guest ::
| Home > Publications database > Individual prediction of chronic motor outcome in the acute post-stroke stage: Behavioral parameters versus functional imaging > print |
| Home > Publications database > Individual prediction of chronic motor outcome in the acute post-stroke stage: Behavioral parameters versus functional imaging > print |
| 001 | 203085 | ||
| 005 | 20210129220259.0 | ||
| 024 | 7 | _ | |a 10.1002/hbm.22936 |2 doi |
| 024 | 7 | _ | |a 1065-9471 |2 ISSN |
| 024 | 7 | _ | |a 1097-0193 |2 ISSN |
| 024 | 7 | _ | |a WOS:000364219500023 |2 WOS |
| 024 | 7 | _ | |a altmetric:4415603 |2 altmetric |
| 024 | 7 | _ | |a pmid:26381168 |2 pmid |
| 037 | _ | _ | |a FZJ-2015-05120 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Rehme, Anne |0 P:(DE-Juel1)165784 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Individual prediction of chronic motor outcome in the acute post-stroke stage: Behavioral parameters versus functional imaging |
| 260 | _ | _ | |a New York, NY |c 2015 |b Wiley-Liss |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1449221956_29476 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a article |2 DRIVER |
| 520 | _ | _ | |a Several neurobiological factors have been found to correlate with functional recovery after brain lesions. However, predicting the individual potential of recovery remains difficult. Here we used multivariate support vector machine (SVM) classification to explore the prognostic value of functional magnetic resonance imaging (fMRI) to predict individual motor outcome at 4–6 months post-stroke. To this end, 21 first-ever stroke patients with hand motor deficits participated in an fMRI hand motor task in the first few days post-stroke. Motor impairment was quantified assessing grip force and the Action Research Arm Test. Linear SVM classifiers were trained to predict good versus poor motor outcome of unseen new patients. We found that fMRI activity acquired in the first week post-stroke correctly predicted the outcome for 86% of all patients. In contrast, the concurrent assessment of motor function provided 76% accuracy with low sensitivity (<60%). Furthermore, the outcome of patients with initially moderate impairment and high outcome variability could not be predicted based on motor tests. In contrast, fMRI provided 87.5% prediction accuracy in these patients. Classifications were driven by activity in ipsilesional motor areas and contralesional cerebellum. The accuracy of subacute fMRI data (two weeks post-stroke), age, time post-stroke, lesion volume, and location were at 50%-chance-level. In conclusion, multivariate decoding of fMRI data with SVM early after stroke enables a robust prediction of motor recovery. The potential for recovery is influenced by the initial dysfunction of the active motor system, particularly in those patients whose outcome cannot be predicted by behavioral tests. |
| 536 | _ | _ | |a 572 - (Dys-)function and Plasticity (POF3-572) |0 G:(DE-HGF)POF3-572 |c POF3-572 |f POF III |x 0 |
| 536 | _ | _ | |a 573 - Neuroimaging (POF3-573) |0 G:(DE-HGF)POF3-573 |c POF3-573 |f POF III |x 1 |
| 536 | _ | _ | |a HBP - The Human Brain Project (604102) |0 G:(EU-Grant)604102 |c 604102 |f FP7-ICT-2013-FET-F |x 2 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Volz, L. |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Feis, D. L. |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Eickhoff, Simon |0 P:(DE-Juel1)131678 |b 3 |
| 700 | 1 | _ | |a Fink, Gereon Rudolf |0 P:(DE-Juel1)131720 |b 4 |
| 700 | 1 | _ | |a Grefkes, Christian |0 P:(DE-Juel1)161406 |b 5 |
| 773 | _ | _ | |a 10.1002/hbm.22936 |0 PERI:(DE-600)1492703-2 |n 11 |p 4553-4565 |t Human brain mapping |v 36 |y 2015 |x 1065-9471 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/203085/files/Rehme_et_al-2015-Human_Brain_Mapping.pdf |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/203085/files/Rehme_et_al-2015-Human_Brain_Mapping.gif?subformat=icon |x icon |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/203085/files/Rehme_et_al-2015-Human_Brain_Mapping.jpg?subformat=icon-1440 |x icon-1440 |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/203085/files/Rehme_et_al-2015-Human_Brain_Mapping.jpg?subformat=icon-180 |x icon-180 |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/203085/files/Rehme_et_al-2015-Human_Brain_Mapping.jpg?subformat=icon-640 |x icon-640 |y Restricted |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/203085/files/Rehme_et_al-2015-Human_Brain_Mapping.pdf?subformat=pdfa |x pdfa |y Restricted |
| 909 | C | O | |o oai:juser.fz-juelich.de:203085 |p openaire |p VDB |p ec_fundedresources |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)165784 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)131678 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)131720 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)161406 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-572 |2 G:(DE-HGF)POF3-500 |v (Dys-)function and Plasticity |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-573 |2 G:(DE-HGF)POF3-500 |v Neuroimaging |x 1 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2015 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b HUM BRAIN MAPP : 2013 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Thomson Reuters Master Journal List |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b HUM BRAIN MAPP : 2013 |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-3-20090406 |k INM-3 |l Kognitive Neurowissenschaften |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-1-20090406 |k INM-1 |l Strukturelle und funktionelle Organisation des Gehirns |x 1 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)INM-3-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-1-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
| 981 | _ | _ | |a I:(DE-Juel1)INM-1-20090406 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|