請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91338
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 吳文超 | zh_TW |
dc.contributor.advisor | Wen-Chau Wu | en |
dc.contributor.author | 凃敏謙 | zh_TW |
dc.contributor.author | MIN-CHIEN TU | en |
dc.date.accessioned | 2024-01-03T16:10:11Z | - |
dc.date.available | 2024-01-04 | - |
dc.date.copyright | 2024-01-03 | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2023-12-12 | - |
dc.identifier.citation | 1. Phillips AA, Chan FH, Zheng MMZ, Krassioukov AV, Ainslie PN. Neurovascular coupling in humans: physiology, methodological advances and clinical implications. Journal of Cerebral Blood Flow & Metabolism 2016; 36(4): 647-664.
2. Cipolla MJ, Li R, Vitullo L. Perivascular innervation of penetrating brain parenchymal arterioles. Journal of cardiovascular pharmacology 2004; 44(1): 1-8. 3. Salinet AS, Robinson TG, Panerai RB. Cerebral blood flow response to neural activation after acute ischemic stroke: a failure of myogenic regulation? Journal of neurology 2013; 260: 2588-2595. 4. Nicolakakis N, Hamel E. Neurovascular function in Alzheimer's disease patients and experimental models. Journal of Cerebral Blood Flow & Metabolism 2011; 31(6): 1354-1370. 5. Phillips AA, Warburton DE, Ainslie PN, Krassioukov AV. Regional neurovascular coupling and cognitive performance in those with low blood pressure secondary to high-level spinal cord injury: improved by alpha-1 agonist midodrine hydrochloride. Journal of Cerebral Blood Flow & Metabolism 2014; 34(5): 794-801. 6. Hinzman JM, Andaluz N, Shutter LA, Okonkwo DO, Pahl C, Strong AJ et al. Inverse neurovascular coupling to cortical spreading depolarizations in severe brain trauma. Brain 2014; 137(11): 2960-2972. 7. Monteiro A, Castro P, Pereira G, Ferreira C, Sorond F, Milstead A et al. Neurovascular coupling is impaired in hypertensive and diabetic subjects without symptomatic cerebrovascular disease. Frontiers in Aging Neuroscience 2021; 13: 728007. 8. Duan W, Zhou GD, Balachandrasekaran A, Bhumkar AB, Boraste PB, Becker JT et al. Cerebral blood flow predicts conversion of mild cognitive impairment into Alzheimer’s disease and cognitive decline: an arterial spin labeling follow-up study. Journal of Alzheimer's Disease 2021; 82(1): 293-305. 9. ElAli A, Thériault P, Préfontaine P, Rivest S. Mild chronic cerebral hypoperfusion induces neurovascular dysfunction, triggering peripheral beta-amyloid brain entry and aggregation. Acta neuropathologica communications 2013; 1(1): 1-15. 10. Sun Y, Cao W, Ding W, Wang Y, Han X, Zhou Y et al. Cerebral blood flow alterations as assessed by 3D ASL in cognitive impairment in patients with subcortical vascular cognitive impairment: a marker for disease severity. Frontiers in aging neuroscience 2016; 8: 211. 11. Sang L, Chen L, Wang L, Zhang J, Zhang Y, Li P et al. Progressively disrupted brain functional connectivity network in subcortical ischemic vascular cognitive impairment patients. Frontiers in neurology 2018; 9: 94. 12. Bahrani AA, Powell DK, Yu G, Johnson ES, Jicha GA, Smith CD. White matter hyperintensity associations with cerebral blood flow in elderly subjects stratified by cerebrovascular risk. Journal of Stroke and Cerebrovascular Diseases 2017; 26(4): 779-786. 13. Zhang R, Huang P, Wang S, Jiaerken Y, Hong H, Zhang Y et al. Decreased cerebral blood flow and delayed arterial transit are independently associated with white matter hyperintensity. Frontiers in Aging Neuroscience 2022; 14. 14. Román GC, Erkinjuntti T, Wallin A, Pantoni L, Chui HC. Subcortical ischaemic vascular dementia. The Lancet Neurology 2002; 1(7): 426-436. 15. van der Veen PH, Muller M, Vincken KL, Hendrikse J, Mali WP, van der Graaf Y et al. Longitudinal relationship between cerebral small-vessel disease and cerebral blood flow: the second manifestations of arterial disease-magnetic resonance study. Stroke 2015; 46(5): 1233-1238. 16. Rizzi L, Rosset I, Roriz-Cruz M. Global epidemiology of dementia: Alzheimer’s and vascular types. BioMed research international 2014; 2014. 17. Kalaria RN. Neuropathological diagnosis of vascular cognitive impairment and vascular dementia with implications for Alzheimer’s disease. Acta neuropathologica 2016; 131(5): 659-685. 18. Dichgans M, Leys D. Vascular cognitive impairment. Circulation research 2017; 120(3): 573-591. 19. Jack Jr CR, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW et al. Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. The Lancet Neurology 2010; 9(1): 119-128. 20. Hachinski VC, Iliff LD, Zilhka E, Du Boulay GH, McAllister VL, Marshall J et al. Cerebral blood flow in dementia. Archives of neurology 1975; 32(9): 632-637. 21. Damulina A, Pirpamer L, Seiler S, Benke T, Dal-Bianco P, Ransmayr G et al. White matter hyperintensities in alzheimer’s disease: a lesion probability mapping study. Journal of Alzheimer's Disease 2019; 68(2): 789-796. 