Robust Precision Mapping of Cortical and Subcortical Brain Metabolic Signatures in AD
AD 中大脑皮层和皮层下代谢特征的稳健精确绘图
基本信息
- 批准号:10746348
- 负责人:
- 金额:$ 81.14万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-09-01 至 2028-05-31
- 项目状态:未结题
- 来源:
- 关键词:3-DimensionalAddressAdoptedAffectAgingAlzheimer&aposs DiseaseAlzheimer&aposs disease brainAlzheimer&aposs disease pathologyAlzheimer&aposs disease related dementiaAlzheimer&aposs disease testAmericanAmyloidAmyloid beta-ProteinAnatomyAreaAssessment toolAtlasesAttentionBioenergeticsBiologicalBrainBrain regionCaringCategoriesCerebral cortexCessation of lifeClinicalClinical ResearchClinical TrialsCognitiveCollaborationsConsensusDataData AnalysesDevelopmentDiseaseDisease ProgressionElderlyEnergy MetabolismEvaluationFrightFutureGeneticHealth Care CostsHealthcare SystemsHeart DiseasesImaging TechniquesImpaired cognitionInflammationInterventionInvestigationLinkLipidsMagnetic ResonanceMagnetic Resonance ImagingMalignant NeoplasmsMapsMeasurementMeasuresMedicineMetabolicMetabolic dysfunctionMetabolismMethodsMolecularMonitorMorphologic artifactsMorphologyMotionMovementNerve DegenerationNeurodegenerative DisordersOutcomeOxidative StressPathologicPatternPersonsPopulationPositioning AttributePositron-Emission TomographyPrevention strategyPublic HealthRecommendationRegistriesResearchResolutionResourcesScalp structureScanningSignal TransductionStrokeSurfaceSystemTechniquesTimeTissuesUnited States National Institutes of HealthWorkage relatedaging populationbrain dysfunctionbrain metabolismbrain volumecognitive functioncohortcortex mappingcostdata acquisitiondesignefficacy evaluationimaging approachimprovedinterestintervention effectmagnetic fieldmagnetic resonance spectroscopic imagingmetabolic imagingmitochondrial dysfunctionnervous system disorderneuroimagingnormal agingnovelnovel therapeutic interventionpharmacologicpopulation basedpreventprospectivespectroscopic imagingtooltreatment effecttreatment strategy
项目摘要
PROJECT SUMMARY/ABSTRACT
Treating and caring for the more than 6.5 million older adults in the U.S. living with Alzheimer’s disease (AD)
presents the largest burden from a single disease on the healthcare system, with costs exceeding $320 billion
per year for AD and related dementias (AD/ADRD). While deaths due to major diseases (e.g., stroke, heart
disease, and cancers) have declined, AD and AD-related deaths have increased substantially, with a projected
cost of about $1 trillion per year to the US economy by 2050. Although AD is currently irreversible, new
therapeutic approaches and prevention strategies are under extensive investigation. Over 50% of the
pharmacologic agents currently being tested for AD target aberrant brain metabolism. Thus, it is essential to
establish a concrete relationship between metabolic dysfunction and pathologic features of AD brains.
