HIGHLY EFFICIENT CEREBRAL PERFUSION MRI
高效脑灌注 MRI
基本信息
- 批准号:9043963
- 负责人:
- 金额:$ 67.94万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-04-01 至 2018-03-31
- 项目状态:已结题
- 来源:
- 关键词:AccelerationAlgorithmsAlzheimer&aposs DiseaseAreaArteriogramBiological MarkersBloodBlood capillariesBolus InfusionBrainBrain DiseasesBrain NeoplasmsBrain imagingBrain scanCaliforniaCerebrovascular CirculationCerebrumCharacteristicsClinicalClinical ProtocolsClinical ResearchComputer softwareDataData SetDegenerative DisorderDiagnosisDiagnosticDiffusionDiseaseEvaluationFamilyFunctional Magnetic Resonance ImagingGeneral HospitalsGoalsHumanImageImage AnalysisImaging TechniquesImaging technologyInjection of therapeutic agentLabelLeukoencephalopathyMagnetic Resonance ImagingManufacturer NameMapsMassachusettsMeasurementMeasuresMedicalMedical ResearchMedical centerMethodologyMethodsMorphologic artifactsMotionMultiple SclerosisNeurodegenerative DisordersNeurosciences ResearchNoiseParkinson DiseasePatientsPennsylvaniaPerformancePerfusionPharmacologic SubstancePharmacotherapyPhasePhysiologic pulsePhysiologicalPredispositionProcessProtocols documentationRadiationResearchResearch PersonnelResolutionSan FranciscoScanningSchemeSensitivity and SpecificitySignal TransductionSiteSliceSpeedSpin LabelsStrokeSumTechniquesTechnologyThickThree-Dimensional ImagingTimeTissuesTracerTrainingUnited States National Institutes of HealthUniversitiesage groupbasebioimagingblood perfusioncapillaryclinical Diagnosisconnectomecontrast enhanceddesignhemodynamicsimprovedinnovationmedical schoolsmillisecondnervous system disorderneurovascularnew technologynormal agingnovel therapeuticspreventprototypepublic health relevancereconstructionresearch clinical testingtime usetooltumor
项目摘要
DESCRIPTION (provided by applicant): MRI cerebral perfusion imaging is a widely disseminated technique on nearly all MRI scanners used for clinical diagnosis of brain disease and for neuroscience research. Over the last five years there has been considerably increased use of arterial spin labeling (ASL) for clinical diagnosis, while still i.v. injections of a gadoliium based contrast bolus are widely used clinically. Both brain perfusion methods, ASL and DSC techniques, involve making images very fast to identify the passage of blood through the capillary compartment. The image signal-to-noise ratio (SNR) is limited by the small (e.g., 3%) fraction of blood in tissue volumes. This is proportionately small but a second limitation is the time window of imaging, which is constrained to about 500-700 milliseconds for the capillary phase of blood passage. Therefore, rapid imaging of blood inflow is essential. For this reason DSC contrast based methods and ASL with multi-slice 2D EPI have not been able to satisfactorily image perfusion in the entire brain except with thick slices hence reduced spatial resolution. 