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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 曾文毅 | |
dc.contributor.author | Yun-Jing Kang | en |
dc.contributor.author | 康云瀞 | zh_TW |
dc.date.accessioned | 2021-07-09T15:53:30Z | - |
dc.date.available | 2024-08-28 | |
dc.date.copyright | 2019-08-28 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-08-14 | |
dc.identifier.citation | Aboitiz, F., Scheibel, A. B., Fisher, R. S., & Zaidel, E. (1992). Fiber composition of the human corpus callosum. Brain Res, 598, 143-153.
Ackman, J. B., Burbridge, T. J., & Crair, M. C. (2012). Retinal waves coordinate patterned activity throughout the developing visual system. Nature, 490(7419), 219-225. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/23060192. doi:10.1038/nature11529 Alexander, A. L., Hurley, S. A., Samsonov, A. A., Adluru, N., Hosseinbor, A. P., Mossahebi, P., . . . Field, A. S. (2011). Characterization of cerebral white matter properties using quantitative magnetic resonance imaging stains. Brain Connect, 1(6), 423-446. doi:10.1089/brain.2011.0071 Alfaro-Almagro, F., Jenkinson, M., Bangerter, N. K., Andersson, J. L. R., Griffanti, L., Douaud, G., . . . Smith, S. M. (2018). Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank. Neuroimage, 166, 400-424. doi:10.1016/j.neuroimage.2017.10.034 Amlien, I., Fjell, A. M., Walhovd, K. B., Selnes, P., Stenset, V., Grambaite, R., . . . Fladby, T. (2013). Mild Cognitive Impairment: Cerebrospinal Fluid Tau Biomarker Pathologic Levels and Longitudinal Changes in White Matter Integrity. Radiology, 266, 295-303. Antonenko, D., & Floel, A. (2014). Healthy aging by staying selectively connected: a mini-review. Gerontology, 60(1), 3-9. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/24080587. doi:10.1159/000354376 Araque Caballero, M. A., Suarez-Calvet, M., Duering, M., Franzmeier, N., Benzinger, T., Fagan, A. M., . . . Ewers, M. (2018). White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer's disease. Brain, 141(10), 3065-3080. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/30239611. doi:10.1093/brain/awy229 Avram, A. V., Sarlls, J. E., Barnett, A. S., Ozarslan, E., Thomas, C., Irfanoglu, M. O., . . . Basser, P. J. (2016). Clinical feasibility of using mean apparent propagator (MAP) MRI to characterize brain tissue microstructure. Neuroimage, 127, 422-434. doi:10.1016/j.neuroimage.2015.11.027 Bartzokis, G. (2004). Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease. Neurobiol Aging, 25(1), 5-18. doi:10.1016/j.neurobiolaging.2003.03.001 Basser, P. J., Mattiello, J., & LeBihan, D. (1994). MR Diffusion Tensor Spectroscopy and Imaging. Biophysical Journal, 66, 259-267. Beaulieu, C. (2002). The basis of anisotropic water diffusion in the nervous system - a technical review. NMR Biomed, 15(7-8), 435-455. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/12489094. doi:10.1002/nbm.782 Bennett, I. J., & Madden, D. J. (2014). Disconnected aging: cerebral white matter integrity and age-related differences in cognition. Neuroscience, 276, 187-205. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/24280637. doi:10.1016/j.neuroscience.2013.11.026 Berent-Spillson, A., Persad, C. C., Love, T., Sowers, M., Randolph, J. F., Zubieta, J. K., & Smith, Y. R. (2012). Hormonal environment affects cognition independent of age during the menopause transition. J Clin Endocrinol Metab, 97(9), E1686-1694. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/22730514. doi:10.1210/jc.2012-1365 Bowley, M. P., Cabral, H., Rosene, D. L., & Peters, A. (2010). Age changes in myelinated nerve fibers of the cingulate bundle and corpus callosum in the rhesus monkey. J Comp Neurol, 518(15), 3046-3064. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/20533359. doi:10.1002/cne.22379 Brugulat-Serrat, A., Salvado, G., Sudre, C. H., Grau-Rivera, O., Suarez-Calvet, M., Falcon, C., . . . Study, A. (2019). Patterns of white matter hyperintensities associated with cognition in middle-aged cognitively healthy individuals. Brain Imaging Behav. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/31278650. doi:10.1007/s11682-019-00151-2 Budde, M. D., Xie, M., Cross, A. H., & Song, S. K. (2009). Axial diffusivity is the primary correlate of axonal injury in the experimental autoimmune encephalomyelitis spinal cord: a quantitative pixelwise analysis. J Neurosci, 29(9), 2805-2813. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/19261876. doi:10.1523/JNEUROSCI.4605-08.2009 Chen, Y. J., Liu, C. M., Hsu, Y. C., Lo, Y. C., Hwang, T. J., Hwu, H. G., . . . Tseng, W. I. (2018). Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity. Hum Brain Mapp, 39(1), 575-587. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/29080229. doi:10.1002/hbm.23867 Chen, Y. J., Lo, Y. C., Hsu, Y. C., Fan, C. C., Hwang, T. J., Liu, C. M., . . . Tseng, W. Y. (2015). Automatic whole brain tract-based analysis using predefined tracts in a diffusion spectrum imaging template and an accurate registration strategy. Hum Brain Mapp, 36(9), 3441-3458. doi:10.1002/hbm.22854 Chien, Y. L., Chen, Y. J., Hsu, Y. C., Tseng, W. I., & Gau, S. S. (2017). Altered white-matter integrity in unaffected siblings of probands with autism spectrum disorders. Hum Brain Mapp, 38(12), 6053-6067. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/28940697. doi:10.1002/hbm.23810 Concha, L., Gross, D. W., Wheatley, B. M., & Beaulieu, C. (2006). Diffusion tensor imaging of time-dependent axonal and myelin degradation after corpus callosotomy in epilepsy patients. NeuroImage, 32(3), 1090-1099. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/16765064. doi:10.1016/j.neuroimage.2006.04.187 Cox, S. R., Ritchie, S. J., Tucker-Drob, E. M., Liewald, D. C., Hagenaars, S. P., Davies, G., . . . Deary, I. J. (2016). Ageing and brain white matter structure in 3,513 UK Biobank participants. Nat Commun, 7, 13629. doi:10.1038/ncomms13629 Decker, M. W. (1987). The effects of aging on hippocampal and cortical projections of the forebrain cholinergic system. . Brain Res Rev, 12, 423-438. Gold, B. T., & Keller, J. N. (Eds.). (2012). Imaging Brain Aging and Neurodegenerative Disease. (Vol. 1822). Ha, D. M., Xu, J., & Janowsky, J. S. (2007). Preliminary evidence that long-term estrogen use reduces white matter loss in aging. Neurobiol Aging, 28(12), 1936-1940. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/17030475. doi:10.1016/j.neurobiolaging.2006.08.007 Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008). Mapping the structural core of human cerebral cortex. PLoS Biol, 6(7), e159. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/18597554. doi:10.1371/journal.pbio.0060159 Hsu, Y. C., Lo, Y. C., Chen, Y. J., Wedeen, V. J., & Isaac Tseng, W. Y. (2015). NTU-DSI-122: A diffusion spectrum imaging template with high anatomical matching to the ICBM-152 space. Hum Brain Mapp, 36(9), 3528-3541. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/26095830. doi:10.1002/hbm.22860 Huang, J. Y., Liu, C. M., Hwang, T. J., Chen, Y. J., Hsu, Y. C., Hwu, H. G., . . . Tseng, W. I. (2018). Shared and distinct alterations of white matter tracts in remitted and nonremitted patients with schizophrenia. Hum Brain Mapp, 39(5), 2007-2019. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/29377322. doi:10.1002/hbm.23982 Hugenschmidt, C. E., Peiffer, A. M., Kraft, R. A., Casanova, R., Deibler, A. R., Burdette, J. H., . . . Laurienti, P. J. (2008). Relating imaging indices of white matter integrity and volume in healthy older adults. Cereb Cortex, 18(2), 433-442. