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| A Review of Cognition Related Macro-Microstructural Changes Based on MRI |
| Wu Qiong1, Chen Yuanyaun2, Zhao Xin1*, Ming Dong1,2# |
1School of precision instruments and optoelectronic engineering, Tianjin University, Tianjin 300072, China;
2Institute of medical engineering and translational medicine, Tianjin University, Tianjin 300072, China |
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Abstract Alzheimer′s disease (AD) is a neurodegenerative disease with cognitive impairment. The mechanism of AD is complex and not clear now and therefore still a great challenge in the field of medical research. The development of structure and diffusion magnetic resonance imaging technology can provide important technical means for studying the mechanism of macroscopic morphology and microstructural pathological characteristics of Alzheimer′s disease. In recent years, studies have observed that there are relationships between the abnormal changes of macroscopic and microscopic structure, which is of great significance for revealing the mechanism of structural changes in age-related diseases including AD. This article reviewed the studies on the pattern and interrelation of brain macro-microstructure changes to cognitive impairment in recent years, and summarized the important analysis methods and research conclusions. The mechanism of brain macro-microstructure pathology was discussed as well.
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Received: 26 April 2018
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[1] Pakkenberg B, Gundersen HJ. Neocortical neuron number in humans: effect of sex and age [J]. Journal of Comparative Neurology, 2015, 384(2):312-320.
[2] Nir TM, Jahanshad N, Villalon‐Reina JE, et al. Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer′s disease deficits [J]. Magnetic Resonance in Medicine, 2017, 78(6):2322-2333.
[3] Schouten TM, Koini M, Vos F, et al. Individual classification of alzheimer′s disease with diffusion magnetic resonance imaging [J]. Neuroimage, 2017, 152:476-481.
[4] Gyebnár G, Szabó Á, Sirály E, et al. What can DTI tell about early cognitive impairment? - Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging [J]. Psychiatry Res, 2017,272:46-57.
[5] Lebel C, Deoni S. The development of brain white matter microstructure [J]. Neuroimage, 2018:s1053811917311217.
[6] Dicks E, Tijms BM, Ten KM, et al. Gray matter network measures are associated with cognitive decline in mild cognitive impairment[J]. Neurobiology of Aging, 2017, 61:198-206.
[7] Scj V, Slot RE, Tijms BM, et al. Thinner cortex in patients with subjective cognitive decline is associated with steeper decline of memory [J]. Neurobiology of Aging, 2017, 61:238-244.
[8] Tromp D, Dufour A, Lithfous S, et al. Episodic memory in normal aging and Alzheimer disease: Insights from imaging and behavioral studies [J]. Ageing Research Reviews, 2015, 24(Pt B):232-262.
[9] Scola E, Bozzali M, Agosta F, et al. A diffusion tensor MRI study of patients with MCI and AD with a 2-year clinical follow-up[J]. J Neurol Neurosurg Psychiatry, 2010, 81(7):798-805.
[10] Yang Caishui, Sun Xuan, Wu Haitao, et al. Multistage grading of amnestic mild cognitive impairment:The associated brain gray matter volume and cognitive behavior characterization [J]. Frontiers in Aging Neuroscience, 2016, 8:332.
[11] Filley CM, Fields RD. White matter and cognition: Making the connection [J]. Journal of Neurophysiology, 2016, 116(5):2093-2104.
[12] Yuan Lixiang, Sun Man, Chen Yuanyaun, et al. Non-Gaussian diffusion alterations on diffusion kurtosis imaging in patients with early alzheimer′s disease [J]. Neuroscience Letters, 2016, 616(3-4):11-18.
[13] 陈运仰. 轻度认知功能障碍与脑白质弥散张量成像的相关性研究 [D]. 昆明:昆明医科大学, 2016.
[14] Vijverberg EG, Tijms BM, Dopp J, et al. Gray matter network differences between behavioral variant frontotemporal dementia and Alzheimer′s disease[J]. Neurobiology of Aging, 2016, 50:77-86.
[15] Tang Xiaoying, Qin Yuanyuan, Wu Jiong, et al. Shape and diffusion tensor imaging based integrative analysis of the hippocampus and the amygdala in Alzheimer′s disease[J]. Magnetic Resonance Imaging, 2016, 34(8):1087-1099.
[16] Berti V, Mosconi L, Glodzik L, et al. Structural brain changes in normal individuals with a maternal history of Alzheimer′s [J]. Neurobiology of Aging, 2011, 32(12):2325. e17-2325.e26.