22. Furuta A, Ishii N, Nishihara Y, Horie A. Medullary arteries in aging and dementia. Stroke 1991; 22(4): 442-446. 23. Chou K-H, Lee P-L, Peng L-N, Lee W-J, Wang P-N, Chen L-K et al. Classification differentiates clinical and neuroanatomic features of cerebral small vessel disease. Brain Communications 2021; 3(2): fcab107. 24. Swinford CG, Risacher SL, Wu Y-C, Apostolova LG, Gao S, Bice PJ et al. Altered cerebral blood flow in older adults with Alzheimer’s disease: a systematic review. Brain Imaging and Behavior 2022: 1-34. 25. Garnier‐Crussard A, Bougacha S, Wirth M, Dautricourt S, Sherif S, Landeau B et al. White matter hyperintensity topography in Alzheimer's disease and links to cognition. Alzheimer's & Dementia 2022; 18(3): 422-433. 26. Serrano-Pozo A, Frosch MP, Masliah E, Hyman BT. Neuropathological alterations in Alzheimer disease. Cold Spring Harbor perspectives in medicine 2011; 1(1): a006189. 27. Nasrallah IM, Pajewski NM, Auchus AP, Chelune G, Cheung AK, Cleveland ML et al. Association of intensive vs standard blood pressure control with cerebral white matter lesions. Jama 2019; 322(6): 524-534. 28. Markus HS, Egle M, Croall ID, Sari H, Khan U, Hassan A et al. PRESERVE: randomized trial of intensive versus standard blood pressure control in small vessel disease. Stroke 2021; 52(8): 2484-2493. 29. Jiménez-Balado J, Riba-Llena I, Abril O, Garde E, Penalba A, Ostos E et al. Cognitive impact of cerebral small vessel disease changes in patients with hypertension. Hypertension 2019; 73(2): 342-349. 30. Xia Y, Shen Y, Wang Y, Yang L, Wang Y, Li Y et al. White matter hyperintensities associated with progression of cerebral small vessel disease: a 7-year Chinese urban community study. Aging (Albany NY) 2020; 12(9): 8506. 31. Schaeffer S, Iadecola C. Revisiting the neurovascular unit. Nature neuroscience 2021; 24(9): 1198-1209. 32. Burgess K, Bennett C, Mosnier H, Kwatra N, Bethel F, Jadavji NM. The antioxidant role of one-carbon metabolism on stroke. Antioxidants 2020; 9(11): 1141. 33. Sasaki T, Watanabe M, Nagai Y, Hoshi T, Takasawa M, Nukata M et al. Association of plasma homocysteine concentration with atherosclerotic carotid plaques and lacunar infarction. Stroke 2002; 33(6): 1493-1496. 34. Bang OY, Chung J-W, Ryoo S, Moon GJ, Kim G-M, Chung C-S et al. Brain microangiopathy and macroangiopathy share common risk factors and biomarkers. Atherosclerosis 2016; 246: 71-77. 35. Hallacoglu B, Sassaroli A, Fantini S, Troen AMJJoCBF, Metabolism. Cerebral perfusion and oxygenation are impaired by folate deficiency in rat: absolute measurements with noninvasive near-infrared spectroscopy. 2011; 31(6): 1482-1492. 36. Kim J-m, Lee H, Chang NJTJon. Hyperhomocysteinemia due to short-term folate deprivation is related to electron microscopic changes in the rat brain. 2002; 132(11): 3418-3421. 37. Peng L, Dreumont N, Coelho D, Guéant J-L, Arnold CJB. Genetic animal models to decipher the pathogenic effects of vitamin B12 and folate deficiency. 2016; 126: 43-51. 38. Roy B, Trivedi R, Garg RK, Gupta PK, Tyagi R, Gupta RK. Assessment of functional and structural damage in brain parenchyma in patients with vitamin B12 deficiency: A longitudinal perfusion and diffusion tensor imaging study. Magnetic Resonance Imaging 2015; 33(5): 537-543. 39. Tu M-C, Lo C-P, Chen C-Y, Huang C-F. Correlation of Tc-99 m ethyl cysteinate dimer single-photon emission computed tomography and clinical presentations in patients with low cobalamin status. BMC neurology 2015; 15: 1-11. 40. De Lau L, Smith A, Refsum H, Johnston C, Breteler M. Plasma vitamin B12 status and cerebral white-matter lesions. Journal of Neurology, Neurosurgery & Psychiatry 2009; 80(2): 149-157. 41. Beydoun MA, Shaked D, Hossain S, Beydoun HA, Katzel LI, Davatzikos C et al. Vitamin D, Folate, and Cobalamin Serum Concentrations Are Related to Brain Volume and White Matter Integrity in Urban Adults. Frontiers in Aging Neuroscience 2020; 12: 140. 42. Tangney C, Aggarwal N, Li H, Wilson R, Decarli C, Evans D et al. Vitamin B12, cognition, and brain MRI measures: a cross-sectional examination. Neurology 2011; 77(13): 1276-1282. 43. Markun S, Gravestock I, Jäger L, Rosemann T, Pichierri G, Burgstaller JM. Effects of vitamin B12 supplementation on cognitive function, depressive symptoms, and fatigue: a systematic review, meta-analysis, and meta-regression. Nutrients 2021; 13(3): 923. 44. Li S, Guo Y, Men J, Fu H, Xu T. The preventive efficacy of vitamin B supplements on the cognitive decline of elderly adults: a systematic review and meta-analysis. BMC geriatrics 2021; 21(1): 1-14. 45. Alexander AL, Lee JE, Lazar M, Field AS. Diffusion tensor imaging of the brain. Neurotherapeutics 2007; 4(3): 316-329. 