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Research progress of magnetic resonance 3D-TIWI and diffusion imaging in Alzheimer's disease
LI Linqin  DUAN Huanqin  QIU Lihua 

Cite this article as LI L Q, DUAN H Q, QIU L H. Research progress of magnetic resonance 3D-TIWI and diffusion imaging in Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2024, 15(5): 181-186. DOI:10.12015/issn.1674-8034.2024.05.029.


[Abstract] Alzheimer's disease (AD) is the most common neurodegenerative disease. The main symptoms are progressive memory decline and cognitive dysfunction. The incidence rate is on the rise, and there is a lack of effective treatment. Therefore, early diagnosis, prevention and delay of AD are essential. In recent years, MRI has been widely used in the study of AD and other cognitive impairment fields. Three-dimensional T1 weighted imaging (3D-T1WI), diffusion MRI can objectively and indirectly reflect abnormal brain structural changes, providing imaging evidence for explaining their mechanisms. This article provides a review of the application of 3D-T1WI, diffusion MRI in AD, exploring the changes in brain structure and pathophysiological mechanisms of AD patient from multiple perspectives, and providing assistance for the early diagnosis of AD.
[Keywords] Alzheimer's disease;magnetic resonance imaging;three-dimensional T1 weighted imaging;diffusion tensor imaging;diffusion kurtosis imaging;neurite direction dispersion and density imaging;brain structure;pathophysiological mechanism;early diagnosis

LI Linqin1, 2   DUAN Huanqin2, 3   QIU Lihua1, 2, 4*  

1 School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China

2 Medical Imaging Center, Second People's Hospital of Yibin, Yibin 644000, China

3 Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China

4 Clinical Medical Research and Transformation Center, the Second People's Hospital of Yibin City-West China Yibin Hospital, Sichuan Univerity, Neuroimaging Big Data Research Center, Yibin 644000, China

Corresponding author: QIU L H, E-mail: qlh20050616@foxmail.com

Conflicts of interest   None.

Received  2024-01-20
Accepted  2024-04-30
DOI: 10.12015/issn.1674-8034.2024.05.029
Cite this article as LI L Q, DUAN H Q, QIU L H. Research progress of magnetic resonance 3D-TIWI and diffusion imaging in Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2024, 15(5): 181-186. DOI:10.12015/issn.1674-8034.2024.05.029.

