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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 曾文毅(Wen-Yih Isaac Tseng) | |
dc.contributor.author | Te-Wei Kao | en |
dc.contributor.author | 高德瑋 | zh_TW |
dc.date.accessioned | 2021-06-17T07:03:55Z | - |
dc.date.available | 2024-08-27 | |
dc.date.copyright | 2019-08-27 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-07-29 | |
dc.identifier.citation | Aboitiz, F., & Montiel, J. (2003). One hundred million years of interhemispheric communication: the history of the corpus callosum. Brazilian journal of medical and biological research, 36(4), 409-420.
Aboitiz, F., Rodriguez, E., Olivares, R., & Zaidel, E. (1996). Age-related changes in fibre composition of the human corpus callosum: sex differences. Neuroreport, 7(11), 1761-1764. Aboitiz, F., Scheibel, A. B., Fisher, R. S., & Zaidel, E. (1992). Fiber composition of the human corpus callosum. Brain research, 598(1-2), 143-153. 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 connectivity, 1(6), 423-446. Ashburner, J., & Friston, K. J. (2005). Unified segmentation. Neuroimage, 26(3), 839-851. Assaf, Y., & Pasternak, O. (2008). Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review. Journal of molecular neuroscience, 34(1), 51-61. Avram, A. V., Sarlls, J. E., Barnett, A. S., Özarslan, 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. Basser, P. J., Mattiello, J., & LeBihan, D. (1994). MR diffusion tensor spectroscopy and imaging. Biophysical journal, 66(1), 259-267. Beaulieu, C. (2002). The basis of anisotropic water diffusion in the nervous system–a technical review. NMR in Biomedicine: An International Journal Devoted to the Development and Application of Magnetic Resonance In Vivo, 15(7-8), 435-455. Bhagat, Y. A., & Beaulieu, C. (2004). Diffusion anisotropy in subcortical white matter and cortical gray matter: Changes with aging and the role of CSF-suppression. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, 20(2), 216-227. Burzynska, A. Z., Preuschhof, C., Bäckman, L., Nyberg, L., Li, S. C., Lindenberger, U., & Heekeren, H. R. (2010). Age-related differences in white matter microstructure: region-specific patterns of diffusivity. Neuroimage, 49(3), 2104-2112. Catani, M., Jones, D. K., Donato, R., & Ffytche, D. H. (2003). Occipito-temporal connections in the human brain. Brain, 126(9), 2093-2107. Chen, Y. J., Lo, Y. C., Hsu, Y. C., Fan, C. C., Hwang, T. J., Liu, C. M., ... & Tseng, W. Y. I. (2015). Automatic whole brain tract-based analysis using predefined tracts in a diffusion spectrum imaging template and an accurate registration strategy. Human brain mapping, 36(9), 3441-3458. Chou, M. C., Lin, Y. R., Huang, T. Y., Wang, C. Y., Chung, H. W., Juan, C. J., & Chen, C. Y. (2005). FLAIR diffusion-tensor MR tractography: comparison of fiber tracking with conventional imaging. American journal of neuroradiology, 26(3), 591-597. Concha, L., Gross, D. W., & Beaulieu, C. (2005). Diffusion tensor tractography of the limbic system. American Journal of Neuroradiology, 26(9), 2267-2274. 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. Nature communications, 7, 13629. Davis, S. W., Dennis, N. A., Buchler, N. G., White, L. E., Madden, D. J., & Cabeza, R. (2009). Assessing the effects of age on long white matter tracts using diffusion tensor tractography. Neuroimage, 46(2), 530-541. Dietrich, O., Raya, J. G., Reeder, S. B., Reiser, M. F., & Schoenberg, S. O. (2007). Measurement of signal-to-noise ratios in MR images: influence of multichannel coils, parallel imaging, and reconstruction filters. