• Laust Vind Knudsen, Parisa Gazerani, Yunyun Duan, Tanja Maria Michel, and VafaeeManouchehr SeyediMShttps://orcid.org/0000-0001-8409-7142Research Unit for Psychiatry, Odense University Hospital, Odense, Denmark..
• Research Unit for Psychiatry, Odense University Hospital, Odense, Denmark.
• J Neuroimaging. 2022 Jan 1; 32 (1): 148-157.

Background And PurposeMild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD), where neurodegeneration is not as considerable, thereby potentially increasing the effect of treatments. Therefore, highly sensitive and specific classification of subjects with MCI is necessary, where various MRI modalities have displayed promise.MethodsStructural, diffusion, and resting-state (RS) functional MRI analyses were performed on the AD (n = 26), MCI (n = 5), and healthy control (HC) (n = 14) group. Structural analysis was performed via voxel-based morphometry (VBM) and volumetric subcortical segmentation analysis. Fractional anisotropy and mean diffusivity were estimated during the diffusion analysis. RS analysis investigated seed-based functional connectivity. Classification via support vector machine was performed to evaluate which MRI modality most accurately differentiated the groups. Multiple linear regression was conducted to evaluate the MRI modalities correlation with clinical assessment scores.ResultsClassification of MCI and HC displayed highest accuracy based on diffusion MRI, which besides demonstrated high correlation with clinical scores. Classification was equally accurate in AD, when using VBM or diffusion tensor imaging measures. Yet, more variance was explained by VBM measures in the clinical assessment scores of the AD group.ConclusionsThis study highlights the potential of diffusion MRI in differentiating MCI from HC and AD. However, the results need to be interpreted with caution as sample size and artifacts in the MRI data probably influenced the results.© 2021 American Society of Neuroimaging.

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