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Research progress of different analysis methods of resting state magnetic resonance imaging in vascular cognitive impairment no dementia
CAI Lina  LI Xiaoling  CUI Xuan  WANG Peng  TONG Xin  WEI Zeyi  GAO Shenglan  HAN Shengwang  HOU Yu 

Co first author: LI Xiaoling DOI:10.12015/issn.1674-8034.2022.09.027.

[Abstract] Vascular cognitive impairment no dementia (VCIND) is a transitional stage between normal aging and vascular dementia . It refers to the disease of cognitive impairment caused by vascular lesions, however, its specific pathogenesis is not very clear, and there is a lack of specific imaging diagnostic markers in clinic. Resting state functional magnetic resonance imaging (rs-fMRI) technology combined with different analysis methods is applied to the study of the mechanism of vascular cognitive impairment no dementia. It can objectively reflect the brain functional activities, obtain the characteristic imaging indexes of VCIND patients, and provide some clues to explain its mechanism. This article reviews the application of different analysis methods of rs-fMRI in VCIND research.
[Keywords] resting state;brain;magnetic resonance imaging;vascular cognitive impairment no dementia

CAI Lina1   LI Xiaoling2   CUI Xuan1   WANG Peng3*   TONG Xin1   WEI Zeyi1   GAO Shenglan1   HAN Shengwang4   HOU Yu5  

1 Graduate School of Heilongjiang University of Traditional Chinese Medicine, Harbin 150040, China

2 Department of CT & MR, the First Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin 150040, China

3 Department of Oncology, the First Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin 150040, China

4 Department of Rehabilitation, the Second Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin 150001, China

5 Department of Gynecology, Harbin Hospital of Traditional Chinese Medicine, Harbin 150010, China

*Wang P, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 82074537); Natural Science Foundation Project of Heilongjiang Province (No. LH2020H103); Heilongjiang Scientific Research Project of Traditional Chinese Medicine (No. ZHY2020-109); Scientific Research Fund Project of Heilongjiang University of Traditional Chinese Medicine (No. 2019MS07).
Received  2022-05-06
Accepted  2022-09-06
DOI: 10.12015/issn.1674-8034.2022.09.027
Co first author: LI Xiaoling DOI:10.12015/issn.1674-8034.2022.09.027.

