Abstract
A new method for analyzing diffusion tensor imaging (DTI) of the brain, based on a recently introduced algorithm, lambda chart analysis (LCA), is presented. Pretreatment of a given DTI data set with LCA, which effectively segregates isotropic and anisotropic components, allows for total removal of the anisotropic component from the DTI data set. The remaining pure isotropic component can therefore be subjected to further analysis similar to that applied in the trace histogram method. Deconvolution of the trace function yielded 3 Gaussian elements. Remapping of these 3 deconvoluted isotropic elements back onto the 2-dimensional image plane provided anatomical correlates of each element. The algorithm, referred to here as isotropic component trace analysis, can be used as a pictorial analytic tool, as well as a numerical analytical tool, for the noninvasive assessment of isotropic parenchymal components. The presented method provides quantitative indices of certain parenchymal parameters with better clarity than currently available methods. A ready-to-use program, EZ-LCA, for this powerful method is provided (available at http://coe.bri. niigata-u.ac.jp).
| Original language | English (US) |
|---|---|
| Pages (from-to) | 233-239 |
| Number of pages | 7 |
| Journal | Journal of Neuroimaging |
| Volume | 15 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jul 2005 |
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Keywords
- Diffusion anisotropy
- Diffusion tensor imaging
- Eigenvalue
- Lambda chart analysis
- Trace
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Clinical Neurology
- Neuroscience(all)
- Radiological and Ultrasound Technology
Cite this
Isotropic component trace analysis. / Matsuzawa, Hitoshi; Nakayama, Naoki; Kwee, Ingrid; Nakada, Tsutomu.
In: Journal of Neuroimaging, Vol. 15, No. 3, 07.2005, p. 233-239.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Isotropic component trace analysis
AU - Matsuzawa, Hitoshi
AU - Nakayama, Naoki
AU - Kwee, Ingrid
AU - Nakada, Tsutomu
PY - 2005/7
Y1 - 2005/7
N2 - A new method for analyzing diffusion tensor imaging (DTI) of the brain, based on a recently introduced algorithm, lambda chart analysis (LCA), is presented. Pretreatment of a given DTI data set with LCA, which effectively segregates isotropic and anisotropic components, allows for total removal of the anisotropic component from the DTI data set. The remaining pure isotropic component can therefore be subjected to further analysis similar to that applied in the trace histogram method. Deconvolution of the trace function yielded 3 Gaussian elements. Remapping of these 3 deconvoluted isotropic elements back onto the 2-dimensional image plane provided anatomical correlates of each element. The algorithm, referred to here as isotropic component trace analysis, can be used as a pictorial analytic tool, as well as a numerical analytical tool, for the noninvasive assessment of isotropic parenchymal components. The presented method provides quantitative indices of certain parenchymal parameters with better clarity than currently available methods. A ready-to-use program, EZ-LCA, for this powerful method is provided (available at http://coe.bri. niigata-u.ac.jp).
AB - A new method for analyzing diffusion tensor imaging (DTI) of the brain, based on a recently introduced algorithm, lambda chart analysis (LCA), is presented. Pretreatment of a given DTI data set with LCA, which effectively segregates isotropic and anisotropic components, allows for total removal of the anisotropic component from the DTI data set. The remaining pure isotropic component can therefore be subjected to further analysis similar to that applied in the trace histogram method. Deconvolution of the trace function yielded 3 Gaussian elements. Remapping of these 3 deconvoluted isotropic elements back onto the 2-dimensional image plane provided anatomical correlates of each element. The algorithm, referred to here as isotropic component trace analysis, can be used as a pictorial analytic tool, as well as a numerical analytical tool, for the noninvasive assessment of isotropic parenchymal components. The presented method provides quantitative indices of certain parenchymal parameters with better clarity than currently available methods. A ready-to-use program, EZ-LCA, for this powerful method is provided (available at http://coe.bri. niigata-u.ac.jp).
KW - Diffusion anisotropy
KW - Diffusion tensor imaging
KW - Eigenvalue
KW - Lambda chart analysis
KW - Trace
UR - http://www.scopus.com/inward/record.url?scp=20844460985&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=20844460985&partnerID=8YFLogxK
U2 - 10.1177/1051228405277404
DO - 10.1177/1051228405277404
M3 - Article
C2 - 15951405
AN - SCOPUS:20844460985
VL - 15
SP - 233
EP - 239
JO - Journal of Neuroimaging
JF - Journal of Neuroimaging
SN - 1051-2284
IS - 3
ER -