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Research advance on resting-state functional magnetic resonance imaging in the early diagnosis of Alzheimer's disease
HE Yujie  YAN Shaozhen  LU Jie 

Cite this article as: HE Y J, YAN S Z, LU J. Research advance on resting-state functional magnetic resonance imaging in the early diagnosis of Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2024, 15(1): 173-178. DOI:10.12015/issn.1674-8034.2024.01.029.


[Abstract] Alzheimer's disease (AD) is a degenerative disease of the central nervous system characterized by cognitive impairment. There is a preclinical period of approximately 20 years before the onset of clinical symptoms, making it the optional time window for disease intervention. Therefore, the early diagnosis of AD is essential for disease delay and prognosis improvement. Resting-state functional magnetic resonance imaging (rs-fMRI) has the advantages of non-invasive and high spatial-temporal resolution. It is one of the most widely used neuroimaging techniques to study brain functional activity abnormalities in AD, which provides the possibility to find non-invasive markers of early AD. Based on rs-fMRI techniques, we reviewed the application value in the early diagnosis of AD in this article, in order to find non-invasive imaging markers for early monitoring of AD.
[Keywords] Alzheimer's disease；mild cognitive impairment；subjective cognitive decline；resting-state functional magnetic resonance imaging；magnetic resonance imaging；early diagnosis

HE Yujie   YAN Shaozhen   LU Jie*  

Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing Key Laboratory of MRI and Brain Informatics, Key Laboratory of Neurodegenerative Diseases, Ministry of Education, Beijing 100053, China

Corresponding author: LU J, E-mail: imaginglu@hotmail.com

Conflicts of interest   None.

Received  2023-09-07
Accepted  2023-12-07
DOI: 10.12015/issn.1674-8034.2024.01.029
Cite this article as: HE Y J, YAN S Z, LU J. Research advance on resting-state functional magnetic resonance imaging in the early diagnosis of Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2024, 15(1): 173-178. DOI:10.12015/issn.1674-8034.2024.01.029.