Petersen RC, Lopez O, Armstrong MJ, et al. Practice guideline update summary: Mildcognitive impairment: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology[J]. Neurology, 2018, 90(3): 126-135. DOI: 10.1212/WNL.0000000000004826.
Sun MK. Potential Therapeutics for Vascular Cognitive Impairment and Dementia[J]. Curr Neuropharmacol, 2018, 16(7): 1036-1044. DOI: 10.2174/1570159X15666171016164734.
Lin Y, Wang K, Ma C, et al. Evaluation of Metformin on Cognitive Improvement in Patients With Non-dementia Vascular Cognitive Impairment and Abnormal Glucose Metabolism[J/OL]. Front Aging Neurosci, 2018 [2022-04-12]. DOI: 10.3389/fnagi.2018.00227.
Li Q, Del Ferraro G, Pasquini L, et al. Core language brain network for fMRI language task used in clinical applications[J]. Netw Neurosci, 2020, 4(1): 134-154. DOI: 10.1162/netna00112.
Wang J, Chen H, Liang H, et al. Low-Frequency Fluctuations Amplitude Signals Exhibit Abnormalities of Intrinsic Brain Activities and Reflect Cognitive Impairment in Leukoaraiosis Patients[J/OL]. Med Sci Monit, 2019 [2022-04-10]. DOI: 10.12659/MSM.915528.
Wang JF, Chen Y, Liang HZ, et al. The role of disturbed small-world networks in patientswith white matter lesions and cognitive impairment revealed by resting state function magnetic resonance images (rs-fMRI)[J/OL]. Med SciMonit, 2019 [2022-04-15]. DOI: 10.12659/MSM.913396.
Jia Q, Huang XH, Liu N, et al. Research progress on resting brain function of cognitive impairment in type 2 diabetes[J]. Chin J Magn Reson Imaging, 2021, 12(10): 89-92. DOI: 10.12015/issn.1674-8034.2021.10.023.
Raichle ME. The brain's default mode network[J/OL]. Annu Rev Neurosci, 2015 [2022-05-02]. DOI: 10.1146/annurev-neuro-071013-014030.
Zhang H, Ding JR, Yan CD, et al. Research progress of rs-fMRI in ischemic whitematter lesions[J]. Chin J Magn Reson Imaging, 2022, 13(4): 154-157. DOI: 10.12015/issn.1674-8034.2022.04.034.
Li H, Jia X, Li Y, et al. Aberrant Amplitude of Low-Frequency Fluctuation and Degree Centrality within the Default Mode Network in Patients with Vascular Mild Cognitive Impairment[J/OL]. Brain Sci, 2021 [2022-05-01]. DOI: 10.3390/brainsci11111534.
Li XL, Cai LN, Cui X, et al. Research progress of magnetic resonance imaging in amnestic mild cognitive impairment[J]. Chin J Magn Reson Imaging, 2021, 12 (11): 94-96. DOI: 10.12015/issn.1674-8034.2021.11.023.
Yang Y, Rui QY, Chen X, et al. Resting state brain functional imaging of cognitive impairment in optic neuromyelitis spectrum diseases based on low frequency amplitu de and local consistency[J]. Chin J Magn Reson Imaging, 2022, 13(4): 62-68. DOI: 10.12015/issn.1674-8034.2022.04.011.
Zang YF, He Y, Zhu CZ, et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI[J]. Brain and Dev, 2007, 29(2): 83-91. DOI: 10.1016/j.braindev.2006.07.002.
Wang Z, Yan C, Zhao C, et al. Spatial pattern so fifintrinsic brain activity in mild cognitive impairment and Alzheimer's disease: a resting-state functional MRI study[J]. Hum Brain Mapp, 2011, 32(10): 1720-1740. DOI: 10.1002/hbm.21140.
Lin HL, Xue YQ, Kang ZW, et al. A preliminary study of resting fMRI in the changes of baseline brain activity in patients with dementia free vascular cognitive impairment[J]. J Clin Radiol, 2013, 32(8): 1070-1074. DOI: 10.13437/j.cnki.jcr.2013.08.034.
Hafkemeijer A, van der Grond J, Rombouts SA. Imaging the default mode network in aging and dementia[J]. Biochim Biophys Acta, 2012, 1822(3): 431-441. DOI: 10.1016/j.bbadis.2011.07.008.
Duan YH, Liang FR, Liu GR. Resting state functional magnetic resonance imaging in patients with subcortical vascular cognitive impairment[J]. Chinese Journal of Integrative Medicine on Cardio/Cerebrovascular Disease, 2019, 7(8): 27-29. DOI: 10.16282/j.cnki.cn11-9336/r.2019.08.016.
Guo HY, Sun F, Ni L, et al. Study on the structure and resting state fMRI of non dementia vascular cognitive impairment[J]. J Clin Radiol, 2014, 33(5): 657-661. DOI: 10.13437/j.cnki.jcr.2014.05.003.
Li L, Chen X, Cao WW, et al. Changes of resting brain function in patients with vascular cognitive impairment under different frequency bands[J]. J Clin Radiol, 2016, 35(9): 1297-1302. DOI: 10.13437/j.cnki.jcr.2016.09.003.
Zang Y, Jiang T, Lu Y, et al. Regional homogeneity approach to fMRI data analysis[J]. NeuroImage, 2004, 22(1): 394-400. DOI: 10.1016/j.neuroimage.2003.12.030.
Liu S, Ma R, Luo Y, et al. Facial Expression Recognition and ReHo Analysis in Major Depressive Disorder[J/OL]. Front Psychol, 2021 [2022-05-01]. DOI: 10.3389/fpsyg.2021.688376.
Zhuang Y, Shi Y, Zhang J, et al. Neurologic Factors in Patients with Vascular Mild Cognitive Impairment Based on fMRI[J/OL]. World Neurosurg, 2021 [2022-05-01]. DOI: 10.1016/j.wneu.2020.11.120.
Peng CY, Chen YC, Cui Y, et al. Regional Coherence Alterations Revealed by Resting-State fMRI in Post-Stroke Patients with Cognitive Dysfunction[J/OL]. PLoS One, 2016 [2022-05-02]. DOI: 10.1371/journal.pone.0159574.
