基于静息态功能磁共振成像的脑功能动态分析及其在神经系统变性疾病中的应用进展

doi:10.3969/j.issn.1672-6731.2022.03.003

摘要/Abstract

摘要： 神经系统变性疾病是异常蛋白沉积导致的神经元进行性缺失，进而引起脑结构和功能改变的一类疾病，主要包括阿尔茨海默病、帕金森病、路易体痴呆和额颞叶痴呆等。静息态fMRI（rs-fMRI）业已广泛应用于神经系统变性疾病的影像学研究，主要评估脑功能静态特征。然而，人类大脑是动态变化的，其神经活动呈非平稳性，基于rs-fMRI的脑功能动态分析可以揭示复杂神经活动的动态特性，探究神经系统变性疾病的病理生理学机制和诊断标志物。本文综述rs-fMRI分析方法、基于rs-fMRI的脑功能动态分析方法及其在神经系统变性疾病中的应用进展。

关键词: 神经变性疾病, 磁共振成像, 综述

Abstract: Neurodegenerative diseases are a group of disorders in which progressive loss of neurons due to abnormal protein deposits causes structural and functional changes in the brain, including Alzheimer's disease (AD), Parkinson's disease (PD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). In brain imaging studies of neurodegenerative diseases, resting-state fMRI (rs-fMRI) has been widely used, with most studies analysing static features of brain function. However, the human brain is dynamic and its neural activity is non-stationary, and static studies can not reveal the time-varying features of brain function. In recent years, many studies have used dynamic analysis of brain function based on rs-fMRI in order to reveal the dynamic nature of complex neural activity in the brain and further investigate the pathophysiological mechanisms and diagnostic markers of disease. In this paper, we will briefly introduce the rs-fMRI analysis method, the common methods of rs-fMRI-based dynamic analysis of brain function and its application and research progress in common neurodegenerative diseases.

Key words: Neurodegenerative diseases, Magnetic resonance imaging, Review

田媛, 李凯, 苏闻. 基于静息态功能磁共振成像的脑功能动态分析及其在神经系统变性疾病中的应用进展[J]. 中国现代神经疾病杂志, 2022, 22(3): 137-141.

TIAN Yuan, LI Kai, SU Wen. Dynamic brain function analysis based on resting-state fMRI and its application in neurodegenerative diseases[J]. Chinese Journal of Contemporary Neurology and Neurosurgery, 2022, 22(3): 137-141.

