令人担忧的是,大脑和组织中射频(RF)和功率的比吸收率(SAR)值升高。
为了更好地解决基于磁共振的医学成像技术所面临的主要技术挑战和局限性,我们将拥有。
通过推出世界上最先进的超高绝缘体介电常数,率先推出了一种全新的创新技术和高性价比的电气工程解决方案。
(UHDC)以前的公司与射频线圈公司合作,在灵敏度和时空分辨率方面有了很大的改善。
FMRI技术与MRSI、和协同降低了超高分辨率油田(UHF)的SAR,并得到了美国国立卫生研究院(NIH)和R24的资金支持,对吧?
我们已经取得了很大的进展,取得了可喜的成果,这是为了证明这一概念。在这项U01建议中,我们将继续进一步发展。
并将以下三项先进技术集成在一起:(I)将固定电源和/或可调电源与先进电源整合在一起。
射频线圈技术,用于最大限度地提高MR成像的灵敏度,并将SAR降至最低;;(II)通过更多的开发来实现光谱成像。
空间谱相关分析(SPICE)技术可显著提高信噪比(SNR)。
时空分辨率;;(III)超高频和MR技术要求进一步提高光谱的灵敏度和分辨率。
MRSI。这些技术的最新集成将在UHF实现更多的累积测试和前所未有的测试改进。
并打破目前时空分辨率的障碍,最终实现超高分辨率的功能磁共振成像。
神经中枢的活动、神经回路的功能和动力学、功能和功能的连通性以及神经网络在中观水平上的表现在3%和3%之间。
7特斯拉(T);;和II)具有非常高的分辨率,以及用于功能成像的全脑和多核磁共振成像技术。
神经能量型神经递质和神经递质在超高场(7T和110.5T)对脑刺激的反应中发生变化。
具有更优越的分辨率(GB5 mm各向同性),其分辨率可与常规磁共振成像相媲美。随着新技术的发展。
将由一个由来自明尼苏达大学和宾夕法尼亚大学的跨学科研究人员组成的国际财团来实施。
伊利诺伊州立大学和伊利诺伊州立大学在厄巴纳-香槟分校合作。这个项目的成功将迎来下一个世纪。
基于MR的新一代智能多模智能神经成像技术全面提供卓越的时空分辨率。
为广博的大脑和研究、技术和技术带来变革性的技术,产生全面的技术和高保真的数据库技术。
人类大脑认为,这一点也可以由科学界共享。
英文摘要
PROJECT SUMMARY
Understanding how neural circuits operate and interconnect at mesoscopic (sub-millimeter) scale, and how
neuroenergetic metabolism and neurotransmitters support brain function at resting and working state is
essential to brain research and BRAIN Initiative. Magnetic resonance (MR) imaging (MRI), including functional
MRI (fMRI) and in vivo MR spectroscopic imaging (MRSI), is the sole modality enabling to imaging neural
activity, functional connectivity and brain structure at cortical layer and column level, neuroenergetics and
neurotransmitters in human brain. However, it remains challenging to address fundamental neuroscience
questions requiring much higher sensitivity and spatiotemporal resolution currently unavailable. Increasing MR
field strength has been the prevailing paradigm to tackle the challenge, however, beside high cost, it poses a
safety concern from elevated specific absorption rate (SAR) of radiofrequency (RF) power in the brain tissue.
To address the technical challenges and limitations faced by the MR-based imaging techniques, we have
pioneered an innovative and cost-effective engineering solution by introducing the ultra-high dielectric constant
(uHDC) former incorporated with RF coils for large improvements of sensitivity and spatiotemporal resolution for
fMRI and MRSI, and synergistically reducing SAR at ultrahigh field (UHF). With the NIH R24 funding support, we
have made progress with promising results for proof of concept. In this U01 proposal, we will further develop
and integrate three advanced technologies: i) fixed and/or tunable uHDC formers incorporated with advanced
RF coil technology for maximizing MR sensitivity and minimizing SAR;; ii) SPectroscopic Imaging by exploiting
spatiospectral CorrElation (SPICE) technique for significantly boosting signal-to-noise ratio (SNR) and
spatiotemporal resolution;; iii) UHF MR technology for further improving sensitivity and spectral resolution of
MRSI. The integration of these technologies will achieve cumulative and unprecedented improvements at UHF
and break current barriers of spatiotemporal resolution, ultimately enable i) ultrahigh-resolution fMRI mapping
of neural activity, circuits and dynamics, and functional connectivity and networks at mesoscopic scale at 3 and
7 tesla(T);; and ii) very high resolution and whole-brain multinuclear MRSI for functional mapping of
neuroenergetic and neurotransmitter changes in response to brain stimulation at ultrahigh fields (7T and 10.5T)
with an superior (£5mm isotropic) resolution comparable to conventional fMRI. The technology developments
will be carried out by a consortium among interdisciplinary researchers from University of Minnesota, Penn
State University and University of Illinois at Urbana-Champaign. Success of this project will usher the next
generation of MR-based multimodal neuroimaging technology offering superior spatiotemporal resolution fully
transformative for broad brain research, and generate comprehensive and high fidelity database of healthy
human brain that can be shared by scientific community.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
An ensemble deep learning model for tumor bud detection and risk stratification in colorectal carcinoma.
