scholarly journals Toward a Standardized Approach to Estimate Kurtosis in Body Applications of a Non-Gaussian Diffusion Kurtosis Imaging Model of Water Diffusion

Radiology ◽  
2017 ◽  
Vol 285 (1) ◽  
pp. 329-331 ◽  
Author(s):  
Marco Giannelli ◽  
Chiara Marzi ◽  
Mario Mascalchi ◽  
Stefano Diciotti ◽  
Carlo Tessa
Keyword(s):  
Water Diffusion ◽  
Diffusion Kurtosis Imaging ◽  
Imaging Model ◽  
Non Gaussian ◽  
Diffusion Kurtosis

Three-dimensional characterization of non-gaussian water diffusion in humans using diffusion kurtosis imaging

2006 ◽  
Vol 19 (2) ◽  
pp. 236-247 ◽  
Author(s):  
Hanzhang Lu ◽  
Jens H. Jensen ◽  
Anita Ramani ◽  
Joseph A. Helpern
Keyword(s):  
Three Dimensional ◽  
Water Diffusion ◽  
Diffusion Kurtosis Imaging ◽  
Non Gaussian ◽  
Diffusion Kurtosis

Investigation of the Non-Gaussian Water Diffusion Properties in Bladder Cancer Using Diffusion Kurtosis Imaging

2015 ◽  
Vol 39 (2) ◽  
pp. 281-285 ◽  
Author(s):  
Shiteng Suo ◽  
Xiaoxi Chen ◽  
Xiang Ji ◽  
Zhiguo Zhuang ◽  
Lianming Wu ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Water Diffusion ◽  
Diffusion Kurtosis Imaging ◽  
Non Gaussian ◽  
Diffusion Kurtosis ◽  
Diffusion Properties

Non-Gaussian water diffusion kurtosis imaging of prostate cancer

2014 ◽  
Vol 32 (5) ◽  
pp. 421-427 ◽  
Author(s):  
Shiteng Suo ◽  
Xiaoxi Chen ◽  
Lianming Wu ◽  
Xiaofei Zhang ◽  
Qiuying Yao ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Water Diffusion ◽  
Diffusion Kurtosis Imaging ◽  
Non Gaussian ◽  
Diffusion Kurtosis

scholarly journals Differential cortical microstructural maturation in the preterm human brain with diffusion kurtosis and tensor imaging

2019 ◽  
Vol 116 (10) ◽  
pp. 4681-4688 ◽  
Author(s):  
Minhui Ouyang ◽  
Tina Jeon ◽  
Aristeidis Sotiras ◽  
Qinmu Peng ◽  
Virendra Mishra ◽  
...  
Keyword(s):  
Human Brain ◽  
Diffusion Tensor ◽  
Cortical Plate ◽  
Diffusion Kurtosis Imaging ◽  
Third Trimester ◽  
Microstructural Changes ◽  
The Third ◽  
Cortical Regions ◽  
Non Gaussian ◽  
Diffusion Kurtosis

During the third trimester, the human brain undergoes rapid cellular and molecular processes that reshape the structural architecture of the cerebral cortex. Knowledge of cortical differentiation obtained predominantly from histological studies is limited in localized and small cortical regions. How cortical microstructure is differentiated across cortical regions in this critical period is unknown. In this study, the cortical microstructural architecture across the entire cortex was delineated with non-Gaussian diffusion kurtosis imaging as well as conventional diffusion tensor imaging of 89 preterm neonates aged 31–42 postmenstrual weeks. The temporal changes of cortical mean kurtosis (MK) or fractional anisotropy (FA) were heterogeneous across the cortical regions. Cortical MK decreases were observed throughout the studied age period, while cortical FA decrease reached its plateau around 37 weeks. More rapid decreases in MK were found in the primary visual region, while faster FA declines were observed in the prefrontal cortex. We found that distinctive cortical microstructural changes were coupled with microstructural maturation of associated white matter tracts. Both cortical MK and FA measurements predicted the postmenstrual age of preterm infants accurately. This study revealed a differential 4D spatiotemporal cytoarchitectural signature inferred by non-Gaussian diffusion barriers inside the cortical plate during the third trimester. The cytoarchitectural processes, including dendritic arborization and neuronal density decreases, were inferred by regional cortical FA and MK measurements. The presented findings suggest that cortical MK and FA measurements could be used as effective imaging markers for cortical microstructural changes in typical and potentially atypical brain development.

scholarly journals White matter microstructural integrity across the adult lifespan: Combined perspective of diffusion tensor and kurtosis imaging

