Background: Mild Cognitive Impairment (MCI) is a clinical state between normal aging and dementia. It may involve impairment in one or several cognitive domains. MCI offers a key window for maintaining cognitive function and studying how deficits develop in the elderly, making it of great research value. Measurement tools for screening MCI are not yet standardized in China. The accuracy of diagnostic criteria and threshold values needs improvement. Previous studies on the neural mechanisms of MCI have examined various aspects, but the changes in the white matter microstructure in older adults with MCI remain unclear. Most past studies used Fractional Anisotropy (FA) analysis to examine changes in white matter fiber orientation, often ignoring fiber density. As a result, findings are often contradictory or difficult to interpret. Therefore, it is necessary to assess cognitive function in MCI populations using more comprehensive and standardized measurement tools. It is also important to explore the association between changes in white matter microstructure and cognitive function in MCI by analyzing FA and Mean Diffusivity (MD).
Methods: First, we assessed cognitive function using the Cognitive Function Measurement Scale for the Elderly, developed by Beijing Normal University, with diagnoses based on the NIA-AA (National Institute on Aging—Alzheimer’s Association) criteria. Second, we employed Diffusion Tensor Imaging (DTI) combined with Tract-Based Spatial Statistics (TBSS) to investigate alterations in the white matter fiber tract integrity in individuals with MCI. Based on the metrics used, this study was divided into two analytical approaches: Analysis Mode 1 utilized FA to explore changes in white matter fiber orientation in the MCI group. Analysis Mode 2 utilized MD to examine changes in white matter fiber density in the MCI group. Third, we further explored the association between alterations in the white matter fiber tract integrity and cognitive function in individuals with MCI. Specifically, FA and MD values from brain regions showing significant differences between the MCI and normal control groups were extracted and correlated with cognitive test scores.
Results: According to the results of the community measurement survey, the prevalence of MCI among the elderly in Shenzhen is approximately 21.54%. Individuals with MCI exhibited functional decline in memory, attention, language, executive function, and spatial processing. DTI results indicated that (1) FA values across the brain’s white matter fiber tracts showed a decreasing trend in the elderly with MCI, with no areas exhibiting significantly higher FA values. Specifically, FA values were significantly lower in the corpus callosum, internal capsule, corona radiata, thalamic radiation, external capsule, superior fronto-occipital fasciculus, and cingulum (cingulate gyrus). (2) White matter fiber tracts with significantly reduced FA values also demonstrated significantly increased MD values. Additionally, MD values in the cingulum (hippocampus), inferior cerebellar peduncle, and corticospinal tract were significantly reduced in the MCI group. (3) Correlation analysis revealed that the significant differences in FA and MD values within the white matter fiber tracts of older adults with MCI were correlated with scores on several cognitive tests.
Conclusions: In the present study, older adults with MCI tended to exhibit functional decline across multiple cognitive domains and relatively extensive microstructural white matter damage. Observations suggested that white matter fiber density may be informative regarding these microstructural alterations, indicating that diffusion biomarkers in key regions such as the cingulum (hippocampus) warrant further investigation.
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