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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 潘斯文 | zh_TW |
| dc.contributor.advisor | Stephen Payne | en |
| dc.contributor.author | 郭人鳳 | zh_TW |
| dc.contributor.author | Jen-Feng Kuo | en |
| dc.date.accessioned | 2024-08-15T16:29:41Z | - |
| dc.date.available | 2024-08-16 | - |
| dc.date.copyright | 2024-08-15 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-08-09 | - |
| dc.identifier.citation | Aaslid, R., Markwalder, T.-M., and Nornes, H. (1982). Noninvasive transcranial Doppler ultrasound recording of flow velocity in basal cerebral arteries. Journal of neurosurgery, 57(6):769–774.
Angleys, H., Jespersen, S. N., and Østergaard, L. (2018). The effects of capillary transit time heterogeneity on the BOLD signal. Human brain mapping, 39(6):2329–2352. Angleys, H., Østergaard, L., and Jespersen, S. N. (2015). The effects of capillary transit time heterogeneity (CTH) on brain oxygenation. Journal of Cerebral Blood Flow & Metabolism, 35(5):806–817. Aschoff, J., Günther, B., and Kramer, K. (1971). Energiehaushalt und temperaturregulation. (No Title). Baron, J.-C. and Jones, T. (2012). Oxygen metabolism, oxygen extraction and positron emission tomography: historical perspective and impact on basic and clinical neuroscience. Neuroimage, 61(2):492–504. Beard, D. A. and Bassingthwaighte, J. B. (2001). Modeling advection and diffusion of oxygen in complex vascular networks. Annals of biomedical engineering, 29:298–310. Blinder, P., Shih, A. Y., Rafie, C., and Kleinfeld, D. (2010). Topological basis for the robust distribution of blood to rodent neocortex. Proceedings of the National Academy of Sciences, 107(28):12670–12675. Bordoni, L., Thoren, A. E., Gutiérrez-Jiménez, E., Åbjørsbråten, K. S., Bjørnstad, D. M., Tang, W., Stern, M., Østergaard, L., Nagelhus, E. A., Frische, S., et al. (2023). Deletion of aquaporin-4 improves capillary blood flow distribution in brain edema. Glia, 71(11):2559–2572. BrainAnatomy (n.d.). Brain anatomy and how the brain works. https://www.hopkinsmedicine.org/health/conditions-and-diseases/anatomy-of-the-brain. Bulte, D. P., Kelly, M., Germuska, M., Xie, J., Chappell, M. A., Okell, T. W., Bright, M. G., and Jezzard, P. (2012). Quantitative measurement of cerebral physiology using respiratory-calibrated MRI. Neuroimage, 60(1):582–591. Bush, A. M., Coates, T. D., and Wood, J. C. (2018). Diminished cerebral oxygen extraction and metabolic rate in sickle cell disease using T2 relaxation under spin tagging MRI. Magnetic resonance in medicine, 80(1):294–303. Carmeliet, P. (2005). Angiogenesis in life, disease and medicine. Nature, 438(7070):932–936. Cassot, F., Lauwers, F., Fouard, C., Prohaska, S., and Lauwers-Cances, V. (2006). A novel three-dimensional computer-assisted method for a quantitative study of microvascular networks of the human cerebral cortex. Microcirculation, 13(1):1–18. Catchlove, S. J., Macpherson, H., Hughes, M. E., Chen, Y., Parrish, T. B., and Pipingas, A. (2018). An investigation of cerebral oxygen utilization, blood flow and cognition in healthy aging. PLoS One, 13(5):e0197055. Celaya-Alcala, J. T., Lee, G. V., Smith, A. F., Li, B., Sakadžić, S., Boas, D. A., and Secomb, T. W. (2021). Simulation of oxygen transport and estimation of tissue perfusion in extensive microvascular networks: Application to cerebral cortex. Journal of Cerebral Blood Flow & Metabolism, 41(3):656–669. Cremer, J. E. and Seville, M. P. (1983). Regional brain blood flow, blood volume, and haematocrit values in the adult rat. Journal of cerebral blood flow & metabolism, 3(2):254–256. Darcy, H. (1856). Les fontaines publiques de la ville de Dijon: exposition et application des principes à suivre volume 1. Victor dalmont. Davis, S. M. and Donnan, G. A. (2004). Why lacunar syndromes are different and important. Stroke, 35(7):1780–1781. De Silva, T. M. and Faraci, F. M. (2020). Contributions of aging to cerebral small vessel disease. Annual review of physiology, 82:275–295. Duvernoy, H. M., Delon, S., and Vannson, J. (1981). Cortical blood vessels of the human brain. Brain research bulletin, 7(5):519–579. El-Bouri, W. K. and Payne, S. J. (2015). Multi-scale homogenization of blood flow in 3-dimensional human cerebral microvascular networks. Journal of theoretical biology, 380:40–47. Eskildsen, S. F., Gyldensted, L., Nagenthiraja, K., Nielsen, R. B., Hansen, M. B., Dalby, R. B., Frandsen, J., Rodell, A., Gyldensted, C., Jespersen, S. N., et al. (2017). Increased cortical