リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。

リケラボ 全国の大学リポジトリにある学位論文・教授論文を一括検索するならリケラボ論文検索大学・研究所にある論文を検索できる

リケラボ 全国の大学リポジトリにある学位論文・教授論文を一括検索するならリケラボ論文検索大学・研究所にある論文を検索できる

大学・研究所にある論文を検索できる 「Exploring the brain's microstructure by using diffusion spectrum imaging and double diffusion encoding magnetic resonance imaging」の論文概要。リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。
リケラボ

コピーが完了しました

URLをコピーしました

論文の公開元へ論文の公開元へ
書き出し

Exploring the brain's microstructure by using diffusion spectrum imaging and double diffusion encoding magnetic resonance imaging

李, 忻南 北海道大学

2022.03.24

概要

Magnetic resonance imaging (MRI) is a non-invasive imaging technique that has been widely used to study brain morphology and function in normal and pathological states. The main advantages of MRI over other imaging techniques are high spatial resolution, superb tissue contrast, and no radiation exposure. Of several MRI techniques, diffusion MRI can provide information about the cellular environment of the brain and characterize brain tissue microstructure by detecting the diffusion of water molecules that is not possible with conventional MRI techniques. Diffusion-weighted imaging (DWI) is the most frequently used and fundamental diffusion MRI sequence. Following the invention of DWI, several diffusion MRI techniques that provide more detailed information about the biological tissue environment have been developed.

Diffusion tensor imaging (DTI) is one of the modifications of diffusion MRI. It is a useful tool to illustrate the microstructural brain changes in various pathological states such as brain tumors, acute stroke, abscess, multiple system atrophy, and major depressive disorder (Kono et al., 2001; Lansberg et al., 2000; Leuthardt et al., 2002; Tha et al., 2010, 2013). It employs a tensor model that consists of three principal orthogonal eigenvectors to evaluate the white matter microstructure. In white matter fibers, diffusion in the principal direction of fibers is faster than that in the perpendicular direction. Such variation in the rate of water diffusion in different directions is termed anisotropy (Fujiyoshi et al., 2013), which can be quantified by a DTI index termed fractional anisotropy (FA). FA ranges from 0 (isotropic diffusion) to 1 (anisotropic diffusion). Decreased FA in white matter fibers is considered to reflect the reduced white matter integrity due to neuronal and volume loss, axonal degeneration, demyelination, etc (Budde et al., 2011). Mean diffusivity (MD) is another DTI index, which quantifies the magnitude of diffusion of water molecules. The faster the diffusion, the greater is the MD. Although DTI has been widely used to evaluate the white matter microstructure in normal and pathological states, drawbacks of DTI have been reported. Because DTI tracks white matter fibers based on the principal orientations, the anisotropy values of all fiber orientations in the same voxel are the same. This fails DTI to resolve anisotropic structures aligned in several orientations, such as dispersing or crossing white matter fibers (Lasič et al., 2014).

To overcome the drawbacks of DTI, several advanced diffusion MRI techniques have been developed. Of these techniques, diffusion spectrum imaging (DSI) is a model-free method, which can display crossing fibers and complex intravoxel fiber orientation distributions reliably and accurately (Wedeen et al., 2008). The angular resolution to model a 3-dimensional (3D) orientation distribution function (ODF) has been reported as satisfactory (Wedeen et al., 2005). DSI is also reported to have higher sensitivity in detecting crossing fibers than the other diffusion MRI techniques such as DTI, diffusional kurtosis imaging, and q-ball imaging (Glenn et al., 2016; Kuo et al., 2008). This high sensitivity of DSI is achieved through the use of higher b values and hundreds of sampling directions (Wedeen et al., 2005). Thus, a high gradient performance MRI system and long scan time are required to acquire DSI. With the recent development of rapid acquisition techniques, the scanning time of DSI has been reduced from 50 to 17 min while retaining high image quality. This allows the clinical applicability of this technique (Bilgic et al., 2012). For a better understanding of changes in DSI indices in pathological states, the regional normative values would be necessary. Diffusion indices such as FA and MD of DTI are known to vary with anatomical location, gender, and age (Bhagat and Beaulieu, 2004; Huster et al., 2009; Panesar et al., 2017). Regional normative values of DSI indices are not known. Chapter 1 of this thesis reports the normative values of DSI indices in the whole brain and their variations of anatomical location, gender, and age. Hemispheric lateralization of these indices and their relationship with neurometabolites are reported in Chapter 2.

