Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Dec;35(6):997-1008.
doi: 10.1007/s10334-022-01030-6. Epub 2022 Jul 22.

Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning

Sevim Cengiz  1 , Dilek Betul Arslan  1 , Ani Kicik  2   3 , Emel Erdogdu  2   4 , Muhammed Yildirim  1 , Gokce Hale Hatay  1 , Zeynep Tufekcioglu  5   6 , Aziz Müfit Uluğ  1   7 , Basar Bilgic  5 , Hasmet Hanagasi  5 , Tamer Demiralp  2   8 , Hakan Gurvit #  5 , Esin Ozturk-Isik #  9
Affiliations

Identification of metabolic correlates of mild cognitive impairment in Parkinson's disease using magnetic resonance spectroscopic imaging and machine learning

Sevim Cengiz et al. MAGMA. 2022 Dec.

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.

Keywords: Cognitive dysfunction; Machine learning; Magnetic resonance spectroscopy; Parkinson’s disease.

PubMed Disclaimer

Similar articles

See all similar articles

Cited by

References

    1. Dorsey ER, Constantinescu R, Thompson JP, Biglan KM, Holloway RG, Kieburtz K, Marshall FJ, Ravina BM, Schifitto G, Siderowf A, Tanner CM (2007) Projected number of people with Parkinson disease in the most populous nations, 2005 through 2030. Neurology 68:384–386 - PubMed
    1. Angel RW, Alston W, Higgins JR (1970) Control of movement in Parkinson’s disease. Brain 93:1–14 - PubMed
    1. Schapira AHV, Chaudhuri KR, Jenner P (2017) Non-motor features of Parkinson disease. Nat Rev Neurosci 18:509 - PubMed
    1. Litvan I, Aarsland D, Adler CH, Goldman JG, Kulisevsky J, Mollenhauer B, Rodriguez-Oroz MC, Troster AI, Weintraub D (2011) MDS task force on mild cognitive impairment in Parkinson’s disease: critical review of PD-MCI. Mov Disord 26:1814–1824 - PubMed - PMC
    1. Aarsland D, Kurz MW (2010) The epidemiology of dementia associated with Parkinson’s disease. Brain Pathol 20:633–639 - PubMed - PMC

LinkOut - more resources