http://journal11.magtechjournal.com/cjcnn/CN/Y2022/V22/I3/137

参考文献

[1] Kovacs GG. Concepts and classification of neurodegenerative diseases[J]. Handb Clin Neurol, 2017, 145:301-307.
[2] Hohenfeld C, Werner CJ, Reetz K. Resting-state connectivity in neurodegenerative disorders:is there potential for an imaging biomarker[J]? Neuroimage Clin, 2018, 18:849-870.
[3] Lv H, Wang Z, Tong E, Williams LM, Zaharchuk G, Zeineh M, Goldstein-Piekarski AN, Ball TM, Liao C, Wintermark M. Resting-state functional MRI:everything that nonexperts have always wanted to know[J]. AJNR Am J Neuroradiol, 2018, 39:1390-1399.
[4] Han L, Zhaohui L, Fei Y, Pengfei Z, Ting L, Cheng D, Zhenchang W. Disrupted neural activity in unilateral vascular pulsatile tinnitus patients in the early stage of disease:evidence from resting-state fMRI[J]. Prog Neuropsychopharmacol Biol Psychiatry, 2015, 59:91-99.
[5] Arbabshirani MR, Havlicek M, Kiehl KA, Pearlson GD, Calhoun VD. Functional network connectivity during rest and task conditions:a comparative study[J]. Hum Brain Mapp, 2013, 34:2959-2971.
[6] Raj A. Graph models of pathology spread in Alzheimer's disease:an alternative to conventional graph theoretic analysis[J]. Brain Connect, 2021, 11:799-814.
[7] de Vos F, Koini M, Schouten TM, Seiler S, van der Grond J, Lechner A, Schmidt R, de Rooij M, Rombouts SARB. A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer's disease[J]. Neuroimage, 2018, 167:62-72.
[8] Bernas A, Aldenkamp AP, Zinger S. Wavelet coherence-based classifier:a resting-state functional MRI study on neurodynamics in adolescents with high-functioning autism[J]. Comput Methods Programs Biomed, 2018, 154:143-151.
[9] Janes AC, Peechatka AL, Frederick BB, Kaiser RH. Dynamic functioning of transient resting-state coactivation networks in the Human Connectome Project[J]. Hum Brain Mapp, 2020, 41:373-387.
[10] Park HJ, Friston KJ, Pae C, Park B, Razi A. Dynamic effective connectivity in resting state fMRI[J]. Neuroimage, 2018, 180(Pt B):594-608.
[11] Agosta F, Pievani M, Geroldi C, Copetti M, Frisoni GB, Filippi M. Resting state fMRI in Alzheimer's disease:beyond the default mode network[J]. Neurobiol Aging, 2012, 33:1564-1578.
[12] Jones DT, Machulda MM, Vemuri P, McDade EM, Zeng G, Senjem ML, Gunter JL, Przybelski SA, Avula RT, Knopman DS, Boeve BF, Peterson RC, Jack CR Jr. Age-related changes in the default mode network are more advanced in Alzheimer disease[J]. Neurology, 2011, 77:1524-1531.
[13] Jones DT, Vemuri P, Murphy MC, Gunter JL, Senjem ML, Machulda MM, Przybelski SA, Gregg BE, Kantarci K, Knopman DS, Boeve BF, Petersen RC, Jack CR Jr. Non-stationarity in the "resting brain's" modular architecture[J]. PLoS One, 2012, 7:e39731.
[14] Córdova-Palomera A, Kaufmann T, Persson K, Alnæs D, Doan NT, Moberget T, Lund MJ, Barca ML, Engvig A, Brækhus A, Engedal K, Andreassen OA, Selbæk G, Westlye LT. Disrupted global metastability and static and dynamic brain connectivity across individuals in the Alzheimer's disease continuum[J]. Sci Rep, 2017, 7:40268.
[15] Demirtaş M, Falcon C, Tucholka A, Gispert JD, Molinuevo JL, Deco G. A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease[J]. Neuroimage Clin, 2017, 16:343-354.
[16] Quevenco FC, Preti MG, van Bergen JM, Hua J, Wyss M, Li X, Schreiner SJ, Steininger SC, Meyer R, Meier IB, Brickman AM, Leh SE, Gietl AF, Buck A, Nitsch RM, Pruessmann KP, van Zijl PC, Hock C, Van De Ville D, Unschuld PG. Memory performance-related dynamic brain connectivity indicates pathological burden and genetic risk for Alzheimer's disease[J]. Alzheimers Res Ther, 2017, 9:24.
[17] Li T, Liao Z, Mao Y, Hu J, Le D, Pei Y, Sun W, Lin J, Qiu Y, Zhu J, Chen Y, Qi C, Ye X, Su H, Yu E. Temporal dynamic changes of intrinsic brain activity in Alzheimer's disease and mild cognitive impairment patients:a resting-state functional magnetic resonance imaging study[J]. Ann Transl Med, 2021, 9:63.
[18] Yu Y, Li Z, Lin Y, Yu J, Peng G, Zhang K, Jia X, Luo B. Depression affects intrinsic brain activity in patients with mild cognitive impairment[J]. Front Neurosci, 2019, 13:1333.
[19] Putcha D, Ross RS, Cronin-Golomb A, Janes AC, Stern CE. Altered intrinsic functional coupling between core neurocognitive networks in Parkinson's disease[J]. Neuroimage Clin, 2015, 7:449-455.
[20] Baggio HC, Segura B, Sala-Llonch R, Marti MJ, Valldeoriola F, Compta Y, Tolosa E, Junqué C. Cognitive impairment and resting-state network connectivity in Parkinson's disease[J]. Hum Brain Mapp, 2015, 36:199-212.