capillary transit time heterogeneity in Alzheimer’s disease: a DSC-MRI perfusion study. Neurobiology of aging, 50:107–118. Fan, A. P., An, H., Moradi, F., Rosenberg, J., Ishii, Y., Nariai, T., Okazawa, H., and Zaharchuk, G. (2020). Quantification of brain oxygen extraction and metabolism with [15O]-gas PET: a technical review in the era of PET/MRI. Neuroimage, 220:117136. Fan, A. P., Benner, T., Bolar, D. S., Rosen, B. R., and Adalsteinsson, E. (2012). Phase-based regional oxygen metabolism (PROM) using MRI. Magnetic resonance in medicine, 67(3):669–678. Fan, A. P., Bilgic, B., Gagnon, L., Witzel, T., Bhat, H., Rosen, B. R., and Adalsteinsson, E. (2014). Quantitative oxygenation venography from MRI phase. Magnetic resonance in medicine, 72(1):149–159. Fantini, S., Sassaroli, A., Tgavalekos, K. T., and Kornbluth, J. (2016). Cerebral blood flow and autoregulation: current measurement techniques and prospects for noninvasive optical methods. Neurophotonics, 3(3):031411–031411. Farrall, A. J. and Wardlaw, J. M. (2009). Blood–brain barrier: ageing and microvascular disease–systematic review and meta-analysis. Neurobiology of aging, 30(3):337–352. Fernández-Seara, M. A., Techawiboonwong, A., Detre, J. A., and Wehrli, F. W. (2006). Mr susceptometry for measuring global brain oxygen extraction. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 55(5):967–973. Fields, M. E., Guilliams, K. P., Ragan, D. K., Binkley, M. M., Eldeniz, C., Chen, Y., Hulbert, M. L., McKinstry, R. C., Shimony, J. S., Vo, K. D., et al. (2018). Regional oxygen extraction predicts border zone vulnerability to stroke in sickle cell disease. Neurology, 90(13):e1134–e1142. Fisher, C. (1969). The arterial lesions underlying lacunes. Acta neuropathologica, 12:1–15. Fry, B. C., Lee, J., Smith, N. P., and Secomb, T. W. (2012). Estimation of blood flow rates in large microvascular networks. Microcirculation, 19(6):530–538. Gauthier, C. J. and Hoge, R. D. (2012). Magnetic resonance imaging of resting OEF and CMRO2 using a generalized calibration model for hypercapnia and hyperoxia. Neuroimage, 60(2):1212–1225. Georgakopoulou, T., van der Wijk, A.-E., Bakker, E. N., et al. (2021). Recovery of hypoxic regions in a rat model of microembolism. Journal of Stroke and Cerebrovascular Diseases, 30(6):105739. Glisky, E. L. (2007). Changes in cognitive function in human aging. Brain aging, pages 3–20. Goirand, F., Le Borgne, T., and Lorthois, S. (2021). Network-driven anomalous transport is a fundamental component of brain microvascular dysfunction. Nature communications, 12(1):7295. Gould, I. G. and Linninger, A. A. (2015). Hematocrit distribution and tissue oxygenation in large microcirculatory networks. Microcirculation, 22(1):1–18. Graff, B. J., Payne, S. J., and El-Bouri, W. K. (2021). The ageing brain: Investigating the role of age in changes to the human cerebral microvasculature with an in silico model. Frontiers in Aging Neuroscience, 13:632521. Grubb Jr, R. L., Derdeyn, C. P., Fritsch, S. M., Carpenter, D. A., Yundt, K. D., Videen, T. O., Spitznagel, E. L., and Powers, W. J. (1998). Importance of hemodynamic factors in the prognosis of symptomatic carotid occlusion. Jama, 280(12):1055–1060. Gutiérrez-Jiménez, E., Angleys, H., Rasmussen, P. M., Mikkelsen, I. K., Mouridsen, K., and Østergaard, L. (2018). The effects of hypercapnia on cortical capillary transit time heterogeneity (CTH) in anesthetized mice. Journal of Cerebral Blood Flow & Metabolism, 38(2):290–303. Gutiérrez-Jiménez, E., Cai, C., Mikkelsen, I. K., Rasmussen, P. M., Angleys, H., Merrild, M., Mouridsen, K., Jespersen, S. N., Lee, J., Iversen, N. K., et al. (2016). Effect of electrical forepaw stimulation on capillary transit-time heterogeneity (CTH). Journal of Cerebral Blood Flow & Metabolism, 36(12):2072–2086. Haacke, E., Tang, J., Neelavalli, J., and Cheng, Y. (2010). Susceptibility mapping as a means to visualize veins and quantify oxygen saturation. Journal of Magnetic Resonance Imaging, 32(3):663–676. Haacke, E. M., Lai, S., Reichenbach, J. R., Kuppusamy, K., Hoogenraad, F. G., Takeichi, H., and Lin, W. (1997). In vivo measurement of blood oxygen saturation using magnetic resonance imaging: a direct validation of the blood oxygen level-dependent concept in functional brain imaging. Human brain mapping, 5(5):341–346. Hall, C. N., Reynell, C., Gesslein, B., Hamilton, N. B., Mishra, A., Sutherland, B. A., O＇Farrell, F. M., Buchan, A. M., Lauritzen, M., and Attwell, D. (2014). Capillary pericytes regulate cerebral blood