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大脑功能连接的纵向变化可预测向阿尔茨海默病的转化。

Longitudinal Changes in Functional Brain Connectivity Predicts Conversion to Alzheimer's Disease.

作者信息

Serra Laura, Cercignani Mara, Mastropasqua Chiara, Torso Mario, Spanò Barbara, Makovac Elena, Viola Vanda, Giulietti Giovanni, Marra Camillo, Caltagirone Carlo, Bozzali Marco

机构信息

Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy.

Brighton & Sussex Medical School, CISC, University of Sussex, Brighton, Falmer East Sussex, UK.

出版信息

J Alzheimers Dis. 2016;51(2):377-89. doi: 10.3233/JAD-150961.

DOI:10.3233/JAD-150961
PMID:26890769
Abstract

This longitudinal study investigates the modifications in structure and function occurring to typical Alzheimer's disease (AD) brains over a 2-year follow-up, from pre-dementia stages of disease, with the aim of identifying biomarkers of prognostic value. Thirty-one patients with amnestic mild cognitive impairment were recruited and followed-up with clinical, neuropsychological, and MRI assessments. Patients were retrospectively classified as AD Converters or Non-Converters, and the data compared between groups. Cross-sectional MRI data at baseline, assessing volume and functional connectivity abnormalities, confirmed previous findings, showing a more severe pattern of regional grey matter atrophy and default-mode network disconnection in Converters than in Non-Converters. Longitudinally, Converters showed more grey matter atrophy in the frontotemporal areas, accompanied by increased connectivity in the precuneus. Discriminant analysis revealed that functional connectivity of the precuneus within the default mode network at baseline is the parameter able to correctly classify patients in Converters and Non-Converters with high sensitivity, specificity, and accuracy.

摘要

这项纵向研究调查了典型阿尔茨海默病(AD)大脑在从疾病的痴呆前期开始的2年随访期间结构和功能的变化,目的是识别具有预后价值的生物标志物。招募了31名遗忘型轻度认知障碍患者,并通过临床、神经心理学和MRI评估进行随访。患者被回顾性地分类为AD转化者或非转化者,并对两组数据进行比较。基线时的横断面MRI数据评估了体积和功能连接异常,证实了先前的发现,表明转化者比非转化者有更严重的区域灰质萎缩和默认模式网络断开模式。纵向来看,转化者在额颞区域表现出更多的灰质萎缩,同时楔前叶的连接性增加。判别分析显示,基线时默认模式网络内楔前叶的功能连接是能够以高敏感性、特异性和准确性正确将患者分类为转化者和非转化者的参数。

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