46. Schuff N, Matsumoto S, Kmiecik J, Studholme C, Du A, Ezekiel F et al. Cerebral blood flow in ischemic vascular dementia and Alzheimer's disease, measured by arterial spin-labeling magnetic resonance imaging. Alzheimer's & Dementia 2009; 5(6): 454-462. 47. Shen Y, Zhao B, Yan L, Jann K, Wang G, Wang J et al. Cerebral hemodynamic and white matter changes of type 2 diabetes revealed by multi-TI arterial spin labeling and double inversion recovery sequence. Frontiers in Neurology 2017; 8: 717. 48. Shao X, Ma SJ, Casey M, D’Orazio L, Ringman JM, Wang DJ. Mapping water exchange across the blood–brain barrier using 3D diffusion‐prepared arterial spin labeled perfusion MRI. Magnetic resonance in medicine 2019; 81(5): 3065-3079. 49. Rane S, Koh N, Boord P, Madhyastha T, Askren MK, Jayadev S et al. Quantitative cerebrovascular pathology in a community-based cohort of older adults. Neurobiology of aging 2018; 65: 77-85. 50. Erkinjuntti T, Inzitari D, Pantoni L, Wallin A, Scheltens P, Rockwood K et al. Research criteria for subcortical vascular dementia in clinical trials. Advances in dementia research 2000: 23-30. 51. Stewart CR, Stringer MS, Shi Y, Thrippleton MJ, Wardlaw JM. Associations between white matter hyperintensity burden, cerebral blood flow and transit time in small vessel disease: an updated meta-analysis. Frontiers in Neurology 2021; 12: 647848. 52. Shi Y, Thrippleton MJ, Makin SD, Marshall I, Geerlings MI, de Craen AJ et al. Cerebral blood flow in small vessel disease: a systematic review and meta-analysis. Journal of cerebral blood flow & metabolism 2016; 36(10): 1653-1667. 53. Wolters FJ, Zonneveld HI, Hofman A, Van Der Lugt A, Koudstaal PJ, Vernooij MW et al. Cerebral perfusion and the risk of dementia: a population-based study. Circulation 2017; 136(8): 719-728. 54. Tu MC, Huang SM, Hsu YH, Yang JJ, Lin CY, Kuo LW. Discriminating subcortical ischemic vascular disease and Alzheimer's disease by diffusion kurtosis imaging in segregated thalamic regions. Human Brain Mapping 2021; 42(7): 2018-2031. 55. Tu M-C, Lo C-P, Huang C-F, Hsu Y-H, Huang W-H, Deng JF et al. Effectiveness of diffusion tensor imaging in differentiating early-stage subcortical ischemic vascular disease, Alzheimer’s disease and normal ageing. PloS one 2017; 12(4): e0175143. 56. Promjunyakul N-o, Dodge HH, Lahna D, Boespflug EL, Kaye JA, Rooney WD et al. Baseline NAWM structural integrity and CBF predict periventricular WMH expansion over time. Neurology 2018; 90(24): e2119-e2126. 57. Tu M-C, Chung H-W, Hsu Y-H, Yang J-J, Wu W-C. Stage-Dependent Cerebral Blood Flow and Leukoaraiosis Couplings in Subcortical Ischemic Vascular Disease and Alzheimer’s Disease. Journal of Alzheimer's Disease 2022; (Preprint): 1-12. 58. Tu M-C, Chung H-W, Hsu Y-H, Yang J-J, Wu W-C. Neurovascular Correlates of Cobalamin, Folate, and Homocysteine in Dementia. Journal of Alzheimer's Disease 2023; (Preprint): 1-10. 59. Shyu Y-IL, Yip P-K. Factor structure and explanatory variables of the Mini-Mental State Examination (MMSE) for elderly persons in Taiwan. Journal of the Formosan Medical Association 2001; 100(10): 676-683. 60. Dubois B, Feldman HH, Jacova C, DeKosky ST, Barberger-Gateau P, Cummings J et al. Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria. The Lancet Neurology 2007; 6(8): 734-746. 61. Lin K-N, Wang P-N, Liu H-C, Teng EL. Cognitive abilities screening instrument, Chinese version 2.0 (CASI C-2.0): administration and clinical application. Acta Neurol Taiwan 2012; 21(4): 180-189. 62. Morris J. Current vision and scoring rules The Clinical Dementia Rating (CDR). Neurology 1993; 43: 2412-14. 63. Chang CC, Kramer JH, Lin KN, Chang WN, Wang Y-L, Huang C-W et al. Validating the Chinese version of the Verbal Learning Test for screening Alzheimer’s disease. Journal of the International Neuropsychological Society 2010; 16(2): 244-251. 64. Wang T-L, Hung Y-H, Yang C-C. Psychometric properties of the Taiwanese (traditional Chinese) version of the Frontal Assessment Battery: A preliminary study. Applied Neuropsychology: Adult 2016; 23(1): 11-20. 65. Wechsler D. Wechsler memory scale (WMS-III), vol. 14. Psychological corporation San Antonio, TX, 1997. 66. Hinton-Bayre A, Geffen G. Comparability, reliability, and practice effects on alternate forms of the Digit Symbol Substitution and Symbol Digit Modalities tests. Psychological assessment 2005; 17(2): 237. 67. Fan J, McCandliss BD, Sommer T, Raz A, Posner MI. Testing the efficiency and independence of attentional networks. Journal of cognitive neuroscience 2002; 14(3): 340-347. 68. Anastasi A, Urbina S. Psychological testing, Prentice Hall/Pearson Education, 1997. 69. Wu WC, Lien SH, Chang JH, Yang SC. Caffeine alters resting‐state functional connectivity measured by blood oxygenation level‐dependent MRI. NMR in biomedicine 2014; 27(4): 444-452. 70. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 2002; 15(1): 273-289. 71. Schmidt P. Bayesian inference for structured additive regression models for large-scale problems with applications to medical imaging. lmu, 2017. 72. Yan C-G, Wang X-D, Zuo X-N, Zang Y-F. DPABI: data processing & analysis for (resting-state) brain imaging. Neuroinformatics 2016; 14: 339-351. 73. Soares JM, Marques P, Alves V, Sousa NJFin. A hitchhiker's guide to diffusion tensor imaging. 2013; 7: 31. 74. Akbas N, Schryver PG, Algeciras-Schimnich A, Baumann NA, Block DR, Budd JR et al. Evaluation of Beckman Coulter DxI 800 immunoassay system using clinically oriented performance goals. 2014; 47(16-17): 158-163. 75. Dipalo M, Dipietro M, Gnocchi C, Musa R, Aloe R, Lippi GJCC et al. Analytical assessment of the novel homocysteine liquid enzymatic assay on Beckman Coulter AU5800. 2015; 53(12): e355-e358. 76. Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of chiropractic medicine 2016; 15(2): 155-163. 77. Hayes AF. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach, Guilford publications, 2017. 78. Hsu Y-H, Huang C-F, Lo C-P, Wang T-L, Yang C-C, Tu M-C. Frontal assessment battery as a useful tool to differentiate mild cognitive impairment due to subcortical ischemic vascular disease from Alzheimer disease. Dementia and geriatric cognitive disorders 2016; 42(5-6): 331-341. 79. Orth L, Meeh J, Gur RC, Neuner I, Sarkheil P. Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review. Frontiers in Human Neuroscience 2022; 16. 80. Cummings JL. Frontal-subcortical circuits and human behavior. Archives of neurology 1993; 50(8): 873-880. 81. Saré RM. Diaschisis: An old concept brought to new life. Journal of Neuroscience 2016; 36(4): 1051-1052. 82. Anenberg E, Chan AW, Xie Y, LeDue JM, Murphy TH. Optogenetic stimulation of GABA neurons can decrease local neuronal activity while increasing cortical blood flow. Journal of Cerebral Blood Flow & Metabolism 2015; 35(10): 1579-1586. 83. Ma Y, Shaik MA, Kozberg MG, Kim SH, Portes JP, Timerman D et al. Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons. Proceedings of the National Academy of Sciences 2016; 113(52): E8463-E8471. 84. Gyanwali B, Tan C, Petr J, Escobosa L, Vrooman H, Chen C et al. Arterial Spin-Labeling Parameters and Their Associations with Risk Factors, Cerebral Small-Vessel Disease, and Etiologic Subtypes of Cognitive Impairment and Dementia. American Journal of Neuroradiology 2022; 43(10): 1418-1423. 85. Firbank M, He J, Blamire A, Singh B, Danson P, Kalaria R et al. Cerebral blood flow by arterial spin labeling in poststroke dementia. Neurology 2011; 76(17): 1478-1484. 86. Park SY, Yoon H, Lee N, Oh JK, Yoo IR, Kim SH et al. Analysis of cerebral blood flow with single photon emission computed tomography in mild subcortical ischemic vascular dementia. Nuclear medicine and molecular imaging 2014; 48: 272-277. 87. Gao Y-Z, Zhang J-J, Liu H, Wu G-Y, Xiong L, Shu M. Regional cerebral blood flow and cerebrovascular reactivity in Alzheimer's disease and vascular dementia assessed by arterial spinlabeling magnetic resonance imaging. Current neurovascular research 2013; 10(1): 49-53. 88. Hu S, Ide JS, Zhang S, Chiang-shan RL. The right superior frontal gyrus and individual variation in proactive control of impulsive response. Journal of Neuroscience 2016; 36(50): 12688-12696. 89. Sebastian A, Jung P, Neuhoff J, Wibral M, Fox PT, Lieb K et al. Dissociable attentional and inhibitory networks of dorsal and ventral areas of the right inferior frontal cortex: a combined task-specific and coordinate-based meta-analytic fMRI study. Brain Structure and Function 2016; 221(3): 1635-1651. 90. Shah-Basak PP, Chen P, Caulfield K, Medina J, Hamilton RH. The role of the right superior temporal gyrus in stimulus-centered spatial processing. Neuropsychologia 2018; 113: 6-13. 91. Koyama MS, O’Connor D, Shehzad Z, Milham MP. Differential contributions of the middle frontal gyrus functional connectivity to literacy and numeracy. Scientific reports 2017; 7(1): 1-13. 92. Beaumont JG. Introduction to neuropsychology, Guilford Press, 2008. 93. Paniukov D, Lebel RM, Giesbrecht G, Lebel C. Cerebral blood flow increases across early childhood. Neuroimage 2020; 204: 116224. 94. Rodriguez G, Warkentin S, Risberg J, Rosadini G. Sex differences in regional cerebral blood flow. Journal of Cerebral Blood Flow & Metabolism 1988; 8(6): 783-789. 95. Stricker NH, Schweinsburg B, Delano-Wood L, Wierenga CE, Bangen KJ, Haaland K et al. Decreased white matter integrity in late-myelinating fiber pathways in Alzheimer's disease supports retrogenesis. Neuroimage 2009; 45(1): 10-16. 96. Deoni SC, Dean III DC, Remer J, Dirks H, O’Muircheartaigh J. Cortical maturation and myelination in healthy toddlers and young children. Neuroimage 2015; 115: 147-161. 