The drawbacks of DTI can also be resolved by employing multiple diffusion encoding schemes such as double diffusion encoding (DDE) MRI. These diffusion schemes are possible with recent improvements in gradient systems of clinical scanners. Compared to DTI that uses only a single diffusion gradient pair, DDE MRI applies two diffusion gradient pairs in parallel and orthogonal directions, which can improve the sensitivity of obtaining microstructural information by quantifying diffusion anisotropy without the influence of orientation dispersion (Mitra, 1995; Ozarslan, 2009). The major diffusion index derived from DDE MRI is microscopic fractional anisotropy (μFA). The superiority of μFA over FA of DTI in characterizing anisotropic structures has been reported. Higher resolution in detecting orientation dispersion in μFA over FA was observed in liquid crystal/yeast and pureed asparagus phantom studies (Lasič et al., 2014). The superiority of μFA over FA in distinguishing white matter lesions in the brain has also been reported in patients with multiple sclerosis and Parkinson's disease (Kamiya et al., 2020; Yang et al., 2018). In Chapter 3, whether μFA can identify neuroplastic changes following cognitive training was evaluated.

論文の公開元へ

この論文で使われている画像

関連論文

関連論文をもっと見る

参考文献

Amunts, K., Schlaug, G., Schleicher, A., Steinmetz, H., Dabringhaus, A., Roland, P.E., Zilles, K. (1996). Asymmetry in the human motor cortex and handedness. Neuroimage 4, 216‐222. Alexander, M. P., Naeser, M. A., Palumbo, C. (1990). Broca's area aphasias: aphasia after lesions including the frontal operculum. Neurology 40, 353-362.

Basser, P.J., Pierpaoli, C. (1996). Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J. Magn. Reson. B. 111, 209-219.

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. J. Magn. Reson. Imaging 20, 216-227.

Bilgic, B., Setsompop, K., Cohen-Adad, J., Wedeen, V., Wald, L. L., Adalsteinsson, E. (2012). Accelerated diffusion spectrum imaging with compressed sensing using adaptive dictionaries. Med. Image Comput. Comput. Assist. Interv. 15, 1-9.

Birch, R., Peet, A.C., Dehghani, H., Wilson, M. (2017). Influence of macromolecule baseline on 1H MR spectroscopic imaging reproducibility. Magn. Reson. Med. 77, 34-43.

Bjartmar, C., Battistuta, J., Terada, N., Dupree, E., Trapp, B.D. (2002). N-acetylaspartate is an axon-specific marker of mature white matter in vivo: a biochemical and immunohistochemical study on the rat optic nerve. Ann. Neurol. 51, 51-58.

Blumenfeld-Katzir, T., Pasternak, O., Dagan, M., Assaf, Y. (2011). Diffusion MRI of structural brain plasticity induced by a learning and memory task. PLoS ONE 6, e20678.

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, 3046-3064.

Brander, A., Kataja, A., Saastamoinen, A., Ryymin, P., Huhtala, H., Ohman, J., Soimakallio, S., Dastidar, P. (2010). Diffusion tensor imaging of the brain in a healthy adult population: Normative values and measurement reproducibility at 3 T and 1.5 T. Acta. Radiol. 51, 800-807.

Budde, M. D., Janes, L., Gold, E., Turtzo, L. C., Frank, J. A. (2011). The contribution of gliosis to diffusion tensor anisotropy and tractography following traumatic brain injury: validation in the rat using Fourier analysis of stained tissue sections. Brain 134, 2248-2260.

