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MONITORING HUMAN BRAIN MATURATION USING MRDTI

MONITORING HUMAN BRAIN MATURATION USING MRDTI
使用 MRDTI 监测人脑成熟度
批准号:
6536259
负责人:
AZIZ M ULUG
金额:
$8.48万
依托单位国家:
美国
项目类别:
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-05-01 至 2004-04-30

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中文摘要
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英文摘要
DESCRIPTION: (Adapted from the applicant's Description) Magnetic resonance diffusion tensor imaging is an emerging MR methodology that is becoming to be routinely used in many facilities. The water diffusion in the human brain is a directionally-dependent quantity. The white matter fiber bundles restrict water diffusion in an orientation dependent manner and by increased myelination the restruction on water molecules increases. Using tensor formalism, information on the important characteristics of the brain tissue such as water mobility, water content, and fiber microstructure can be obtained. During human brain maturation important anatomical changes occur. The water content decreases, the number of cell and neuronal connections increase, and myelination progresses. Theses changes affect the diffusional properties of the tissue. By quantifying the diffusional changes in the maturing human brain, structural changes can be inferred. The purpose of this project is to develop quantitative methods that can be used to monitor brain maturation through non-invasive MR diffusion tensor imaging (MRDTI). The investigators recently showed that 3D MR diffusion tensor images can be reduced to single parameters that describe the entire brain structure by using distribution analysis and modeling. This way, brains of different subjects can be compared with each other in an unbiased manner. The proposed aims are: Aim 1: To develop and measure quantifiable parameters that describe the normal brain maturation using the 3D diffusion tensor data sets and modeling. Aim 2: To explore to use of these parameters to diagnose pathological states such as developmental delay or hydrocephalus. The investigators will use the routinely obtained diffusion tensor images and post-process them to obtain quantitative data. In this way a large amount of brain maturation data can be collected and processed in a short time.
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