flow in health and disease. Nature, 508(7494):55–60. Hartung, G., Badr, S., Moeini, M., Lesage, F., Kleinfeld, D., Alaraj, A., and Linninger, A. (2021). Voxelized simulation of cerebral oxygen perfusion elucidates hypoxia in aged mouse cortex. PLoS computational biology, 17(1):e1008584. Hassan, A., Hunt, B. J., O＇Sullivan, M., Parmar, K., Bamford, J. M., Briley, D., Brown, M. M., Thomas, D. J., and Markus, H. S. (2003). Markers of endothelial dysfunction in lacunar infarction and ischaemic leukoaraiosis. Brain, 126(2):424–432. Henriksen, O. M., Gjedde, A., Vang, K., Law, I., Aanerud, J., and Rostrup, E. (2021). Regional and interindividual relationships between cerebral perfusion and oxygen metabolism. Journal of Applied Physiology, 130(6):1836–1847. Hsu, R. and Secomb, T. W. (1989). A Green’s function method for analysis of oxygen delivery to tissue by microvascular networks. Mathematical biosciences, 96(1):61–78. Hyde, J. S., Biswal, B. B., and Jesmanowicz, A. (2001). High-resolution fMRI using multislice partial k-space GR-EPI with cubic voxels. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 46(1):114–125. Ito, H., Kanno, I., Kato, C., Sasaki, T., Ishii, K., Ouchi, Y., Iida, A., Okazawa, H., Hayashida, K., Tsuyuguchi, N., et al. (2004). Database of normal human cerebral blood flow, cerebral blood volume, cerebral oxygen extraction fraction and cerebral metabolic rate of oxygen measured by positron emission tomography with 15 o-labelled carbon dioxide or water, carbon monoxide and oxygen: a multicentre study in japan. European journal of nuclear medicine and molecular imaging, 31:635–643. Jain, V., Langham, M. C., and Wehrli, F. W. (2010). MRI estimation of global brain oxygen consumption rate. Journal of Cerebral Blood Flow & Metabolism, 30(9):1598–1607. Jespersen, S. N. and Østergaard, L. (2012). The roles of cerebral blood flow, capillary transit time heterogeneity, and oxygen tension in brain oxygenation and metabolism. Journal of cerebral blood flow & metabolism, 32(2):264–277. Jiang, D., Lin, Z., Liu, P., Sur, S., Xu, C., Hazel, K., Pottanat, G., Darrow, J., Pillai, J. J., Yasar, S., et al. (2020). Brain oxygen extraction is differentially altered by Alzheimer’s and vascular diseases. Journal of Magnetic Resonance Imaging, 52(6):1829–1837. Jiang, D. and Lu, H. (2022). Cerebral oxygen extraction fraction MRI: Techniques and applications. Magnetic resonance in medicine, 88(2):575–600. John, S. (2019). Deaths registered in England and Wales: 2018. Office for National Statistics. Kalaria, R. N. (1999). The blood-brain barrier and cerebrovascular pathology in Alzheimer’s disease. Annals of the New York Academy of Sciences, 893(1):113–125. Kane, I., Sandercock, P., and Wardlaw, J. (2007). Magnetic resonance perfusion diffusion mismatch and thrombolysis in acute ischaemic stroke: a systematic review of the evidence to date. Journal of Neurology, Neurosurgery & Psychiatry, 78(5):485–491. Kang, P., Ying, C., Chen, Y., Ford, A. L., An, H., and Lee, J.-M. (2022). Oxygen metabolic stress and white matter injury in patients with cerebral small vessel disease. Stroke, 53(5):1570–1579. Karst, N. J. and Geddes, J. B. (2023). Modeling transit time distributions in microvascular networks. Journal of Theoretical Biology, 572:111584. Kassab, G. S., Lin, D. H., and Fung, Y. (1994). Morphometry of pig coronary venous system. American Journal of Physiology-Heart and Circulatory Physiology, 267(6):H2100–H2113. Koh, T., Cheong, L. D., Tan, C. M., and Lim, C. T. (2006). A distributed parameter model of cerebral blood-tissue exchange with account of capillary transit time distribution. Neuroimage, 30(2):426–435. Krogh, A. (1919). The number and distribution of capillaries in muscles with calculations of the oxygen pressure head necessary for supplying the tissue. The Journal of physiology, 52(6):409. Lammie, G., Brannan, F., and Wardlaw, J. (1998). Incomplete lacunar infarction (Type I b lacunes). Acta neuropathologica, 96:163–171. Larsson, H. B., Vestergaard, M. B., Lindberg, U., Iversen, H. K., and Cramer, S. P. (2017). Brain capillary transit time heterogeneity in healthy volunteers measured by dynamic contrast-enhanced T1-weighted perfusion MRI. Journal of Magnetic Resonance Imaging, 45(6):1809–1820. Lauwers, F., Cassot, F., Lauwers-Cances, V., Puwanarajah, P., and Duvernoy, H. (2008). Morphometry of the human cerebral cortex microcirculation: general characteristics and space-related profiles. Neuroimage, 39(3):936–948. le Noble, F., Fleury, V., Pries, A., Corvol, P., Eichmann, A., and Reneman, R. (2005). Control of arterial branching morphogenesis in embryogenesis: go with the flow. Cardiovascular research, 65(3):619–628. Lee, R. M. (1995). Morphology of cerebral arteries. Pharmacology & therapeutics, 66(1):149–173. Li, B., Lu, X., Moeini, M., Sakadžić, S., Thorin, E., and Lesage, F. (2019). Atherosclerosis is associated with a decrease in cerebral microvascular blood flow and tissue oxygenation. PLoS One, 14(8):e0221547. Li, W. and van Zijl, P. C. (2020). Quantitative theory for the transverse relaxation time of blood water. NMR in Biomedicine, 33(5):e4207. Linninger, A., Gould, I., Marinnan, T., Hsu, C.