Chiu, C.H., Lo, Y.C., Tang, H.S., Liu, I.C., Chiang, W.Y., Yeh, F.C., Jaw, F.S., Tseng, W.Y. (2011). White matter abnormalities of fronto-striato-thalamic circuitry in obsessive-compulsive disorder: A study using diffusion spectrum imaging tractography. Psychiatry Res. 192, 176- 182.

Coghill, R. C., Gilron, I., Iadarola, M. J. (2001). Hemispheric lateralization of somatosensory processing. J. Neurophysiol. 85, 2602-2612.

Compston, A., Zajicek, J., Sussman, J., Webb, A., Hall, G., Muir, D., Shaw, C., Wood, A., Scolding, N. (1997). Glial lineages and myelination in the central nervous system. J. Anat. 190, 161-200.

Cramer, S.C., Sur, M., Dobkin, B.H., O'Brien, C., Sanger, T.D., Trojanowski, J.Q., Rumsey, J.M., Hicks, R., Cameron, J., Chen, D., et al. (2011). Harnessing neuroplasticity for clinical applications. Brain 134, 1591–1609.

Crespi, C., Laureiro-Martínez, D., Dodich, A., Cappa, S. F., Brusoni, S., Zollo, M., Falini, A., Canessa, N. (2018). Improving innovative decision-making: Training-induced changes in fronto-parietal networks. Brain Cogn. 128, 46-55.

Uylings, H.B., Jacobsen, A.M., Zilles, K., Amunts, K. (2006). Left-right asymmetry in volume and number of neurons in adult Broca’s area. Cortex 42, 652-658.

Das, S.K., Wang, J.L., Bing, L., Bhetuwal, A., Yang, H.F. (2017). Regional Values of Diffusional Kurtosis Estimates in the Healthy Brain during Normal Aging. Clin. Neuroradiol. 27, 283-298.

Ding, X.Q., Maudsley, A.A., Sabati, M., Sheriff, S., Dellani, P.R., Lanfermann, H. (2015). Reproducibility and reliability of short-TE whole-brain MR spectroscopic imaging of human brain at 3T. Magn. Reson. Med. 73, 921-928.

Faizy, T.D., Thaler, C., Broocks, G., Flottmann, F., Leischner, H., Kniep, H., Nawabi, J., Schön, G., Stellmann, J.P., Kemmling, A., et al. (2020). The Myelin Water Fraction Serves as a Marker for Age-Related Myelin Alterations in the Cerebral White Matter - A Multiparametric MRI Aging Study. Front. Neurosci. 14, 136.

Fan, J., McCandliss, B.D., Sommer, T., Raz, A., Posner, M.I. (2002). Testing the efficiency and independence of attentional networks. J. Cogn. Neurosci. 14, 340-347.

Faul, F., Erdfelder, E., Buchner, A., Lang, A.G. (2009). Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav. Res. Methods 41, 1149-1160. Fernández -Miranda, J.C., Wang, Y., Pathak, S., Stefaneau, L., Verstynen, T., Yeh, F.C. (2015). Asymmetry, connectivity, and segmentation of the arcuate fascicle in the human brain. Brain Struct. Funct. 220, 1665‐1680.

Forster, K.I., Forster, J.C. (2003). DMDX: a Windows display program with millisecond accuracy. Behav. Res. Methods Instrum. Comput. 35, 116-124.

Friedrich, P., Fraenz, C., Schlüter, C., Ocklenburg, S., Mädler, B., Güntürkün, O., Genç, E. (2020). The Relationship Between Axon Density, Myelination, and Fractional Anisotropy in the Human Corpus Callosum. Cereb. Cortex 30, 2042-2056.

Fujiyoshi, K., Konomi, T., Yamada, M., Hikishima, K., Tsuji, O., Komaki, Y., Okano, H. (2013). Diffusion tensor imaging and tractography of the spinal cord: from experimental studies to clinical application. Exp. Neurol. 242, 74-82.

Ghio, M., Locatelli, M., Tettamanti, A., Perani, D., Gatti, R., Tettamanti, M. (2018). Cognitive training with action-related verbs induces neural plasticity in the action representation system as assessed by gray matter brain morphometry. Neuropsychologia 114, 186-194.