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/17575289. doi:10.1093/cercor/bhm080 Jang, S. H., & Seo, J. P. (2015). Aging of corticospinal tract fibers according to the cerebral origin in the human brain: a diffusion tensor imaging study. Neurosci Lett, 585, 77-81. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/25445381. doi:10.1016/j.neulet.2014.11.030 Jelescu, I. O., Zurek, M., Winters, K. V., Veraart, J., Rajaratnam, A., Kim, N. S., . . . Fieremans, E. (2016). In vivo quantification of demyelination and recovery using compartment-specific diffusion MRI metrics validated by electron microscopy. NeuroImage, 132, 104-114. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/26876473. doi:10.1016/j.neuroimage.2016.02.004 Kao, T. W., Hsu, Y. C., & Tseng, W. I. (2019). Characteristic Normal Ageing Patterns of White Matter Tracts in 610 Cambridge Centre for Ageing and Neuroscience (Cam-CAN) Healthy Participants. Paper presented at the International Society for Magnetic Resonance in Medicine Montreal, Canada. Le Bihan, D., & Iima, M. (2015). Diffusion Magnetic Resonance Imaging: What Water Tells Us about Biological Tissues. PLoS Biol, 13(7), e1002203. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/26204162. doi:10.1371/journal.pbio.1002203 Lebel, C., Gee, M., Camicioli, R., Wieler, M., Martin, W., & Beaulieu, C. (2012). Diffusion tensor imaging of white matter tract evolution over the lifespan. Neuroimage, 60(1), 340-352. doi:10.1016/j.neuroimage.2011.11.094 Liewald, D., Miller, R., Logothetis, N., Wagner, H. J., & Schuz, A. (2014). Distribution of axon diameters in cortical white matter: an electron-microscopic study on three human brains and a macaque. Biol Cybern, 108(5), 541-557. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/25142940. doi:10.1007/s00422-014-0626-2 Lo, Y. C., Chen, Y. J., Hsu, Y. C., Chien, Y. L., Gau, S. S., & Tseng, W. I. (2019). Altered frontal aslant tracts as a heritable neural basis of social communication deficits in autism spectrum disorder: A sibling study using tract-based automatic analysis. Autism Res, 12(2), 225-238. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/30548800. doi:10.1002/aur.2044 Lyttelton, O., Boucher, M., Robbins, S., & Evans, A. (2007). An unbiased iterative group registration template for cortical surface analysis. NeuroImage, 34(4), 1535-1544. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/17188895. doi:10.1016/j.neuroimage.2006.10.041 Marner, L., & Pakkenberg, B. (2003). Total length of nerve fibers in prefrontal and global white matter of chronic schizophrenics. Journal of Psychiatric Research, 37(6), 539-547. doi:10.1016/s0022-3956(03)00069-4 Meier-Ruge, W., Ulrich, J., Bruhlmann, M., & Meier, E. (1992). Age-Related White Matter Atrophy in the Human Brain. Ann N Y Acad Sci, 673, 260-269. Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., . . . Smith, S. M. (2016). Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat Neurosci, 19(11), 1523-1536. doi:10.1038/nn.4393 Mora, F., & Phil, D. (2013). Successful brain aging: plasticity, environmental enrichment, and lifestyle. Dialogues in Clinical Neuroscience, 15(1), 45-52. Mosconi, L., Berti, V., Quinn, C., McHugh, P., Petrongolo, G., Varsavsky, I., . . . Brinton, R. D. (2017). Sex differences in Alzheimer risk. Neurology, 89, 1-9. Munoz Maniega, S., Chappell, F. M., Valdes Hernandez, M. C., Armitage, P. A., Makin, S. D., Heye, A. K., . . . Wardlaw, J. M. (2017). Integrity of normal-appearing white matter: Influence of age, visible lesion burden and hypertension in patients with small-vessel disease. J Cereb Blood Flow Metab, 37(2), 644-656. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/26933133. doi:10.1177/0271678X16635657 O'Sullivan, M., Lythgoe, D. J., Pereira, A. C., Summers, P. E., Jarosz, J. M., Williams, S. C. R., & Markus, H. S. (2002). Patterns of cerebral blood flow reduction in patients with ischemic leukoaraiosis. Neurology, 59(3). Ozarslan, E., Koay, C. G., Shepherd, T. M., Komlosh, M. E., Irfanoglu, M. O., Pierpaoli, C., & Basser, P. J. (2013). Mean apparent propagator (MAP) MRI: a novel diffusion imaging method for mapping tissue microstructure. Neuroimage, 78, 16-32. doi:10.1016/j.neuroimage.2013.04.016 Pakkenberg, B., & Gundersen, H. J. (1997). Neocortical neuron number in humans: effect of sex and age. Journal of Comparative Neurology, 384, 312-320. Pakkenberg, B., Pelvig, D., Marner, L., Bundgaard, M. J., Gundersen, H. J., Nyengaard, J. R., & Regeur, L. (2003). Aging and the human neocortex. Exp. Gerontol., 38, 95-99. Peper, J. S., van den Heuvel, M. P., Mandl, R. C., Hulshoff Pol, H. E., & van Honk, J. (2011). Sex steroids and connectivity in the human brain: a review of neuroimaging studies. Psychoneuroendocrinology, 36(8), 1101-1113. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/21641727. doi:10.1016/j.psyneuen.2011.05.004 Peters, A., & Folger, C. (2013). A website entitled 'The fine structure of the aging brain'. J Comp Neurol, 521(6), 1203-1206. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/23229793. doi:10.1002/cne.23280 Peters, A., Morrison, J. H., Rosene, D. L., & Hyman, B. T. (1998). Feature Article Are Neurons Lost from the Primate Cerebral Cortex during Normal Aging? Cereb Cortex, 8, 295-300. Peters, A., Moss, M. B., & Sethares, C. (2000). Effects of Aging on Myelinated Nerve Fibers in Monkey Primary Visual Cortex. Journal of Comparative Neurology, 419, 364-376. Peters, A., & Sethares, C. (2002). Aging and the myelinated fibers in prefrontal cortex and corpus callosum of the monkey. J Comp Neurol, 442(3), 277-291. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11774342. Prins, N. D., & Scheltens, P. (2015). White matter hyperintensities, cognitive impairment and dementia: an update. Nature Reviews Neurology, 11(3), 157-165. doi:10.1038/nrneurol.2015.10 Reginold, W., Sam, K., Poublanc, J., Fisher, J., Crawley, A., & Mikulis, D. J. (2018). Impact of white matter hyperintensities on surrounding white matter tracts. Neuroradiology, 60(9), 933-944. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/30030550. doi:10.1007/s00234-018-2053-x Ritchie, S. J., Cox, S. R., Shen, X., Lombardo, M. V., Reus, L. M., Alloza, C., . . . Deary, I. J. (2018). Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants. Cereb Cortex, 28(8), 2959-2975. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/29771288. doi:10.1093/cercor/bhy109 Ritchie, S. J., Tucker-Drob, E. M., Cox, S. R., Dickie, D. A., Del, C. V. H. M., Corley, J., . . . Deary, I. J. (2017). Risk and protective factors for structural brain ageing in the eighth decade of life. Brain Struct Funct, 222(8), 3477-3490. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/28424895. doi:10.1007/s00429-017-1414-2 Rosenbluth, J., Stoffel, W., & Schiff, R. (1996). Myelin Structure in Proteolipid Protein (PLP)-Null Mouse Spinal Cord. Journal of Comparative Neurology, 371, 336-344. Schmidt, P., Gaser, C., Arsic, M., Buck, D., Forschler, A., Berthele, A., . . . Muhlau, M. (2012). An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis. Neuroimage, 59(4), 3774-3783. doi:10.1016/j.neuroimage.2011.11.032 Seltzer, B., Zolnouni, P., Nunez, M., Goldman, R., Kumar, D., Ieni, J., . . . Group, D. S. (2004). Efficacy of donepezil in early-stage Alzheimer disease: a randomized placebo-controlled trial. Arch Neurol, 61(12), 1852-1856. Song, S.