[17] Pegueroles J, Vilaplana E, Montal V, et al. Longitudinal brain structural changes in preclinical Alzheimer′s disease [J]. Alzheimers & Dementia, 2017,13:499-509.
[18] Fiford CM, Ridgway GR, Cash DM, et al. Patterns of progressive atrophy vary with age in Alzheimer′s disease patients [J]. Neurobiology of Aging, 2017, 63:22-32.
[19] Poulakis K, Pereira JB, Mevocci P, et al.Heterogeneous patterns of brain atrophy in Alzheimer′s disease [J]. Neurobiology of Aging, 2018,65:98-108.
[20] Pereira JB, Westman E, Hansson O. Association between cerebrospinal fluid and plasma neurodegeneration biomarkers with brain atrophy in Alzheimer′s disease.[J]. Neurobiology of Aging, 2017, 58(7):14-29.
[21] Mosconi L, Murray J, Tsui WH, et al. Brain imaging of cognitively normal individuals with 2 parents affected by late-onset AD [J]. Neurology, 2014, 82(9):752-760.
[22] Apostolova LG, Steiner CA, Akopyan GG, et al. Three-dimensional gray matter atrophy mapping in mild cognitive impairment and mild Alzheimer disease [J]. Archives of Neurology, 2007, 64(10):1489-1495.
[23] Chételat G, Landeau B, Eustache F, et al. Using voxel-based morphometry to map the structural changes associated with rapid conversion in MCI: a longitudinal MRI study [J]. Neuroimage, 2005, 27(4):934-946.
[24] Risacher SL, Shen L, West JD, et al. Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort [J]. Neurobiology of Aging, 2010, 31(8):1401-1418.
[25] Villemagne VL, Ataka S, Mizuno T, et al. High striatal amyloid beta-peptide deposition across different autosomal Alzheimer disease mutation types [J]. Archives of Neurology, 2009, 66(12):1537-1544.
[26] Arab A, Wojna-Pelczar A, Khairnar A, et al. Principles of diffusion kurtosis imaging and its role in early diagnosis of neurodegenerative disorders [J]. Brain Research Bulletin, 2018, 139:91-98.
[27] Annavarapu RN, Kathi S, Krishna VV. Non-invasive imaging modalities to study neurodegenerative diseases of aging brain [J]. Journal of Chemical Neuroanatomy, 21 Feb, 2018 [Epub ahead of print].
[28] Redolfi A, Manset D, Barkhof F, et al. Head-to-head comparison of two popular cortical thickness extraction algorithms: A cross-sectional and longitudinal study [J]. PLoS ONE, 2015, 10(3):e0117692.
[29] Hossein TJ, Shaw ME, Nicolas C. Cerebral atrophy in mild cognitive impairment: A systematic review with meta-analysis:[J]. Alzheimers & Dementia Diagnosis Assessment & Disease Monitoring, 2015, 1(4):487-504.
[30] Fiford CM, Ridgway GR, Cash DM, et al. Patterns of progressive atrophy vary with age in Alzheimer′s disease patients.[J]. Neurobiology of Aging, 2017, 63:22-32.
[31] Frisoni GB, Prestia A, Rasser PE, et al. In vivo mapping of incremental cortical atrophy from incipient to overt Alzheimer′s disease [J]. Journal of Neurology, 2009, 256(6):916-924.
[32] Gomar JJ, Ragland JD, Ulugˇ AM, et al. Differential medial temporal lobe morphometric predictors of item- and relational-encoded memories in healthy individuals and in individuals with mild cognitive impairment and Alzheimer′s disease [J]. Alzheimers & Dementia Translational Research & Clinical Interventions, 2017, 3(2):238-246
[33] Silvio RBDSF, Oliveira Barbosa J H, Rondinoni C, et al. Neuro-degeneration profile of Alzheimer′s patients: A brain morphometry study [J]. Neuroimage Clinical, 2017, 15:15-24.
[34] Ferreira D, Verhagen C, Cavallin L, et al. Distinct subtypes of Alzheimer′s disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications [J]. Scientific Reports, 2017, 7:46263.
[35] Yi HA, Möller C, Dieleman N, et al. Relation between subcortical grey matter atrophy and conversion from mild cognitive impairment to Alzheimer′s disease [J]. Journal of Neurology Neurosurgery & Psychiatry, 2015, 87(4): 425-432.
[36] Insausti R, Tuñón T, Sobreviela T, et al. The human entorhinal cortex: a cytoarchitectonic analysis [J]. Journal of Comparative Neurology, 1995, 355(2):171-198.
