Cerebrovascular Reserve Imaging with Simultaneous PET/MRI Using Arterial Spin Labeling and Deep Learning
使用动脉自旋标记和深度学习同时进行 PET/MRI 脑血管储备成像
基本信息
- 批准号:9789276
- 负责人:
- 金额:$ 58.63万
- 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
- 起止时间:2018-09-20 至 2022-05-31
- 项目状态:已结题
- 来源:
- 关键词:AcetazolamideAddressAgeArtificial IntelligenceBiologicalBlood flowBrainBrain imagingBypassCardiacCardiologyCarotid StenosisCause of DeathCerebrovascular CirculationCerebrovascular DisordersClinicalClinical Trials DesignComputer Vision SystemsConsensusCytolysisDataDepositionDiagnosticExcisionGadoliniumGenderGoalsGoldGuidelinesImProvImageImaging problemImpairmentIndividualInterventionIntervention TrialJapanese PopulationLabelLinkMachine LearningMagnetic Resonance ImagingMeasurementMeasuresMeta-AnalysisMethodologyMethodsModelingMotionNoiseNutrientOutcomeOxygenPatient TriagePatientsPhysiologic pulsePhysiologicalPlayPositron-Emission TomographyPremenopauseProceduresRadiationReference StandardsReproducibilityRestRiskRoleScanningSignal TransductionSolidSpin LabelsStress TestsStroke preventionTechniquesTestingTimeTrainingUnited StatesValidationWaste ProductsWaterWomanXenonbaseblood flow measurementcerebral hemodynamicscerebrovascularcerebrovascular imagingclinical applicationcohortconvolutional neural networkdeep field surveydeep learningdesigndirect applicationdisabilityevidence based guidelinesgender differenceimaging modalityimprovedlearning networkmennervous system disordernovel strategiesperformance testsprospectiveresponsestressorstroke risksystematic reviewtime usetool
项目摘要
Cerebrovascular disease remains a common cause of death and major disability
in the United States, and identifying and preventing strokes should be a high
priority. Direct measurement of regional cerebral blood flow (CBF) is challeng-
ing in these patients, since we do not have a non-invasive, radiation-free
imaging method that has been appropriately validated against gold standard
techniques. This is important, because there is compelling evidence that
measuring the CBF change before and after a stress test meant to increase CBF
(a measurement known as cerebrovascular reserve [CVR]) can identify patients
at increased stroke risk. Stress tests have been a mainstay of the diagnostic
workup of cardiology patients for many years, and we believe strongly that their
use will benefit cerebrovascular disease patients as well.
The goal of this project is to improve the quality of arterial spin label (ASL)
MRI using deep learning, a powerful form of machine learning, that is currently
undergoing tremendous progress. We will then to apply this in a prospective,
adaptive validation trial against oxygen-15 water PET CBF, using simultaneous
PET/MRI to minimize biological variability. Finally, we will apply this improv-
ed tool to study the effects of gender on CVR and its reproducibility.
Successful completion of this study will result in a validated methodology to
assess CVR in cerebrovascular disease patients without the use of radiation or
contrast. As such, it will provide solid, evidence-based recommendations for
clinicians developing new paradigms and interventions in patients with
impaired CVR.
脑血管疾病仍然是死亡和重大残疾的常见原因
在美国,识别和预防中风应该是一项高度重视的工作
优先事项。直接测量局部脑血流量 (CBF) 具有挑战性
对这些患者进行治疗,因为我们没有无创、无辐射的治疗方法
已根据金标准进行适当验证的成像方法
技术。这很重要,因为有令人信服的证据表明
测量旨在增加 CBF 的压力测试前后的 CBF 变化
(一种称为脑血管储备 [CVR] 的测量方法)可以识别患者
中风风险增加。压力测试一直是诊断的主要手段
对心脏病患者进行了多年的检查,我们坚信他们的
使用也将使脑血管疾病患者受益。
该项目的目标是提高动脉旋转标签(ASL)的质量
使用深度学习的 MRI,深度学习是机器学习的一种强大形式,目前
正在取得巨大的进步。然后我们将把它应用到未来,
针对氧 15 水 PET CBF 的自适应验证试验,使用同时
PET/MRI 可最大限度地减少生物变异性。最后,我们将应用这个改进
ed 工具来研究性别对 CVR 及其再现性的影响。
成功完成这项研究将产生一种经过验证的方法
评估脑血管疾病患者的 CVR,无需使用放射或
对比。因此,它将提供可靠的、基于证据的建议
临床医生为患者开发新的范例和干预措施
CVR 受损。
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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Gregory George Zaharchuk其他文献
Gregory George Zaharchuk的其他文献
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{{ truncateString('Gregory George Zaharchuk', 18)}}的其他基金
Predicting Tissue and Functional Outcome in Acute Stroke
预测急性中风的组织和功能结果
- 批准号:
10568740 - 财政年份:2023
- 资助金额:
$ 58.63万 - 项目类别:
AI-Enhanced Brain PET Imaging for Alzheimer's Disease
AI 增强型大脑 PET 成像治疗阿尔茨海默病
- 批准号:
10670483 - 财政年份:2022
- 资助金额:
$ 58.63万 - 项目类别:
Cerebrovascular Reserve Imaging with Simultaneous PET/MRI Using Arterial Spin Labeling and Deep Learning
使用动脉自旋标记和深度学习同时进行 PET/MRI 脑血管储备成像
- 批准号:
10181176 - 财政年份:2020
- 资助金额:
$ 58.63万 - 项目类别:
Cerebrovascular Reserve Imaging with Simultaneous PET/MRI Using Arterial Spin Labeling and Deep Learning
使用动脉自旋标记和深度学习同时进行 PET/MRI 脑血管储备成像
- 批准号:
10205063 - 财政年份:2018
- 资助金额:
$ 58.63万 - 项目类别:
Oxygenation Fingerprinting with MRI for Ischemic Stroke
缺血性中风的 MRI 氧合指纹图谱
- 批准号:
8827866 - 财政年份:2014
- 资助金额:
$ 58.63万 - 项目类别:
Oxygenation Fingerprinting with MRI for Ischemic Stroke
缺血性中风的 MRI 氧合指纹图谱
- 批准号:
8684656 - 财政年份:2014
- 资助金额:
$ 58.63万 - 项目类别:
USING ARTERIAL SPIN LABEL AND PWI TO MEASURE QUANTITATIVE CBF
使用动脉旋转标签和 PWI 定量测量 CBF
- 批准号:
8362921 - 财政年份:2011
- 资助金额:
$ 58.63万 - 项目类别:
Imaging Collaterals in Acute Stroke (iCAS)
急性中风的侧枝循环成像 (iCAS)
- 批准号:
9314645 - 财政年份:2009
- 资助金额:
$ 58.63万 - 项目类别:
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