-K., Sun, S.-W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002). Dysmyelination Revealed through MRI as Increased Radial (but Unchanged Axial) Diffusion of Water. NeuroImage, 17(3), 1429-1436. doi:10.1006/nimg.2002.1267 Sporns, O., Tononi, G., & Kotter, R. (2005). The human connectome: A structural description of the human brain. PLoS Comput Biol, 1(4), e42. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/16201007. doi:10.1371/journal.pcbi.0010042 Stadlbauer, A., Salomonowitz, E., Strunk, G., Hammen, T., & Ganslandt, O. (2008). Assessment with Diffusion-Tensor Imaging and Quantitative Fiber Tracking. Radiology, 247, 179-188. Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., . . . Collins, R. (2015). UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med, 12(3), e1001779. doi:10.1371/journal.pmed.1001779 Sullivan, E. V., Adalsteinsson, E., & Pfefferbaum, A. (2006). Selective age-related degradation of anterior callosal fiber bundles quantified in vivo with fiber tracking. Cereb Cortex, 16, 1030-1039. Tian, Q., Glynn, N. W., Erickson, K. I., Aizenstein, H. J., Simonsick, E. M., Yaffe, K., . . . Health, A. B. C. S. (2015). Objective measures of physical activity, white matter integrity and cognitive status in adults over age 80. Behav Brain Res, 284, 51-57. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/25655514. doi:10.1016/j.bbr.2015.01.045 Tomasi, D., & Volkow, N. D. (2012). Laterality patterns of brain functional connectivity: gender effects. Cereb Cortex, 22(6), 1455-1462. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/21878483. doi:10.1093/cercor/bhr230 Tsai, T. H., Su, H. T., Hsu, Y. C., Shih, Y. C., Chen, C. C., Hu, F. R., & Tseng, W. I. (2019). White matter microstructural alterations in amblyopic adults revealed by diffusion spectrum imaging with systematic tract-based automatic analysis. Br J Ophthalmol, 103(4), 511-516. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/29844086. doi:10.1136/bjophthalmol-2017-311733 Tuch, D. S. (2004). Q-ball imaging. Magn Reson Med, 52, 1358-1372. Waiter, G., Hsu, Y. C., Kang, Y. J., Kao, T. W., Chen, C. L., Chen, P. Y., & Tseng, W. I. (2019). Microstructural changes of white matter tracts across late lifespan on 7,167 UK Biobank participants. Paper presented at the Organization for Human Brain Mapping, Rome, Italy. Wallace, E. J., Mathias, J. L., & Ward, L. (2018). The relationship between diffusion tensor imaging findings and cognitive outcomes following adult traumatic brain injury: A meta-analysis. Neurosci Biobehav Rev, 92, 93-103. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/29803527. doi:10.1016/j.neubiorev.2018.05.023 Williamson, W., Lewandowski, A. J., Forkert, N. D., Griffanti, L., Okell, T. W., Betts, J., . . . Leeson, P. (2018). Association of Cardiovascular Risk Factors With MRI Indices of Cerebrovascular Structure and Function and White Matter Hyperintensities in Young Adults. JAMA, 320(7), 665-673. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/30140877. doi:10.1001/jama.2018.11498 Wong, S. M., Jansen, J. F. A., Zhang, E., Hoff, E. I., Staals, J., van Oostenbrugge, R. J., & Backes, W. H. (2019). Blood-brain barrier impairment and hypoperfusion are linked in cerebral small vessel disease. Neurology, 92, e1-e9. Wu, C. H., Hwang, T. J., Chen, Y. J., Hsu, Y. C., Lo, Y. C., Liu, C. M., . . . Isaac Tseng, W. Y. (2015). Primary and secondary alterations of white matter connectivity in schizophrenia: A study on first-episode and chronic patients using whole-brain tractography-based analysis. Schizophr Res, 169(1-3), 54-61. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/26443482. doi:10.1016/j.schres.2015.09.023 Ycaza Herrera, A., & Mather, M. (2015). Actions and interactions of estradiol and glucocorticoids in cognition and the brain: Implications for aging women. Neurosci Biobehav Rev, 55, 36-52. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/25929443. doi:10.1016/j.neubiorev.2015.04.005 Yoon, B., Shim, Y. S., Lee, K. S., Shon, Y. M., & Yang, D. W. (2008). Region-specific changes of cerebral white matter during normal aging: a diffusion-tensor analysis. Arch Gerontol Geriatr, 47(1), 129-138. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/17764763. doi:10.1016/j.archger.2007.07.004 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/76510 | - |
dc.description.abstract | 神經纖維在正常老化和神經退化性疾病中逐漸退化。過去在神經解剖學和神經影像學研究發現,不同區域的神經纖維隨著年歲增長而退化的現象具異質性;然而,仍缺乏從中年到老年完整大腦白質隨著年齡增加退化模式的完整描述。在此,我們使用英國生物銀行的擴散磁振造影資料,來分析7167名47到76歲、神經系統正常的受試者老化過程神經纖維束的變化。擴散磁振影像和結構磁振影像資料皆在兩年內於同一台3T磁振造影掃描儀上取得,透過四個擴散指標來看神經纖維束變化率,包含概化部分不等向性(GFA )、軸向擴散係數(AD)、徑向擴散係數(RD)、平均擴散係數(MD),編碼76條神經纖維束的神經特異變化率,可呈現出神經退化的空間形態。另外我們分析T2-FLAIR影像與年齡相關的腦白質病變(WMHL)的變化。為了探討是否有性別差異,我們依生理性別把受試者分為男性(3368名)與女性(3799名)兩族群。我們的研究發現,所有受試者的神經纖維束完整性,隨年齡增長呈現緩慢穩定的下降趨勢。在大部分的慢性退行性病變的神經纖維束中(76條中的41條),隨著年齡增長,GFA呈下降趨勢,AD、RD和MD呈上升趨勢。這些纖維束包含大多數聯絡神經纖維(association fibers)、以及連接前額葉的投射神經纖維(projection fibers)和聯合神經纖維(commissure fibers)。另外有16條神經纖維,擴散指數隨年齡增長呈非典型變化,這些神經纖維束涉及負責快速視覺處理、學習和記憶等功能,顯示出對老化影響相對強的韌性。相較之下,WMHL累積率最高的空間形態包括圍繞側腦室的神經纖維束,佔據周腦室和深部白質區。女性受試者的纖維完整性(GFA)退化程度較男性受試者嚴重,但在WMHL並沒有顯著的性別差異。這種差異表明,這兩種截然不同的年齡相關變化之間的相互作用很弱。綜合以上所述,對老化模式的完整描述可揭示衰老或抗衰老的研究,有助於找出神經退化性疾病影像的生物標記。 | zh_TW |
dc.description.abstract | Nerve fibers degenerate during normal aging and in neurodegenerative disease. Previous neuroanatomical and neuroimaging studies have found heterogeneous vulnerabilities of nerve fibers to age-related degeneration. However, a complete description of spatial and temporal patterns of degeneration over the whole brain tracts from middle to late adulthood is lacking. Here, we analyzed diffusion MRI data in the UK Biobank and estimated tract-specific age-related changes of fiber degeneration on 7167 neurologically normal participants aged 47 to 76 years. Diffusion MRI and structure MRI were acquired on the same 3T scanner within two years. Nerve fiber degeneration was estimated in terms of the rate of change in four diffusion indices, i.e. generalized fractional anisotropy (GFA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD). Spatial patterns of fiber degeneration were rendered by encoding tract-specific rates of change to 76 fiber tracts. Age-related change of white matter hyperintensity lesions (WMHL) was also analyzed on T2-FLAIR tract wise. To appreciate sex difference, male (N = 3368) and female (N = 3799) participants were displayed separately. The results showed that the study population presented a slow and monotonic decline of fiber integrity with age. The diffusion profile of chronic degeneration change, as presented with decreased GFA, increased AD, RD and MD with age, constituted the majority of the tracts (41 out of 76 tracts). The tracts included most of the association fibers, as well as the projection and commissure fibers connecting the prefrontal lobe. Another 16 tracts constituted a minority, exhibiting atypical changes of diffusion indices with age. These tracts involved the tracts responsible for fast visual processing, learning and memory, suggesting relative resilience to aging effects. In contrast, the spatial pattern of highest rates of WMHL accumulation comprised a cluster of tracts surrounding the lateral ventricle, occupying the periventricular and deep white matter regions. Female participants tended to have more profound degeneration of fiber integrity (GFA) than male participants, but there was no significant sex difference in WMHL. The disparity suggests weak interactions between these two distinct age-related changes. In conclusion, the complete description of degenerative patterns could shed light on the aging or anti-aging research, and facilitate the discovery of new imaging biomarkers of neurodegenerative disease. | en |
