AUTHOR=Zhao Xinle , You Mengyue , Ren Wenyu , Ji Lixin , Liu Yongbo , Lu Meng 

TITLE=The application of diffusion tensor imaging in patients with mild cognitive impairment: a systematic review and meta-analysis

JOURNAL=Frontiers in Neurology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1467578

DOI=10.3389/fneur.2025.1467578

ISSN=1664-2295

ABSTRACT=ObjectiveTo systematically evaluate the diagnostic value of diffusion tensor imaging (DTI) for mild cognitive impairment (MCI) based on Meta-analysis.Materials and methodsDatabases including PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang and VIP database were searched for literature on the use of DTI in studying MCI. The search was conducted from the inception of each database up to February 20, 2024. Literature was screened based on predefined inclusion and exclusion criteria, relevant data were extracted, and the quality of the included studies was assessed using the QUADAS-2 tool. Heterogeneity was evaluated using the Q-test and I2 statistics. Fractional anisotropy (FA) values for different brain regions (frontal lobe, parietal lobe, temporal lobe, occipital lobe, fornix, hippocampus, parahippocampal gyrus, posterior cingulum, posterior limb of the internal capsule, uncinate fasciculus, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, inferior longitudinal fasciculus, genu and splenium of the corpus callosum) were extracted from the MCI and normal control (NC) groups. Meta-analysis software (Review Manager 5.4) was used to perform a pooled analysis of the eligible studies to obtain the weighted mean difference (WMD) and 95% confidence interval (95% CI).ResultsA total of 76 studies were included (41 in English and 35 in Chinese). The overall pooled WMD and its 95% CI were −0.03 [−0.04, −0.03], with statistically significant differences in all brain regions except for the occipital lobe and the posterior limb of the internal capsule.ConclusionDTI technology can identify microstructural damage in the brain white matter of MCI patients, which holds significant implications for early diagnosis and intervention.