Imaging the Brain in Autism by Manuel F. Casanova Ayman S. El-Baz & Jasjit S. Suri
Author:Manuel F. Casanova, Ayman S. El-Baz & Jasjit S. Suri
Language: eng
Format: epub
Publisher: Springer New York, New York, NY
8.2.2 Diffusion Tensor Imaging: Measures of the Physical Properties of Tissue Microstructure and Macrostructure
Fractional anisotropy (FA) is a normalized standard deviation of the diffusion tensor eigenvalues that characterizes the directional variation in the apparent diffusion (Basser and Pierpaoli 1996),
(8.1)
where MD is the mean diffusivity defined by the average of the three eigenvalues.
(8.2)
FA is the most ubiquitous DTI measure and is a normalized standard deviation of the eigenvalues; FA ranges from 0 to 1 with smaller FA in more isotropic tissues (i.e., gray matter and cerebrospinal fluid) and higher FA in regions of WM. Higher FA values are indicative of more elongated and skinnier ellipsoids, with the greatest diffusion parallel to the tract. In contrast, lower FA values are indicative of more spherical ellipsoids, suggesting more even diffusion among the three directions. FA is highly sensitive to microstructural changes or differences in WM including myelination and axonal density and therefore is often called a measure of WM integrity or structural connectivity.
Although FA is the most popular DTI measure, FA cannot provide a complete description of WM microstructure (Alexander et al. 2000), and therefore, additional DTI measures should be investigated in order to better interpret the underlying changes in microstructure of the tissue (Alexander et al. 2007). Additional DTI measures include mean diffusivity (MD), axial diffusivity, and radial diffusivity. MD (Eq. 8.2), the average radius of the diffusion tensor ellipsoid, is sensitive to the density of tissue barriers in all directions. Axial diffusivity (AD) is the length of the first (longest) eigenvalue of the tensor (AD = λ 1). Radial diffusivity (RD), also known as the perpendicular diffusivity, is the average of the second and third eigenvalues (RD = (λ 2 + λ 3)/2) and measures water diffusion perpendicular to the WM tract. RD is thought to be indicative of myelin integrity in animal models of dys- and demyelination (Song et al. 2002, 2005; Harsan et al. 2006; Tyszka et al. 2006). However, changes in density or diameter of the axons, changes in cytoskeletal properties, or swelling from neuroinflammation are also plausible explanations for changes to RD and other DTI measures (including FA). Therefore, caution must be used to not overinterpret DTI changes in these measures (Wheeler-Kingshott and Cercignani 2009).
A significant limitation of DTI is that it is inadequate for describing WM microstructure in regions where there are crossing WM fibers (Alexander et al. 2001a; Wedeen et al. 2008). This often occurs in regions of crossing fibers which make the diffusion tensor more isotropic. Thus, FA is reduced in regions with complex WM fiber crossings. Currently, new methods (diffusion spectrum imaging, high angular resolution diffusion imaging) are being developed to try to characterize crossing tracts in DTI (Wedeen et al. 2008; Tournier et al. 2011). However, until these new methods are used to study autism, some caution should be used in the interpretation of DTI measures in the WM tracts that are known to have a number of crossing fibers.
Download
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.
Algorithms of the Intelligent Web by Haralambos Marmanis;Dmitry Babenko(8332)
Test-Driven Development with Java by Alan Mellor(7017)
Data Augmentation with Python by Duc Haba(6941)
Principles of Data Fabric by Sonia Mezzetta(6673)
Learn Blender Simulations the Right Way by Stephen Pearson(6581)
Microservices with Spring Boot 3 and Spring Cloud by Magnus Larsson(6443)
Hadoop in Practice by Alex Holmes(5977)
RPA Solution Architect's Handbook by Sachin Sahgal(5835)
Jquery UI in Action : Master the concepts Of Jquery UI: A Step By Step Approach by ANMOL GOYAL(5831)
The Infinite Retina by Robert Scoble Irena Cronin(5533)
Big Data Analysis with Python by Ivan Marin(5505)
Life 3.0: Being Human in the Age of Artificial Intelligence by Tegmark Max(5182)
Pretrain Vision and Large Language Models in Python by Emily Webber(4468)
Infrastructure as Code for Beginners by Russ McKendrick(4255)
Functional Programming in JavaScript by Mantyla Dan(4059)
The Age of Surveillance Capitalism by Shoshana Zuboff(3980)
WordPress Plugin Development Cookbook by Yannick Lefebvre(3962)
Embracing Microservices Design by Ovais Mehboob Ahmed Khan Nabil Siddiqui and Timothy Oleson(3763)
Applied Machine Learning for Healthcare and Life Sciences Using AWS by Ujjwal Ratan(3737)