[1]
JESSEN F, WOLFSGRUBER S, KLEINEINDAM L, et al. Subjective cognitive decline and stage 2 of Alzheimer disease in patients from memory centers[J]. Alzheimer's & Dementia, 2023, 19: 487-497. DOI: 10.1002/alz.12674.
[2]
MONDINI S, PUCCI V, MONTEMURRO S, et al. Protective factors for subjective cognitive decline individuals: trajectories and changes in a longitudinal study with Italian elderly[J]. Eur J Neurol, 2022, 29: 691-697. DOI: 10.1111/ene.15183.
[3]
MCGRATTAN A M, PAKPAHAN E, SIERVO M, et al. Risk of conversion from mild cognitive impairment to dementia in low- and middle-income countries: A systematic review and meta-analysis[J/OL]. Alzheimers Dement (N Y), 2022, 8: e12267 [2023-09-07]. https://pubmed.ncbi.nlm.gov/35310524/. DOI: 10.1002/trc2.12267.
[4]
LI Q, YUE X P, BAI Y, et al. Application value of multi-modal imaging technique in early diagnosis of Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2022, 13(11): 110-114. DOI: 10.12015/issn.1674-8034.2022.11.021.
[5]
ZHANG Y L, WANG J, ZHANG Z N, et al. The relationship between amyloid-beta and brain capillary endothelial cells in Alzheimer's disease[J]. Neural Regen Res, 2022, 17: 2355-2363. DOI: 10.4103/1673-5374.335829.
[6]
JIANG D, LIU L, KONG Y, et al. Regional glymphatic abnormality in behavioral variant frontotemporal dementia[J]. Ann Neurol, 2023, 94: 442-456. DOI: 10.1002/ana.26710.
[7]
HAN F, CHEN J, BELKIN-ROSEN A, et al. Reduced coupling between cerebrospinal fluid flow and global brain activity is linked to Alzheimer disease-related pathology[J/OL]. PLoS Biol, 2021, 19: e3001233 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/34061820/. DOI: 10.1371/journal.pbio.3001233.
[8]
ALORF A, KHAN M U G. Multi-label classification of Alzheimer's disease stages from resting-state fMRI-based correlation connectivity data and deep learning[J/OL]. Comput Biol Med, 2022, 151: 106240 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/36423532/. DOI: 10.1016/j.compbiomed.2022.106240.
[9]
LI S, DAAMEN M, SCHEEF L, et al. Abnormal regional and global connectivity measures in subjective cognitive decline depending on cerebral amyloid status[J]. J Alzheimers Dis, 2021, 79: 493-509. DOI: 10.3233/jad-200472.
[10]
CAO T, LIN R, ZHENG Y, et al. A novel approach analysing the dynamic brain functional connectivity for improved MCI detection[J]. IEEE Trans Biomed Eng, 2024, 71(1): 207-216. DOI: 10.1109/tbme.2023.3294511.
[11]
DENG S, FRANKLIN C G, O'BOYLE M, et al. Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults[J/OL]. Neuroimage, 2022, 250: 118923 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/35066157/. DOI: 10.1016/j.neuroimage.2022.118923.
[12]
LI G Z, LIU P H, ZHANG A X, et al. A resting state fMRI study of major depressive disorder with and without anxiety[J/OL]. Psychiatry Res, 2022, 315: 114697 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/35839636/. DOI: 10.1016/j.psychres.2022.114697.
[13]
CANARIO E, CHEN D, BISWAL B. A review of resting-state fMRI and its use to examine psychiatric disorders[J]. Psychoradiology, 2021, 1: 42-53. DOI: 10.1093/psyrad/kkab003.
[14]
ABREU R, JORGE J, LEAL A, et al. EEG Microstates Predict Concurrent fMRI dynamic functional connectivity states[J]. Brain Topogr, 2021, 34: 41-55. DOI: 10.1007/s10548-020-00805-1.
[15]
JIANG X, HU X, DAAMEN M, et al. Altered limbic functional connectivity in individuals with subjective cognitive decline: Converging and diverging findings across Chinese and German cohorts[J/OL]. Alzheimers Dement, 2023 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/37070734/. DOI: 10.1002/alz.13068.
[16]
ZHANG Z, CUI L, HUANG Y, et al. Changes of regional neural activity homogeneity in preclinical Alzheimer's disease: Compensation and dysfunction[J/OL]. Front Neurosci, 2021, 15: 646414 [2023-11-30]. https://pubmed.ncbi.nlm.nih.gov/34220418/. DOI: 10.3389/fnins.2021.646414.
[17]
PALMQVIST S, SCHOLL M, STRANDBERG O, et al. Earliest accumulation of beta-amyloid occurs within the default-mode network and concurrently affects brain connectivity[J/OL]. Nat Commun, 2017, 8: 1214 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/37070734/. DOI: 10.1038/s41467-017-01150-x.
[18]
VIVIANO R P, HAYES J M, PRUITT P J, et al. Aberrant memory system connectivity and working memory performance in subjective cognitive decline[J]. Neuroimage, 2019, 185: 556-564. DOI: 10.1016/j.neuroimage.2018.10.015.
[19]
BUCKNER R L, SEPULCRE J, TALUKDAR T, et al. Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease[J]. J Neurosci, 2009, 29: 1860-1873. DOI: 10.1523/JNEUROSCI.5062-08.2009.
[20]
BUCKNER R L, SNYDER A Z, SHANNON B J, et al. Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory[J]. J Neurosci, 2005, 25: 7709-7717. DOI: 10.1523/jneurosci.2177-05.2005.
[21]