-Y., Chojecki, M., and Alaraj, A. (2013). Cerebral microcirculation and oxygen tension in the human secondary cortex. Annals of biomedical engineering, 41:2264–2284. Logothetis, N. K. and Wandell, B. A. (2004). Interpreting the BOLD signal. Annu. Rev. Physiol., 66:735–769. Loomba, S., Straehle, J., Gangadharan, V., Heike, N., Khalifa, A., Motta, A., Ju, N., Sievers, M., Gempt, J., Meyer, H. S., et al. (2022). Connectomic comparison of mouse and human cortex. Science, 377(6602):eabo0924. Lorthois, S., Cassot, F., and Lauwers, F. (2011). Simulation study of brain blood flow regulation by intra-cortical arterioles in an anatomically accurate large human vascular network. Part II: flow variations induced by global or localized modifications of arteriolar diameters. Neuroimage, 54(4):2840–2853. Lu, X., Moeini, M., Li, B., de Montgolfier, O., Lu, Y., Bélanger, S., Thorin, É., and Lesage, F. (2020). Voluntary exercise increases brain tissue oxygenation and spatially homogenizes oxygen delivery in a mouse model of Alzheimer’s disease. Neurobiology of aging, 88:11–23. Lücker, A., Secomb, T. W., Barrett, M. J., Weber, B., and Jenny, P. (2018). The relation between capillary transit times and hemoglobin saturation heterogeneity. Part 2: Capillary networks. Frontiers in physiology, 9:334629. Ma, K.-C. and Olsson, Y. (1997). The role of chronic brain edema in the formation of lacunes in Binswanger’s encephalopathy: Histopathological and immunohistochemical observations. Cerebrovascular Diseases, 7(6):324–331. MacDonald, M. E. and Pike, G. B. (2021). MRI of healthy brain aging: A review. NMR in Biomedicine, 34(9):e4564. Madsen, L. S., Kjeldsen, P. L., Ismail, R., Parbo, P., Østergaard, L., Brooks, D. J., and Eskildsen, S. F. (2024). Capillary dysfunction in healthy elderly APOE ε4 carriers with raised brain Aβ deposition. Alzheimer’s & Dementia, 20(1):459–471. Madsen, L. S., Nielsen, R. B., Parbo, P., Ismail, R., Mikkelsen, I. K., Gottrup, H., Østergaard, L., Brooks, D. J., and Eskildsen, S. F. (2022). Capillary function progressively deteriorates in prodromal Alzheimer＇s disease: A longitudinal MRI perfusion study. Aging brain, 2:100035. Magata, Y., Temma, T., Iida, H., Ogawa, M., Mukai, T., Iida, Y., Morimoto, T., Konishi, J., and Saji, H. (2003). Development of injectable o-15 oxygen and estimation of rat oef. Journal of Cerebral Blood Flow & Metabolism, 23(6):671–676. Mehndiratta, A., MacIntosh, B. J., Crane, D. E., Payne, S. J., and Chappell, M. A. (2013). A control point interpolation method for the non-parametric quantification of cerebral haemodynamics from dynamic susceptibility contrast MRI. Neuroimage, 64:560–570. Mink, J. W., Blumenschine, R. J., and Adams, D. B. (1981). Ratio of central nervous system to body metabolism in vertebrates: its constancy and functional basis. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, 241(3):R203–R212. Moeini, M., Lu, X., Avti, P. K., Damseh, R., Bélanger, S., Picard, F., Boas, D., Kakkar, A., and Lesage, F. (2018). Compromised microvascular oxygen delivery increases brain tissue vulnerability with age. Scientific reports, 8(1):8219. Mouridsen, K., Friston, K., Hjort, N., Gyldensted, L., Østergaard, L., and Kiebel, S. (2006). Bayesian estimation of cerebral perfusion using a physiological model of microvasculature. Neuroimage, 33(2):570–579. Nelson, S., Mantz, M., and Maxwell, J. (1971). Use of specific gravity in the measurement of cerebral edema. Journal of applied physiology, 30(2):268–271. Numan, T., Bain, A. R., Hoiland, R. L., Smirl, J. D., Lewis, N. C., and Ainslie, P. N. (2014). Static autoregulation in humans: a review and reanalysis. Medical engineering & physics, 36(11):1487–1495. Obrist, W. D., Thompson Jr, H. K., KING, H., and Wang, H. S. (1967). Determination of regional cerebral blood flow by inhalation of 133-xenon. Circulation