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Neurological Sciences

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26.06.2019 | Original Article

Diffusion tensor imaging reveals abnormal brain networks in elderly subjects with subjective cognitive deficits

verfasst von: Daegyeom Kim, Suji Lee, Myungwon Choi, HyunChul Youn, Sangil Suh, Hyun-Ghang Jeong, Cheol E. Han

Erschienen in: Neurological Sciences | Ausgabe 11/2019

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Abstract

Purpose

Some elders with subjective cognitive deficits (SCD) develop prodromal phase of dementia over time; however, little is known about how they differ from those with normal cognition (NC). Thus, we aim to distinguish the differences in the brain network of elders with SCD and NC.

Methods

Multiple diffusion-weighted images (DWI) and T1-weighted images were obtained from 18 subjects with NC and 26 subjects with SCD. Using network-based statistics (NBS) analysis, we extracted abnormal brain subnetworks and localized abnormal brain connectivity. We also ran correlation analysis to compare the affected regions and the results of the neurocognitive assessments.

Results

Altered subnetworks were found in the superior parietal gyrus, angular gyrus, precuneus, posterior cingulum, putamen, precentral gyrus, postcentral gyrus, and paracentral lobule. They were also associated with scores on the word list recall, word list recognition, and Boston naming test.

Conclusions

Elders with SCD had distinctive brain network alterations when compared with those of elders with NC. The results are also in line with the previously identified characteristics of mild cognitive impairment (MCI) and of Alzheimer’s disease (AD) in a milder form. We speculate that it may be possible to predict AD progression early in the SCD stage using NBS analysis.

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Titel: Diffusion tensor imaging reveals abnormal brain networks in elderly subjects with subjective cognitive deficits
verfasst von: Daegyeom Kim
Suji Lee
Myungwon Choi
HyunChul Youn
Sangil Suh
Hyun-Ghang Jeong
Cheol E. Han
Publikationsdatum: 26.06.2019
Verlag: Springer International Publishing
Erschienen in: Neurological Sciences / Ausgabe 11/2019
Print ISSN: 1590-1874
Elektronische ISSN: 1590-3478
DOI: https://doi.org/10.1007/s10072-019-03981-6

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