HAN F, LIU X, MAILMAN R B, et al. Resting-state global brain activity affects early beta-amyloid accumulation in default mode network[J/OL]. Nat Commun, 2023, 14: 7788 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/38012153/. DOI: 10.1038/s41467-023-43627-y.
[22]
WANG S, SUN H, HU G, et al. Altered insular subregional connectivity associated with cognitions for distinguishing the spectrum of pre-clinical Alzheimer's disease[J/OL]. Front Aging Neurosci, 2021, 13: 597455 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/33643021/. DOI: 10.3389/fnagi.2021.597455.
[23]
YANG L, YAN Y, WANG Y, et al. Gradual disturbances of the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF in Alzheimer spectrum[J/OL]. Front Neurosci, 2018, 12: 975 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/30618593/. DOI: 10.3389/fnins.2018.00975.
[24]
CHEN H, SHENG X, LUO C, et al. The compensatory phenomenon of the functional connectome related to pathological biomarkers in individuals with subjective cognitive decline[J/OL]. Transl Neurodegener, 2020, 9: 21 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/32460888/. DOI: 10.1186/s40035-020-00201-6.
[25]
YUE J, HAN S W, LIU X, et al. Functional brain activity in patients with amnestic mild cognitive impairment: an rs-fMRI study[J/OL]. Front Neurol, 2023, 14: 1244696 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/37674874/. DOI: 10.3389/fneur.2023.1244696.
[26]
WU H, SONG Y, YANG X, et al. Functional and structural alterations of dorsal attention network in preclinical and early-stage Alzheimer's disease[J]. CNS Neurosci Ther, 2023, 29: 1512-1524. DOI: 10.1111/cns.14092.
[27]
LIANG X, YUAN Q, XUE C, et al. Convergent functional changes of the episodic memory impairment in mild cognitive impairment: An ALE meta-analysis[J/OL]. Front Aging Neurosci, 2022, 14: 919859 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/35912082/. DOI: 10.3389/fnagi.2022.919859.
[28]
ZHANG X, XUE C, CAO X, et al. Altered patterns of amplitude of low-frequency fluctuations and fractional amplitude of low-frequency fluctuations between amnestic and vascular mild cognitive impairment: An ALE-based comparative meta-analysis[J/OL]. Front Aging Neurosci, 2021, 13: 711023 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/34531735/. DOI: 10.3389/fnagi.2021.711023.
[29]
CHUNG S E, KIM H J, JO S, et al. Patterns of focal amyloid deposition using (18)F-Florbetaben PET in patients with cognitive impairment[J/OL]. Diagnostics (Basel), 2022, 12 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/35741166/. DOI: 10.3390/diagnostics12061357.
[30]
KATO T, INUI Y, NAKAMURA A, et al. Brain fluorodeoxyglucose (FDG) PET in dementia[J]. Ageing Res Rev, 2016, 30: 73-84. DOI: 10.1016/j.arr.2016.02.003.
[31]
PASQUINI L, BENSON G, GROTHE M J, et al. Individual correspondence of amyloid-beta and intrinsic connectivity in the posterior default mode network across stages of Alzheimer's disease[J]. J Alzheimers Dis, 2017, 58: 763-773. DOI: 10.3233/JAD-170096.
[32]
SCHEEL N, TARUMI T, TOMOTO T, et al. Resting-state functional MRI signal fluctuation amplitudes are correlated with brain amyloid-beta deposition in patients with mild cognitive impairment[J]. J Cereb Blood Flow Metab, 2022, 42: 876-890. DOI: 10.1177/0271678X211064846.
[33]
GAO Y, ZHAO X, HUANG J, et al. Abnormal regional homogeneity in right caudate as a potential neuroimaging biomarker for mild cognitive impairment: A resting-state fMRI study and support vector machine analysis[J/OL]. Front Aging Neurosci, 2022, 14: 979183 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/36118689/. DOI: 10.3389/fnagi.2022.979183.
[34]
ZHU Q, WANG Y, ZHUO C, et al. Classification of Alzheimer's disease based on abnormal hippocampal functional connectivity and machine learning[J]. Front Aging Neurosci, 2022, 14: 754334 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/35273489/. DOI: 10.3389/fnagi.2022.754334.
[35]
KHATRI U, KWON G R. Alzheimer's disease diagnosis and biomarker analysis using resting-state functional MRI functional brain network with multi-measures features and hippocampal subfield and amygdala volume of structural MRI[J/OL]. Front Aging Neurosci, 2022, 14: 818871 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/35707703/. DOI: 10.3389/fnagi.2022.818871.
[36]
IBRAHIM B, SUPPIAH S, IBRAHIM N, et al. Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review[J]. Hum Brain Mapp, 2021, 42: 2941-2968. DOI: 10.1002/hbm.25369.
[37]
SHE Y X, WANG S W, MA W L, et al. Regional homogeneity of Alzheimer's disease at resting-state and voxel-mirrored homotopic connectivity[J]. Chin J Med Imaging, 2018, 26(10): 721-725. DOI: 10.3969/j.issn.1005-5185.2018.10.001.
[38]
ZHENG W, CUI B, HAN Y, et al. Disrupted regional cerebral blood flow, functional activity and connectivity in Alzheimer's disease: A combined ASL perfusion and resting state fMRI study[J/OL]. Front Neurosci, 2019, 13: 738 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/31396033/. DOI: 10.3389/fnins.2019.00738.