Feng L, Shi QL, Li YX, et al. Changes of whole brain local consistency in patients with white matter lesions with cognitive impairment[J]. Chinese Journal of Medicine, 2020, 55(2): 147-151. DOI: 10.3969/j.issn.1008-1070.2020.02.010.
Frantellizzi V, Pani A, Ricci M, et al. Neuroimaging in Vascular Cognitive Impairmet and Dementia: A Systematic Review[J]. J Alzheimers Dis, 2020, 73(4): 1279-1294. DOI: 10.3233/JAD-191046.
Huang J, Cheng R, Liu X, et al. Abnormal static and dynamic functional connectivity of networks related to cognition in patients with subcortical ischemic vascular disease[J]. Neuroradiology, 2022, 64(6): 1201-1211. DOI: 10.1007/s00234-022-02895-z.
Bi XA, Sun Q, Zhao J, et al. Non-linear ICA Analysis of Resting-State fMRI in Mild Cognitive Impairment[J/OL]. Front Neurosci, 2018 [2022-05-04]. DOI: 10.3389/fnins.2018.00413.
Wu J, Yu Y, Yang Y. Independent component analysis and extraction of functional magnetic resonance images[J]. Progress in Biomedical Engineering, 2018, 39(4): 192-195. DOI: 10.3969/j.issn.1674-1242.2018.04.002.
Damoiseaux JS, Rombouts SA, Barkhof F, et al. Consistent resting-state networks across healthy subjects[J]. Proc Natl Acad Sci USA, 2006, 103(37): 13848-13853. DOI: 10.1073/pnas.0601417103.
Shi Q L, Chen H Y, Jia Q, et al. Altered Granger Causal Connectivity of Resting-State Neural Networks in Patients With Leukoaraiosis-Associated Cognitive Impairment-A Cross-Sectional Study[J/OL]. Front Neurol, 2020 [2022-05-06]. DOI: 10.3389/fneur.2020.00457.
Song X, Panych LP, Chen NK. Data-Driven and Predefined ROI-Based Quantification of Long-Term Resting-State fMRI Reproducibility[J]. Brain Connect, 2016, 6(2): 136-151. DOI: 10.1089/brain.2015.0349.
Azeez AK, Biswal BB. A Review of Resting-State Analysis Methods[J]. Neuroimaging Clin N Am, 2017, 27(4): 581-592. DOI: 10.1016/j.nic.2017.06.001.
Sun YW, Qin LD, Zhou Y, et al. Abnormal functional connectivity in patients with vascular cognitive impairment, no dementia: a resting-state functional magnetic resonance imaging study[J]. Behav Brain Res, 2011, 223(2): 388-394. DOI: 10.1016/j.bbr.2011.05.006.
Choi Y, Jung IC, Kim AR, et al. Feasibility and Effect of Electroacupuncture on Cognitive Function Domains in Patients with Mild Cognitive Impairment: A Pilot Exploratory Randomized Controlled Trial[J/OL]. Brain Sci, 2021 [2022-04-27]. DOI: 10.3390/brainsci11060756.
Chen Y, Wang C, Liang H, et al. Resting-state functional magnetic resonance imaging in patients with leukoaraiosis-associated subcortical vascular cognitive impairment: a cross-sectional study[J]. Neurological Research, 2016, 38(6): 510-517. DOI: 10.1080/01616412.2016.1177929.
Lin R, Huang J, Xu J, et al. Effect and Neuroimaging Mechanism of Electroacupuncture for Vascular Cognitive Impairment No Dementia: Study Protocol for a Randomized, Assessor-Blind, Controlled Clinical Trial[J/OL]. Evid Based Complement Alternat Med, 2020 [2022-05-05]. DOI: 10.1155/2020/7190495.
Yi LY, Liang X, Liu DM, et al. Disrupted topological organization of resting-state functional brain network in subcortical vascular mild cognitive impairment[J/OL]. CNS Neurosci Ther, 2015 [2022-04-20]. DOI: 10.1111/cns.12424.
Zhao X, Wu J, Peng H, et al. Deep reinforcement learning guided graph neural networks for brain network analysis[J/OL]. Neural Netw, 2022 [2022-05-05]. DOI: 10.1016/j.neunet.2022.06.035.
Lei Y, Song BS, Chen L, et al. Reconfifigured functional network dynamics in adult moyamoya disease: a resting-state fMRI study[J]. Brain Imaging Behav, 2020, 14(3): 715-727. DOI: 10.1007/s11682-018-0009-8.
Watts DJ, Strogatz SH. Collective dynamics of 'small-world' networks[J]. Nature, 1998, 393(6684): 440-442. DOI: 10.1038/30918.
He MX, Ping LL, Xu XF. Research progress of complex brain network analysis based on graph theory in mental diseases[J]. Journal of Kunming Medical University, 2019, 40(5): 129-134.
Li R, Li S, Roh J, et al. Multimodal Neuroimaging Using Concurrent EEG/fNIRS for Poststroke Recovery Assessment: An Exploratory Study[J]. Neurorehabil Neural Repai r, 2020, 34(12): 1099-1100. DOI: 10.1177/1545968320969937.
Yu Y, Zhou X, Wang H, et al. Small-World Brain Network and Dynamic Functional Distribution in Patients with Subcortical Vascular Cognitive Impairment[J/OL]. PLoS One, 2015 [2022-04-25]. DOI: 10.1371/journal.pone.0131893.
Wang JF, Chen HY, Li YX, et al. Resting fMRI study on the small world attribute of brain function network in patients with leukoaraiosis[J]. Chinese Journal of Behavioral Medicine and Brain Science, 2017, 26(11): 977-982. DOI: 10.3760/cma.j.issn.1674-6554.2017.11.004.
Sang L, Chen L, Wang L, et al. Progressively Disrupted Brain Functional Connectivity Network in Subcortical Ischemic Vascular Cognitive Impairment Patients[J/OL]. Front Neurol, 2018 [2022-04-23]. DOI: 10.3389/fneur.2018.00094.
Guan Y, Zhu LW, Li XL, et al. Application of different RS fMRI data processing methods in vascular cognitive impairment[J]. Journal of rehabilitation, 2019, 29(1): 70-74. DOI: 10.3724/SP.J.1329.2019.01070.

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