97. Kinney HC, Brody BA, Kloman AS, Gilles FH. Sequence of central nervous system myelination in human infancy: II. Patterns of myelination in autopsied infants. Journal of Neuropathology & Experimental Neurology 1988; 47(3): 217-234. 98. Dubois J, Dehaene‐Lambertz G, Perrin M, Mangin JF, Cointepas Y, Duchesnay E et al. Asynchrony of the early maturation of white matter bundles in healthy infants: quantitative landmarks revealed noninvasively by diffusion tensor imaging. Human brain mapping 2008; 29(1): 14-27. 99. Saunders A, Macosko EZ, Wysoker A, Goldman M, Krienen FM, de Rivera H et al. Molecular diversity and specializations among the cells of the adult mouse brain. Cell 2018; 174(4): 1015-1030. e16. 100. Charidimou A, Boulouis G, Haley K, Auriel E, van Etten ES, Fotiadis P et al. White matter hyperintensity patterns in cerebral amyloid angiopathy and hypertensive arteriopathy. Neurology 2016; 86(6): 505-511. 101. Staffaroni AM, Cobigo Y, Elahi FM, Casaletto KB, Walters SM, Wolf A et al. A longitudinal characterization of perfusion in the aging brain and associations with cognition and neural structure. Human brain mapping 2019; 40(12): 3522-3533. 102. Xu Z, Li F, Wang B, Xing D, Pei Y, Yang B et al. New insights in addressing cerebral small vessel disease: association with the deep medullary veins. Frontiers in aging neuroscience 2020; 12: 597799. 103. Schnerr RS, Jansen JF, Uludag K, Hofman PA, Wildberger JE, Van Oostenbrugge RJ et al. Pulsatility of lenticulostriate arteries assessed by 7 Tesla flow MRI—Measurement, reproducibility, and applicability to aging effect. Frontiers in physiology 2017; 8: 961. 104. Brozici M, Van Der Zwan A, Hillen B. Anatomy and functionality of leptomeningeal anastomoses: a review. Stroke 2003; 34(11): 2750-2762. 105. Van Den Bergh R. Centrifugal elements in the vascular pattern of the deep intracerebral blood supply. Angiology 1969; 20(2): 88-94. 106. Huynh T, Murphy B, Pettersen J, Tu H, Sahlas D, Zhang L et al. CT perfusion quantification of small-vessel ischemic severity. American Journal of Neuroradiology 2008; 29(10): 1831-1836. 107. Hallacoglu B, Sassaroli A, Fantini S, Troen AM. Cerebral perfusion and oxygenation are impaired by folate deficiency in rat: absolute measurements with noninvasive near-infrared spectroscopy. Journal of Cerebral Blood Flow & Metabolism 2011; 31(6): 1482-1492. 108. Kim J-m, Lee H, Chang N. Hyperhomocysteinemia due to short-term folate deprivation is related to electron microscopic changes in the rat brain. The Journal of nutrition 2002; 132(11): 3418-3421. 109. Peng L, Dreumont N, Coelho D, Guéant J-L, Arnold C. Genetic animal models to decipher the pathogenic effects of vitamin B12 and folate deficiency. Biochimie 2016; 126: 43-51. 110. Cattaneo M. Hyperhomocysteinemia, atherosclerosis and thrombosis. Thrombosis and haemostasis 1999; 81(02): 165-176. 111. Thomason ME, Thompson PM. Diffusion imaging, white matter, and psychopathology. Annual review of clinical psychology 2011; 7: 63-85. 112. Wu D, Pardridge WM. Blood-brain barrier transport of reduced folic acid. Pharmaceutical research 1999; 16: 415-419. 113. Roh JH, Lee J-H. Recent updates on subcortical ischemic vascular dementia. Journal of stroke 2014; 16(1): 18. 114. Soh Y, Lee DH, Won CW. Association between Vitamin B12 levels and cognitive function in the elderly Korean population. Medicine 2020; 99(30). 115. Selhub J, Morris MS, Jacques PF. In vitamin B12 deficiency, higher serum folate is associated with increased total homocysteine and methylmalonic acid concentrations. Proceedings of the National Academy of Sciences 2007; 104(50): 19995-20000. 116. Mills JL, Carter TC, Scott JM, Troendle JF, Gibney ER, Shane B et al. Do high blood folate concentrations exacerbate metabolic abnormalities in people with low vitamin B-12 status? The American journal of clinical nutrition 2011; 94(2): 495-500. 117. Doets EL, Ueland PM, Tell GS, Vollset SE, Nygård OK, Van't Veer P et al. Interactions between plasma concentrations of folate and markers of vitamin B12 status with cognitive performance in elderly people not exposed to folic acid fortification: the Hordaland Health Study. British journal of nutrition 2014; 111(6): 1085-1095. 118. Van der Zwaluw NL, Brouwer-Brolsma EM, Van de Rest O, Van Wijngaarden JP, In’t Veld PH, Kourie DI et al. Folate and vitamin B12-related biomarkers in relation to brain volumes. nutrients 2016; 9(1): 8. 119. Faux NG, Ellis KA, Porter L, Fowler CJ, Laws SM, Martins RN et al. Homocysteine, vitamin B12, and folic acid levels in Alzheimer's disease, mild cognitive impairment, and healthy elderly: baseline characteristics in subjects of the Australian Imaging Biomarker Lifestyle study. Journal of Alzheimer's Disease 2011; 27(4): 909-922. 120. Grothe MJ, Barthel H, Sepulcre J, Dyrba M, Sabri O, Teipel SJ et al. In vivo staging of regional amyloid deposition. Neurology 2017; 89(20): 2031-2038. 