Hakan Gurvit1, Esin Ozturk-Isik2, Sevim Cengiz3, Dilek Betul Arslan3, Ani Kicik4,5, Emel Erdogdu4,6, Muhammed Yildirim3, Gokce Hale Hatay3, Zeynep Tufekcioglu1,7, Aziz Müfit Uluğ3,8, Basar Bilgic1, Hasmet Hanagasi1, Tamer Demiralp4,9. 1. Behavioral Neurology and Movement Disorders Unit, Department of Neurology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey. 2. Institute of Biomedical Engineering, Bogazici University, 34684, Istanbul, Turkey. esin.ozturk@boun.edu.tr. 3. Institute of Biomedical Engineering, Bogazici University, 34684, Istanbul, Turkey. 4. Neuroimaging Unit, Hulusi Behcet Life Sciences Research Center, Istanbul University, Istanbul, Turkey. 5. Department of Physiology, Faculty of Medicine, Demiroglu Bilim University, Istanbul, Turkey. 6. Department of Psychology, Faculty of Economics and Administrative Sciences, Isik University, Istanbul, Turkey. 7. Department of Neurology, Faculty of Medicine, Istanbul Aydin University, Istanbul, Turkey. 8. CorTechs Labs, San Diego, CA, USA. 9. Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey.
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.
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.
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