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http://hdl.handle.net/2445/181941
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DC Field | Value | Language |
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dc.contributor.author | Campabadal, Anna | - |
dc.contributor.author | Abós, Alexandra | - |
dc.contributor.author | Segura i Fàbregas, Bàrbara | - |
dc.contributor.author | Monte Rubio, Gemma | - |
dc.contributor.author | Pérez Soriano, Alexandra | - |
dc.contributor.author | Giraldo, Darly M. | - |
dc.contributor.author | Muñoz, Esteban | - |
dc.contributor.author | Compta, Yaroslau | - |
dc.contributor.author | Junqué i Plaja, Carme, 1955- | - |
dc.contributor.author | Martí Domènech, Ma. Josep | - |
dc.date.accessioned | 2021-12-21T17:50:10Z | - |
dc.date.available | 2021-12-21T17:50:10Z | - |
dc.date.issued | 2021-09-10 | - |
dc.identifier.issn | 1051-2284 | - |
dc.identifier.uri | http://hdl.handle.net/2445/181941 | - |
dc.description.abstract | Background and purpose: Multiple system atrophy(MSA) is a rare adult-onset synucleinopathy that can be divided in two subtypes depending on whether the prevalence of its symptoms is more parkinsonian or cerebellar (MSA-P and MSA-C, respectively). The aim of this work is to investigate the structural MRI changes able to discriminate MSA phenotypes. Methods: The sample includes 31 MSA patients (15 MSA-C and 16 MSA-P) and 39 healthy controls. Participants underwent a comprehensive motor and neuropsychological battery. MRI data were acquired with a 3T scanner (MAGNETOM Trio, Siemens, Germany). FreeSurfer was used to obtain volumetric and cortical thickness measures. A Support Vector Machine (SVM) algorithm was used to assess the classification between patients' group using cortical and subcortical structural data. Results: After correction for multiple comparisons, MSA-C patients had greater atrophy than MSA-P in the left cerebellum, whereas MSA-P showed reduced volume bilaterally in the pallidum and putamen. Using deep gray matter volume ratios and mean cortical thickness as features, the SVM algorithm provided a consistent classification between MSA-C and MSA-P patients (balanced accuracy 74.2%, specificity 75.0%, and sensitivity 73.3%). The cerebellum, putamen, thalamus, ventral diencephalon, pallidum, and caudate were the most contributing features to the classification decision (z > 3.28; p < .05 [false discovery rate]). Conclusions: MSA-C and MSA-P with similar disease severity and duration have a differential distribution of gray matter atrophy. Although cerebellar atrophy is a clear differentiator between groups, thalamic and basal ganglia structures are also relevant contributors to distinguishing MSA subtypes. Keywords: cognition; cortical thickness; machine learning; multiple system atrophy; neuroimaging. | - |
dc.format.extent | 10 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Wiley | - |
dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.1111/jon.12927 | - |
dc.relation.ispartof | Journal of Neuroimaging, 2021 | - |
dc.relation.uri | https://doi.org/10.1111/jon.12927 | - |
dc.rights | cc by-nc-nd (c) Campabadal, Anna et al., 2021 | - |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.source | Articles publicats en revistes (Medicina) | - |
dc.subject.classification | Cognició | - |
dc.subject.classification | Atròfia muscular | - |
dc.subject.other | Cognition | - |
dc.subject.other | Muscular atrophy | - |
dc.title | Differentiation of multiple system atrophy subtypes by gray matter atrophy | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 714870 | - |
dc.date.updated | 2021-12-21T17:50:10Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
Appears in Collections: | Articles publicats en revistes (Medicina) Articles publicats en revistes (Institut de Neurociències (UBNeuro)) Articles publicats en revistes (IDIBAPS: Institut d'investigacions Biomèdiques August Pi i Sunyer) |
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714870.pdf | 3.01 MB | Adobe PDF | View/Open |
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