121. Schöll M, Maass A, Mattsson N, Ashton NJ, Blennow K, Zetterberg H et al. Biomarkers for tau pathology. Molecular and Cellular Neuroscience 2019; 97: 18-33. 122. Swinford CG, Risacher SL, Wu Y-C, Apostolova LG, Gao S, Bice PJ et al. Altered cerebral blood flow in older adults with Alzheimer’s disease: a systematic review. Brain imaging and behavior 2023; 17(2): 223-256. 123. Van Gelderen P, De Zwart J, Duyn J. Pittfalls of MRI measurement of white matter perfusion based on arterial spin labeling. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine 2008; 59(4): 788-795. 124. Özbay PS, Chang C, Picchioni D, Mandelkow H, Moehlman TM, Chappel-Farley MG et al. Contribution of systemic vascular effects to fMRI activity in white matter. Neuroimage 2018; 176: 541-549. 125. Zinck JW, de Groh M, MacFarlane AJ. Genetic modifiers of folate, vitamin B-12, and homocysteine status in a cross-sectional study of the Canadian population. The American journal of clinical nutrition 2015; 101(6): 1295-1304. 126. Panagiotakos DB, Pitsavos C, Zeimbekis A, Chrysohoou C, Stefanadis C. The association between lifestyle-related factors and plasma homocysteine levels in healthy individuals from the “ATTICA” Study. International journal of cardiology 2005; 98(3): 471-477. 127. Galukande M, Jombwe J, Fualal J, Baingana R, Gakwaya A. Reference values for serum levels of folic acid and vitamin B12 in a young adult Ugandan population. African Health Sciences 2011; 11(2). 128. Amos R, Dawson D, Fish D, Leeming R, Linnell J. Guidelines on the investigation and diagnosis of cobalamin and folate deficiencies. Clinical & Laboratory Haematology 1994; 16(2): 101-115. 129. Vogiatzoglou A, Refsum H, Johnston C, Smith S, Bradley K, De Jager C et al. Vitamin B12 status and rate of brain volume loss in community-dwelling elderly. Neurology 2008; 71(11): 826-832. | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91338 | - |
dc.description.abstract | 研究背景:神經血管耦合(neurovascular coupling; NVC) 對人類大腦具有重要功能。然而,失智症患者的神經血管耦合的機轉因子仍有待探討。我們因此針對以下兩點進行本研究:(一)運用腦血流(cerebral blood flow; CBF)與白質變化(white matter hyperintensities; WMHs)做為神經血管耦合因子之於認知功能的影響;(二)檢視上述神經血管耦合是否將隨失智症病程、亞型、及營養狀態而改變。
研究材料與方法:本研究招募皮質下缺血疾病患者(subcortical ischemic vascular disease; SIVD)、阿茲海默症患者(Alzheimer's disease; AD)、及認知功能正常受試者。以上個案均接受認知功能評估暨多模式腦部磁振造影檢查(magnetic resonance imaging; MRI) (含擬連續動脈自旋標記及擴散張量造影)。病患族群額外接受血清檢驗:包含維生素B12 (cobalamin; Cbl)、葉酸、及同半胱胺酸(homocysteine; Hcy)。在實驗一,我們比較組間磁振造影測量之腦血流及白質變化指標差異,並分析這些指標預測認知分數的效力。接著,經由「腦血流―白質變化」呈現神經血管耦合指標,依照失智症病程及亞型予以拓撲特徵描述。在實驗二,腦血流及白質變化容積分別依維生素B12、葉酸、及同半胱胺酸濃度三分位數分群進行組間比較,並依淨相關分析建立腦血流/白質變化與維生素B12/葉酸/同半胱胺酸關聯性。承接上述結果,我們聚焦於「額葉―皮質下迴路」,進一步檢視維生素B12/葉酸/同半胱胺酸對於腦血流以及白質(white matter; WM)微小結構參數的關聯。 結果:在實驗一,額葉與基底核(basal ganglia ;BG)的白質變化分別對於整體認知功能及執行功能有微顯著效應。同樣區域的腦血流則對於整體認知功能、記憶力、及(某種程度的)專注力/執行功能有更顯著的影響。結合白質變化與腦血流指標可達到最佳的認知可解釋變異。失智症亞型組間比較顯示:相較於其他組別,皮質下缺血疾病組呈現額顳葉腦血流指標低下;這跟該類型患者具有較高的白質變化及較嚴重的執行功能/專注力缺損相符合。此外,皮質下缺血疾病組的神經血管耦合拓撲特徵顯示:額顳葉的白質變化與雙側視丘的腦血流在失智症初期【臨床失智症量表(Clinical Dementia Rating; CDR = 0.5)】相關:而基底核的白質變化則與額顳葉的腦血流在失智症較後期【臨床失智症量表= 1-2】相關。阿茲海默症組亦呈現類似的「皮質―皮質下」腦血流耦合,但耦合區域較皮質下缺血疾病組少。在實驗二,失智症患者整體分析顯示:維生素B12及葉酸血清濃度的上升與區域性腦血流增加有關,而同半胱胺酸血清濃度上升與白質變化容積增加有關。失智症亞型組間分析顯示:皮質下缺血疾病組比阿茲海默症組的腦血流與維生素B12/葉酸呈現出更顯著的相關性;其中維生素B12相關腦區範圍廣泛,而葉酸相關腦區範圍較侷限。值得注意的是,皮質下缺血疾病組於雙側「內側前額葉皮質―基底核」迴路呈現腦血流交互作用;無論是否考慮同半胱胺酸濃度,該「額葉―皮質下迴路」腦血流耦合均為維生素B12所調控。而葉酸/同半胱胺酸血清濃度,則與在該「額葉―皮質下迴路」內的白質纖維之軸向及徑向擴散指標分別呈現負/正相關。 討論:在實驗一,我們呈現統合腦血流與白質變化指標做為神經血管耦合的適當性:腦血流與白質變化對於認知功能各有獨特貢獻。我們詳細記載了隨失智症病程而變化的腦血流。皮質下缺血疾病組及阿茲海默症組均呈現右側額顳葉腦血流低下(即腦血流偏側化現象):其中,皮質下缺血疾病組右側額葉腦血流下降現象比阿茲海默症組更早期發生。統合「腦血流―白質變化」反應之「皮質―皮質下」神經血管耦合觀察顯示:皮質下缺血疾病組比阿茲海默症組有更寬廣的腦區影響。這呼應了皮質下缺血疾病患者的「皮質―皮質下」迴路存在著重要的致病機轉。在實驗二,我們藉由區分失智症患者維生素B12/葉酸/同半胱胺酸相關之神經血管耦合,進一步延伸了解這些維生素暨代謝物的神經生化效應。維生素B12/葉酸主要與腦血流有關,而同半胱胺酸只跟白質變化有關。神經血管耦合關聯性因失智症亞型而改變:「維生素B12―腦血流」的神經滋養效應以及「同半胱胺酸―白質完整性」的神經毒害效應主要存在於皮質下缺血疾病組,「葉酸―白質完整性」的神經滋養效應以及「葉酸―腦血流」的矛盾效應則存在於皮質下缺血疾病組及阿茲海默症組。藉由神經血管耦合的概念,維生素B12於皮質下缺血疾病組「額葉―皮質下迴路」的調節作用以及「葉酸/同半胱胺酸―白質完整性」的關聯分析延伸了該研究領域既有發現。葉酸/同半胱胺酸與擴散指標的關聯性代表著軸突與髓鞘的微小結構改變。 結論:統合腦血流與白質變化指標做為神經血管耦合是一個具有潛力的生物標記;相關臨床運用包含其認知功能關聯性及鑑別診斷。雖然皮質下缺血疾病及阿茲海默症患者均呈現「皮質―皮質下」神經血管耦合特徵(其中「皮質白質變化―皮質下腦血流」耦合將早於「皮質下白質變化―皮質腦血流」耦合)。但是相較於阿茲海默症,失智症早期右側額葉腦血流下降以及隨失智症病程呈現較廣泛的「皮質―皮質下」神經血管耦合皆暗示皮質下缺血疾病的可能性。。另外,維生素B12/葉酸/同半胱胺酸各自對應之神經血管耦合關聯因子會隨失智症亞型有所變化。本研究結果可協助評估維生素B12/葉酸於失智症患者相關治療效益、劑量、及追蹤。 | zh_TW |
dc.description.abstract | Background: Neurovascular coupling (NVC) plays a critical role in human brain functioning. However, the mechanistic determinants of NCV among dementia patients remain largely unknown. The current research therefore aimed to (i) investigate the effect of factors related to NCV including cerebral blood flow (CBF) and white matter hyperintensities (WMHs) on cognition, and (ii) test the hypothesis that NCV varies by dementia stage, dementia subtype, and nutritional status.