[21] Kim J, Criaud M, Cho SS, Díez-Cirarda M, Mihaescu A, Coakeley S, Ghadery C, Valli M, Jacobs MF, Houle S, Strafella AP. Abnormal intrinsic brain functional network dynamics in Parkinson's disease[J]. Brain, 2017, 140:2955-2967.
[22] Cordes D, Zhuang X, Kaleem M, Sreenivasan K, Yang Z, Mishra V, Banks SJ, Bluett B, Cummings JL. Advances in functional magnetic resonance imaging data analysis methods using Empirical Mode Decomposition to investigate temporal changes in early Parkinson's disease[J]. Alzheimers Dement (NY), 2018, 4:372-386.
[23] Fiorenzato E, Strafella AP, Kim J, Schifano R, Weis L, Antonini A, Biundo R. Dynamic functional connectivity changes associated with dementia in Parkinson's disease[J]. Brain, 2019, 142:2860-2872.
[24] Díez-Cirarda M, Strafella AP, Kim J, Peña J, Ojeda N, Cabrera-Zubizarreta A, Ibarretxe-Bilbao N. Dynamic functional connectivity in Parkinson's disease patients with mild cognitive impairment and normal cognition[J]. Neuroimage Clin, 2017, 17:847-855.
[25] Navalpotro-Gomez I, Kim J, Paz-Alonso PM, Delgado-Alvarado M, Quiroga-Varela A, Jimenez-Urbieta H, Carreiras M, Strafella AP, Rodriguez-Oroz MC. Disrupted salience network dynamics in Parkinson's disease patients with impulse control disorders[J]. Parkinsonism Relat Disord, 2020, 70:74-81.
[26] Li X, Xiong Y, Liu S, Zhou R, Hu Z, Tong Y, He L, Niu Z, Ma Y, Guo H. Predicting the Post-therapy Severity Level (UPDRS-Ⅲ) of patients with Parkinson's disease after drug therapy by using the dynamic connectivity efficiency of fMRI[J]. Front Neurol, 2019, 10:668.
[27] Zhang C, Dou B, Wang J, Xu K, Zhang H, Sami MU, Hu C, Rong Y, Xiao Q, Chen N, Li K. Dynamic alterations of spontaneous neural activity in Parkinson's disease:a resting-state fMRI study[J]. Front Neurol, 2019, 10:1052.
[28] McKeith IG, Boeve BF, Dickson DW, Halliday G, Taylor JP, Weintraub D, Aarsland D, Galvin J, Attems J, Ballard CG, Bayston A, Beach TG, Blanc F, Bohnen N, Bonanni L, Bras J, Brundin P, Burn D, Chen-Plotkin A, Duda JE, El-Agnaf O, Feldman H, Ferman TJ, Ffytche D, Fujishiro H, Galasko D, Goldman JG, Gomperts SN, Graff-Radford NR, Honig LS, Iranzo A, Kantarci K, Kaufer D, Kukull W, Lee VMY, Leverenz JB, Lewis S, Lippa C, Lunde A, Masellis M, Masliah E, McLean P, Mollenhauer B, Montine TJ, Moreno E, Mori E, Murray M, O'Brien JT, Orimo S, Postuma RB, Ramaswamy S, Ross OA, Salmon DP, Singleton A, Taylor A, Thomas A, Tiraboschi P, Toledo JB, Trojanowski JQ, Tsuang D, Walker Z, Yamada M, Kosaka K. Diagnosis and management of dementia with Lewy bodies:fourth consensus report of the DLB Consortium[J]. Neurology, 2017, 89:88-100.
[29] Lowther ER, O'Brien JT, Firbank MJ, Blamire AM. Lewy body compared with Alzheimer dementia is associated with decreased functional connectivity in resting state networks[J]. Psychiatry Res, 2014, 223:192-201.
[30] Sourty M, Thoraval L, Roquet D, Armspach JP, Foucher J, Blanc F. Identifying dynamic functional connectivity changes in dementia with Lewy Bodies based on Product Hidden Markov Models[J]. Front Comput Neurosci, 2016, 10:60.
[31] Schumacher J, Taylor JP, Hamilton CA, Firbank M, Cromarty RA, Donaghy PC, Roberts G, Allan L, Lloyd J, Durcan R, Barnett N, O'Brien JT, Thomas AJ. Quantitative EEG as a biomarker in mild cognitive impairment with Lewy bodies[J]. Alzheimers Res Ther, 2020, 12:82.
[32] Schumacher J, Taylor JP, Hamilton CA, Firbank M, Donaghy PC, Roberts G, Allan L, Durcan R, Barnett N, O'Brien JT, Thomas AJ. Functional connectivity in mild cognitive impairment with Lewy bodies[J]. J Neurol, 2021, 268:4707-4720.
[33] Miller B, Llibre Guerra JJ. Frontotemporal dementia[J]. Handb Clin Neurol, 2019, 165:33-45.
[34] Rohrer JD, Warren JD. Phenotypic signatures of genetic frontotemporal dementia[J]. Curr Opin Neurol, 2011, 24:542-549.
[35] Premi E, Calhoun VD, Diano M, Gazzina S, Cosseddu M, Alberici A, Archetti S, Paternicò D, Gasparotti R, van Swieten J, Galimberti D, Sanchez-Valle R, Laforce R Jr, Moreno F, Synofzik M, Graff C, Masellis M, Tartaglia MC, Rowe J, Vandenberghe R, Finger E, Tagliavini F, de Mendonça A, Santana I, Butler C, Ducharme S, Gerhard A, Danek A, Levin J, Otto M, Frisoni G, Cappa S, Sorbi S, Padovani A, Rohrer JD, Borroni B; Genetic FTD Initiative, GENFI. The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia:the chronnectome fingerprint[J]. Neuroimage, 2019, 189:645-654.

