Sub-Voxel Tissue Characterization With In-Vivo MRI
Sub-Voxel Tissue Characterization With In-Vivo MRI
批准号:
8237221
负责人:
MARK D DOES
金额:
$34.6万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-09-30 至 2015-07-31
关键词:
AddressAnatomyAutistic DisorderBiological MarkersCaliberCerebrumCharacteristicsChemicalsClinicalComplexComputer SimulationDataDevelopmentDiagnosticDiagnostic ImagingDiffusionDiseaseDuchenne muscular dystrophyEnvironmentEvaluationExhibitsFibrosisFoundationsFundingGoldHistologyImageImageryInflammationInjuryMagnetic Resonance ImagingMeasuresMethodsModelingMuscleMuscular DystrophiesMyelinNeuraxisNuclear Magnetic ResonancePaperPeripheralPhysiologic pulsePreparationProtocols documentationProtonsRattusRelaxationReperfusion InjuryResearchResearch PersonnelSchizophreniaSignal TransductionSkeletal MuscleSliceSpecificitySpinalTestingThickTissue ModelTissuesTranslatingVariantWaterWorkbaseclinically relevantcomputerized toolsimaging modalityin vivoinjuredmethod developmentmodel developmentmouse modelnovelprognosticprogramsrelating to nervous systemresearch studysimulationsoft tissuewater diffusionwhite matter
中文摘要
描述(由申请人提供):磁共振成像(MRI)是一种独特的信息丰富的软组织成像方式,具有对比度,对组织的无数物理,化学和功能特征敏感,但通常缺乏特异性。在与水质子(1H)核磁共振(NMR)相关的空间尺度上,组织是异质的,因此表现出的核磁共振信号是空间变化特征的复杂总和。大多数MRI方案提供了可以在空间上分辨的组织之间的对比,但很少或根本没有在较小尺度(即亚体素尺度)上存在的核磁共振信号变化的定量信息。这种定量的亚体素信息是诱人的,因为它提供了组织微观解剖的特异性。定量亚体素MRI组织表征的发展需要在两个方面协调推进:1)将相关微观解剖特征与1H NMR信号特征联系起来的定量模型,以及2)实用有效的定量MRI方法,可以将这些亚体素组织模型的使用转化为研究人员和临床医生的广泛应用。拟议的研究涉及建模和方法开发,旨在为白质和骨骼肌的微观解剖特征开发实用和定量的成像生物标志物,包括1)正常、发育和异常发育白质中的髓磷脂体积分数和髓磷脂厚度,以及2)存在炎症和纤维化的肌纤维体积分数和大小。这些生物标志物有可能影响研究和临床诊断,提供定量和具体的措施来跟踪与异常白质发育相关的疾病的变化,如精神分裂症和自闭症,以及肌肉损伤和肌肉萎缩症等疾病。
英文摘要
DESCRIPTION (provided by applicant): Magnetic resonance imaging (MRI) is a uniquely informative soft tissue imaging modality with contrast that is sensitive to a myriad of physical, chemical, and functional characteristics of tissue but often lacks specificity. On the spatial scale relevant to water proton (1H) nuclear magnetic resonance (NMR), tissues are heterogeneous and, consequently, exhibit an NMR signal that is the complex summation of spatially varying characteristics. Most MRI protocols provide contrast between tissues that can be resolved spatially, but yield little or no quantitative information about the variation in NMR signal that exists on a smaller scale, that is, the sub-voxel scale. This quantitative sub-voxel information is alluring because it provides specificity to tissue micro-anatomy. Development of quantitative sub-voxel MRI tissue characterization requires coordinated advancement on two fronts: 1) quantitative models that relate relevant micro-anatomical characteristics to 1H NMR signal characteristics, and 2) practical and effective quantitative MRI methods that can translate these the use of sub-voxel tissue models to widespread utility for researchers and clinicians. The proposed studies address both modeling and method development with the aim to develop practical and quantitative imaging biomarkers for micro-anatomical characteristics of white matter and skeletal muscle, including 1) myelin volume fraction and myelin thickness in normal, developing, and abnormally developing white matter, and 2) myofiber volume fraction and size, in the presence of inflammation and fibrosis. Such biomarkers have the potential to impact research and clinical diagnostics by providing quantitative and specific measures to track changes in disorders associated with abnormal white matter development, such as Schizophrenia and Autism, as well muscle injuries and diseases such as Muscular Dystrophy.
PUBLIC HEALTH RELEVANCE: MRI is a widespread diagnostic imaging modality capable of relatively non-invasive visualization of soft tissue. The contrast in MRI results from many complex interactions of water molecules in the body with each other and the physical and chemical characteristics of their local environments. This research program aims to better relate MRI contrast to specific micro-anatomical characteristics in neural tissue and skeletal muscle. This work has broad potential impact the diagnostic and prognostic capabilities of MRI for a wide array of diseases and injuries.
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