[1]
DOU K X, TAN L, YU J T. The risk factors and prevention for Alzheimer's disease[J]. Chinese Journal of Behavioral Medicine and Brain Science, 2019, 28(4): 305-10. DOI: 10.3760/cma.j.issn.1674-6554.2019.04.004.
[2]
TUO Z J, ZHAO Y J, SHANG P J, et al. Recent advance in abnormal neuronal and astrocytic calcium signalw involved in Alzheimer's disease progression[J]. Chin J Neuromed, 2022, 21(6): 624-628. DOI: 10.3760/cma.j.cn115354-20211211-00808.
[3]
CHANDRA A, VALKIMADI P E, PAGANO G, et al. Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment[J]. Hum Brain Mapp, 2019, 40(18): 5424-5442. DOI: 10.1002/hbm.24782.
[4]
YU L, HE X L. Preliminary evaluation of common experimental animal models for Alzheimer's disease and mild cognitive impairment[J]. Chinese Pharmacological Bulletin, 2020, 36(1): 1-5. DOI: 10.3969/j.issn.1001-1978.2020.01.001.
[5]
CONVIT A, DE LEON M J, TARSHISH C, et al. Specific hippocampal volume reductions in individuals at risk for Alzheimer's disease[J]. Neurobiol Aging, 1997, 18(2): 131-138. DOI: 10.1016/s0197-4580(97)00001-8.
[6]
BACHMANN T, SCHROETER M L, CHEN K, et al. Longitudinal changes in surface based brain morphometry measures in amnestic mild cognitive impairment and Alzheimer's Disease[J/OL]. Neuroimage Clin, 2023, 38: 103371 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/36924681/. DOI: 10.1016/j.nicl.2023.103371.
[7]
KRAJCOVICOVA L, KLOBUSIAKOVA P, REKTOROVA I. Gray matter changes in Parkinson's and Alzheimer's disease and relation to cognition[J/OL]. Curr Neurol Neurosci Rep, 2019, 19(11): 85 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/31720859/. DOI: 10.1007/s11910-019-1006-z.
[8]
MIAO D, ZHOU X, WU X, et al. Hippocampal morphological atrophy and distinct patterns of structural covariance network in Alzheimer's disease and mild cognitive impairment[J/OL]. Front Psychol, 2022, 13: 980954 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/36160522/. DOI: 10.3389/fpsyg.2022.980954.
[9]
DRENTHEN G S, BACKES W H, FREEZE W M, et al. Rich-club connectivity of the structural covariance network relates to memory processes in mild cognitive impairment and Alzheimer's disease[J]. J Alzheimers Dis, 2022, 89(1): 209-217. DOI: 10.3233/JAD-220175.
[10]
SUN W Y, SHI X H, FAN Y, et al. Research progress of MRI in cognitive impairment of Parkinson's disease[J]. Chin J Magn Reson Imaging, 2023, 14(7): 134-138. DOI: 10.12015/issn.1674-8034.2023.07.024.
[11]
HUANG H, ZHENG S, YANG Z, et al. Voxel-based morphometry and a deep learning model for the diagnosis of early Alzheimer's disease based on cerebral gray matter changes[J]. Cereb Cortex, 2023, 33(3): 754-763. DOI: 10.1093/cercor/bhac099.
[12]
PINI L, PIEVANI M, BOCCHETTA M, et al. Brain atrophy in Alzheimer's Disease and aging[J]. Ageing Res Rev, 2016, 30: 25-48. DOI: 10.1016/j.arr.2016.01.002.
[13]
MAO C, HOU B, LI J, et al. Distribution of cortical atrophy associated with cognitive decline in Alzheimer's disease: A cross-sectional quantitative structural MRI study from PUMCH dementia cohort[J]. Curr Alzheimer Res, 2022, 19(8): 618-627. DOI: 10.2174/1567205019666220905145756.
[14]
MINKOVA L, HABICH A, PETER J, et al. Gray matter asymmetries in aging and neurodegeneration: A review and meta-analysis[J]. Hum Brain Mapp, 2017, 38(12): 5890-5904. DOI: 10.1002/hbm.23772.
[15]
CONVIT A, DE ASIS J, DE LEON M J, et al. Atrophy of the medial occipitotemporal, inferior, and middle temporal gyri in non-demented elderly predict decline to Alzheimer's disease[J]. Neurobiol Aging, 2000, 21(1): 19-26. DOI: 10.1016/s0197-4580(99)00107-4.
[16]
YU Y L, XIAO Z B, ZHANG H, et al. Alterations in gray matter volume and brain function in Alzheimer disease and mild cognitive impairmen[J]. Chin J Med Imag Technol, 2021, 37(2): 200-205. DOI: 10.13929/j.issn.1003-3289.2021.02.009.
[17]