research, 20(1):124–135. Østergaard, L. (2005). Principles of cerebral perfusion imaging by bolus tracking. Journal of Magnetic Resonance Imaging: An official journal of the international society for magnetic resonance in medicine, 22(6):710–717. Østergaard, L. (2020). Blood flow, capillary transit times, and tissue oxygenation: the centennial of capillary recruitment. Journal of Applied Physiology. Østergaard, L., Engedal, T. S., Aamand, R., Mikkelsen, R., Iversen, N. K., Anzabi, M., Næss-Schmidt, E. T., Drasbek, K. R., Bay, V., Blicher, J. U., et al. (2014). Capillary transit time heterogeneity and flow-metabolism coupling after traumatic brain injury. Journal of Cerebral Blood Flow & Metabolism, 34(10):1585–1598. Østergaard, L., Sorensen, A. G., Kwong, K. K., Weisskoff, R. M., Gyldensted, C., and Rosen, B. R. (1996a). High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: Experimental comparison and preliminary results. Magnetic resonance in medicine, 36(5):726–736. Østergaard, L., Weisskoff, R. M., Chesler, D. A., Gyldensted, C., and Rosen, B. R. (1996b). High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magnetic resonance in medicine, 36(5):715–725. Ovbiagele, B. and Saver, J. L. (2006). Cerebral white matter hyperintensities on MRI: current concepts and therapeutic implications. Cerebrovascular Diseases, 22(2-3):83–90. Pantano, P., Baron, J., Lebrun-Grandie, P., Duquesnoy, N., Bousser, M., and Comar, D. (1984). Regional cerebral blood flow and oxygen consumption in human aging. Stroke, 15(4):635–641. Pantoni, L. (2002). Pathophysiology of age-related cerebral white matter changes. Cerebrovascular diseases, 13(Suppl. 2):7–10. Park, C. S. and Payne, S. J. (2016). Modelling the effects of cerebral microvasculature morphology on oxygen transport. Medical engineering & physics, 38(1):41–47. Payne, S., Józsa, T. I., and El-Bouri, W. K. (2023). Review of in silico models of cerebral blood flow in health and pathology. Progress in Biomedical Engineering, 5(2):022003. Payne, S. J. and Lucas, C. (2018). Oxygen delivery from the cerebral microvasculature to tissue is governed by a single time constant of approximately 6 seconds. Microcirculation, 25(2):e12428. Peppiatt, C. M., Howarth, C., Mobbs, P., and Attwell, D. (2006). Bidirectional control of CNS capillary diameter by pericytes. Nature, 443(7112):700–704. Pries, A. R., Neuhaus, D., and Gaehtgens, P. (1992). Blood viscosity in tube flow: dependence on diameter and hematocrit. American Journal of Physiology-Heart and Circulatory Physiology, 263(6):H1770–H1778. Pries, A. R., Reglin, B., and Secomb, T. W. (2003). Structural response of microcirculatory networks to changes in demand: information transfer by shear stress. American Journal of Physiology-Heart and Circulatory Physiology, 284(6):H2204–H2212. Pries, A. R., Secomb, T., Gessner, T., Sperandio, M., Gross, J., and Gaehtgens, P. (1994). Resistance to blood flow in microvessels in vivo. Circulation research, 75(5):904–915. Pries, A. R. and Secomb, T. W. (2005). Control of blood vessel structure: insights from theoretical models. American journal of physiology-Heart and circulatory physiology, 288(3):H1010–H1015. Rasmussen, M., Koch, K. U., Espelund, U. S., Mohamad, N., Korshøj, A. R., Juul, N., Angleys, H., Meng, L., Østergaard, L., and Mikkelsen, I. K. (2023). Blood-brain Barrier Permeability May Influence Vasopressor Effects in Anesthetized Patients With Brain Tumor: An Analysis of Magnetic Resonance Imaging Data. Journal of Neurosurgical Anesthesiology, pages 10–1097. Reich, T. and Rusinek, H. (1989). Cerebral cortical and white matter reactivity to carbon dioxide. Stroke, 20(4):453–457. Reichold, J., Stampanoni, M., Keller, A. L., Buck, A., Jenny, P., and Weber, B. (2009). Vascular graph model to simulate the cerebral blood flow in realistic vascular networks. Journal of Cerebral Blood Flow & Metabolism, 29(8):1429–1443. Reina-De La Torre, F., Rodriguez-Baeza, A., and Sahuquillo-Barris, J. (1998). Morphological characteristics and distribution pattern of the arterial vessels in human cerebral cortex: a scanning electron microscope study. The Anatomical Record: An Official Publication of the American Association of Anatomists, 251(1):87–96. Robb, W. H., Khan, O. A., Ahmed, H. A., Li, J., Moore, E. E., Cambronero, F. E., Pechman, K. R., Liu, D., Gifford, K. A., Landman, B. A., et al. (2022). Lower cerebral oxygen utilization is associated with Alzheimer＇s disease-related neurodegeneration and poorer cognitive performance among