[37] Sasaki T, Leutgeb S, Leutgeb JK. Spatial and memory circuits in the medial entorhinal cortex [J]. Current Opinion in Neurobiology, 2015, 32:16-23.
[38] Canto CB, Wouterlood FG, Witter MP. What does the anatomical organization of the entorhinal cortextell us? [J]. Neural Plasticity, 2008, 2008(Special):381243.
[39] Nadel L, Hardt O. Update on memory systems and processes [J]. Neuropsychopharmacology, 2011, 36(1):251-273.
[40] Squire LR, Zolamorgan S. The medial temporal lobe memory system [J]. Cold Spring Harbor Symposia on Quantitative Biology, 1991, 253(5026):185-195.
[41] Braak H, Braak E. Staging of Alzheimer′s disease-related neurofibrillary changes [J]. Neurobiology of Aging, 1995, 16(3):271-278.
[42] Teipel SJ, Pruessner JC, Faltraco F, et al. Comprehensive dissection of the medial temporal lobe in AD: Measurement of hippocampus, amygdala, entorhinal, perirhinal and parahippocampal cortices using MRI [J]. Journal of Neurology, 2006, 253(6):794-800.
[43] Bosco P, Redolfi A, Bocchetta M, et al. The impact of automated hippocampal volumetry on diagnostic confidence in patients with suspected Alzheimer′s disease:An European Alzheimer′s disease consortium study [J]. Alzheimers & Dementia the Journal of the Alzheimers Association, 2017, 13(9):1013-1023.
[44] Shim G, Choi KY, Kim D, et al. Predicting neurocognitive function with hippocampal volumes and DTI metrics in patients with Alzheimer′s dementia and mild cognitive impairment [J]. Brain Behav, 2017, 7(9):e00766.
[45] Dhikav V, Duraiswamy S, Anand KS. Correlation between hippocampal volumes and medial temporal lobe atrophy in patients with Alzheimer′s disease [J]. Annals of Indian Academy of Neurology, 2017, 20(1):29-35.
[46] Wm VDF, van Straaten EC, Barkhof F, et al. Medial temporal lobe atrophy and white matter hyperintensities are associated with mild cognitive deficits in non-disabled elderly people: the LADIS study [J]. Digest of the World Core Medical Journals, 2006, 76(11):1497-1500.
[47] Shi Feng, Liu Bing, Zhou Yuan, et al. Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer′s disease: Meta-analyses of MRI studies [J]. Hippocampus, 2010, 19(11):1055-1064.
[48] Barnes J, Bartlett JW, La VDP, et al. A meta-analysis of hippocampal atrophy rates in Alzheimer′s disease [J]. Neurobiology of Aging, 2009, 30(11):1711-1723.
[49] Mcdonald CR, Gharapetian L, Mcevoy LK, et al. Relationship between regional atrophy rates and cognitive decline in mild cognitive impairment [J]. Neurobiology of Aging, 2012, 33(2):242-253.
[50] Kalaria RN. The pathology and pathophysiology of vascular dementia[J]. Neuropharmacology, 2018,134(Pt B):226-239.
[51] 郭起浩, 陈科良. 语义性痴呆的研究进展 [J]. 重庆医科大学学报, 2017(6):634-637.
[52] Deng Xia, Zhou Meihong, Tang Chunyan, et al. The alterations of cortical volume, thickness, surface, and density in the intermediate sporadic Parkinson′s disease from the Han population of mainland China [J]. Frontiers in Aging Neuroscience, 2016, 8:185.
[53] Scott SA, Dekosky ST, Scheff SW. Volumetric atrophy of the amygdala in Alzheimer′s disease: quantitative serial reconstruction [J]. Neurology, 1991, 41(3):351-356.
[54] Yang EJ, Mahmood U, Kim H, et al. Alterations in protein phosphorylation in the amygdala of the 5XFamilial Alzheimer′s disease animal model[J]. Journal of Pharmacological Sciences, 2017, 133(4):261-267.
[55] Hamann S. Cognitive and neural mechanisms of emotional memory [J]. Trends in Cognitive Sciences, 2001, 5(9):394-400.
[56] Cuénod CA, Denys A, Michot JL, et al. Amygdala atrophy in Alzheimer′s disease. An in vivo magnetic resonance imaging study [J]. Archives of Neurology, 1993, 50(9):941-945.
[57] Deweer B, Lehéricy S, Pillon B, et al. Memory disorders in probable Alzheimer′s disease: the role of hippocampal atrophy as shown with MRI [J]. Journal of Neurology Neurosurgery & Psychiatry, 1995, 58(5):590-597.