TUOKKOLA T, KARRASCH M, KOIKKALAINEN J, et al. Association between deep gray matter changes and neurocognitive function in mild cognitive impairment and Alzheimer's disease: A tensor-based morphometric MRI study[J]. Dement Geriatr Cogn Disord, 2019, 48(1-2): 68-78. DOI: 10.1159/000502476.
[18]
LUO S L, LI X S, ZHU W Q, et al. Sex differences in gray matter volume change in Alzheimer's disease and their correlations with cognitive impairment[J]. Acta Universitatis Medicinalis Anhui, 2021, 56(10): 1650-1655. DOI: 10.19405/j.cnki.issn1000-1492.2021.10.028.
[19]
GAO L, GU L, SHU H, et al. The reduced left hippocampal volume related to the delayed P300 latency in amnestic mild cognitive impairment[J]. Psychol Med, 2021, 51(12): 2054-2062. DOI: 10.1017/S0033291720000811.
[20]
HENRIQUES A D, BENEDET A L, CAMARGOS E F, et al. Fluid and imaging biomarkers for Alzheimer's disease: Where we stand and where to head to[J]. Exp Gerontol, 2018, 107: 169-177. DOI: 10.1016/j.exger.2018.01.002.
[21]
GOTO M, ABE O, HAGIWARA A, et al. Advantages of using both voxel- and surface-based morphometry in cortical morphology analysis: A review of various applications[J]. Magn Reson Med Sci, 2022, 21(1): 41-57. DOI: 10.2463/mrms.rev.2021-0096.
[22]
SHENG L, ZHAO P, MA H, et al. Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis[J]. Aging (Albany NY), 2021, 13(3): 4007-4023. DOI: 10.18632/aging.202368.
[23]
RECHBERGER S, LI Y, KOPETZKY S J, et al. Automated high-definition MRI processing routine robustly detects longitudinal morphometry changes in Alzheimer's disease patients[J/OL]. Front Aging Neurosci, 2022, 14: 832828 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/35747446/. DOI: 10.3389/fnagi.2022.832828.
[24]
TUSTISON N J, HOLBROOK A J, AVANTS B B, et al. Longitudinal mapping of cortical thickness measurements: An Alzheimer's disease neuroimaging initiative-based evaluation study[J]. J Alzheimers Dis, 2019, 71(1): 165-183. DOI: 10.3233/JAD-190283.
[25]
CHEN F, WANG Z G, WU S C, et al. Automatic brain structural features extraction and classification in Alzheimer's disease based on independent component analysis and support vector machine[J]. China Journal of Alzheimer's Disease and Related Disorders, 2019, 2(4): 504-509. DOI: 10.3969/j.issn.2096-5516.2019.04.009.
[26]
GROECHEL R C, TRIPODIS Y, ALOSCO M L, et al. Biomarkers of Alzheimer's disease in Black and/or African American Alzheimer's Disease Neuroimaging Initiative (ADNI) participants[J]. Neurobiol Aging, 2023, 131: 144-152. DOI: 10.1016/j.neurobiolaging.2023.07.021.
[27]
HAN L, JIANG H, YAO X, et al. Revealing the correlations between brain cortical characteristics and susceptibility genes for Alzheimer disease: a cross-sectional study[J]. Quant Imaging Med Surg, 2023, 13(4): 2451-2465. DOI: 10.21037/qims-22-602.
[28]
VAN OOSTVEEN W M, DE LANGE E C M. Imaging techniques in Alzheimer's disease: A review of applications in early diagnosis and longitudinal monitoring[J/OL]. Int J Mol Sci, 2021, 22(4): 2110 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/33672696/. DOI: 10.3390/ijms22042110.
[29]
LI K, QU H, MA M, et al. Correlation between brain structure atrophy and plasma amyloid-beta and phosphorylated tau in patients with Alzheimer's disease and amnestic mild cognitive impairment explored by surface-based morphometry[J/OL]. Front Aging Neurosci, 2022, 14: 816043 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/35547625/. DOI: 10.3389/fnagi.2022.816043.
[30]
YANG H, XU H, LI Q, et al. Study of brain morphology change in Alzheimer's disease and amnestic mild cognitive impairment compared with normal controls[J/OL]. Gen Psychiatr, 2019, 32(2): e100005 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/31179429/. DOI: 10.1136/gpsych-2018-100005.
[31]
DICKERSON B C, FECZKO E, AUGUSTINACK J C, et al. Differential effects of aging and Alzheimer's disease on medial temporal lobe cortical thickness and surface area[J]. Neurobiol Aging, 2009, 30(3): 432-440. DOI: 10.1016/j.neurobiolaging.2007.07.022.
[32]