apolipoprotein E ε4 carriers. Journal of Cerebral Blood Flow & Metabolism, 42(4):642–655. Schmid, F., Tsai, P. S., Kleinfeld, D., Jenny, P., and Weber, B. (2017). Depthdependent flow and pressure characteristics in cortical microvascular networks. PLoS computational biology, 13(2):e1005392. Secomb, T. and Hsu, R. (1994). Simulation of O2 transport in skeletal muscle: diffusive exchange between arterioles and capillaries. American Journal of Physiology-Heart and Circulatory Physiology, 267(3):H1214–H1221. Secomb, T. W., Bullock, K. V., Boas, D. A., and Sakadžić, S. (2020). The mass transfer coefficient for oxygen transport from blood to tissue in cerebral cortex. Journal of Cerebral Blood Flow & Metabolism, 40(8):1634–1646. Secomb, T. W., Hsu, R., Park, E. Y., and Dewhirst, M. W. (2004). Green’s function methods for analysis of oxygen delivery to tissue by microvascular networks. Annals of biomedical engineering, 32:1519–1529. Shin, P., Pian, Q., Ishikawa, H., Hamanaka, G., Mandeville, E. T., Guo, S., Fu, B., Al- fadhel, M., Allu, S. R., Şencan-Eğilmez, I., et al. (2023). Aerobic exercise reverses aging-induced depth-dependent decline in cerebral microcirculation. Elife, 12:e86329. Sims, D. E. (1991). Recent advances in pericyte biology–implications for health and disease. The Canadian journal of cardiology, 7(10):431–443. Stadlbauer, A., Zimmermann, M., Kitzwögerer, M., Oberndorfer, S., Rössler, K., Dörfler, A., Buchfelder, M., and Heinz, G. (2017). MR imaging–derived oxygen metabolism and neovascularization characterization for grading and IDH gene mutation detection of gliomas. Radiology, 283(3):799–809. Stephen J Payne, Yidan Xue, J.-F. K. and El-Bouri, W. K. (2024). Transit time mean and variance are markers of vascular network structure, wall shear stress distribution and oxygen extraction fraction. Journal of Cerebral Blood Flow and Metabolism. [Manuscript submitted for publication]. Storey, A. (2018). Living longer: how our population is changing and why it matters. Office for National Statistics: London, UK, page 21. SU, S.-W., Catherall, M., and Payne, S. (2012). The influence of network structure on the transport of blood in the human cerebral microvasculature. Microcirculation, 19(2):175–187. Sweeney, P. W., d＇Esposito, A., Walker-Samuel, S., and Shipley, R. J. (2019). Modelling the transport of fluid through heterogeneous, whole tumours in silico. PLoS computational biology, 15(6):e1006751. Thomas, B. P., Sheng, M., Tseng, B. Y., Tarumi, T., Martin-Cook, K., Womack, K. B., Cullum, M. C., Levine, B. D., Zhang, R., and Lu, H. (2017). Reduced global brain metabolism but maintained vascular function in amnestic mild cognitive impairment. Journal of Cerebral Blood Flow & Metabolism, 37(4):1508–1516. Thulborn, K. R., Waterton, J. C., Matthews, P. M., and Radda, G. K. (1982). Oxygenation dependence of the transverse relaxation time of water protons in whole blood at high field. Biochimica et Biophysica Acta (BBA)-General Subjects, 714(2):265–270. Tian, P., Teng, I. C., May, L. D., Kurz, R., Lu, K., Scadeng, M., Hillman, E. M., De Crespigny, A. J., D＇Arceuil, H. E., Mandeville, J. B., et al. (2010). Cortical depth-specific microvascular dilation underlies laminar differences in blood oxygenation level-dependent functional MRI signal. Proceedings of the National Academy of Sciences, 107(34):15246–15251. Ujiie, H., Kawasaki, M., Suzuki, Y., and Kaibara, M. (2009). Influence of age and hematocrit on the coagulation of blood. Journal of biorheology, 23:111–114. Vafaee, M. S. and Gjedde, A. (2000). Model of blood–brain transfer of oxygen explains nonlinear flow-metabolism coupling during stimulation of visual cortex. Journal of Cerebral Blood Flow & Metabolism, 20(4):747–754. Van Zijl, P. C., Eleff, S. M., Ulatowski, J. A., Oja, J. M., Uluǧ, A. M., Traystman, R. J., and Kauppinen, R. A. (1998). Quantitative assessment of blood flow, blood volume and blood oxygenation effects in functional magnetic resonance imaging. Nature medicine, 4(2):159–167. Vessels, B. (n.d.). Structure and function of blood vessels. https://courses.lumenlearning.com/suny-ap2/chapter/structure-and-function-of-blood-vessels/3/. Vestergaard, M. B., Jensen, M. L., Arngrim, N., Lindberg, U., and Larsson, H. B. (2020). Higher physiological vulnerability to hypoxic exposure with advancing age in the human brain. Journal of Cerebral Blood Flow & Metabolism, 40(2):341–353. Wang, Y. and Payne, S. J. (2023). Static autoregulation in humans. Journal of Cerebral Blood Flow & Metabolism, page 0271678X231210430. Wei, Z., Chen, L., Hou, X., Van Zijl, P. C., Xu, J., and Lu, H. (2020a). Age-related alterations in brain perfusion, venous oxygenation, and oxygen metabolic rate of mice: a 17-month longitudinal MRI study. Frontiers in Neurology, 11:559. Wei, Z., Wang, Q., Modi, H. R., Cho, S.