Imaging for Autism: Diffusion Tensor Imaging (form of MRI)
DTI = Diffusion Tensor Imaging (form of MRI)
measures white matter microstructure
more specifically maps directions of water diffusion in a local brain tissue
DTI produces in vivo images of biological tissues
weighted with the local microstructural characteristics of water diffusion
diffusion weighted MRI: info re damage to parts of the nervous system
diffusion tensor MRI: info re connections among brain regions
DWI
each image voxel (three dimensional pixel) reflects rate of water diffusion at that location
suggestive of edema formation
great to dx vascular strokes by early detection of hypoxic edema
more sensitive to early changes after a stroke than more traditional MRI T1 or T2 relaxation rates
most applicable when the tissue of interest is dominated by isotropic water movement
zb: grey matter in cortex and major nuclei (where diffusion rate appears same along any axis)
DTI
see internal fibrous structure of neural white matter or cardiac muscle fibers
there is a preferred direction of flow
traditionally three gradient-directions are applied (sufficient but not fancy)
extended DTI scans derive neural tract directional information
from 3D vector algorithms based on six or more gradient directions
sufficient to compute the diffusion tensor
assumes homogeneity and linearity of diffusion within each image voxel
diffusion anisotropy measures such as fractional anisotropy (FA) may then be computed
*principal direction of the diffusion tensor can be used to infer the white-matter connectivity of the brain
"tractography"
new models of diffusion process proposed
q-space imaging and generalized diffusion tensor imaging
NEW AUTISM STUDY
Autism Res. Published online November 29, 2010
NIH sponsored, authors Lange and Lainhart at BYU in Provo, UT
compared: superior temporal gyrus and temporal stem
in 30 high-functioning autistic males aged 7 to 28 years
(dxd via standard subjective scoring system)
30 matched controls
in autistic subjects found:
less info exchange in brain areas responsible for language, social functioning, emotional behavior
test detected autism with 94% accuracy
"less organized wiring" said Dr Lange but I'm not sure, it is less or differently organized?
Dr Lange wants to MRI kid's brains to dx autism early-->tx best started early, customized to child
autistic pts have difficulty reading body language
"We are continuing to study and develop the test, and more findings are due out a year or 2 from now. We are also planning future studies to look at patients with high-severity autism and younger children less than 7 years of age and patients with brain disorders, such as developmental language disorders, attention-deficit/hyperactivity disorder, and obsessive compulsive disorder, who do not have autism."
Classification in DTI using shapes of white matter tracts
Adluru, N.; Hinrichs, C.; Chung, M.K.; Lee, J.-E.; Singh, V.; Bigler, E.D.; Lange, N.; Lainhart, J.E.; Alexander, A.L.;
Dept. of Psychol., Brigham Young Univ, Provo, UT, USA
This paper appears in: Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Issue Date: 3-6 Sept. 2009
On page(s): 2719 - 2722
Date of Current Version: 13 November 2009
ABSTRACT
Diffusion tensor imaging (DTI) provides unique information about the underlying tissue structure of brain white matter in vivo, including both the geometry of fiber bundles as well as quantitative information about tissue properties as characterized by measures such as tensor orientation, anisotropy, and size. Our objective in this paper is to evaluate the utility of shape representations of white matter tracts extracted from DTI data for classification of clinically different population groups (here autistic vs control). As a first step, our algorithm extracts fiber bundles passing through approximately marked regions of interest on affinely aligned brain volumes. The subsequent analysis is entirely based on the geometric modeling of the extracted tracts. A key advantage of using such an abstraction is that it allows us to capture invariant features of brains allowing for efficient large sample size studies. We demonstrate that with the use of an appropriate representation of the tract shapes, classifiers can be built with reasonable prediction accuracies without making heavy use of the spatial normalization machinery needed when using voxel based features.
AFFINE = of, relating to, or being a transformation (as a translation, a rotation, or a uniform stretching) that carries straight lines into straight lines and parallel lines into parallel lines but may alter distance between points and angles between lines
SOURCES
http://www.medscape.com/viewarticle/733476?src=mpnews&spon=12
http://en.wikipedia.org/wiki/Diffusion_MRI
http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5333386
http://www.merriam-webster.com/dictionary/affinely