3D imaging has therefore been developed as an alternative to 2D EPI. However, 2D images have certain desirable characteristics compared with 3D if there are patient motion artifacts. To overcome these limitations we propose to develop novel technology to acquire images simultaneously instead of separately. This approach called simultaneous multi-slice imaging ASL (SMS ASL) and SMS DSC increases by several fold the number of images that are acquired during the limited time window of capillary perfusion phase so the whole brain can be imaged. Another benefit of SMS-ASL is that the time to scan the brain can be greatly reduced by avoiding repeated scans of different brain areas, thus, reducing motion artifacts. A second major innovation in this project is the Hadamard encoded ASL, which is highly useful in clinical studies where the blood arterial transit time (ATT) is not known as in normal aging of people. The Hadamard-ASL acquires images at several different inflow times (TI) to be sure to capture the capillary perfusion phase of blood in at least one set of images. By acquiring the different TI values in a well-defined sub-bolus partitioning of the labeling period, their combination gives separated images at the distinct TI with essentially 2x the SNR and half the net scan time as required by current methodology which acquires each TI data set independently and sequentially. Both the Hadamard and the SMS can be combined for further improvements in SNR, speed and spatial resolution. This will highly impact the accessibility to patients and the robustness of the perfusion technology in clinical use. The availability of the new simultaneous perfusion imaging technology will give clinicians and researchers the capability of performing significantly improved MRI perfusion measurements in patients and these improvements will impact the diagnosis of many different brain diseases, including stroke, leukoencephalopathies and degenerative diseases; i.e., Alzheimer's disease and Parkinson's disease. Perfusion measurements of quantitative cerebral blood flow (CBF) and ATT are important quantitative biomarkers useful as physiological imaging in evaluating new drug therapies for brain diseases. This family of new perfusion imaging techniques utilizes more efficient pulse sequences that provide major advantages in resolution, slice coverage, SNR and speed. The new simultaneous imaging will have high utility and be highly desirable for use on clinical scanners worldwide. The improved quantitative MRI perfusion imaging offers overall increased efficiency that is highly commercializable given they provide improved diagnostic approaches to evaluate brain disease and further improve specificity and sensitivity in MRI neuroradiological exams. The new sequences will be designed, implemented and evaluated on MRI scanners operating at 1.5 Tesla at AMRIT, at 3T at University of California Berkeley and at 3T and 7T at University of California, San Francisco Medical Center and at Martinos Center for Biomedical Imaging, Massachusetts General Hospital, and Harvard Medical School. Once the new perfusion sequences are optimized they will be further evaluated and optimized in collaborative clinical test sites of UCSF Medical Center, UCLA and University of Pennsylvania. In addition to establishing their value in neuroradiology exams, they will be made into useful tools for basic and clinical neuroscience research.
