Cited by 49Dementia and Cognitive Impairment ResearchAdvanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity Studies

What can DTI tell about early cognitive impairment?—Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging

Gyebnár, Gyula, Szabó, Ádám, Sirály, Enikő, Fodor, Zsuzsanna, Sákovics, Anna, Salacz, Pál, Hidasi, Zoltán, Csibri, Éva +3 more·2018·Psychiatry Research: Neuroimaging

Abstract

Mild cognitive impairment (MCI) gained a lot of interest recently, especially that the conversion rate to Alzheimer Disease (AD) in the amnestic subtype (aMCI) is higher than in the non-amnestic subtype (naMCI). We aimed to determine whether and how diffusion-weighted MRI (DWI) using the diffusion tensor model (DTI) can differentiate MCI subtypes from healthy subjects. High resolution 3D T1W and DWI images of patients (aMCI, n = 18; naMCI, n = 20; according to Petersen criteria) and controls (n = 27) were acquired at 3T and processed using ExploreDTI and SPM. Voxel-wise and region of interest (ROI) analyses of fractional anisotropy (FA) and mean diffusivity (MD) were performed with ANCOVA; MD was higher in aMCI compared to controls or naMCI in several grey and white matter (GM, WM) regions (especially in the temporal pole and the inferior temporal lobes), while FA was lower in WM ROI-s (e.g. left Cingulum). Moreover, significant correlations were identified between verbal fluency, visual and verbal memory performance and DTI metrics. Logistic regression showed that measuring FA of the crus of fornix along GM volumetry improves the discrimination of aMCI from naMCI. Additional information from DWI/DTI aids preclinical detection of AD and may help detecting early non-Alzheimer type dementia, too.

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Crossref · 10.1016/j.pscychresns.2017.10.007

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Authors
Gyebnár, G., Szabó, Á., Sirály, E., Fodor, Z., Sákovics, A., Salacz, P., Hidasi, Z., Csibri, É., Rudas, G., Kozák, L. R., & Csukly, G.
Affiliations
  • Semmelweis University (HU)
  • Országos Idegsebészeti Tudományos Intézet (HU)
Corresponding author
Gyebnár, Gyula
Venue
Psychiatry Research: Neuroimaging
Publisher
Elsevier BV
Published
2018-02
Volume
272
Pages
46-57
ISSN
0925-4927 (ISSN-L)
OpenAlex
W2766651361
Cited by
49
References
9
Citations by year
2026: 1 · 2025: 4 · 2024: 3 · 2023: 5 · 2022: 8 · 2021: 6 · 2020: 14 · 2019: 5 · 2018: 3
FWCI
4.90
Type
journal article
Language
en
Open access
closed
Locations
  • Psychiatry Research Neuroimaging (publishedVersion)
  • PubMed (publishedVersion)
  • Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
  • Semmelweis University Repository (Semmelweis University) (submittedVersion)
Funders
  • Hungarian Scientific Research Fund (PD 115837)
  • Magyar Tudományos Akadémia
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords
mild cognitive impairment, amnestic MCI, non-amnestic MCI, diffusion tensor imaging, fractional anisotropy, mean diffusivity, Alzheimer's disease, preclinical detection, temporal pole, white matter, grey matter, memory performance
MeSH terms
Aged, Alzheimer Disease, Amnesia, Diagnosis, Differential, Female, Humans, Male, Memory, Middle Aged, Case-Control Studies, Anisotropy, Diffusion Tensor Imaging, Cognitive Dysfunction, White Matter

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