Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain

2016 ◽  
Vol 43 (5) ◽  
pp. 2464-2475 ◽  
Author(s):  
S. Lanzafame ◽  
M. Giannelli ◽  
F. Garaci ◽  
R. Floris ◽  
A. Duggento ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Human Brain ◽  
Diffusion Tensor ◽  
Diffusion Kurtosis Imaging ◽  
Model Based ◽  
Tensor Invariants ◽  
Imaging Model ◽  
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 Widespread White Matter Microstructure Alterations Based on Diffusion Tensor Imaging and Diffusion Kurtosis Imaging in Patients With Pontine Infarction

2021 ◽  
Vol 13 ◽  
Author(s):  
Ying Wei ◽  
Caihong Wang ◽  
Jingchun Liu ◽  
Peifang Miao ◽  
Sen Wei ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Diffusion Kurtosis Imaging ◽  
White Matter Tracts ◽  
Microstructure Changes ◽  
Diffusion Parameters ◽  
White Matter Microstructure ◽  
Pontine Infarction ◽  
Diffusion Kurtosis

Neurological deficits after stroke are closely related to white matter microstructure damage. However, secondary changes in white matter microstructure after pontine infarction (PI) in the whole brain remain unclear. This study aimed to investigate the correlation of diffusion kurtosis imaging (DKI)-derived diffusion and kurtosis parameters of abnormal white matter tracts with behavioral function in patients with chronic PI. Overall, 60 patients with unilateral chronic PI (33 patients with left PI and 27 patients with right PI) and 30 normal subjects were recruited and underwent DKI scans. Diffusion parameters derived from diffusion tensor imaging (DTI) and DKI and kurtosis parameters derived from DKI were obtained. Between-group differences in multiple parameters were analyzed to assess the changes in abnormal white matter microstructure. Moreover, we also calculated the sensitivities of different diffusion and kurtosis parameters of DTI and DKI for identifying abnormal white matter tracts. Correlations between the DKI-derived parameters in secondary microstructure changes and behavioral scores in the PI were analyzed. Compared with the NC group, both left PI and right PI groups showed more extensive perilesional and remote white matter microstructure changes. The DKI-derived diffusion parameters showed higher sensitivities than did the DTI-derived parameters. Further, DKI-derived diffusion and kurtosis parameters in abnormal white matter regions were correlated with impaired motor and cognitive function in patients with PI. In conclusion, PI could lead to extensive white matter tracts impairment in perilesional and remote regions. Further, the diffusion and kurtosis parameters could be complementary for identifying comprehensive tissue microstructural damage after PI.

Performance of Diffusion Kurtosis Imaging Versus Diffusion Tensor Imaging in Discriminating Between Benign Tissue, Low and High Gleason Grade Prostate Cancer

2019 ◽  
Vol 26 (10) ◽  
pp. 1328-1337 ◽  
Author(s):  
Maria Giovanna Di Trani ◽  
Marco Nezzo ◽  
Alessandra S. Caporale ◽  
Riccardo De Feo ◽  
Roberto Miano ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Diffusion Kurtosis Imaging ◽  
Gleason Grade ◽  
Benign Tissue ◽  
Diffusion Kurtosis

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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