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, 26(2), 375-385. Fjell, A. M., Westlye, L. T., Greve, D. N., Fischl, B., Benner, T., van der Kouwe, A. J., ... & Walhovd, K. B. (2008). The relationship between diffusion tensor imaging and volumetry as measures of white matter properties. Neuroimage, 42(4), 1654-1668. Fritzsche, K. H., Laun, F. B., Meinzer, H. P., & Stieltjes, B. (2010). Opportunities and pitfalls in the quantification of fiber integrity: what can we gain from Q-ball imaging?. NeuroImage, 51(1), 242-251. Gorczewski, K., Mang, S., & Klose, U. (2009). Reproducibility and consistency of evaluation techniques for HARDI data. Magnetic Resonance Materials in Physics, Biology and Medicine, 22(1), 63. Grieve, S. M., Williams, L. M., Paul, R. H., Clark, C. R., & Gordon, E. (2007). Cognitive aging, executive function, and fractional anisotropy: a diffusion tensor MR imaging study. American Journal of Neuroradiology, 28(2), 226-235. Hasan, K. M., Iftikhar, A., Kamali, A., Kramer, L. A., Ashtari, M., Cirino, P. T., ... & Ewing-Cobbs, L. (2009). Development and aging of the healthy human brain uncinate fasciculus across the lifespan using diffusion tensor tractography. Brain research, 1276, 67-76. Hasan, K. M., Kamali, A., Abid, H., Kramer, L. A., Fletcher, J. M., & Ewing-Cobbs, L. (2010). Quantification of the spatiotemporal microstructural organization of the human brain association, projection and commissural pathways across the lifespan using diffusion tensor tractography. Brain Structure and Function, 214(4), 361-373. Hasan, K. M., Kamali, A., Iftikhar, A., Kramer, L. A., Papanicolaou, A. C., Fletcher, J. M., & Ewing-Cobbs, L. (2009). Diffusion tensor tractography quantification of the human corpus callosum fiber pathways across the lifespan. Brain research, 1249, 91-100. Hoy, A. R., Kecskemeti, S. R., & Alexander, A. L. (2015). Free water elimination diffusion tractography: A comparison with conventional and fluid-attenuated inversion recovery, diffusion tensor imaging acquisitions. Journal of Magnetic Resonance Imaging, 42(6), 1572-1581. Hsu, Y. C., & Tseng, W. Y. I. (2018). An efficient regularization method for diffusion MAP-MRI estimation. Poster session presented at the Annual Meeting ISMRM – ESMRMB, Paris, France Hsu, Y. C., Hsu, C. H., & Tseng, W. Y. I. (2012). A large deformation diffeomorphic metric mapping solution for diffusion spectrum imaging datasets. NeuroImage, 63(2), 818-834. 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. Human brain mapping, 36(9), 3528-3541. Jones, D. K., & Cercignani, M. (2010). Twenty-five pitfalls in the analysis of diffusion MRI data. NMR in Biomedicine, 23(7), 803-820. Kochunov, P., Williamson, D. E., Lancaster, J., Fox, P., Cornell, J., Blangero, J., & Glahn, D. C. (2012). Fractional anisotropy of water diffusion in cerebral white matter across the lifespan. Neurobiology of aging, 33(1), 9-20. 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. Madden, D. J., Bennett, I. J., Burzynska, A., Potter, G. G., Chen, N. K., & Song, A. W. (2012). Diffusion tensor imaging of cerebral white matter integrity in cognitive aging. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease, 1822(3), 386-400. Madden, D. J., Spaniol, J., Costello, M. C., Bucur, B., White, L. E., Cabeza, R., ... & Huettel, S. A. (2008). Cerebral white matter integrity mediates adult age differences in cognitive performance. Journal of cognitive neuroscience, 21(2), 289-302. MEIER-RUGE, W. I. L. L. I. A. M., Ulrich, J., Brühlmann, M., & Meier, E. (1992). Age-related white matter atrophy in the human brain. Annals of the New York Academy of Sciences, 673(1), 260-269. Metzler-Baddeley, C., O'sullivan, M. J., Bells, S., Pasternak, O., & Jones, D. K. (2012). How and how not to correct for CSF-contamination in diffusion MRI. Neuroimage, 59(2), 1394-1403. Moseley, M. (2002). Diffusion tensor imaging and aging–a review. NMR in Biomedicine: An International Journal Devoted to the Development and Application of Magnetic Resonance In Vivo, 15(7-8), 553-560. Mukherjee, P., Miller, J. H., Shimony, J. S., Philip, J. V., Nehra, D., Snyder, A. Z., ... & McKinstry, R. C. (2002). Diffusion-tensor MR imaging of gray and white matter development during normal human brain maturation. American Journal of Neuroradiology, 23(9), 1445-1456. Nations, U. (2016). World population ageing 1950-2050. United Nations, Department of Economic and Social Affairs, Population Division. Norris, D. G. (2001). The effects of microscopic tissue parameters on the diffusion weighted magnetic resonance imaging experiment. NMR in Biomedicine: An International Journal Devoted to the Development and Application of Magnetic Resonance In Vivo, 14(2), 77-93. O’Sullivan, M., Morris, R. G., Huckstep, B., Jones, D. K., Williams, S. C. R., & Markus, H. S. (2004). Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis. Journal of Neurology, Neurosurgery & Psychiatry, 75(3), 441-447. Papadakis, N. G., Martin, K. M., Mustafa, M. H., Wilkinson, I. D., Griffiths, P. D., Huang, C. L. H., & Woodruff, P. W. (2002). Study of the effect of CSF suppression on white matter diffusion anisotropy mapping of healthy human brain. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 48(2), 394-398. Parker, G. J., Luzzi, S., Alexander, D. C., Wheeler-Kingshott, C. A., Ciccarelli, O., & Ralph, M. A. L. (2005). Lateralization of ventral and dorsal auditory-language pathways in the human brain. Neuroimage, 24(3), 656-666. Pasternak, O., Sochen, N., Gur, Y., Intrator, N., & Assaf, Y. (2009). Free water elimination and mapping from diffusion MRI. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine, 62(3), 717-730. Pierpaoli, C., & Jones, D. K. (2004). Removing CSF contamination in brain DT-MRIs by using a two-compartment tensor model. In International Society for Magnetic Resonance in Medicine Meeting (p. 1215). Rashid, W., Hadjiprocopis, A., Griffin, C. M., Chard, D. T., Davies, G. R., Barker, G. J., ... & Miller, D. H. (2004). Diffusion tensor imaging of early relapsing-remitting multiple sclerosis with histogram analysis using automated segmentation and brain volume correction. Multiple Sclerosis Journal, 10(1), 9-15. Salminen, L. E., Conturo, T. E., Bolzenius, J. D., Cabeen, R. P., Akbudak, E., & Paul, R. H. (2016). Reducing CSF partial volume effects to enhance diffusion tensor imaging metrics of brain microstructure. Technology and innovation, 18(1), 