源于阿尔茨海默病的轻度认知障碍患者脑结构及#br#
静息态功能磁共振研究进展

李瑜霞1; 李永秋2; 孙  宇1; 盛  灿1; 李红艳1; 牛海晶3; 韩  璎1

中国临床医学影像杂志 ›› 2016, Vol. 27 ›› Issue (2) : 131-134.

综述

源于阿尔茨海默病的轻度认知障碍患者脑结构及#br# 静息态功能磁共振研究进展

作者信息 +

Structural and resting state functional MRI characteristics of patients with #br# mild cognitive impairment due to Alzheimer’s disease

Author information +

文章历史 +

摘要

轻度认知障碍（MCI）是介于正常老化与痴呆之间的一种过渡状态，从MCI进展到阿尔茨海默病（AD）痴呆是一个脑功能和脑结构损害不断进展的过程，磁共振成像（MRI）可以无创地观察患者在疾病进展过程中脑结构与功能的变化，因此，近年来借助MRI技术建立新的AD早期诊断方法已成为热点。本文对近年来结构磁共振以及静息态功能磁共振对MCI向AD痴呆转化的研究进行综述。MRI对研究MCI向AD的转化起到了重要作用，为其提供影像学依据，并起到动态监测其进展的作用。

Abstract

Mild cognitive impairment(MCI) is considered as a transitional stage between normal aging and Alzheimer’s disease(AD). It is a gradually progressing process from MCI to AD dementia. The changes of the structure and function in the process of disease progression can be seen noninvasively using MRI technology, so it has become the focus that studies the conversion of MCI to AD dementia using the technology of MRI. The studies of the structural MRI and the resting state functional MRI from MCI to AD dementia in recent years were reviewed in this paper. It has played an important role for MRI in the study of the conversion from MCI to AD, and it has the effect of dynamic monitoring on the progression at the imaging basis.

导出引用

李瑜霞1，李永秋2，孙宇1，盛灿1，李红艳1，牛海晶3，韩璎1. 源于阿尔茨海默病的轻度认知障碍患者脑结构及#br# 静息态功能磁共振研究进展[J]. 中国临床医学影像杂志. 2016, 27(2): 131-134

LI Yu-xia1, LI Yong-qiu2, SUN Yu1, SHENG Can1, LI Hong-yan1, NIU Hai-jing3, HAN Ying1. Structural and resting state functional MRI characteristics of patients with #br# mild cognitive impairment due to Alzheimer’s disease[J]. Journal of China Clinic Medical Imaging. 2016, 27(2): 131-134

