Development of a Frontier Magnetic Resonance (MR) Imaging Technology As a Tool for Visualization and Quantified Vascular-Feature Measurement for Use in Brain and Behavioral Research on Small Animals
开发前沿磁共振 (MR) 成像技术作为可视化和量化血管特征测量的工具,用于小动物的大脑和行为研究
基本信息
- 批准号:10384839
- 负责人:
- 金额:$ 43.66万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-01-11 至 2024-01-10
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAccelerationAddressAgeAnimal ExperimentationAnimal ModelAnimalsAnxietyBehavioral ResearchBenzodiazepinesBiological MarkersBlood - brain barrier anatomyBlood VesselsBrainBrain DiseasesCalibrationCerebrumCitalopramClinicalCollaborationsCommunitiesComplementComputer softwareConeDataData SetDevelopmentDiazepamDiseaseDrug FormulationsEngineeringEnsureExhibitsExtravasationFunctional Magnetic Resonance ImagingGoalsHourImageImaging DeviceImaging TechniquesImaging technologyIndividualIndustryIndustry StandardInterventionIntravenousInvestigationIsofluraneJournalsMagnetic ResonanceMagnetic Resonance ImagingMajor Depressive DisorderMapsMeasurementMedicineMental disordersMethodsModalityNeurosciencesNeurotransmittersNoiseObsessive-Compulsive DisorderPanic DisorderPeer ReviewPharmaceutical PreparationsPhasePhysicsPhysiologic pulsePhysiologicalPhysiologyProductionProtocols documentationPsyche structurePublishingRadialReproducibilityResearchResearch PersonnelResolutionSamplingScanningScientistSelective Serotonin Reuptake InhibitorServicesSignal TransductionSlideSocial PhobiaSprague-Dawley RatsStandardizationStructureTechniquesTechnologyTestingTimeTranslatingTranslational ResearchTranslationsTreatment EfficacyUnited StatesVisualizationVisualization softwareanalytical toolanimal carebiomarker panelbrain behaviorbrain researchcancer therapycontrast enhancedcontrast imagingcostdrug developmentdrug discoveryexperimental studyferumoxytolflexibilityfrontiergamma-Aminobutyric Acidimage reconstructionimaging biomarkerimaging modalityimprovedin vivoinsightmagnetic fieldmouse developmentneurovascularnovelpre-clinicalpre-clinical researchprimary endpointprototypereconstructionresearch studyresponse biomarkertemporal measurementtool
项目摘要
PROJECT SUMMARY
The burden of mental illness continues to be a growing challenge in the United States. At the same time, the
scientific community continues to study the brain and behavior, revealing relationships between brain structure
and function and physiology and illness. The outer scope of brain and behavior research is governed by the
imaging and analytical tools available to scientists. Magnetic resonance imaging (MRI) has greatly improved the
study of the brain. However, even advanced forms of the technology have significant limitations. Specifically, all
MRI techniques rely on a qualitative signal for semi-quantitative measurements. Moreover, standard MRI
acquisition exhibit as much as 70% signal amplitude bias change with the orientation of the cerebral cortical (and
hence the large pial vessels) relative to magnetic field. Quantitative Ultra-short Time-to-Echo Contrast-Enhanced
(QUTE-CE, pronounced “cute-see”) MRI is a novel imaging modality that generates a quantitative signal directly
representative of physiological information that can broaden the outer limit of what current technology makes
possible. QUTE-CE advantages, thus far, include production of the highest quantitative measurement of CA
concentration in mice; development of unprecedent non-invasive in vivo maps of brain vascular structure (CBV);
mapping of neurofunctional response; biomarkers for cancer treatment efficacy; and, measurement of blood-
brain barrier (BBB) leakage. This project strives to create a robust software suite to overcome current limitations
unlocking the potential of phMRI and fMRI measurement with higher sampling time, increasing signal-to-noise
by 1.67 compared to radial sampling and enabling sliding-window reconstruction for simultaneous high-spatial
and temporal image reconstruction using the same data set. To achieve this, the project aims to develop and
optimize a software prototype for use with industry-standard 7T small animal research scanners, implementing
Imaginostics’ proprietary 3D UTE Radial Cones Pulse Sequence. Next, the project strives to test software
prototypes and analytically characterize biomarkers. The goal of the project is to ultimately improve and
standardize measurements to complement or replace existing options for a more precise approach that is
uniquely quantitative at both the individual and group levels. This means potentially fewer animals would be
needed to arrive at meaningful results. Moreover, structural, functional and BBB leakage metrics can be captured
within one imaging session, greatly enriching the study of healthy and disordered brains. Overall, these efforts
can help advance pre-clinical and related brain research efforts on small animals, by incorporating a novel MRI
imaging technology into the repertoire of researchers.
项目摘要
在美国,精神疾病的负担仍然是一个日益严峻的挑战。同时对
科学界继续研究大脑和行为,揭示大脑结构之间的关系,
功能、生理和疾病。大脑和行为研究的外部范围由
成像和分析工具。磁共振成像(MRI)大大改善了
大脑的研究。然而,即使是先进的技术形式也有很大的局限性。具体而言,所有
MRI技术依赖于半定量测量的定性信号。此外,标准MRI
采集表现出多达70%的信号幅度偏置随着大脑皮层的取向而变化(以及
因此是大的软膜血管)相对于磁场。定量超短回波时间对比度增强
(QUTE-CE,发音为“cute-see”)MRI是一种新的成像方式,可直接生成定量信号
生理信息的代表,可以扩大当前技术的外部限制,
可能迄今为止,QUTE-CE的优势包括生产CA的最高定量测量
开发前所未有的脑血管结构(CBV)的非侵入性体内图;
神经功能反应的映射;癌症治疗功效的生物标志物;以及血液-
脑屏障(BBB)渗漏。该项目致力于创建一个强大的软件套件,以克服当前的限制
通过更高的采样时间释放phMRI和fMRI测量的潜力,提高信噪比
与径向采样相比提高了1.67倍,
和使用相同数据集的时间图像重建。为了实现这一目标,该项目旨在开发和
优化软件原型,用于行业标准的7 T小型动物研究扫描仪,
Imaginostics专有的3D UTE径向锥体脉冲序列。接下来,该项目努力测试软件
原型和分析表征生物标志物。该项目的目标是最终改善和
标准化测量,以补充或取代现有的更精确的方法,
在个人和群体层面上都是独一无二的。这意味着可能会减少动物数量
需要达成有意义的结果。此外,可以捕获结构、功能和BBB泄漏指标
这极大地丰富了对健康和紊乱大脑的研究。总的来说,这些努力
通过整合一种新型的MRI,
成像技术进入研究人员的剧目。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Codi Amir Gharagouzloo其他文献
Codi Amir Gharagouzloo的其他文献
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{{ truncateString('Codi Amir Gharagouzloo', 18)}}的其他基金
Validation of a Novel Magnetic Resonance Imaging (MRI) Technology for both Diagnostic Screening and Quantification of Brain Vascular Physiology in Alzheimer's-Disease-Related Dementias
验证一种新型磁共振成像 (MRI) 技术,用于诊断筛查和量化阿尔茨海默病相关痴呆症的脑血管生理学
- 批准号:
10547491 - 财政年份:2022
- 资助金额:
$ 43.66万 - 项目类别:
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