Suppr超能文献

基线脑容量预测轻度认知障碍患者未来的脑萎缩:一项基于张量的形态测量学对阿尔茨海默病连续体的研究。

Baseline Brain Volumes Predict Future Brain Atrophy in Mild Cognitive Impairment: A Tensor-based Morphometry Study of the Alzheimer Continuum.

作者信息

Mozafar Mehrdad, Amanollahi Mobina, Sadeghi Mohammad, Rafati Ali, Hejazian Seyyed Sina, Jelodar Faraz, Khodadadi Negar, Kohanfekr Artemis, Kamali Arash

机构信息

Department of Radiology, Tehran University of Medical Sciences.

Department of Surgery, Division of Vascular and Endovascular Surgery, Shohada-Tajrish Medical Center, Shahid Beheshti University of Medical Sciences.

出版信息

J Comput Assist Tomogr. 2025;49(5):816-824. doi: 10.1097/RCT.0000000000001744. Epub 2025 Mar 18.

Abstract

OBJECTIVE

Prognostic evaluation of patients with mild cognitive impairment (MCI) is of great importance, and magnetic resonance imaging, as a readily available modality, can play a pivotal role in this field.

METHODS

Using the Alzheimer Disease Neuroimaging Initiative database, we conducted a retrospective longitudinal study of the associations between volumetric brain magnetic resonance imaging and cognitive composite scores in all domains (memory, executive function, language, and visuospatial) with annual whole-brain atrophy based on tensor-based morphometry (TBM) scores among patients with MCI and healthy controls (HCs). The Reliable Change Index was further used to categorize patients into 2 groups including (1) patients with meaningful 1-year reliable cognitive changes [reliable change (RC) group] and (2) patients without (non-RC).

RESULTS

One hundred thirty-seven patients with MCI and 132 HCs were enrolled. The 2 groups showed no significant differences in age, sex, and apolipoprotein E4 expression ( P > 0.05). Based on the TBM score, patients with MCI had more significant 1-year brain volume loss than HCs ( P < 0.001). After multiple comparison corrections, the 1-year TBM atrophy score was positively correlated with baseline whole brain ( P = 0.03), hippocampus ( P < 0.0001), entorhinal ( P < 0.0001), and middle temporal ( P < 0.0001) volumes among MCI patients, indicating that lower volumes in these regions were associated with greater 1-year atrophy rates. Regression analyses showed a positive correlation between baseline and 1-year memory composite scores and annual brain atrophy rate in MCI patients ( P = 0.01, 0.04), demonstrating that lower cognitive scores were associated with a greater annual atrophy rate. However, the correlations no longer held significance after correction for multiple comparison ( P = 0.05, 0.17). MCI participants with RCs in language composite scores initially had significantly greater brain atrophy than those without ( P = 0.03, corrected P = 0.06). However, TBM scores showed no significant differences between RC and non-RC groups for other composite scores ( P > 0.05).

CONCLUSIONS

Lower baseline volumes in multiple brain regions of MCI are associated with greater annual brain volume loss based on TBM, suggesting TBM as a potential imaging marker for conventional volumetric studies in MCI. Further research is needed to explore the link between cognitive scores and the application of Reliable Change Index in TBM imaging across the Alzheimer disease spectrum.

摘要

目的

轻度认知障碍(MCI)患者的预后评估至关重要,磁共振成像作为一种易于获得的检查手段,在该领域可发挥关键作用。

方法

利用阿尔茨海默病神经影像学倡议数据库,我们对MCI患者和健康对照(HCs)进行了一项回顾性纵向研究,基于张量形态测量(TBM)分数,分析全脑体积磁共振成像与所有认知领域(记忆、执行功能、语言和视觉空间)的认知综合评分以及年度全脑萎缩之间的关联。进一步使用可靠变化指数将患者分为两组,包括(1)有意义的1年可靠认知变化患者[可靠变化(RC)组]和(2)无变化患者(非RC)。

结果

纳入137例MCI患者和132例HCs。两组在年龄、性别和载脂蛋白E4表达方面无显著差异(P>0.05)。基于TBM分数,MCI患者1年脑体积损失比HCs更显著(P<0.001)。经过多重比较校正后,MCI患者中,1年TBM萎缩分数与基线全脑(P=0.03)、海马体(P<0.0001)、内嗅区(P<0.0001)和颞中回(P<0.0001)体积呈正相关,表明这些区域体积越小,1年萎缩率越高。回归分析显示,MCI患者基线和1年记忆综合评分与年度脑萎缩率呈正相关(P=0.01,0.04),表明较低的认知评分与较高的年度萎缩率相关。然而,经过多重比较校正后,相关性不再显著(P=0.05,0.17)。语言综合评分有可靠变化的MCI参与者最初的脑萎缩明显大于无变化者(P=0.03,校正后P=0.06)。然而,对于其他综合评分,RC组和非RC组的TBM分数无显著差异(P>0.05)。

结论

基于TBM,MCI患者多个脑区较低的基线体积与更大的年度脑体积损失相关,提示TBM可作为MCI传统体积研究的潜在影像学标志物。需要进一步研究探索认知评分与可靠变化指数在阿尔茨海默病谱系中TBM成像应用之间的联系。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验