5. Shafto, M. A., Tyler, L. K., Dixon, M., Taylor, J. R., Rowe, J. B., Cusack, R., ... & Henson, R. N. (2014). The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study protocol: a cross-sectional, lifespan, multidisciplinary examination of healthy cognitive ageing. BMC neurology, 14(1), 204. Shiffler, R. E. (1988). Maximum Z scores and outliers. The American Statistician, 42(1), 79-80. Smith, S. M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., ... & Behrens, T. E. (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage, 31(4), 1487-1505. Song, S. K., Sun, S. W., Ju, W. K., Lin, S. J., Cross, A. H., & Neufeld, A. H. (2003). Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage, 20(3), 1714-1722. Song, S. K., Yoshino, J., Le, T. Q., Lin, S. J., Sun, S. W., Cross, A. H., & Armstrong, R. C. (2005). Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage, 26(1), 132-140. Takao, H., Hayashi, N., Inano, S., & Ohtomo, K. (2011). Effect of head size on diffusion tensor imaging. Neuroimage, 57(3), 958-967. Taylor, J. R., Williams, N., Cusack, R., Auer, T., Shafto, M. A., Dixon, M., ... & Henson, R. N. (2017). The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample. Neuroimage, 144, 262-269. Vos, S. B., Jones, D. K., Viergever, M. A., & Leemans, A. (2011). Partial volume effect as a hidden covariate in DTI analyses. Neuroimage, 55(4), 1566-1576. Westerhausen, R., Kompus, K., Dramsdahl, M., Falkenberg, L. E., Grüner, R., Hjelmervik, H., ... & Hugdahl, K. (2011). A critical re-examination of sexual dimorphism in the corpus callosum microstructure. Neuroimage, 56(3), 874-880. Westlye, L. T., Walhovd, K. B., Dale, A. M., Bjørnerud, A., Due-Tønnessen, P., Engvig, A., ... & Fjell, A. M. (2009). Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. Cerebral cortex, 20(9), 2055-2068. Yendiki, A., Koldewyn, K., Kakunoori, S., Kanwisher, N., & Fischl, B. (2014). Spurious group differences due to head motion in a diffusion MRI study. Neuroimage, 88, 79-90. Zhang, Y., Du, A. T., Hayasaka, S., Jahng, G. H., Hlavin, J., Zhan, W., ... & Schuff, N. (2010). Patterns of age-related water diffusion changes in human brain by concordance and discordance analysis. Neurobiology of aging, 31(11), 1991-2001. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72699 | - |
dc.description.abstract | 擴散張量磁振造影(diffusion tensor imaging, DTI)是一種可以評估大腦白質神經纖維微結構的技術,但是因其固有的造影技術限制,幾乎無法避免腦脊髓液部分體積效應(cerebrospinal fluid partial volume effect, PVECSF)的產生。因此,在先前與年齡相關變化的研究中,因為大腦白質神經纖維微結構與 PVECSF皆會隨著年齡而變化,使得兩者常常被混淆。
在本研究中,我們使用結合了高階對位策略的腦神經纖維自動化分析(tract-based automatic analysis, TBAA)技術來測量擴散參數指標,並提出一種藉由估計擴散參數指標和CSF機率之間的線性關係來排除PVECSF的新創校正方法。為了確保此方法的可行性,我們設計了多種情況來進行模擬驗證、以及確認不同PVECSF程度的大腦白質神經纖維在校正後的兩側對稱性,並且更進一步視覺化以比較未校正和校正結果在各方面的差異性。 在排除PVECSF的影響後,我們透過一群橫跨生命週期且年齡均勻分布之正常受試者,建構出大腦白質神經纖維微結構隨著年齡變化的軌跡,並清楚地揭示了各個主要的神經纖維束組別的特性,包括終其一生的特異性質、於各個年齡的成熟與衰退速率、以及發育和退化的時間點。而統計檢定的結果表示PVECSF對於年齡相關變化的研究確實會造成顯著的影響,因此使用此新創校正方法是必要的,而且將有助於產生更精闢的研究。 本研究提出了一種快速、簡單、可行的新創校正方法,並證明了校正PVECSF對於相關研究的重要性,也藉此清楚地揭示基於大腦白質神經纖維微結構於年齡相關變化的“真實”正常模式。 | zh_TW |
dc.description.abstract | Diffusion tensor imaging (DTI) is a technique that can investigate white matter microstructure, while its inherent limitations are cerebrospinal fluid partial volume effect (PVECSF). Furthermore, white matter microstructure is often confused with the changes of PVECSF in age-related studies previously.
