dc.contributor.author | Cengiz, Sevim | en_US |
dc.contributor.author | Arslan, Dilek Betül | en_US |
dc.contributor.author | Kıçik, Ani | en_US |
dc.contributor.author | Erdoğdu, Emel | en_US |
dc.contributor.author | Yıldırım, Muhammed | en_US |
dc.contributor.author | Hatay, Gökçe Hale | en_US |
dc.contributor.author | Tüfekçioğlu, Zeynep | en_US |
dc.contributor.author | Uluğ, Aziz Müfit | en_US |
dc.contributor.author | Bilgiç, Başar | en_US |
dc.contributor.author | Hanagasi, Haşmet | en_US |
dc.contributor.author | Demiralp, Tamer | en_US |
dc.contributor.author | Gürvit, Hakan | en_US |
dc.date.accessioned | 2022-08-31T08:36:56Z | |
dc.date.available | 2022-08-31T08:36:56Z | |
dc.date.issued | 2022-12 | |
dc.identifier.citation | Cengiz, S., Arslan, D. B., Kıçik, A., Erdoğdu, E., Yıldırım, M., Hatay, G. H., Tüfekçioğlu, Z., Uluğ, A. M., Bilgiç, B., Hanagasi, H., Demiralp, T. & Gürvit, H. (2022). Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning. Magnetic Resonance Materials in Physics, Biology and Medicine, 35(6), 997-1008. doi:10.1007/s10334-022-01030-6 | en_US |
dc.identifier.issn | 1352-8661 | |
dc.identifier.issn | 0968-5243 | |
dc.identifier.uri | https://hdl.handle.net/11729/4804 | |
dc.identifier.uri | http://dx.doi.org/10.1007/s10334-022-01030-6 | |
dc.description | This study was funded by The Scientific and Technological Research Council of Turkey (TUBITAK) 1001 Grant #115S219 and Istanbul University Scientific Research Projects Unit project #1567/42362. | en_US |
dc.description.abstract | Objective: To investigate metabolic changes of mild cognitive impairment in Parkinson’s disease (PD-MCI) using proton magnetic resonance spectroscopic imaging (1H-MRSI). Methods: Sixteen healthy controls (HC), 26 cognitively normal Parkinson’s disease (PD-CN) patients, and 34 PD-MCI patients were scanned in this prospective study. Neuropsychological tests were performed, and three-dimensional 1H-MRSI was obtained at 3 T. Metabolic parameters and neuropsychological test scores were compared between PD-MCI, PD-CN, and HC. The correlations between neuropsychological test scores and metabolic intensities were also assessed. Supervised machine learning algorithms were applied to classify HC, PD-CN, and PD-MCI groups based on metabolite levels. Results: PD-MCI had a lower corrected total N-acetylaspartate over total creatine ratio (tNAA/tCr) in the right precentral gyrus, corresponding to the sensorimotor network (p = 0.01), and a lower tNAA over myoinositol ratio (tNAA/mI) at a part of the default mode network, corresponding to the retrosplenial cortex (p = 0.04) than PD-CN. The HC and PD-MCI patients were classified with an accuracy of 86.4% (sensitivity = 72.7% and specificity = 81.8%) using bagged trees. Conclusion: 1H-MRSI revealed metabolic changes in the default mode, ventral attention/salience, and sensorimotor networks of PD-MCI patients, which could be summarized mainly as ‘posterior cortical metabolic changes’ related with cognitive dysfunction. | en_US |
dc.description.sponsorship | Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) | en_US |
dc.description.sponsorship | Istanbul University | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer Science and Business Media Deutschland GmbH | en_US |
dc.relation.isversionof | 10.1007/s10334-022-01030-6 | |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Cognitive dysfunction | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Magnetic resonance spectroscopy | en_US |
dc.subject | Parkinson’s disease | en_US |
dc.subject | Posterior cingulate cortex | en_US |
dc.subject | Nondemented patients | en_US |
dc.subject | Diagnostic criteria | en_US |
dc.subject | Dementia | en_US |
dc.subject | Movement | en_US |
dc.subject | Connectivity | en_US |
dc.subject | Networks | en_US |
dc.subject | Hypoperfusion | en_US |
dc.subject | Associations | en_US |
dc.subject | Robust | en_US |
dc.subject | Creatine | en_US |
dc.subject | N Acetylaspartic acid | en_US |
dc.subject | Cognitive dysfunction | en_US |
dc.title | Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning | en_US |
dc.type | article | en_US |
dc.description.version | Publisher's Version | en_US |
dc.relation.journal | Magnetic Resonance Materials in Physics, Biology and Medicine | en_US |
dc.contributor.department | Işık Üniversitesi, İktisadi, İdari ve Sosyal Bilimler Fakültesi, Psikoloji Bölümü | en_US |
dc.contributor.department | Işık Üniversitesi, Faculty Of Economics, Administrative And Social Sciences, Psychology Department | en_US |
dc.contributor.authorID | 0000-0002-2817-5596 | |
dc.identifier.volume | 35 | |
dc.identifier.issue | 6 | |
dc.identifier.startpage | 997 | |
dc.identifier.endpage | 1008 | |
dc.peerreviewed | Yes | en_US |
dc.publicationstatus | Published | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.contributor.institutionauthor | Erdoğdu, Emel | en_US |
dc.relation.index | WOS | en_US |
dc.relation.index | Scopus | en_US |
dc.relation.index | PubMed | en_US |
dc.relation.index | Science Citation Index Expanded (SCI-EXPANDED) | en_US |
dc.description.quality | Q3 | |
dc.description.wosid | WOS:000828927500002 | |
dc.description.pubmedid | PMID:35867235 | |