Document Detail


Multivariate pattern classification of gray matter pathology in multiple sclerosis.
MedLine Citation:
PMID:  22245259     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Univariate analyses have identified gray matter (GM) alterations in different groups of MS patients. While these methods detect differences on the basis of the single voxel or cluster, multivariate methods like support vector machines (SVM) identify the complex neuroanatomical patterns of GM differences. Using multivariate linear SVM analysis and leave-one-out cross-validation, we aimed at identifying neuroanatomical GM patterns relevant for individual classification of MS patients. We used SVM to separate GM segmentations of T1-weighted three-dimensional magnetic resonance (MR) imaging scans within different age- and sex-matched groups of MS patients with either early (n=17) or late MS (n=17) (contrast I), low (n=20) or high (n=20) white matter lesion load (contrast II), and benign MS (BMS, n=13) or non-benign MS (NBMS, n=13) (contrast III) scanned on a single 1.5T MR scanner. GM patterns most relevant for individual separation of MS patients comprised cortical areas of all the cerebral lobes as well as deep GM structures, including the thalamus and caudate. The patterns detected were sufficiently informative to separate individuals of the respective groups with high sensitivity and specificity in 85% (contrast I), 83% (contrast II) and 77% (contrast III) of cases. The study demonstrates that neuroanatomical spatial patterns of GM segmentations contain information sufficient for correct classification of MS patients at the single case level, thus making multivariate SVM analysis a promising clinical application.
Authors:
Kerstin Bendfeldt; Stefan Klöppel; Thomas E Nichols; Renata Smieskova; Pascal Kuster; Stefan Traud; Nicole Mueller-Lenke; Yvonne Naegelin; Ludwig Kappos; Ernst-Wilhelm Radue; Stefan J Borgwardt
Related Documents :
19994499 - Neurotransmission spect and mr registration combining mutual and gradient information.
22210599 - Disaster victim identification-experiences of the "autobahn a19" disaster.
17272049 - Modeling susceptibility difference artifacts produced by metallic implants in magnetic ...
21913989 - Brain magnetic resonance angiography in splenectomized adults with β thalassemia inter...
22146869 - Whole-body mri in neurofibromatosis: incidental findings and prevalence of scoliosis.
8327799 - Modifications of the compass stereotactic magnetic resonance localizer: technical note.
15994059 - Transient left paraduodenal hernia.
10541039 - Identification of microtubule-organizing centers in interphase melanophores of xenopus ...
7769939 - Preoperative identification of benign versus malignant parotid masses: a comparative st...
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-1-5
Journal Detail:
Title:  NeuroImage     Volume:  -     ISSN:  1095-9572     ISO Abbreviation:  -     Publication Date:  2012 Jan 
Date Detail:
Created Date:  2012-1-16     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9215515     Medline TA:  Neuroimage     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011. Published by Elsevier Inc.
Affiliation:
Medical Image Analysis Center (MIAC), University Hospital Basel, CH-4031 Basel, Switzerland.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Magnetic nanocomposite of anti-human IgG/COOH-multiwalled carbon nanotubes/Fe(3)O(4) as a platform f...
Next Document:  A reliable protocol for the manual segmentation of the human amygdala and its subregions using ultra...