dc.description.provenance | Made available in DSpace on 2021-07-09T15:53:30Z (GMT). No. of bitstreams: 1 ntu-108-R06458007-1.pdf: 10118704 bytes, checksum: e2bf855fc9e444152a0f4aa35839872d (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 口試委員審定書 i
誌謝 ii 摘要 iii Abstract iv List of Figures ix List of Tables x Chapter 1 Introduction 1 1.1 Axons, connectomics, and cognitive functions 1 1.2 Degeneration of nerve fibers in brain aging 1 1.3 Patterns of fiber degeneration as a potential biomarker of abnormal brain aging 3 1.4 Axonal fiber tracts in neuroimaging of brain aging 4 1.5 Opportunities for mapping fiber degeneration in normal aging..5 1.6 Purpose of the study 6 Chapter 2 Methods 8 2.1 Data source 8 2.1.1 Participants 8 2.1.2 MRI data acquisition 8 2.1.3 Data screening 9 2.2 Image processing 10 2.2.1 Reconstruction of dMRI data 10 2.2.2 Tract-based analysis of diffusion indices 11 2.2.3 Tract-specific sampling of WMHL 12 2.3 Correction for cerebrospinal fluid (CSF) partial volume effect 13 2.4 Tract grouping 14 2.5 Statistics 14 Chapter 3 Results 16 3.1 Demographics 16 3.2 Rates of change in tract integrity at different levels of tract grouping 17 3.3 Brain-wide patterns of rates of change in WMHL 26 3.4 Normative models of white matter tract property in the UK Biobank cohort 29 Chapter 4 Discussion 31 4.1 Summary 31 4.2 Age-related microstructural change as reflected by diffusion changes 32 4.3 White matter tracts showing a dominant diffusion change profile 34 4.4 Age-related diffusion changes deviating from the dominant profile 35 4.5 Spatial patterns of WMHL changes with age 37 4.6 Sex differences in age-related tract changes 38 4.7 Temporal patterns of tract changes with age 39 4.8 Partial volume correction for CSF 40 4.9 Limitations 41 4.10 Conclusions 42 4.11 Acknowledgments 43 References 44 Supplementary Files 52 SF1. Screening of MRI data 52 SF2. Procedures of image registration 54 SF3. The results of diffusion indices after CSF partial volume correction as compared with uncorrected diffusion indices 57 SF4. Detailed information of 76 tracts and 5 levels of grouping 60 SF5. Justification of the use of the linear model as opposed to the quadratic model in the analysis of age-associated change in tract integrity 65 SF6. The β_1and P values of GFA, AD, RD, and MD derived from the linear model at five levels of tract grouping 67 SF7. The β1and P values of WMHL derived from the linear model at five levels of tract grouping 74 SF8. Normative models of white matter tract integrity of the UK Biobank cohort 76 | |
dc.language.iso | en | |
dc.title | 利用擴散磁振造影探討英國生物銀行7167名中老年人大腦白質微結構之變化 | zh_TW |
dc.title | Microstructural changes of white matter tracts across late lifespan: A diffusion MRI study on 7167 healthy adults in the UK Biobank | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 黃宣銘,吳恩賜 | |
dc.subject.keyword | 白質老化,擴散磁振造影,白質病變,性?差異,白質微結構特性, | zh_TW |
dc.subject.keyword | White matter aging,Diffusion MRI,white matter hyperintensity,Sex differences,White matter microstructural property, | en |
dc.relation.page | 96 | |
dc.identifier.doi | 10.6342/NTU201902945 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2019-08-14 | |
dc.contributor.author-college | 醫學院 | zh_TW |
dc.contributor.author-dept | 醫療器材與醫學影像研究所 | zh_TW |
dc.date.embargo-lift | 2024-08-28 | - |
顯示於系所單位: | 醫療器材與醫學影像研究所 |
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