2021 ◽  
Author(s):  
Hiba Taha ◽  
Jordan A Chad ◽  
J. Jean Chen
Keyword(s):  
White Matter ◽  
Brain Aging ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
General Pattern ◽  
B Value ◽  
Diffusion Kurtosis Imaging ◽  
Adult Lifespan ◽  
Non Gaussian ◽  
Diffusion Kurtosis

Studies of healthy brain aging have reported diffusivity patterns associated with white matter degeneration using diffusion tensor imaging (DTI), which assumes that diffusion measured at the typical b-value (approximately 1000 s/mm2) is Gaussian. Diffusion kurtosis imaging (DKI) is an extension of DTI that measures non-Gaussian diffusion (kurtosis) to better capture microenvironmental changes by incorporating additional data at a higher b-value. In this study, using UK Biobank data (b values of 1000 and 2000 s/mm2), we investigate (1) the extent of novel information gained from adding diffusional kurtosis to diffusivity observations in aging, and (2) how conventional DTI metrics in aging compare with diffusivity metrics derived from DKI, which are corrected for kurtosis. We find a general pattern of lower kurtosis alongside higher diffusivity among older adults. We also find differences between diffusivity metrics derived from DTI and DKI, emphasizing the importance of accounting for non-Gaussian diffusion. This work highlights the utility of measuring diffusional kurtosis as a simple addition to conventional diffusion imaging of aging.

scholarly journals The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review

2021 ◽  
Vol 10 (12) ◽  
pp. 2641
Author(s):  
Liberatore Tramontano ◽  
Carlo Cavaliere ◽  
Marco Salvatore ◽  
Valentina Brancato
Keyword(s):  
Hepatocellular Carcinoma ◽  
Systematic Review ◽  
Current Knowledge ◽  
Exponential Model ◽  
Response To Treatment ◽  
Diffusion Kurtosis Imaging ◽  
Diffusion Weighted ◽  
Non Gaussian ◽  
Diffusion Kurtosis

The importance of Diffusion Weighted Imaging (DWI) in hepatocellular carcinoma (HCC) has been widely handled in the literature. Due to the mono-exponential model limitations, several studies recently investigated the role of non-Gaussian DWI models in HCC. However, their results are variable and inconsistent. Therefore, the aim of this systematic review is to summarize current knowledge on non-Gaussian DWI techniques in HCC. A systematic search of the literature, including PubMed, Google Scholar, MEDLINE, and ScienceDirect databases, was performed to identify original articles since 2010 that evaluated the role of non-Gaussian DWI models for HCC diagnosis, grading, response to treatment, and prognosis. Studies were grouped and summarized according to the non-Gaussian DWI models investigated. We focused on the most used non-Gaussian DWI models (Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Stretched Exponential—SE). The quality of included studies was evaluated by using QUADAS-2 and QUIPS tools. Forty-three articles were included, with IVIM and DKI being the most investigated models. Although the role of non-Gaussian DWI models in clinical settings has not fully been established, our findings showed that their parameters may potentially play a role in HCC. Further studies are required to identify a standardized DWI acquisition protocol for HCC diagnosis, grading, response to treatment, and prognosis.

scholarly journals Parametric Mapping of Brain Tissues from Diffusion Kurtosis Tensor

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Yuanyuan Chen ◽  
Xin Zhao ◽  
Hongyan Ni ◽  
Jie Feng ◽  
Hao Ding ◽  
...  
Keyword(s):  
Diffusion Tensor ◽  
Regional Analysis ◽  
Gaussian Model ◽  
Gaussian Mixture ◽  
Diffusion Kurtosis Imaging ◽  
Mean Values ◽  
Detailed Classification ◽  
Magnetic Resonance Imaging Mri ◽  
Non Gaussian ◽  
Diffusion Kurtosis

Diffusion kurtosis imaging (DKI) is a new diffusion magnetic resonance imaging (MRI) technique to go beyond the shortages of conventional diffusion tensor imaging (DTI) from the assumption that water diffuse in biological tissue is Gaussian. Kurtosis is used to measure the deviation of water diffusion from Gaussian model, which is called non-Gaussian, in DKI. However, the high-order kurtosis tensor in the model brings great difficulties in feature extraction. In this study, parameters like fractional anisotropy of kurtosis eigenvalues (FAek) and mean values of kurtosis eigenvalues (Mek) were proposed, and regional analysis was performed for 4 different tissues: corpus callosum, crossing fibers, thalamus, and cerebral cortex, compared with other parameters. Scatterplot analysis and Gaussian mixture decomposition of different parametric maps are used for tissues identification. Diffusion kurtosis information extracted from kurtosis tensor presented a more detailed classification of tissues actually as well as clinical significance, and the FAek ofD-eigenvalues showed good sensitivity of tissues complexity which is important for further study of DKI.

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