Individual voxel‐based subtype prediction can differentiate progressive supranuclear palsy from idiopathic parkinson syndrome and healthy controls
Identifieur interne : 000286 ( Main/Exploration ); précédent : 000285; suivant : 000287Individual voxel‐based subtype prediction can differentiate progressive supranuclear palsy from idiopathic parkinson syndrome and healthy controls
Auteurs : Niels K. Focke [Allemagne] ; Gunther Helms [Allemagne] ; Sebstian Scheewe [Allemagne] ; Pia M. Pantel [Allemagne] ; Cornelius G. Bachmann [Allemagne] ; Peter Dechent [Allemagne] ; Jens Ebentheuer [Allemagne] ; Alexander Mohr [Allemagne] ; Walter Paulus [Allemagne] ; Claudia Trenkwalder [Allemagne]Source :
- Human Brain Mapping [ 1065-9471 ] ; 2011-11.
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Abstract
Voxel‐based morphometry (VBM) shows a differentiated pattern in patients with atypical Parkinson syndrome but so far has had little impact in individual cases. It is desirable to translate VBM findings into clinical practice and individual classification. To this end, we examined whether a support vector machine (SVM) can provide useful accuracies for the differential diagnosis. We acquired a volumetric 3D T1‐weighted MRI of 21 patients with idiopathic Parkinson syndrome (IPS), 11 multiple systems atrophy (MSA‐P) and 10 progressive supranuclear palsy (PSP), and 22 healthy controls. Images were segmented, normalized, and compared at group level with SPM8 in a classical VBM design. Next, a SVM analysis was performed on an individual basis with leave‐one‐out cross‐validation. VBM showed a strong white matter loss in the mesencephalon of patients with PSP, a putaminal grey matter loss in MSA, and a cerebellar grey matter loss in patients with PSP compared with IPS. The SVM allowed for an individual classification in PSP versus IPS with up to 96.8% accuracy with 90% sensitivity and 100% specificity. In MSA versus IPS, an accuracy of 71.9% was achieved; sensitivity, however, was low with 36.4%. Patients with IPS could not be differentiated from controls. In summary, a voxel‐based SVM analysis allows for a reliable classification of individual cases in PSP that can be directly clinically useful. For patients with MSA and IPS, further developments like quantitative MRI are needed. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc.
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DOI: 10.1002/hbm.21161
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Brain Mapp.</title><idno type="ISSN">1065-9471</idno><idno type="eISSN">1097-0193</idno><imprint><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><pubPlace>Hoboken</pubPlace><date type="published" when="2011-11">2011-11</date><biblScope unit="volume">32</biblScope><biblScope unit="issue">11</biblScope><biblScope unit="page" from="1905">1905</biblScope><biblScope unit="page" to="1915">1915</biblScope></imprint><idno type="ISSN">1065-9471</idno></series><idno type="istex">80ACABBF0B0CBB9C8EEFAC707DA53A4CAE32E4F5</idno><idno type="DOI">10.1002/hbm.21161</idno><idno type="ArticleID">HBM21161</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1065-9471</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Parkinson syndrome, progressive supranuclear palsy</term><term>individual classification</term><term>multiple systems atrophy</term><term>support vector machine</term><term>voxel‐based morphometry</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Voxel‐based morphometry (VBM) shows a differentiated pattern in patients with atypical Parkinson syndrome but so far has had little impact in individual cases. 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In MSA versus IPS, an accuracy of 71.9% was achieved; sensitivity, however, was low with 36.4%. Patients with IPS could not be differentiated from controls. In summary, a voxel‐based SVM analysis allows for a reliable classification of individual cases in PSP that can be directly clinically useful. For patients with MSA and IPS, further developments like quantitative MRI are needed. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc.</div></front></TEI><affiliations><list><country><li>Allemagne</li></country><region><li>Basse-Saxe</li><li>District de Kassel</li><li>Hesse (Land)</li></region><settlement><li>Cassel (Hesse)</li><li>Göttingen</li></settlement></list><tree><country name="Allemagne"><region name="Basse-Saxe"><name sortKey="Focke, Niels K" sort="Focke, Niels K" uniqKey="Focke N" first="Niels K." last="Focke">Niels K. Focke</name></region><name sortKey="Bachmann, Cornelius G" sort="Bachmann, Cornelius G" uniqKey="Bachmann C" first="Cornelius G." last="Bachmann">Cornelius G. Bachmann</name><name sortKey="Dechent, Peter" sort="Dechent, Peter" uniqKey="Dechent P" first="Peter" last="Dechent">Peter Dechent</name><name sortKey="Ebentheuer, Jens" sort="Ebentheuer, Jens" uniqKey="Ebentheuer J" first="Jens" last="Ebentheuer">Jens Ebentheuer</name><name sortKey="Helms, Gunther" sort="Helms, Gunther" uniqKey="Helms G" first="Gunther" last="Helms">Gunther Helms</name><name sortKey="Mohr, Alexander" sort="Mohr, Alexander" uniqKey="Mohr A" first="Alexander" last="Mohr">Alexander Mohr</name><name sortKey="Pantel, Pia M" sort="Pantel, Pia M" uniqKey="Pantel P" first="Pia M." last="Pantel">Pia M. Pantel</name><name sortKey="Paulus, Walter" sort="Paulus, Walter" uniqKey="Paulus W" first="Walter" last="Paulus">Walter Paulus</name><name sortKey="Scheewe, Sebstian" sort="Scheewe, Sebstian" uniqKey="Scheewe S" first="Sebstian" last="Scheewe">Sebstian Scheewe</name><name sortKey="Trenkwalder, Claudia" sort="Trenkwalder, Claudia" uniqKey="Trenkwalder C" first="Claudia" last="Trenkwalder">Claudia Trenkwalder</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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