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Cardiac photon counting CT and its application in studying interactions between Alzheimer's and heart disease

Cardiac photon counting CT and its application in studying interactions between Alzheimer's and heart disease
心脏光子计数CT及其在研究阿尔茨海默病与心脏病相互作用中的应用
批准号:
10094804
负责人:
CRISTIAN T BADEA
金额:
$187.31万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-02-15 至 2024-01-31
关键词:
3-DimensionalAddressAdoptionAffectAgingAlgorithmsAllelesAlzheimer&aposs DiseaseAlzheimer&aposs disease modelAlzheimer&aposs disease riskAnimal ExperimentsAnimal ModelApolipoprotein EArterial Fatty StreakAtherosclerosisBase of the BrainBehaviorBehavior assessmentBiological MarkersBrainCardiacCardiovascular DiseasesCardiovascular systemCause of DeathCharacteristicsClinicalCognitiveDataDevelopmentDietDimensionsDisease MarkerDoseEnvironmental ImpactEpidemiologyExerciseExposure toFatty acid glycerol estersFoundationsGenerationsGenesGeneticGenetic ModelsGenetic RiskGenotypeHeart DiseasesHumanImageImaging DeviceImmune responseImpaired cognitionInterventionLinkMagnetic ResonanceMagnetic Resonance ImagingMalignant NeoplasmsMeasurementMeasuresMethodologyMethodsModelingMonitorMorphologic artifactsMouse StrainsMusMyocardial perfusionNOS2A geneNamesNitric Oxide SynthaseNoiseOutcomeOxidation-ReductionPathologicPerformancePhenotypePhotonsPhysiologic MonitoringPre-Clinical ModelProcessProtein IsoformsProtocols documentationResearchResolutionRiskRisk FactorsRoleScanningSystemTechnologyTestingTimeX-Ray Computed Tomographybasebehavioral studycardiac plaquecardiovascular risk factorcombatcomputerized data processingdata acquisitiondeep learningdetectorenvironmental stressorexercise interventionexercise regimenheart functionheart imaginghuman subjectimaging modalityimprovedin vivoinsightlearning strategymagnetic resonance imaging biomarkermouse modelnon-invasive imagingnovelphoton-counting detectorpre-clinicalpreclinical imagingpreclinical studypredictive modelingprototypereconstructionresilienceresponsesedentary lifestylesimulationspectral distortionsugartool

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PROJECT SUMMARY/ABSTRACT Aging is accompanied by increasing vulnerability to cardiovascular disease (CVD) and Alzheimer’s disease (AD). The ongoing rise in both AD and CVD has been ascribed to the increasing adoption of a Western sedentary lifestyle accompanied by a diet rich in fats and sugars. To understand the links between AD and CVD in human subjects, non-invasive imaging methods such X-ray computed tomography (CT) and magnetic resonance (MR) are essential. Cardiac CT is one of the most powerful applications of these methodologies at both clinical and preclinical levels, but it is currently limited by its low contrast resolution. Our primary objective in this proposal is to improve the current status of cardiac CT based on photon counting detector technology and demonstrate its capabilities in preclinical studies focused on studying the interaction between CVD and AD. Our central hypothesis is that cardiac photon counting CT will provide low dose spectral characterization of atherosclerotic plaques together with cardiac function, while enabling longitudinal monitoring of interventions such as exercise. We will pursue three specific aims. In specific aim 1, we will develop the theoretical foundation and GPU optimized tools for reconstruction of cardiac 5D (3D + Time + Energy) photon counting CT data. We will incorporate deep learning solutions to overcome fundamental barriers to the advancement of this technology: regularization to deal with image noise associated with photon binning, robust material decomposition to combat spectral distortion, and automated cardiac function and plaque analysis to handle data dimensionality. During the second specific aim, we will characterize the performance of our novel cardiac photon counting CT imaging using simulations, phantoms and animal experiments to show its benefits for atherosclerotic plaque characterization and cardiac function estimation. Finally, in specific aim 3 we will investigate if cardiovascular risk impacts brain phenotypes in animal models of genetic risk for AD. CVD and AD share a genetic link via the ApoE gene and its isomorphic allele 4 (APOE4). We will use APOE3/HN and APOE4/HN mouse strains that express the corresponding specific targeted-replacement human APOE allele, on a humanized Nitric Oxide Synthase 2 (denoted here as HN) background. Using these models, we will first assess the impact of a high fat, high sugar diet on cardiovascular phenotypes (atherosclerotic plaque size, numbers; cardiac function measured with CT) and how these genetic differences are reflected in behavior and brain MR based biomarkers compared with control mice in the same background. Finally, we will also investigate the potential to rescue these phenotypes using exercise as the intervention. The impact of the proposed research will validate the usage of photon counting CT technology to enhance routine cardiac CT imaging applications. Our project will enable new powerful integrative approaches to examine the impact of environmental stressors to alter APOE genotype- specific vulnerability, or resilience to CVD and AD.
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A multi-channel reconstruction toolkit for computed tomography
  • 批准号:
    10605585
  • 项目类别:
  • 资助金额:
    $22.63万
  • 财政年份:
    2021
  • 负责人:
    CRISTIAN T BADEA
  • 依托单位:
The Duke Preclinical Research Resources for Quantitative Imaging Biomarkers
  • 批准号:
    9387149
  • 项目类别:
  • 资助金额:
    $59.27万
  • 财政年份:
    2017
  • 负责人:
    CRISTIAN T BADEA
  • 依托单位:
The Duke Preclinical Research Resources for Quantitative Imaging Biomarkers
  • 批准号:
    10216193
  • 项目类别:
  • 资助金额:
    $57.74万
  • 财政年份:
    2017
  • 负责人:
    CRISTIAN T BADEA
  • 依托单位:
The Duke Preclinical Research Resources for Quantitative Imaging Biomarkers
  • 批准号:
    9980797
  • 项目类别:
  • 资助金额:
    $44.84万
  • 财政年份:
    2017
  • 负责人:
    CRISTIAN T BADEA
  • 依托单位:
海外基金