Here, tract-based automatic analysis (TBAA) was used to measure the diffusion indices and a novel correction method which regressed out PVECSF by estimating the linear relationship between diffusion indices and CSF probability was proposed. Moreover, demonstration was conducted to ensure the feasibility, and comparisons of the differences between uncorrected and corrected results were performed. Through eliminating PVECSF, the characteristics of the trajectories on large healthy participants whose age distribute uniformly across lifespan clearly revealed the specific properties, rates of maturation and decline, and timing of development and degeneration for each tract group. In addition, statistical results suggested our novel correction method could be recommended for incisive studies. The present study demonstrates the importance of correcting PVECSF and the ‘true’ normal patterns of age-related changes in tract-based white matter microstructure. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T07:03:55Z (GMT). No. of bitstreams: 1 ntu-108-R06458004-1.pdf: 11362405 bytes, checksum: 5291bb3c49f5279830265f1c61374b90 (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 Contents v Contents of Figures viii Contents of Tables ix Chapter 1 Introduction 1 1.1 Background 1 1.2 Diffusion MRI and normal patterns of age-related changes 3 1.3 Cerebrospinal fluid partial volume effect 5 1.4 Current correction methods and potential limitations 7 1.5 Motivation and aim of the present study 9 Chapter 2 Materials and Methods 10 2.1 Participants 10 2.2 MRI data acquisition 12 2.3 Imaging and tract-based analysis 13 2.3.1 Image quality assurance 13 2.3.2 Tissue class segmentation 14 2.3.3 Diffusion indices estimation 15 2.3.4 Tract-based automatic analysis 16 2.4 Method of correcting cerebrospinal fluid partial volume effect 20 2.5 Validation of the correction method 22 2.5.1 Simulation study 22 2.5.2 Effects of correction on tract profiles 24 2.5.3 Mapping correction effects on anatomical MRI images 24 2.6 Integration of 25 white matter tract groups 25 2.7 Poisson curve fitting for age-related changes 27 2.7.1 Fitting parameters and options 27 2.7.2 Curve fitting I: exclusion of outliers in 76 tracts 27 2.7.3 Curve fitting II: merging into 25 tract groups 27 2.8 Calculation of characteristics 28 2.8.1 The values across lifespan 28 2.8.2 The slopes of each age 28 2.8.3 The age of peaks or dips 28 2.9 Statistical analysis of uncorrected and corrected fitting parameters 29 Chapter 3 Results 30 3.1 Demonstration of the effects of the correction method 30 3.2 The age-related trajectories over the lifespan 33 3.3 Characteristic normal patterns of white matter tract groups 36 3.3.1 Tract specific properties 36 3.3.2 Rates of maturation and decline 39 3.3.3 Timing of development and degeneration 42 3.4 Evaluation of cerebrospinal fluid partial volume effect 45 Chapter 4 Discussion 46 4.1 Brief summary 46 4.2 Characteristic normal patterns of age-related changes 47 4.3 The importance of correcting cerebrospinal fluid partial volume effect 51 4.4 Limitations 54 Chapter 5 Conclusion 55 References 56 Appendix 61 | |
dc.language.iso | en | |
dc.title | 神經纖維束白質微結構之年齡相關變化的正常模式:
校正腦脊髓液部分體積效應的重要性 | zh_TW |
dc.title | Normal Patterns of Age-related Changes in Tract-based White Matter Microstructure:
A Novel Method and Its Importance of Correcting CSF Partial Volume Effect | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 吳恩賜(Joshua Goh Oon Soo),黃宣銘(Hsuan-Ming Huang) | |
dc.subject.keyword | 擴散張量磁振造影,腦神經纖維自動化分析,年齡相關變化的正常模式,大腦白質神經纖維微結構,校正腦脊髓液部分體積效應, | zh_TW |
dc.subject.keyword | Diffusion tensor imaging (DTI),tract-based automatic analysis (TBAA),normal patterns of age-related changes,white matter microstructure,cerebrospinal fluid partial volume effect correction (PVECSF correction), | en |
dc.relation.page | 62 | |
dc.identifier.doi | 10.6342/NTU201902017 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-07-30 | |
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 |
顯示於系所單位: | 醫療器材與醫學影像研究所 |
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