选择文件类型/文献管理软件名称

选择包含的内容

2 基于静息态功能磁共振成像的脑功能动态分析及其在神经系统变性疾病中的应用进展

Dynamic brain function analysis based on resting-state fMRI and its application in neurodegenerative diseases

RichHTML

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	薛蓉, 张轩. 睡眠障碍对脑血管病的影响[J]. 中国现代神经疾病杂志, 2023, 23(8): 659-662.
[2]	张鹏, 陈涛, 许莉. 成人失眠认知行为疗法关键技术与流程改进建议[J]. 中国现代神经疾病杂志, 2023, 23(8): 663-667.
[3]	张轩, 薛蓉. 特发性快速眼动睡眠期行为障碍向神经系统变性疾病转化的生物学标志物研究进展[J]. 中国现代神经疾病杂志, 2023, 23(8): 668-673.
[4]	刘引, 汤永红, 翟锦霞, 邱媛. 慢性低度炎症与睡眠障碍研究进展[J]. 中国现代神经疾病杂志, 2023, 23(8): 674-677.
[5]	于洁洋, 张亚男, 李惠敏, 黄真灿, 李宛儒, 王赞. 发作性睡病与焦虑研究进展[J]. 中国现代神经疾病杂志, 2023, 23(8): 678-682.
[6]	库成心, 邓丽影, 谢亮. 缺血性卒中继发日间过度思睡研究进展[J]. 中国现代神经疾病杂志, 2023, 23(8): 683-686.
[7]	姜佳凤, 赵莲花, 赵伟. 褪黑素在阿尔茨海默病病理损害机制中的作用[J]. 中国现代神经疾病杂志, 2023, 23(8): 687-692.
[8]	黄沛, 王刚. 功能性帕金森综合征诊断与治疗[J]. 中国现代神经疾病杂志, 2023, 23(8): 738-741.
[9]	洪涛, 唐斌. 如何成为一名优秀的颅底外科医师[J]. 中国现代神经疾病杂志, 2023, 23(7): 571-574.
[10]	张庆硕, 宋丹丹, 周世越, 张金璐, 韩晓旭, 许顺良. 功能性步态障碍诊断与治疗[J]. 中国现代神经疾病杂志, 2023, 23(7): 604-609.
[11]	潘希娟, 邢英琦, 刘玉梅. 脑小血管病影像学评分方法[J]. 中国现代神经疾病杂志, 2023, 23(7): 633-637.
[12]	俞淑凤, 李宁, 徐健, 王鹏. 颈动脉漂浮血栓相关缺血性卒中诊断与治疗进展[J]. 中国现代神经疾病杂志, 2023, 23(7): 638-642.
[13]	魏俊吉. 神经外科重症医学规范化诊断与治疗[J]. 中国现代神经疾病杂志, 2023, 23(6): 477-478.
[14]	杜倩, 邓素君, 邹姗, 金珺, 周青山. 宏基因组第二代测序技术在重症中枢神经系统感染中的应用[J]. 中国现代神经疾病杂志, 2023, 23(6): 479-484.
[15]	曲鑫, 赵浩, 尚峰, 王宁. 神经重症目标温度管理[J]. 中国现代神经疾病杂志, 2023, 23(6): 485-489.

模态框（Modal）标题

选择文件类型/文献管理软件名称

选择包含的内容

2 基于静息态功能磁共振成像的脑功能动态分析及其在神经系统变性疾病中的应用进展

Dynamic brain function analysis based on resting-state fMRI and its application in neurodegenerative diseases

RichHTML

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价