However, comprehensive whole-brain metabolic mapping, including cortical and subcortical brain regions that
are highly relevant to AD pathology, has not been achieved, due to substantial technical challenges in
acquiring high-quality magnetic resonance (MR) spectroscopic imaging data with sufficient spatial resolution
across the entire brain in clinically acceptable scan time. In this regard, we propose to generate a robust and
reliable metabolic mapping of the whole brain, including the cortical regions, by establishing technical
capabilities for three-dimensional echo-planar spectroscopic imaging (3D-EPSI). Building on our team’s
pioneering work in MR technical development and an existing collaboration, we are ideally positioned to make
integrative technical advances in nuisance signal reduction, improved spatial encoding, and real-time motion
and B0 correction, to create a state-of-the-art metabolic imaging approach. Accurate anatomy-based regional
data analysis tools (namely MetaSurfer) will also be developed to provide a novel surface-based approach to
processing whole brain metabolic imaging data. Thus, this project offers comprehensive whole-brain metabolic
imaging packages for a full end-to-end solution from robust data acquisition to novel data analysis. Using the
developed packages, we will create population-averaged normative whole-brain metabolic atlases in the aging
population after stratifying amyloid status (Aβ- and Aβ+), which will provide a statistical basis for assessing
metabolic alterations in AD. In our pilot clinical study of early AD, we will investigate the relationship between
brain metabolic imaging outcomes and molecular, genetic, morphological, clinical, and cognitive measures in
people with early AD, leveraging the available data from NIA AD Research Center (ADRC) resources and
ongoing AD clinical studies. This study will provide critical data for future large-scale clinical trials evaluating
new AD-treatment strategies as a part of the emerging field of metabolic and bioenergetic medicine for
AD/ADRD.
项目概要/摘要
治疗和护理美国超过 650 万患有阿尔茨海默病 (AD) 的老年人
单一疾病对医疗保健系统造成的最大负担,成本超过 3200 亿美元
每年因 AD 和相关痴呆症 (AD/ADRD) 导致的死亡人数。
疾病和癌症)有所下降,AD 和 AD 相关死亡人数大幅增加,预计
到 2050 年,美国经济每年将损失约 1 万亿美元。尽管 AD 目前不可逆转,但新的
超过 50% 的方法和预防策略正在接受广泛的治疗研究。
目前正在测试针对 AD 异常脑代谢的药物。
建立代谢功能障碍与 AD 大脑病理特征之间的具体关系。
然而,全面的全脑代谢图谱,包括皮质和皮质下大脑区域,
与 AD 病理学高度相关,但由于存在巨大的技术挑战而尚未实现
获取具有足够空间分辨率的高质量磁共振 (MR) 波谱成像数据
在临床可接受的扫描时间内扫描整个大脑。在这方面,我们建议生成一个强大且可靠的扫描。
通过建立技术,对整个大脑(包括皮质区域)进行可靠的代谢绘图
基于我们团队的三维回波平面光谱成像 (3D-EPSI) 功能。
在 MR 技术开发和现有合作方面的开创性工作,我们处于理想的位置,可以使
减少干扰信号、改进空间编码和实时运动方面的综合技术进步
和 B0 校正,创建最先进的基于解剖学的区域成像方法。
还将开发数据分析工具(即 MetaSurfer),以提供一种新颖的基于表面的方法
处理全脑代谢成像数据因此,该项目提供全面的全脑代谢成像数据。
成像包提供从强大的数据采集到新颖的数据分析的完整端到端解决方案。
开发的软件包,我们将创建人口平均的老龄化全脑代谢图谱
对淀粉样蛋白状态(Aβ-和Aβ+)进行分层后的人群,这将为评估提供统计基础
在我们对早期 AD 的初步临床研究中,我们将研究 AD 代谢改变之间的关系。
脑代谢成像结果以及分子、遗传、形态、临床和认知测量
患有早期 AD 的人,利用 NIA AD 研究中心 (ADRC) 资源中的可用数据,
正在进行的 AD 临床研究将为未来大规模临床试验评估提供关键数据。
新的 AD 治疗策略作为代谢和生物能量医学新兴领域的一部分
AD/ADRD。
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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Phil Lee其他文献
Phil Lee的其他文献
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{{ truncateString('Phil Lee', 18)}}的其他基金
Antioxidant Imaging Marker of Investigating Gains in Neurocognition in an Intervention Trial of Exercise (AIM-IGNITE)
研究运动干预试验中神经认知增益的抗氧化成像标记 (AIM-IGNITE)
- 批准号:
10321247 - 财政年份:2019
- 资助金额:
$ 81.14万 - 项目类别:
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