-M., Geocadin, R., Thakor, N. V., and Lu, H. (2020b). Acute-stage MRI cerebral oxygen consumption biomarkers predict 24-hour neurological outcome in a rat cardiac arrest model. NMR in Biomedicine, 33(11):e4377. Weisskoff, R. M. and Kiihne, S. (1992). MRI susceptometry: image-based measurement of absolute susceptibility of MR contrast agents and human blood. Magnetic resonance in medicine, 24(2):375–383. Wiesner, H. M., Balla, D. Z., Scheffler, K., Uğurbil, K., Zhu, X.-H., Chen, W., Uludağ, K., and Pohmann, R. (2021). Quantitative and simultaneous measurement of oxygen consumption rates in rat brain and skeletal muscle using 17o mrs imaging at 16.4 t. Magnetic resonance in medicine, 85(4):2232–2246. Wintermark, M., Sesay, M., Barbier, E., Borbély, K., Dillon, W. P., Eastwood, J. D., Glenn, T. C., Grandin, C. B., Pedraza, S., Soustiel, J.-F., et al. (2005). Comparative overview of brain perfusion imaging techniques. Stroke, 36(9):e83–e99. Wirestam, R., Lundberg, A., Chakwizira, A., van Westen, D., Knutsson, L., and Lind, E. (2022). Test-retest analysis of cerebral oxygen extraction estimates in healthy volunteers: comparison of methods based on quantitative susceptibility mapping and dynamic susceptibility contrast magnetic resonance imaging. Heliyon, 8(12). Wise, R. G., Harris, A. D., Stone, A. J., and Murphy, K. (2013). Measurement of OEF and absolute CMRO2: MRI-based methods using interleaved and combined hypercapnia and hyperoxia. Neuroimage, 83:135–147. Xu, N., LaGrow, T. J., Anumba, N., Lee, A., Zhang, X., Yousefi, B., Bassil, Y., Clavijo, G. P., Khalilzad Sharghi, V., Maltbie, E., et al. (2022). Functional connectivity of the brain across rodents and humans. Frontiers in Neuroscience, 16:816331. Xu, X., Wang, B., Ren, C., Hu, J., Greenberg, D. A., Chen, T., Xie, L., and Jin, K. (2017). Age-related impairment of vascular structure and functions. Aging and disease, 8(5):590. Xue, Y., Georgakopoulou, T., Van der Wijk, A.-E., Józsa, T. I., van Bavel, E., and Payne, S. J. (2022). Quantification of hypoxic regions distant from occlusions in cerebral penetrating arteriole trees. PLoS computational biology, 18(8):e1010166. Zhang, J., Liu, T., Gupta, A., Spincemaille, P., Nguyen, T. D., and Wang, Y. (2015). Quantitative mapping of cerebral metabolic rate of oxygen (CMRO2) using quantitative susceptibility mapping (QSM). Magnetic resonance in medicine, 74(4):945–952. Zhong, W., Ji, Z., and Sun, C. (2021). A review of monitoring methods for cerebral blood oxygen saturation. Healthcare, 9(9):1104. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94260 | - |
| dc.description.abstract | 老化顯著改變了人類大腦微血管系統的結構，影響了氧氣代謝和運輸。目前的模型專注於健康成年人的大腦，並未考慮老化相關的變化，而這些變化對於研究神經退行性疾病至關重要。微血管通過時間異質性 (CTH)與平均通過時間 (MTT)的比值，稱為通過時間異質性比(RTH)，作為壁剪切應力(WSS)變異性的指標。數值模擬在任意網絡和10個統計生成的微血管立方體中進行。人類大腦微血管模型通過修剪血管並基於三個不同年齡組的老鼠的活體測量數據創建連續的老化梯度來適應老化。計算了不同年齡組的通過時間分佈，並比較了這些組別的氧氣提取分數(OEF)、大腦氧氣代謝率 (CMRO2)和氧氣的分壓 (PO2)。RTH與網絡的氧氣提取分數成反比，並受老化和疾病等生理變化的影響，因此成為血管健康的重要標誌。在老化的大腦中，CMRO2每年下降0.94%，PO2每年下降0.12%，而OEF每年增加0.24%。年齡是開發用於評估微血管健康和認知衰退風險因素的in-silico模型的重要因素。CMRO2隨年齡的變化改變了對缺氧的脆弱性，影響了灌注。隨著CMRO2恆定的情況下增加腦血流量(CBF)，缺氧部分呈非線性減少；而隨著CBF恆定的情況下增加CMRO2，PO2呈非線性減少。 | zh_TW |
| dc.description.abstract | Ageing significantly alters the structure of the human cerebral microvasculature, impacting oxygen metabolism and transport. Existing models focus on the brains of healthy adults and do not account for the changes associated with ageing, which are crucial for studying neurodegenerative diseases. The ratio of capillary transit time heterogeneity (CTH) to mean transit time (MTT), referred to as ratio of transit time heterogeneity (RTH), serves as an indicator of wall shear stress (WSS) variability. Numerical simulations were conducted in arbitrary networks and 10 statistically generated microvascular cubes. The human cerebral microvasculature model was adapted for ageing by pruning vessels and creating a continuous ageing gradient based on in vivo measurements from mice in three different age groups. The transit time distribution for different age groups was calculated, and the oxygen extraction fraction (OEF), cerebral metabolic rate of oxygen (CMRO2), and partial pressure of oxygen PO2 were compared across these groups.