[58] Krasuski JS, Alexander GE, Horwitz B, et al. Volumes of medial temporal lobe structures in patients with Alzheimer′s disease and mild cognitive impairment (and in healthy controls) [J]. Biol Psychiatry, 1998, 43(1):60-68.
[59] 胡瑞, 谭凡, 陈学强,等. 扩散峰度成像评价阿尔茨海默病患者脑白质微观结构的改变 [J]. 中国医学影像技术, 2016, 32(1):35-39.
[60] 王军, 王效春, 张辉,等. 非高斯扩散MR成像在轻度认知障碍和阿尔茨海默病中的应用价值 [J]. 中西医结合心脑血管病杂志, 2016, 14(3):304-308.
[61] Mayo CD, Mazerolle EL, Ritchie L, et al. Longitudinal changes in microstructural white matter metrics in Alzheimer′s disease [J]. Neuroimage Clinical, 2016, 13(C):330-338.
[62] Gyebnár G,Á Szabó, Sirály E, et al. What can DTI tell about early cognitive impairment? - Differentiation between MCI subtypes and healthy controls by diffusion tensor imaging [J]. Neuroimaging, 2018, 272:46-57.
[63] Liu Jianghong, Liang Peipeng, Yin Linlin, et al. White matter abnormalities in two different subtypes ofamnestic mild cognitive impairment [J]. PLoS ONE, 2017, 12(1): e0170185.
[64] Tang Shouxian, Feng Qingliang, Wang Guihong, et al. Diffusion characteristics of the fornix in patients with Alzheimer′s disease [J]. Neuroimaging, 2017, 265:72-76.
[65] Choo IH, Dong YL, Oh JS, et al. Posterior cingulate cortex atrophy and regional cingulum disruption in mild cognitive impairment and Alzheimer′s disease [J]. Neurobiology of Aging, 2010, 31(5):772-779.
[66] Stahl R, Dietrich O, Teipel SJ, et al. White matter damage in Alzheimer disease and mild cognitive impairment: Assessment with diffusion-tensor MR imaging and parallel imaging techniques [J]. Radiology, 2007, 243(2):483-492.
[67] Gong Nanjie, Wong CS, Chan CC. Correlations between microstructural alterations and severity of cognitive deficiency in Alzheimer′s disease and mild cognitive impairment: a diffusional kurtosis imaging study [J]. Magnetic Resonance Imaging, 2013, 31(5):688-694.
[68] Gong Nanjie, Chan CC, Leung LM, et al. Differential microstructural and morphological abnormalities in mild cognitive impairment and Alzheimer′s disease: Evidence from cortical and deep gray matter [J]. Human Brain Mapping, 2017, 38:2495-2508.
[69] Steenwijk MD, Daams M, Pouwels PJW, et al. Unraveling the relationship between regional gray matter atrophy and pathology in connected white matter tracts in long-standing multiple sclerosis [J]. Human Brain Mapping, 2015, 36(5):1796-1807.
[70] Sterling NW, Du G, Lewis MM, et al. Cortical gray and subcortical white matter associations in Parkinson′s disease [J]. Neurobiology of Aging, 2017, 49:100-108.
[71] Yoon B, Shim YS, Hong YJ, et al. Comparison of diffusion tensor imaging and voxel-based morphometry to detect white matter damage in Alzheimer′s disease [J]. Journal of the Neurological Sciences, 2011, 302(1):89-95.
[72] Bosch B, Arenaza-Urquijo EM, Rami L, et al. Multiple DTI index analysis in normal aging, amnestic MCI and AD. Relationship with neuropsychological performance [J]. Neurobiology of Aging, 2012, 33(1):61-74.
[73] Henf J, Grothe MJ, Brueggen K, et al. Mean diffusivity in cortical gray matter in Alzheimer′s disease: The importance of partial volume correction [J]. Neuroimage Clinical, 2018, 17:579-586.
[74] Bozzali M, Falini A, Franceschi M, et al. White matter damage in Alzheimer9s disease assessed in vivo using diffusion tensor magnetic resonance imaging [J]. Journal of Neurology Neurosurgery & Psychiatry, 2002, 72(6):742-746.
[75] Fields RD. White matter in learning, cognition and psychiatric disorders [J]. Trends in Neurosciences, 2008, 31(7):361-370.
[76] Catani M, Dell’Acqua F, Bizzi A, et al. Beyond cortical localization in clinico-anatomical correlation [J]. Cortex, 2012, 48(10):1262-1287. |
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