IANNOPOLLO E, GARCIA K, Alzheimer' Disease Neuroimaging Initiative. Enhanced detection of cortical atrophy in Alzheimer's disease using structural MRI with anatomically constrained longitudinal registration[J]. Hum Brain Mapp, 2021, 42(11): 3576-3592. DOI: 10.1002/hbm.25455.
[33]
QIN Y, CUI J, GE X, et al. Hierarchical multi-class Alzheimer's disease diagnostic framework using imaging and clinical features[J/OL]. Front Aging Neurosci, 2022, 14: 935055 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/36034132/. DOI: 10.3389/fnagi.2022.935055.
[34]
SERRA L, GIANCATERINO G, GIULIETTI G, et al. Cognitive reserve modulates brain structure and cortical architecture in the Alzheimer's disease[J]. J Alzheimers Dis, 2022, 89(3): 811-824. DOI: 10.3233/JAD-220377.
[35]
NUNEZ C, CALLEN A, LOMBARDINI F, et al. Different cortical gyrification patterns in Alzheimer's disease and impact on memory performance[J]. Ann Neurol, 2020, 88(1): 67-80. DOI: 10.1002/ana.25741.
[36]
QIU Y H, CHEN Q Y, SHI L W, et al. Clinical diagnosis value of multi-b value diffusion weighted imaging in Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2023, 14(12): 6-14. DOI: 10.12015/issn.1674-8034.2023.12.002.
[37]
YAN Z, WANG X, ZHU Q, et al. Alterations in white matter fiber tracts characterized by automated fiber-tract quantification and their correlations with cognitive impairment in neuromyelitis optica spectrum disorder patients[J/OL]. Front Neurosci, 2022, 16: 904309 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/35844220/. DOI: 10.3389/fnins.2022.904309.
[38]
RASHIDI F, KHANMIRZAEI M H, HOSSEINZADEH F, et al. Cingulum and uncinate fasciculus microstructural abnormalities in Parkinson's disease: A systematic review of diffusion tensor imaging studies[J/OL]. Biology (Basel), 2023, 12(3): 475 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/36979166/. DOI: 10.3390/biology12030475.
[39]
AMLIEN I K, FJELL A M. Diffusion tensor imaging of white matter degeneration in Alzheimer's disease and mild cognitive impairment[J]. Neuroscience, 2014, 276: 206-215. DOI: 10.1016/j.neuroscience.2014.02.017.
[40]
MAGALHAES T N C, CASSEB R F, GERBELLI C L B, et al. Whole-brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease[J/OL]. Brain Behav, 2023, 13(2): e2863 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/36601694/. DOI: 10.1002/brb3.2863.
[41]
GORGES M, MULLER H P, LIEPELT-SCARFONE I, et al. Structural brain signature of cognitive decline in Parkinson's disease: DTI-based evidence from the LANDSCAPE study[J/OL]. Ther Adv Neurol Disord, 2019, 12: 1756286419843447 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/31205489/. DOI: 10.1177/1756286419843447.
[42]
LUO C, LI M, QIN R, et al. Long longitudinal tract lesion contributes to the progression of Alzheimer's disease[J/OL]. Front Neurol, 2020, 11: 503235 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/33178095/. DOI: 10.3389/fneur.2020.503235.
[43]
ZHANG X, SUN Y, LI W, et al. Characterization of white matter changes along fibers by automated fiber quantification in the early stages of Alzheimer's disease[J/OL]. Neuroimage Clin, 2019, 22: 101723 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/30798166/. DOI: 10.1016/j.nicl.2019.101723.
[44]
KUMAR A, SINGH S, SINGH A, et al. Diffusion tensor imaging based white matter changes and antioxidant enzymes status for early identification of mild cognitive impairment[J]. Int J Neurosci, 2019, 129(3): 209-216. DOI: 10.1080/00207454.2018.1521401.
[45]
YU B, DING Z, WANG L, et al. Application of diffusion tensor imaging based on automatic fiber quantification in Alzheimer's disease[J]. Curr Alzheimer Res, 2022, 19(6): 469-478. DOI: 10.2174/1567205019666220718142130.
[46]
QIN L, GUO Z, MCCLURE M A, et al. White matter changes from mild cognitive impairment to Alzheimer's disease: a meta-analysis[J]. Acta Neurol Belg, 2021, 121(6): 1435-1447. DOI: 10.1007/s13760-020-01322-5.
[47]