Materials and Methods: This study recruited patients with subcortical ischemic vascular disease (SIVD), patients with Alzheimer's disease (AD), and cognitively normal subjects. All participants underwent cognitive assessments and multimodal brain magnetic resonance imaging (MRI) including pseudo-continuous arterial spin-labelling and diffusion tensor imaging. Serum samples were obtained from the patient groups to measure the values of cobalamin (Cbl), folate, and homocysteine (Hcy). In Experiment I, the MRI-based CBF and WMH metrics were compared by groups and then analyzed as predictors of cognitive scores. The NVC reflected by CBF-WMH coupling was topologically characterized by the dementia stage and subtype. In Experiment II, CBF and WMH volumes were compared among the tertile groups separately defined by Cbl, folate, and Hcy. Partial correlations were analyzed between CBF/WMHs and Cbl/folate/Hcy. Within the frontal-subcortical circuits, the moderation effects of Cbl/folate/Hcy on CBF and their correlations with white matter (WM) microstructural indices were examined. Results: In Experiment I, WMHs within the frontal and basal ganglia (BG) regions had marginal effects on global cognition and executive function, respectively. CBF within the same regions had a more noticeable effect on global cognition, memory, and attention/executive function to a certain degree. Combining WMH and CBF metrics yielded the best explanatory variance for cognition. CBF metrics by dementia subtype revealed a picture showing decreased CBF within the frontotemporal regions in the SIVD group, which was consistent with the greater WMHs and executive/attention deficits compared to the other two groups. The topological evolution of NVC in the SIVD group showed that WMHs in frontotemporal areas were correlated with CBF in bilateral thalami at an earlier stage (Clinical Dementia Rating; CDR = 0.5), followed by the correlations between WMHs in BG areas and CBF in frontotemporal areas at a later stage (CDR = 1 or 2). Similar corticosubcortical coupling was observed in the AD group, however, the coupling involved fewer areas. In Experiment II, increased serum levels of Cbl and folate were associated with higher CBF, while an increased serum level of Hcy was associated with greater WMH volumes in both the SIVD and AD groups. When dementia subtypes were considered, more noticeable CBF correlations (spatially pervasive with Cbl and focal with folate) were noted in the SIVD group than in the AD group. Of note, bilateral CBF interactions were found between the medial prefrontal cortex and ipsilateral BG in the SIVD group, and this frontal-subcortical CBF coupling was moderated by Cbl before and after controlling for Hcy. Within the frontal-subcortical WM tracts, serum levels of folate and Hcy were correlated with axial/radial diffusivity in an inverse and positive direction, respectively. Discussion: In Experiment I, preferable NVC was demonstrated according to its cognitive effect, in which distinct contributions from WMH and CBF metrics were shown. Stage-dependent CBF changes were delineated. Shared CBF lateralization was noted in both the SIVD and AD groups as evidenced by hypoperfusion within the right frontotemporal regions, while right hypofrontality presented earlier in the SIVD group than in the AD group. Using the CBF-WMH association as the corticosubcortical NVC, the SIVD group showed greater changes in CBF by the dementia stage compared to the AD group, underpinning that cortico-subcortical circuits appeared to be critical for the pathogenesis of SIVD. In Experiment II, we extended the neurobiological knowledge of Cbl/folate/Hcy by parceling NCV correlates among dementia patients. Cbl and folate were mainly associated with CBF, while Hcy was exclusively associated with WMHs. The NVC correlations differed by dementia subtype. The neurotrophic effect of Cbl on CBF and the neurotoxic effect of Hcy on WM integrity were mainly found in the SIVD group, while the neurotrophic effect of folate on WM integrity and paradoxical effect of folate on CBF were found in both the SIVD and AD groups. Within the frontal-subcortical circuits in the SIVD group, the significant moderation effect of Cbl on CBF in line with the significant correlations between folate/Hcy and WM integrity provided an NCV-centered reference under the known pathogenesis. The associations between folate/Hcy and diffusivity parameters were further related to axon and myelin sheath damage as the corresponding microstructural changes. Conclusions: NVC involving WMHs and CBF is a potential biomarker that may be able to provide cognitively relevant information and could be useful in differential diagnostics. A stage-dependent yet reciprocal cortico-subcortical NVC pattern was characterized in both the SIVD and AD groups, where the extent of “cortical WMH-subcortical CBF” coupling predated “subcortical WMH-cortical CBF” coupling. Right hypofrontality during the early stage of dementia indicated the possibility of SIVD. The greater topological evolution of NVC, along with the dementia stage, also favored SIVD more than AD. In addition, the dissociable NCV correlates of serum Cbl/folate/Hcy varied by dementia subtype. Our results may help resolve the inconsistent findings of the efficacy of Cbl/folate treatment for dementia and optimize the adjuvant Cbl/folate supplementation. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-01-03T16:10:11Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2024-01-03T16:10:11Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 口試委員會審定書 i
誌謝ii 中文摘要iii-iv 英文摘要v-vi 第一章 論述背景重點(Background)1-9 1.1 Neurovascular coupling (NVC): physiological and pathophysiological importance 1-2 1.2 Brain-intrinsic factors: NVC-centered pathophysiological review in subcortical ischemic vascular disease (SIVD) and Alzheimer’s disease (AD) 2-6 1.3 Systemic factors of NVC: the known, unknown, and undetermined regarding nutritional status 6-7 1.4 MRI-measured NVC: targets, rationale, and considerations 7-8 1.5 Aims of this research 9 第二章 受試者與方法 (Participants and Methods) 9-17 2.1 Study workflow and participants 10-11 2.2 Cognitive evaluations 11-12 2.3 MRI protocol 12-13 2.4 Assessment of white matter hyperintensities (WMHs) and cerebral blood flow (CBF)13-15 2.5 Assessment of white mater (WM) integrity 15-16 2.6 Serology tests 16 2.7 Statistical analysis 16-17 第三章 結果(Results) 17-27 3.1 Exp. I NVC Regarding CBF-WMH Correlations 17-23 3.1-1 Demographic data 18 3.1-2 Cognitive construct of the participants 18 3.1-3 Validation tests for the WMH and CBF measures 18-19 3.1-4 Group comparisons of WMHs and CBF: Composite region analysis 19 3.1-5 Effect of CBF and WMHs on cognition 20 3.1-6 Group comparisons of CBF: Segregated region analysis 21 3.1-7 Comparisons of CBF and WMHs by dementia stage 21-22 3.1-8 Comparisons of “CBF-WMHs” correlations by dementia stage 22 3.2 Exp. II Variations in NVC by Serum Cobalamin (Cbl)/Folate Levels and Dementia Subtype 23-27 3.2-1 Demographic data 23 3.2-2 Correlations between two CBF measures and two WMH quantitative analyses 23-24 3.2-3 Dependence of CBF and WMHs on the status of Cbl/folate/homocysteine(Hcy) 24 3.2-4 Correlates of Cbl/folate/Hcy with CBF and WMHs by dementia subtype 24-25 3.2-5 Moderation analysis of Cbl on fronto-subcortical CBF coupling in SIVD 25-26 3.2-6 WM microstructural correlates with the serum level of Hcy 26-27 第四章 討論(Discussion) 27-41 4.1 Clinical significance of NVC: Discernable cognitive effect of CBF and WMHs 29 4.2 Spatial distribution of perturbed CBF and WMHs: Regional vulnerability from an NVC perspective 29-32 4.3 Changes in the “CBF-WMH association” as NVC by dementia subtype and dementia stage 32-34 4.4 NVC correlates of Cbl, folate, and Hcy 34-35 4.5 Hcy-dissociable effect of Cbl on the frontal-subcortical circuits in SIVD 35-36 4.6 Paradoxical association between folate and CBF 36-37 4.7 Limitations 37-41 4.7-1 Diagnostic criteria, neurobiological bases, and NCV components 37-38 4.7-2 Exp. I: Methodological issues and limitations inherent in arterial spin-labelling 38-40 4.7-3 Exp. II: Confounders of serum Cbl/folate/Hcy level and unproven cause-effect relationships 40-41 第五章 結論(Conclusion) 41-43 第六章 縮寫(Abbreviations) 44 參考文獻 45-58 表目錄 59-66 圖目錄 67-75 附錄 76-82 | - |
dc.language.iso | en | - |
dc.title | 皮質下缺血疾病與阿茲海默症患者之神經血管耦合 暨血清維生素B12及葉酸濃度關聯性 | zh_TW |
dc.title | Neurovascular Coupling and the Associations with Serum Cobalamin and Folate Levels in Patients with Subcortical Ischemic Vascular Disease and Alzheimer’s Disease | en |
dc.type | Thesis | - |
dc.date.schoolyear | 112-1 | - |
dc.description.degree | 博士 | - |
dc.contributor.coadvisor | 鍾孝文 | zh_TW |
dc.contributor.coadvisor | Hsiao-Wen Chung | en |
dc.contributor.oralexamcommittee | 王昭穎;蔡尚岳;莊子肇;陳達夫 | zh_TW |
dc.contributor.oralexamcommittee | Chao-Ying Wang;Shang-Yueh Tsai;Tzu-Chao Chuang;Da-Fu Chen | en |
dc.subject.keyword | 皮質下缺血性腦血管疾病,阿茲海默症,腦血流,磁振造影,維生素B12,葉酸,同半胱胺酸, | zh_TW |
dc.subject.keyword | Subcortical ischemic vascular disease,Alzheimer’s disease,cerebral blood flow,magnetic resonance imaging,cobalamin,folate,homocysteine, | en |
dc.relation.page | 82 | - |
dc.identifier.doi | 10.6342/NTU202304504 | - |
dc.rights.note | 同意授權(限校園內公開) | - |
dc.date.accepted | 2023-12-13 | - |
dc.contributor.author-college | 電機資訊學院 | - |
dc.contributor.author-dept | 生醫電子與資訊學研究所 | - |
顯示於系所單位: | 生醫電子與資訊學研究所 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-112-1.pdf 授權僅限NTU校內IP使用(校園外請利用VPN校外連線服務) | 3.24 MB | Adobe PDF | 檢視/開啟 |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。