描述(由申请人提供):MRI脑灌注成像是一种广泛应用于几乎所有MRI扫描仪的技术,用于脑部疾病的临床诊断和神经科学研究。在过去的五年中,动脉自旋标记(ASL)在临床诊断中的应用显著增加,而静脉内注射钆基造影剂在临床上仍被广泛使用。两种脑灌注方法,ASL和DSC技术,都涉及非常快速地制作图像以识别血液通过毛细血管室。图像信噪比(SNR)受到小的(例如,3%)组织体积中的血液分数。这是相当小的,但是第二个限制是成像的时间窗口,对于血液通道的毛细血管阶段,成像的时间窗口被约束到大约500-700毫秒。因此,快速成像的血液流入是必要的。因此,基于DSC对比度的方法和具有多层2D EPI的ASL不能令人满意地对整个大脑中的灌注成像,除了厚切片,因此降低了空间分辨率。因此,3D成像已被开发为2D EPI的替代方案。然而,如果存在患者运动伪影,则与3D相比,2D图像具有某些期望的特性。为了克服这些限制,我们建议开发新的技术,同时而不是单独获取图像。这种称为同步多层成像ASL(SMS ASL)和SMS DSC的方法将在毛细血管灌注阶段的有限时间窗口期间采集的图像数量增加了数倍,因此可以对整个大脑进行成像。SMS-ASL的另一个好处是,通过避免重复扫描不同的大脑区域,可以大大减少扫描大脑的时间,从而减少运动伪影。该项目的第二个主要创新是Hadamard编码的ASL,它在临床研究中非常有用,其中血液动脉通过时间(ATT)不像正常衰老的人那样已知。Hadamard-ASL在几个不同的流入时间(TI)采集图像,以确保在至少一组图像中捕获血液的毛细血管灌注相。通过在标记期的明确定义的子团注分区中采集不同的TI值,它们的组合在不同的TI处给出分离的图像,基本上是SNR的2倍和净扫描时间的一半,如当前方法所要求的,该方法独立地和顺序地采集每个TI数据集。Hadamard和SMS可以结合使用,以进一步提高SNR、速度和空间分辨率。这将极大地影响患者的可及性和灌注技术在临床使用中的稳健性。新的同步灌注成像技术的可用性将使临床医生和研究人员能够在患者中进行显着改进的MRI灌注测量,这些改进将影响许多不同脑部疾病的诊断,包括中风,白质脑病和退行性疾病;即,阿尔茨海默病和帕金森病。定量脑血流量(CBF)和ATT的灌注测量是重要的定量生物标志物,可用作评价脑部疾病新药治疗的生理成像。这一系列新的灌注成像技术利用更有效的脉冲序列,在分辨率、切片覆盖、SNR和速度方面具有重大优势。新的同步成像将具有很高的实用性,非常适合在全球范围内的临床扫描仪上使用。改进的定量MRI灌注成像提供了整体提高的效率,这是高度商业化的,因为它们提供了改进的诊断方法来评估脑部疾病,并进一步提高MRI神经放射学检查的特异性和灵敏度。新序列将在AMRIT的1.5特斯拉、加州大学伯克利分校的3 T、加州大学弗朗西斯科医学中心的3 T和7 T以及马萨诸塞州总医院和哈佛医学院的Martinos生物医学成像中心的MRI扫描仪上设计、实施和评估。一旦新的灌注序列得到优化,它们将在UCSF医学中心、UCLA和宾夕法尼亚大学的合作临床试验中心进行进一步评估和优化。除了在神经放射学检查中确立其价值外,它们还将成为基础和临床神经科学研究的有用工具。
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)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
David Alan Feinberg其他文献
David Alan Feinberg的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('David Alan Feinberg', 18)}}的其他基金
MRI CORTICOGRAPHY: DEVELOPING NEXT GENERATION MICROSCALE HUMAN CORTEX MRI SCANNER
MRI 皮质成像:开发下一代微型人类皮质 MRI 扫描仪
- 批准号:
10265466 - 财政年份:2017
- 资助金额:
$ 67.94万 - 项目类别:
MRI CORTICOGRAPHY: DEVELOPING NEXT GENERATION MICROSCALE HUMAN CORTEX MRI SCANNER
MRI 皮质成像:开发下一代微型人类皮质 MRI 扫描仪
- 批准号:
9768463 - 财政年份:2017
- 资助金额:
$ 67.94万 - 项目类别:
Foundations of MRI Corticography for mesoscale organization and neuronal circuitry
中尺度组织和神经元回路的 MRI 皮质成像基础
- 批准号:
9206105 - 财政年份:2016
- 资助金额:
$ 67.94万 - 项目类别:
Highly Accelerated Simultaneous Multi-Slice Phase Contrast MRI
高加速同步多层相衬 MRI
- 批准号:
9142186 - 财政年份:2016
- 资助金额:
$ 67.94万 - 项目类别:
Foundations of MRI Corticography for mesoscale organization and neuronal circuitry
中尺度组织和神经元回路的 MRI 皮质成像基础
- 批准号:
9763650 - 财政年份:2016
- 资助金额:
$ 67.94万 - 项目类别:
Highly Accelerated Simultaneous Multi-Slice Phase Contrast MRI
高加速同步多层相衬 MRI
- 批准号:
9322305 - 财政年份:2016
- 资助金额:
$ 67.94万 - 项目类别:
MRI Corticography (MRCoG): Micro-scale Human Cortical Imaging
MRI 皮质成像 (MRCoG):微型人体皮质成像
- 批准号:
9085397 - 财政年份:2014
- 资助金额:
$ 67.94万 - 项目类别:
MRI Corticography (MRCoG): Micro-scale Human Cortical Imaging
MRI 皮质成像 (MRCoG):微型人体皮质成像
- 批准号:
8828462 - 财政年份:2014
- 资助金额:
$ 67.94万 - 项目类别:
fMRI of human LGN: Functional subdivisions and geniculocortical connectivity
人类 LGN 的功能磁共振成像:功能细分和膝皮质连接
- 批准号:
8815317 - 财政年份:2014
- 资助金额:
$ 67.94万 - 项目类别:
相似海外基金
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
- 批准号:
2337776 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
- 批准号:
2338816 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
- 批准号:
2338846 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
- 批准号:
2348261 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
- 批准号:
2348346 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
- 批准号:
2348457 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
- 批准号:
2404989 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
- 批准号:
2339310 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
- 批准号:
2339669 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Continuing Grant
DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
- 批准号:
EP/Y029089/1 - 财政年份:2024
- 资助金额:
$ 67.94万 - 项目类别:
Research Grant