Diffusion tensor imaging of early relapsing-remitting multiple sclerosis
with histogram analysis using automated segmentation and brain volume
correction.
Diffusion tensor magnetic resonance imaging (DTI) reveals measurable
abnormalities in normal-appearing brain tissue (NABT) in established
multiple sclerosis (MS). However, it is unclear how early this occurs.
Recent studies have employed whole brain histogram analysis to improve
sensitivity, but concern exists regarding reliability of tissue/cerebrospinal
fluid segmentation and possible intersubject brain volume differences,
which can introduce partial volume error: To address this, 28 early
relapsing-remitting MS subjects median disease duration 1.6 years;
median Expanded Disability Status Scale (EDSS) score 1.5 and 20
controls were compared with whole brain histogram analysis using
an automated segmentation algorithm to improve reproducibility.
Brain parenchymal volumes (BPV) were estimated for each subject
in the analysis. The mean, peak height and peak location were calculated
for DTI parameters fractional anisotropy (FA), mean diffusivity
and volume ratio. An increased FA peak height in MS subject NABT
was observed (P = 0.02) accounting for age, gender and BPV. Removing
BPV revealed additional abnormalities in NABT. The main conclusions
are i) FA peak height is increased in NABT in early MS, ii) partial
volume edge effects may contribute to apparent NABT histogram abnormalities,
and iii) correction for brain volume differences should reduce potential
partial volume edge effects.
%0 Journal Article
%1 Rashid2004
%A Rashid, W.
%A Hadjiprocopis, A.
%A Griffin, C. M.
%A Chard, D. T.
%A Davies, G. R.
%A Barker, G. J.
%A Tofts, P. S.
%A Thompson, A. J.
%A Miller, D. H.
%D 2004
%J Multiple Sclerosis
%K Middle Studies, Aged, Processing, Female, Male, Evaluation, Imaging, Adult, Multiple Resonance 14760947 Automation, Non-U.S. Support, Anisotropy, Disability Cohort Diffusion Algorithms, Brain, of Image Results, Computer-Assisted, Sclerosis, Research Gov't, Case-Control Relapsing-Remitting, Magnetic Reproducibility Humans,
%N 1
%P 9--15
%T Diffusion tensor imaging of early relapsing-remitting multiple sclerosis
with histogram analysis using automated segmentation and brain volume
correction.
%V 10
%X Diffusion tensor magnetic resonance imaging (DTI) reveals measurable
abnormalities in normal-appearing brain tissue (NABT) in established
multiple sclerosis (MS). However, it is unclear how early this occurs.
Recent studies have employed whole brain histogram analysis to improve
sensitivity, but concern exists regarding reliability of tissue/cerebrospinal
fluid segmentation and possible intersubject brain volume differences,
which can introduce partial volume error: To address this, 28 early
relapsing-remitting MS subjects median disease duration 1.6 years;
median Expanded Disability Status Scale (EDSS) score 1.5 and 20
controls were compared with whole brain histogram analysis using
an automated segmentation algorithm to improve reproducibility.
Brain parenchymal volumes (BPV) were estimated for each subject
in the analysis. The mean, peak height and peak location were calculated
for DTI parameters fractional anisotropy (FA), mean diffusivity
and volume ratio. An increased FA peak height in MS subject NABT
was observed (P = 0.02) accounting for age, gender and BPV. Removing
BPV revealed additional abnormalities in NABT. The main conclusions
are i) FA peak height is increased in NABT in early MS, ii) partial
volume edge effects may contribute to apparent NABT histogram abnormalities,
and iii) correction for brain volume differences should reduce potential
partial volume edge effects.
@article{Rashid2004,
abstract = {Diffusion tensor magnetic resonance imaging (DTI) reveals measurable
abnormalities in normal-appearing brain tissue (NABT) in established
multiple sclerosis (MS). However, it is unclear how early this occurs.
Recent studies have employed whole brain histogram analysis to improve
sensitivity, but concern exists regarding reliability of tissue/cerebrospinal
fluid segmentation and possible intersubject brain volume differences,
which can introduce partial volume error: To address this, 28 early
relapsing-remitting MS subjects [median disease duration 1.6 years;
median Expanded Disability Status Scale (EDSS) score 1.5] and 20
controls were compared with whole brain histogram analysis using
an automated segmentation algorithm to improve reproducibility.
Brain parenchymal volumes (BPV) were estimated for each subject
in the analysis. The mean, peak height and peak location were calculated
for DTI parameters [fractional anisotropy (FA), mean diffusivity
and volume ratio]. An increased FA peak height in MS subject NABT
was observed (P = 0.02) accounting for age, gender and BPV. Removing
BPV revealed additional abnormalities in NABT. The main conclusions
are i) FA peak height is increased in NABT in early MS, ii) partial
volume edge effects may contribute to apparent NABT histogram abnormalities,
and iii) correction for brain volume differences should reduce potential
partial volume edge effects.},
added-at = {2007-01-10T11:32:01.000+0100},
author = {Rashid, W. and Hadjiprocopis, A. and Griffin, C. M. and Chard, D. T. and Davies, G. R. and Barker, G. J. and Tofts, P. S. and Thompson, A. J. and Miller, D. H.},
biburl = {https://www.bibsonomy.org/bibtex/2cae66b19115a4b7b5f0aa4a52c941069/bmeyer},
description = {Diffusion Tensor Imaging (DTI)},
interhash = {098d4bea05d313b1399b0861593c9e42},
intrahash = {cae66b19115a4b7b5f0aa4a52c941069},
journal = {Multiple Sclerosis},
keywords = {Middle Studies, Aged, Processing, Female, Male, Evaluation, Imaging, Adult, Multiple Resonance 14760947 Automation, Non-U.S. Support, Anisotropy, Disability Cohort Diffusion Algorithms, Brain, of Image Results, Computer-Assisted, Sclerosis, Research Gov't, Case-Control Relapsing-Remitting, Magnetic Reproducibility Humans,},
month = Feb,
number = 1,
owner = {bzfbmeye},
pages = {9--15},
pmid = {14760947},
timestamp = {2007-01-10T11:32:01.000+0100},
title = {Diffusion tensor imaging of early relapsing-remitting multiple sclerosis
with histogram analysis using automated segmentation and brain volume
correction.},
volume = 10,
year = 2004
}