Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
1997-7-18
pubmed:abstractText
Magnetic resonance spectroscopy can image axonal damage specifically based on changes in N-acetyl aspartate (NAA), a neuronal marker. We have developed statistical methods for multimodal analysis of MR spectroscopic images. These methods, which are extensions of mixed-effect models, have allowed us to quantify differences in images from different subgroups of patients with multiple sclerosis (MS) and to determine the dependence of chemical pathology on clinical disability, duration of disease and lesions on T2-weighted MRI. Statistical power was improved by using all reliable resonance intensities in the spectroscopic images while taking into consideration the intra-subject correlations. We studied 17 normal subjects, 14 patients with relapsing remitting (RR) MS and 21 patients with chronic progressive (CP) MS. The ratio of resonance intensities of N-acetylaspartate over creatine (Cr) was found to be significantly lower than normal in normal appearing white matter (NAWM) of both RR and CP patients (19.6% in RR, 28.8% in CP), NAA/Cr was decreased even more in MS plaques than in NAWM (44.2% in RR, 17.7% in CP), NAA/Cr was correlated with clinical disability (p < 0.02) and disease duration (p < 0.1). Our results suggest that, in this setting, MRS reflects accumulated neuronal loss or damage and can be used as a measure of disease severity. The methods developed provide opportunities to evaluate the relationship between inflammation, demyelination, axonal loss and clinical disability in future studies.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0952-3480
pubmed:author
pubmed:issnType
Print
pubmed:volume
9
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
339-46
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
Statistics for investigation of multimodal MR imaging data and an application to multiple sclerosis patients.
pubmed:affiliation
Montreal Neurological Institute, McGill University, Quebec, Canada.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't