Details

Autor(en) / Beteiligte

• Mu, Ronghua
• Qin, Xiaoyan
• Zheng, Wei
• Yang, Peng
• Huang, Bingqin
• Li, Xin
• Liu, Fuzhen
• Deng, Kan
• Zhu, Xiqi

Titel

Amide proton transfer could be a surrogate imaging marker for predicting vascular cognitive impairment

Ist Teil von

• Brain research bulletin, 2023-11, Vol.204, p.110793-110793, Article 110793

Ort / Verlag

Elsevier

Erscheinungsjahr

2023

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• BACKGROUDEmerging evidence suggests an overlap in the underlying pathways contributing to both cerebral small vessel disease (CSVD) and the neurodegenerative disease. Studies investigating the progression of CSVD should incorporate markers that reflect neurodegenerative lesions.OBJECTIVEWe aim to investigate whether Amide proton transfer (APT) can serve as a potential marker for reflecting vascular cognitive impairment (VCI).METHODParticipants were categorized into one of three groups based on their Montreal Cognitive Assessment (MoCA) scores: normal control group (age,54.9 ± 7.9; male, 52.9%), mild cognitive impairment (MCI) group (age,55.7 ± 6.9; male, 42.6%), or vascular dementia (VaD) group (age,57.6 ± 5.5, male, 58.5%). One way analysis of variance was performed to compare the demographic and APT variables between groups. Multiple logistic regression analysis wwas constructed to examine the relationship between APT values and VCI grouping. A hierarchical linear regression model was employed to examine the associations between patients' demographic factors, imaging markers, APT values, and MoCA.RESULTSThe APT values of frontal white matter, hippocampus, amygdala, and thalamus were significantly different among different groups (p < 0.05). The APT values of frontal white matter, amygdala, and thalamus indicate a significant positive effect on MCI grouping. the APT values of frontal white matter, amygdala, and thalamus indicate a significant positive effect on VaD grouping. The demographic data, CSVD imaging markers and APT values can account for 5.1%, 20.1% and 27.7% of the variation in MoCA, respectively.CONCLUSIONAPT imaging can partially identifying and predicting the occurrence of VCI.