Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

被引:39
|
作者
Mueller, Hans-Peter [1 ]
Kassubek, Jan [1 ]
机构
[1] Univ Ulm, Dept Neurol, D-89069 Ulm, Germany
来源
基金
美国国家卫生研究院;
关键词
Medicine; Issue; 77; Neuroscience; Neurobiology; Molecular Biology; Biomedical Engineering; Anatomy; Physiology; Neurodegenerative Diseases; nuclear magnetic resonance; NMR; MR; MRI; diffusion tensor imaging; fiber tracking; group level comparison; neurodegenerative diseases; brain; imaging; clinical techniques;
D O I
10.3791/50427
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i. e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional interdependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i. e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
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页数:16
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