MRI quantification of non-Gaussian water diffusion by kurtosis analysis.
MRI quantification of non-Gaussian water diffusion by kurtosis analysis.
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DOI：
10.1002/nbm.1518
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发表时间：
2010-08
影响因子：
2.9
通讯作者：
Helpern, Joseph A.
中科院分区：
文献类型：
--
作者：
Jensen, Jens H.;Helpern, Joseph A.
本文综述了利用扩散峰度成像（DKI）定量研究脑内水扩散的非高斯性。扩散非高斯性是产生扩散屏障和隔室的组织结构的结果。非高斯性的程度可以方便地通过扩散峰度和导数度量（例如平均值、轴向和径向峰度）来量化。DKI是一种弥散加权MRI技术，允许使用标准弥散加权脉冲序列和相对适中的采集时间，通过临床扫描仪估计弥散峰度。DKI是广泛使用的扩散张量成像方法的扩展，但需要使用至少3个b值和15个扩散方向。本文讨论了DKI的基本理论以及与数据采集和后处理相关的实际考虑。有人认为，扩散峰度是敏感的扩散异质性，并建议，DKI可能是有用的缺血性中风和神经病理学，如阿尔茨海默氏病和精神分裂症的调查。
Quantification of non-Gaussianity for water diffusion in brain by means of diffusional kurtosis imaging (DKI) is reviewed. Diffusional non-Gaussianity is a consequence of tissue structure that creates diffusion barriers and compartments. The degree of non-Gaussianity is conveniently quantified by the diffusional kurtosis and derivative metrics, such as the mean, axial, and radial kurtoses. DKI is a diffusion-weighted MRI technique that allows the diffusional kurtosis to be estimated with clinical scanners using standard diffusion-weighted pulse sequences and relatively modest acquisition times. DKI is an extension of the widely used diffusion tensor imaging method, but requires the use of at least 3 b-values and 15 diffusion directions. This review discusses the underlying theory of DKI as well as practical considerations related to data acquisition and post-processing. It is argued that the diffusional kurtosis is sensitive to diffusional heterogeneity and suggested that DKI may be useful for investigating ischemic stroke and neuropathologies, such as Alzheimer’s disease and schizophrenia.
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影响因子：
2.2
作者：
Frohlich, AF;Ostergaard, L;Kiselev, VG
通讯作者：
Kiselev, VG
DOI：
10.1006/jmrb.1994.1037
发表时间：
1994-03-01
期刊：
JOURNAL OF MAGNETIC RESONANCE SERIES B
影响因子：
--
作者：
BASSER, PJ;MATTIELLO, J;LEBIHAN, D
通讯作者：
LEBIHAN, D
影响因子：
4.4
作者：
Falangola, Maria F.;Jensen, Jens H.;Babb, James S.;Hu, Caixia;Castellanos, Francisco X.;Di Martino, Adriana;Ferris, Steven H.;Helpern, Joseph A.
通讯作者：
Helpern, Joseph A.
影响因子：
5.7
作者：
Jian, Bing;Vemuri, Baba C.;Mareci, Thomas H.
通讯作者：
Mareci, Thomas H.
影响因子：
7
作者：
DeCarlo, LT
通讯作者：
DeCarlo, LT