[39]
ZHAO C, HUANG W J, FENG F, et al. Abnormal characterization of dynamic functional connectivity in Alzheimer's disease[J]. Neural Regen Res, 2022, 17: 2014-2021. DOI: 10.4103/1673-5374.332161.
[40]
ZHANG Q, WANG Q, HE C, et al. Altered regional cerebral blood flow and brain function across the Alzheimer's disease spectrum: A potential biomarker[J/OL]. Front Aging Neurosci, 2021, 13: 630382 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/33692680/. DOI: 10.3389/fnagi.2021.630382.
[41]
MOHTASIB R, ALGHAMDI J, JOBEIR A, et al. MRI biomarkers for Alzheimer's disease: the impact of functional connectivity in the default mode network and structural connectivity between lobes on diagnostic accuracy[J/OL]. Heliyon, 2022, 8: e08901 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/35198768/. DOI: 10.1016/j.heliyon.2022.e08901.
[42]
PARK J E, PARK B, KIM S J, et al. Improved diagnostic accuracy of Alzheimer's disease by combining regional cortical thickness and default mode network functional connectivity: Validated in the Alzheimer's disease neuroimaging initiative set[J]. Korean J Radiol, 2017, 18: 983-991. DOI: 10.3348/kjr.2017.18.6.983.
[43]
ZHANG Q, FAN C, WANG L, et al. Glucose metabolism in posterior cingulate cortex has supplementary value to predict the progression of cognitively unimpaired to dementia due to Alzheimer's disease: an exploratory study of (18)F-FDG-PET[J/OL]. Geroscience, 2023 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/37610594/. DOI: 10.1007/s11357-023-00897-0.
[44]
KANG D W, CHOI W H, JUNG W S, et al. Impact of amyloid burden on regional functional synchronization in the cognitively normal older adults[J/OL]. Sci Rep, 2017, 7: 14690 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/29089631/. DOI: 10.1038/s41598-017-15001-8.
[45]
YOON H J, KIM B S, JEONG J H, et al. Asymmetric amyloid deposition as an early sign of progression in mild cognitive impairment due to Alzheimer disease[J]. Clin Nucl Med, 2021, 46: 527-531. DOI: 10.1097/rlu.0000000000003662.
[46]
LUBBEN N, ENSINK E, COETZEE G A, et al. The enigma and implications of brain hemispheric asymmetry in neurodegenerative diseases[J/OL]. Brain Commun, 2021, 3: fcab211 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/34557668/. DOI: 10.1093/braincomms/fcab211.
[47]
CAI S, WANG Y, KANG Y, et al. Differentiated regional homogeneity in progressive mild cognitive impairment: A study with post hoc label[J]. Am J Alzheimers Dis Other Demen, 2018, 33: 373-384. DOI: 10.1177/1533317518778513.
[48]
KJELDSEN P L, PARBO P, HANSEN K V, et al. Asymmetric amyloid deposition in preclinical Alzheimer's disease: A PET study[J/OL]. Aging Brain, 2022, 2: 100048 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/36908895/. DOI: 10.1016/j.nbas.2022.100048.
[49]
SACHER C, BLUME T, BEYER L, et al. Asymmetry of fibrillar plaque burden in amyloid mouse models[J]. J Nucl Med, 2020, 61: 1825-1831. DOI: 10.2967/jnumed.120.242750.
[50]
HU Q, WANG Q, LI Y, et al. Intrinsic brain activity alterations in patients with mild cognitive impairment-to-normal reversion: A resting-state functional magnetic resonance imaging study from voxel to whole-brain level[J/OL]. Front Aging Neurosci, 2021, 13: 788765 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/35111039/. DOI: 10.3389/fnagi.2021.788765.
[51]
PAN P, ZHU L, YU T, et al. Aberrant spontaneous low-frequency brain activity in amnestic mild cognitive impairment: A meta-analysis of resting-state fMRI studies[J]. Ageing Res Rev, 2017, 35: 12-21. DOI: 10.1016/j.arr.2016.12.001.
[52]
QIAO Z, YUAN L L, ZHAO X B, et al. Dynamic functional connectivity analysis of stable and progressive mild cognitive impairment[J]. Chin J Magn Reson Imaging, 2022, 13(08): 1-6. DOI: 10.12015/issn.1674-8034.2022.08.001.
[53]
ZHANG T, LIAO Q, ZHANG D, et al. Predicting MCI to AD conversation using integrated sMRI and rs-fMRI: Machine learning and graph theory approach[J/OL]. Front Aging Neurosci, 2021, 13: 688926 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/34421570/. DOI: 10.3389/fnagi.2021.688926.
[54]
HEIJ J, RAIMONDO L, SIERO J C W, et al. A selection and targeting framework of cortical locations for line-scanning fMRI[J]. Hum Brain Mapp, 2023, 44: 5471-5484. DOI: 10.1002/hbm.26459.
[55]
RAIMONDO L, OLIVEIRA L A F, HEIJ J, et al. Advances in resting state fMRI acquisitions for functional connectomics[J/OL]. Neuroimage, 2021, 243: 118503 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/34479041/. DOI: 10.1016/j.neuroimage.2021.118503.
[56]
GONNEAUD J, BARIA A T, PICHET BINETTE A, et al. Accelerated functional brain aging in pre-clinical familial Alzheimer's disease[J/OL]. Nat Commun, 2021, 12: 5346 [2023-09-07]. https://pubmed.ncbi.nlm.nih.gov/34504080/. DOI: 10.1038/s41467-021-25492-9.

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