Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning
Yükleniyor...
Tarih
2022-12
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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.
Açıklama
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.
Anahtar Kelimeler
Cognitive dysfunction, Machine learning, Magnetic resonance spectroscopy, Parkinson’s disease, Posterior cingulate cortex, Nondemented patients, Diagnostic criteria, Dementia, Movement, Connectivity, Networks, Hypoperfusion, Associations, Robust, Creatine, N Acetylaspartic acid, Cognitive dysfunction
Kaynak
Magnetic Resonance Materials in Physics, Biology and Medicine
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
35
Sayı
6
Künye
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