-
批准号:10564824
-
项目类别:
-
资助金额:$54.37万
-
财政年份:2023
-
负责人:Wei Chen
-
依托单位:
Establishing translational neuroimaging tools for quantitative assessment of energy metabolism and metabolic reprogramming in healthy and diseased human brain at 7T
-
批准号:10714863
-
项目类别:
-
资助金额:$63.02万
-
财政年份:2023
-
负责人:Wei Chen
-
依托单位:
SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate
-
批准号:10601180
-
项目类别:
-
资助金额:$30.0万
-
财政年份:2022
-
负责人:Wei Chen
-
依托单位:
SCH: New Advanced Machine Learning Framework for Mining Heterogeneous Ocular Data to Accelerate
-
批准号:10665804
-
项目类别:
-
资助金额:$30.0万
-
财政年份:2022
-
负责人:Wei Chen
-
依托单位:
Cellular Interactions in Vascular Calcification of Chronic Kidney Disease
-
批准号:10525401
-
项目类别:
-
资助金额:$12.53万
-
财政年份:2022
-
负责人:Wei Chen
-
依托单位:
Console Replacement and Upgrade of 9.4 Tesla Animal Instrument
-
批准号:10414184
-
项目类别:
-
资助金额:$132.8万
-
财政年份:2022
-
负责人:Wei Chen
-
依托单位:
Deep-learning-based prediction of AMD and its progression with GWAS and fundus image data
-
批准号:10226322
-
项目类别:
-
资助金额:$22.03万
-
财政年份:2020
-
负责人:Wei Chen
-
依托单位:
Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field
-
批准号:10043972
-
项目类别:
-
资助金额:$46.69万
-
财政年份:2020
-
负责人:Wei Chen
-
依托单位:
Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field
-
批准号:10268184
-
项目类别:
-
资助金额:$54.75万
-
财政年份:2020
-
负责人:Wei Chen
-
依托单位:
Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field
-
批准号:10463737
-
项目类别:
-
资助金额:$55.69万
-
财政年份:2020
-
负责人:Wei Chen
-
依托单位:
Deep-learning-based prediction of AMD and its progression with GWAS and fundus image data
-
批准号:10056062
-
项目类别:
-
资助金额:$18.82万
-
财政年份:2020
-
负责人:Wei Chen
-
依托单位:
Advancing simultaneous fMRI-multiphoton imaging technique to study brain function and connectivity across different scales at ultrahigh field
-
批准号:10670768
-
项目类别:
-
资助金额:$56.59万
-
财政年份:2020
-
负责人:Wei Chen
-
依托单位:
Cbfβ mediates articular cartilage regeneration and repair in aging
-
批准号:9982158
-
项目类别:
-
资助金额:$40.73万
-
财政年份:2019
-
负责人:Wei Chen
-
依托单位:
Cbf mediates articular cartilage regeneration and repair in aging
-
批准号:10615874
-
项目类别:
-
资助金额:$41.69万
-
财政年份:2019
-
负责人:Wei Chen
-
依托单位:
Cbf mediates articular cartilage regeneration and repair in aging
-
批准号:10405827
-
项目类别:
-
资助金额:$41.69万
-
财政年份:2019
-
负责人:Wei Chen
-
依托单位:
Cbf mediates articular cartilage regeneration and repair in aging
-
批准号:10430288
-
项目类别:
-
资助金额:$41.69万
-
财政年份:2019
-
负责人:Wei Chen
-
依托单位:
Breaking Spatiotemporal Barriers of MR Imaging Technologies to Study Human Brain Function and Neuroenergetics
-
批准号:10455036
-
项目类别:
-
资助金额:$131.5万
-
财政年份:2018
-
负责人:Wei Chen
-
依托单位:
Calcification Propensity, using Dynamic Light Scattering, to Study Vascular Calcification in Patients with Advanced Chronic Kidney Disease
-
批准号:10171838
-
项目类别:
-
资助金额:$19.72万
-
财政年份:2018
-
负责人:Wei Chen
-
依托单位:
Calcification Propensity, using Dynamic Light Scattering, to Study Vascular Calcification in Patients with Advanced Chronic Kidney Disease
-
批准号:10418310
-
项目类别:
-
资助金额:$16.16万
-
财政年份:2018
-
负责人:Wei Chen
-
依托单位:
Breaking Spatiotemporal Barriers of MR Imaging Technologies to Study Human Brain Function and Neuroenergetics
-
批准号:10252903
-
项目类别:
-
资助金额:$122.91万
-
财政年份:2018
-
负责人:Wei Chen
-
依托单位:
海外基金