NOWRANGI M A, ROSENBERG P B. The fornix in mild cognitive impairment and Alzheimer's disease[J/OL]. Front Aging Neurosci, 2015, 7: 1 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/25653617/. DOI: 10.3389/fnagi.2015.00001.
[48]
SHAIKH I, BEAULIEU C, GEE M, et al. Diffusion tensor tractography of the fornix in cerebral amyloid angiopathy, mild cognitive impairment and Alzheimer's disease[J/OL]. Neuroimage Clin, 2022, 34: 103002 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/35413649/. DOI: 10.1016/j.nicl.2022.103002.
[49]
SUN X R, WANG X C, ZHANG H, et al. Research progress of diffusion magnetic resonance imaging in mild cognitive impairment[J]. Chin J Magn Reson Imaging, 2021, 12(1): 70-72, 84. DOI: 10.12015/issn.1674-8034.2021.01.015.
[50]
RAJ S, VYAS S, MODI M, et al. Comparative evaluation of diffusion kurtosis imaging and diffusion tensor imaging in detecting cerebral microstructural changes in Alzheimer disease[J]. Acad Radiol, 2022, 29(Suppl 3): S63-S70. DOI: 10.1016/j.acra.2021.01.018.
[51]
NIU X, GUO Y, CHANG Z, et al. The correlation between changes in gray matter microstructure and cerebral blood flow in Alzheimer's disease[J/OL]. Front Aging Neurosci, 2023, 15: 1205838 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/37333456/. DOI: 10.3389/fnagi.2023.1205838.
[52]
ZHANG H, WANG Z, CHAN K H, et al. The use of diffusion kurtosis imaging for the differential diagnosis of Alzheimer's disease spectrum[J/OL]. Brain Sci, 2023, 13(4): 595 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/37190560/. DOI: 10.3390/brainsci13040595.
[53]
KUMAR S, DE LUCA A, LEEMANS A, et al. Topology of diffusion changes in corpus callosum in Alzheimer's disease: An exploratory case-control study[J/OL]. Front Neurol, 2022, 13: 1005406 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/36530616/. DOI: 10.3389/fneur.2022.1005406.
[54]
KAYA I, JENNISCHE E, LANGE S, et al. Brain region-specific amyloid plaque-associated myelin lipid loss, APOE deposition and disruption of the myelin sheath in familial Alzheimer's disease mice[J]. J Neurochem, 2020, 154(1): 84-98. DOI: 10.1111/jnc.14999.
[55]
WU Q, CHEN Y Y, ZHAO X, et al. A review of cognition related macro-microstructural changes based on MRI[J]. Chin J Biomed Eng, 2019, 38(1): 94-101. DOI: 10.3969/j.issn.0258-8021.2019.01.012.
[56]
AZAD A, CABEEN R P, SEPEHRBAND F, et al. Microstructural properties within the amygdala and affiliated white matter tracts across adolescence[J/OL]. Neuroimage, 2021, 243: 118489 [2024-01-20]. https://pubmed.ncbi.nlm.nih.gov/34450260/. DOI: 10.1016/j.neuroimage.2021.118489.
[57]
ZHANG H, SCHNEIDER T, WHEELER-KINGSHOTT C A, et al. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain[J]. Neuroimage, 2012, 61(4): 1000-1016. DOI: 10.1016/j.neuroimage.2012.03.072.
[58]
VOGT N M, HUNT J F, ADLURU N, et al. Cortical microstructural alterations in mild cognitive impairment and Alzheimer's disease dementia[J]. Cereb Cortex, 2020, 30(5): 2948-2960. DOI: 10.1093/cercor/bhz286.
[59]
GOZDAS E, FINGERHUT H, DACORRO L, et al. Neurite imaging reveals widespread alterations in gray and white matter neurite morphology in healthy aging and amnestic mild cognitive impairment[J]. Cereb Cortex, 2021, 31(12): 5570-5578. DOI: 10.1093/cercor/bhab180.
[60]
LIU Y, ZENG H. Study on the microstructure of hippocampus and parahippocampal gyrus in patients with cognitive impairment by NODDI[J]. J Med Imaging, 2023, 33(12): 2153-2157.
[61]
FU X, SHRESTHA S, SUN M, et al. Microstructural white matter alterations in mild cognitive impairment and Alzheimer's disease: Study based on neurite orientation dispersion and density imaging (NODDI)[J]. Clin Neuroradiol, 2020, 30(3): 569-579. DOI: 10.1007/s00062-019-00805-0.
[62]
WEI Z H, WANG H, JU C, et al. NODDI study of the microstructure of cingulate gyrus in Alzheimer's disease and mild cognitive impairment[J]. Diagnostic Imaging & Interventional Radiology, 2022, 31(2): 83-88. DOI: 10.3969/j.issn.1005-8001.2022.02.001.

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