中图分类号： Ｒ745.7 Ｒ445.2

参考文献

[1]Albert MS, DeKosky ST, Dickson D, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease[J]. Alzheimers Dement, 2011, 7(3): 270-279.
[2]韩璎. 解读NIA_AA新理解对于阿尔茨海默病的二级预防理念影响[J]. 医学研究杂志，2014，43（8）：1-3.
[3]Gauthier S, Reisberg B, Zaudig M, et al. Mild cognitive impairment[J]. Lancet, 2006, 367(9518): 1262-1270.
[4]Bai F, Watson DR, Shi Y, et al. Specifically progressive deficits of brain functional marker in amnestic type mild cognitive impairment[J]. PLoS One, 2011, 6(9): e24271.
[5]Jack CR Jr, Albert MS, Knopman DS, et al. Introduction to the recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease[J]. Alzheimers Dement, 2011, 7(3): 257-262.
[6]Kakeda S, Korogi Y. The efficacy of a voxel-based morphometry on the analysis of imaging in schizophrenia, temporal lobe epilepsy, and Alzheimer’s disease/mild cognitive impairment: a review[J]. Neuroradiology, 2010, 52(8): 711-721.
[7]Guo Y, Zhang Z, Zhou B, et al. Grey-matter volume as a potential feature for the classification of Alzheimer’s disease and mild cognitive impairment: an exploratory study[J]. Neurosci Bull, 2014, 30(3): 477-489.
[8]Fennema-Notestine C, McEvoy LK, Hagler DJ Jr, et al. Structural neuroimaging in the detection and prognosis of pre-clinical and early AD[J]. Behav Neurol, 2009, 21(1): 3-12.
[9]Risacher SL, Saykin AJ, West JD, et al. Baseline MRI predictors of conversion from MCI to probable AD in the ADNI cohort[J]. Curr Alzheimer Res, 2009, 6(4): 347-361.
[10]Reuter M, Tisdall MD, Qureshi A, et al. Head motion during MRI acquisition reduces gray matter volume and thickness estimates[J]. Neuroimage, 2015, 107(2): 107-115.
[11]Raamana PR, Wen W, Kochan NA, et al. The Sub-Classification of Amnestic Mild Cognitive Impairment Using MRI-Based Cortical Thickness Measures[J]. Front Neurol, 2014, 5(5): 76.
[12]Spulber G, Simmons A, Muehlboeck JS, et al. An MRI-based index to measure the severity of Alzheimer’s disease-like structural pattern in subjects with mild cognitive impairment[J]. J Intern Med, 2013, 273(4): 396-409.
[13]Barnes J, Bartlett JW, van de Pol LA, et al. A Meta-analysis of hippocampal atrophy rates in Alzheimer’s disease[J]. Neurobiol Aging, 2009, 30(11): 1711-1723.
[14]Sluimer JD, van der Flier WM, Karas GB, et al. Whole-brain atrophy rate and cognitive decline: longitudinal MR study of memory clinic patients[J]. Radiology, 2008, 248(2): 590-598.
[15]Jack CR Jr, Petersen RC, Xu Y, et al. Rates of hippocampal atrophy correlate with change in clinical status in aging and AD[J]. Neurology, 2000, 55(4): 484-489.
[16]Grodd W, Beckmann CF. Resting state functional MRI of the brain[J]. Nervenarzt, 2014, 85(6): 690-700.
[17]Biswal B, Yetkin FZ, Haughton VM, et al. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI[J]. Magn Reson Med, 1995, 34(4): 537-541.
[18]Greicius MD, Srivastava G, Reiss AL, et al. Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: evidence from functional MRI[J]. Proc Natl Acad Sci USA, 2004, 101(13): 4637-4642.
[19]Buckner RL, Andrews-Hanna JR, Schacter DL. The brain’s default network: anatomy, function, and relevance to disease[J]. Ann N Y Acad Sci, 2008, 1124(3): 1-38.
[20]Zang Y, Jiang T, Lu Y, et al. Regional homogeneity approach to fMRI data analysis[J]. Neuroimage, 2004, 22(1): 394-400.
[21]Liu Y, Wang K, Yu C, et al. Regional homogeneity, functional connectivity and imaging markers of Alzheimer’s disease: a review of resting-state fMRI studies[J]. Neuropsychologia, 2008, 46(6): 1648-1656.
[22]Yuan BK, Wang J, Zang YF, et al. Amplitude differences in high-frequency fMRI signals between eyes open and eyes closed resting states[J]. Front Hum Neurosci, 2014, 8(7): 503.
[23]Han Y, Wang J, Zhao Z, et al. Frequency-dependent changes in the amplitude of low-frequency fluctuations in amnestic mild cognitive impairment: a resting-state fMRI study[J]. Neuroimage, 2011, 55(1): 287-295.
[24]Arbabshirani MR, Havlicek M, Kiehl KA, et al. Functional network connectivity during rest and task conditions: a comparative study[J]. Hum Brain Mapp, 2013, 34(11): 2959-2971.
[25]Calhoun VD, Adali T, Pearlson GD, et al. Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms[J]. Hum Brain Mapp, 2001, 13(1): 43-53.
[26]Damoiseaux JS, Prater KE, Miller BL, et al. Functional connectivity tracks clinical deterioration in Alzheimer’s disease[J]. Neurobiol Aging, 2012, 33(4): 828.
[27]Bai F, Xie C, Watson DR, et al. Aberrant hippocampal subregion networks associated with the classifications of aMCI subjects: a longitudinal resting-state study[J]. PLoS One, 2011, 6(12): e29288.
[28]Han SD, Arfanakis K, Fleischman DA, et al. Functional connectivity variations in mild cognitive impairment: associations with cognitive function[J]. J Int Neuropsychol Soc, 2012, 18(1): 39-48.
[29]Wang Z, Liang P, Jia X, et al. The baseline and longitudinal changes of PCC connectivity in mild cognitive impairment: a combined structure and resting-state fMRI study[J]. PLoS One, 2012, 7(5): e36838.
[30]Wang Z, Jia X, Liang P, et al. Changes in thalamus connectivity in mild cognitive impairment: evidence from resting state fMRI[J]. Eur J Radiol, 2012, 81(2): 277-285.
[31]McKeown MJ, Sejnowski TJ. Independent component analysis of fMRI data: examining the assumptions[J]. Hum Brain Mapp, 1998, 6(5-6): 368-372.
[32]Jin M, Pelak VS, Cordes D. Aberrant default mode network in subjects with amnestic mild cognitive impairment using resting-state functional MRI[J]. Magn Reson Imaging, 2012, 30(1): 48-61.
[33]Cha J, Jo HJ, Kim HJ, et al. Functional alteration patterns of default mode networks: comparisons of normal aging, amnestic mild cognitive impairment and Alzheimer’s disease[J]. Eur J Neurosci, 2013, 37(12): 1916-1924.
[34]Vincent JL, Snyder AZ, Fox MD, et al. Coherent spontaneous activity identifies a hippocampal-parietal memory network[J]. J Neurophysiol, 2006, 96(6): 3517-3531.
[35]Xie T, He Y. Mapping the Alzheimer’s brain with connectomics[J]. Front Psychiatry, 2011, 2(1): 77.
[36]Dickerson BC, Sperling RA. Large-scale functional brain network abnormalities in Alzheimer’s disease: insights from functional neuroimaging[J]. Behav Neurol, 2009, 21(1): 63-75.
[37]Wang J, Zuo X, Dai Z, et al. Disrupted functional brain connectome in individuals at risk for Alzheimer’s disease[J]. Biol Psychiatry, 2013, 73(5): 472-481.
[38]Delbeuck X, Van der Linden M, Collette F. Alzheimer’s disease as a disconnection syndrome?[J]. Neuropsychol Rev, 2003, 13(2): 79-92.