scholarly journals Impact of transcytolemmal water exchange on estimates of tissue microstructural properties derived from diffusion MRI

2016 ◽  
Vol 77 (6) ◽  
pp. 2239-2249 ◽  
Author(s):  
Hua Li ◽  
Xiaoyu Jiang ◽  
Jingping Xie ◽  
John C. Gore ◽  
Junzhong Xu
Keyword(s):  
Diffusion Mri ◽  
Water Exchange ◽  
Microstructural Properties

Effect of myelin water exchange on DTI-derived parameters in diffusion MRI: Elucidation of TE dependence

2017 ◽  
Vol 79 (3) ◽  
pp. 1650-1660 ◽  
Author(s):  
Mu Lin ◽  
Hongjian He ◽  
Qiqi Tong ◽  
Qiuping Ding ◽  
Xu Yan ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Water Exchange

scholarly journals An Analytical Model for Estimating Water Exchange Rate in White Matter Using Diffusion MRI

PLoS ONE ◽  
2014 ◽  
Vol 9 (5) ◽  
pp. e95921 ◽  
Author(s):  
Esmaeil Davoodi-Bojd ◽  
Michael Chopp ◽  
Hamid Soltanian-Zadeh ◽  
Shiyang Wang ◽  
Guangliang Ding ◽  
...  
Keyword(s):  
Exchange Rate ◽  
White Matter ◽  
Analytical Model ◽  
Diffusion Mri ◽  
Water Exchange ◽  
Water Exchange Rate

scholarly journals Post mortem mapping of connectional anatomy for the validation of diffusion MRI

2021 ◽  
Author(s):  
Anastasia Yendiki ◽  
Manisha Aggarwal ◽  
Markus Axer ◽  
Amy FD Howard ◽  
Anne-Marie van Cappellen van Walsum ◽  
...  
Keyword(s):  
Optical Imaging ◽  
Diffusion Mri ◽  
Imaging Techniques ◽  
Post Mortem ◽  
Microstructural Properties ◽  
Label Free ◽  
Tracer Studies ◽  
Basic Principles ◽  
The Brain ◽  
Source Of Information

Despite the impressive advances in diffusion MRI (dMRI) acquisition and analysis that have taken place during the Human Connectome era, dMRI tractography is still an imperfect source of information on the circuitry of the brain. In this review, we discuss methods for post mortem validation of dMRI tractography, fiber orientations, and other microstructural properties of axon bundles that are typically extracted from dMRI data. These methods include anatomic tracer studies, Klingler's dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.

scholarly journals Cumulant expansions for measuring water exchange using diffusion MRI

2018 ◽  
Vol 148 (7) ◽  
pp. 074109 ◽  
Author(s):  
Lipeng Ning ◽  
Markus Nilsson ◽  
Samo Lasič ◽  
Carl-Fredrik Westin ◽  
Yogesh Rathi
Keyword(s):  
Diffusion Mri ◽  
Water Exchange ◽  
Cumulant Expansions

scholarly journals The sensitivity of diffusion MRI to microstructural properties and experimental factors

2021 ◽  
Vol 347 ◽  
pp. 108951 ◽  
Author(s):  
Maryam Afzali ◽  
Tomasz Pieciak ◽  
Sharlene Newman ◽  
Eleftherios Garyfallidis ◽  
Evren Özarslan ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Microstructural Properties

Spectral and Topographic Microstructure of Brain Alpha Activity During Drowsiness at Sleep Onset and REM Sleep

2000 ◽  
Vol 14 (3) ◽  
pp. 151-158 ◽  
Author(s):  
José Luis Cantero ◽  
Mercedes Atienza
Keyword(s):  
Rem Sleep ◽  
Spectral Component ◽  
Sleep Onset ◽  
Quantitative Information ◽  
Maximum Energy ◽  
Alpha Activity ◽  
The Other ◽  
Classification Algorithms ◽  
Microstructural Properties ◽  
Brain States

Abstract High-resolution frequency methods were used to describe the spectral and topographic microstructure of human spontaneous alpha activity in the drowsiness (DR) period at sleep onset and during REM sleep. Electroencephalographic (EEG), electrooculographic (EOG), and electromyographic (EMG) measurements were obtained during sleep in 10 healthy volunteer subjects. Spectral microstructure of alpha activity during DR showed a significant maximum power with respect to REM-alpha bursts for the components in the 9.7-10.9 Hz range, whereas REM-alpha bursts reached their maximum statistical differentiation from the sleep onset alpha activity at the components between 7.8 and 8.6 Hz. Furthermore, the maximum energy over occipital regions appeared in a different spectral component in each brain activation state, namely, 10.1 Hz in drowsiness and 8.6 Hz in REM sleep. These results provide quantitative information for differentiating the drowsiness alpha activity and REM-alpha by studying their microstructural properties. On the other hand, these data suggest that the spectral microstructure of alpha activity during sleep onset and REM sleep could be a useful index to implement in automatic classification algorithms in order to improve the differentiation between the two brain states.

Clinically indicated functional and diffusion MRI in children: The Tübingen experience

2013 ◽  
Vol 44 (S 01) ◽  
Author(s):  
M Wilke ◽  
S Groeschel ◽  
M Schuhmann ◽  
S Rona ◽  
M Alber ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
And Diffusion
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