RTH is inversely proportional to the network's oxygen extraction fraction and is influenced by physiological changes such as ageing and disease, making it a valuable marker of vascular health. In the ageing brain, CMRO2 decreases by 0.94% per year, PO2 decreases by 0.12% per year, and OEF increases by 0.24% per year. Age is a crucial factor in developing in-silico models to assess microvascular health and cognitive decline risk factors. Changes in CMRO2 with age alter vulnerability to hypoxia, affecting perfusion. Increasing cerebral blood flow (CBF) with constant CMRO2 decreases the hypoxic fraction nonlinearly, while increases in CMRO2 with constant CBF nonlinearly decrease PO2. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-08-15T16:29:41Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-08-15T16:29:41Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Acknowledgements i
摘要iii Abstract v Contents vii List of Figures xi List of Tables xv Chapter 1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Chapter 2 Literature Review 5 2.1 Human Brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Brain Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.2 Brain Vasculature . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 Geometric and Topological Structure of the Cerebral Microvasculature 9 2.3 Brain Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.4 Comparison of Human and Rat Brain Models . . . . . . . . . . . . . 16 2.5 Ageing model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.5.1 Macrovascular . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.5.2 Microvascular . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.6 Haemodynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.7 Transit Time Distribution . . . . . . . . . . . . . . . . . . . . . . . . 25 2.7.1 Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 2.7.2 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.8 Oxygen Extraction Fraction . . . . . . . . . . . . . . . . . . . . . . 33 2.9 Oxygen Mass Transfer Coefficient . . . . . . . . . . . . . . . . . . . 37 2.10 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Chapter 3 Methods 41 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.2 Ageing Brain Model Development . . . . . . . . . . . . . . . . . . . 41 3.3 Calculate Permeability Tensor . . . . . . . . . . . . . . . . . . . . . 45 3.4 Transit Time Distribution Calculation . . . . . . . . . . . . . . . . . 46 3.5 Wall Shear Stress Distribution . . . . . . . . . . . . . . . . . . . . . 49 3.6 Brain Tissue Partial Pressure of Oxygen . . . . . . . . . . . . . . . . 50 3.7 Oxygen Transport Simulation . . . . . . . . . . . . . . . . . . . . . 52 3.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Chapter 4 Results 55 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.2 Geometry features in ageing . . . . . . . . . . . . . . . . . . . . . . 55 4.3 Flow in Ageing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.4 Transit Time Distribution in Ageing . . . . . . . . . . . . . . . . . . 59 4.5 Wall Shear Stress in Ageing . . . . . . . . . . . . . . . . . . . . . . 64 4.6 Impact of the Average Partial Pressure of Oxygen on Oxygen Consumption Rate Dynamics . . . . . . . . . . . . . . . . . . . . . . . . 68 4.7 Impact of Changing Cerebral Blood Flow on Hypoxic Fraction . . . . 72 4.8 Microvasculature Network and the Impact of Pruned Vessels . . . . . 73 4.9 Vessel Distance and Partial Pressure of Oxygen . . . . . . . . . . . . 75 4.10 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Chapter 5 Discussion 79 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 5.2 Rat Model in Healthy Ageing and Disease States . . . . . . . . . . . 79 5.3 Human Data in Healthy Ageing and Disease States . . . . . . . . . . 81 5.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Chapter 6 Conclusions and Future Work 87 6.1 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 6.2 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 6.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 References 91 Appendix A — Modelling Oxygen Dynamics in Microvascular Networks Using Green’s Function 111 | - |
| dc.language.iso | en | - |
| dc.subject | 微血管 | zh_TW |
| dc.subject | 腦血流 | zh_TW |
| dc.subject | 健康老化 | zh_TW |
| dc.subject | 氧運輸 | zh_TW |
| dc.subject | 缺氧 | zh_TW |
| dc.subject | 全腦氧氣擷取率 | zh_TW |
| dc.subject | 平均通過時間 | zh_TW |
| dc.subject | 通過時間異質性 | zh_TW |
| dc.subject | 通過時間異質性比 | zh_TW |
| dc.subject | oxygen transport | en |
| dc.subject | Capillaries | en |
| dc.subject | mean transit time | en |
| dc.subject | oxygen extraction fraction | en |
| dc.subject | hypoxia | en |
| dc.subject | cerebral blood flow | en |
| dc.subject | healthy ageing | en |
| dc.subject | relative transit time heterogeneity | en |
| dc.subject | capillary transit time heterogeneity | en |
| dc.title | 老化與腦微循環：生命期間氧氣輸送、傳遞時間分布和管壁剪應力的影響 | zh_TW |
| dc.title | Aging and Cerebral Microcirculation: Effects on Oxygen Delivery, Transit Time Distribution, and Wall Shear Stress Across Lifespan | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 艾洼比;吉美爾 | zh_TW |
| dc.contributor.oralexamcommittee | Wahbi El-Bouri;Mohd Jamil Mohamed Mokhtarudin | en |
| dc.subject.keyword | 微血管,腦血流,健康老化,氧運輸,缺氧,全腦氧氣擷取率,平均通過時間,通過時間異質性,通過時間異質性比, | zh_TW |
| dc.subject.keyword | Capillaries,cerebral blood flow,healthy ageing,oxygen transport,hypoxia,oxygen extraction fraction,mean transit time,capillary transit time heterogeneity,relative transit time heterogeneity, | en |
| dc.relation.page | 113 | - |
| dc.identifier.doi | 10.6342/NTU202403449 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2024-08-12 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 應用力學研究所 | - |
| 顯示於系所單位： | 應用力學研究所 | |
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