Glenn, G.R., Kuo, L.W., Chao, Y.P., Lee, C.Y., Helpern, J.A., Jensen, J.H. (2016). Mapping the Orientation of White Matter Fiber Bundles: A Comparative Study of Diffusion Tensor Imaging, Diffusional Kurtosis Imaging, and Diffusion Spectrum Imaging. AJNR. Am. J. Neuroradiol. 37, 1216-1222.

Highley, J.R., Walker, M.A., Esiri, M.M., Crow, T.J., Harrison, P.J. (2002). Asymmetry of the uncinate fasciculus: a post-mortem study of normal subjects and patients with schizophrenia. Cereb. Cortex 12, 1218-1224.

Huster, R.J., Westerhausen, R., Kreuder, F., Schweiger, E., Wittling, W. (2009). Hemispheric and gender related differences in the midcingulum bundle: a DTI study. Hum. Brain Mapp. 30, 383-391.

Ikenouchi, Y., Kamagata, K., Andica, C., Hatano, T., Ogawa, T., Takeshige-Amano, H., Kamiya, K., Wada, A., Suzuki, M., Fujita, S., et al. (2020). Evaluation of white matter microstructure in patients with Parkinson's disease using microscopic fractional anisotropy. Neuroradiology 62, 197-203.

Jack, C.R., Jr, Twomey, C.K., Zinsmeister, A.R., Sharbrough, F.W., Petersen, R.C., Cascino, G.D. (1989). Anterior temporal lobes and hippocampal formations: normative volumetric measurements from MR images in young adults. Radiology 172, 549‐554.

Jaeggi, S.M., Buschkuehl, M., Jonides, J., Perrig, W.J. (2008). Improving fluid intelligence with training on working memory. Proc. Natl. Acad. Sci. U. S. A. 105, 6829-6833.

Jensen, J.H., Helpern, J.A., Ramani, A., Lu, H., Kaczynski, K. (2005). Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magn. Reson. Med. 53, 1432-1440.

Kamiya, K., Kamagata, K., Ogaki, K., Hatano, T., Ogawa, T., Takeshige-Amano, H., Murata, S., Andica, C., Murata, K., Feiweier, T., et al. (2020). Brain White-Matter Degeneration Due to Aging and Parkinson Disease as Revealed by Double Diffusion Encoding. Front. Neurosci. 14, 584510.

Kimura, D. (1996). Sex, sexual orientation and sex hormones influence human cognitive function. Curr. Opin. Neurobiol. 6, 259–263.

Kono, K., Inoue, Y., Nakayama, K., Shakudo, M., Morino, M., Ohata, K., Wakasa, K., Yamada, R. (2001). The role of diffusion-weighted imaging in patients with brain tumors. AJNR. Am. J. Neuroradiol. 22, 1081-1088.

Kuo, L. W., Chen, J. H., Wedeen, V. J., Tseng, W. Y. (2008). Optimization of diffusion spectrum imaging and q-ball imaging on clinical MRI system. Neuroimage 41, 7-18.

Lampit, A., Hallock, H., Suo, C., Naismith, S. L., Valenzuela, M. (2015). Cognitive training- induced short-term functional and long-term structural plastic change is related to gains in global cognition in healthy older adults: a pilot study. Front. Aging Neurosci. 7, 14.

Lansberg, M.G., Norbash, A.M., Marks, M.P., Tong, D.C., Moseley, M.E., Albers, G.W. (2000). Advantages of adding diffusion-weighted magnetic resonance imaging to conventional magnetic resonance imaging for evaluating acute stroke. Arch. Neurol. 57, 1311-1316.

Lasič, S., Szczepankiewicz, F., Eriksson, S., Nilsson, M., Topgaard, D. (2014). Microanisotropy imaging: quantification of microscopic diffusion anisotropy and orientational order parameter by diffusion MRI with magic-angle spinning of the q-vector. Front. Phys. 2, 11.

Lätt, J., Nilsson, M., Wirestam, R., Ståhlberg, F., Karlsson, N., J ohansson, M., Sundgren, P.C., van Westen, D. (2013). Regional values of diffusional kurtosis estimates in the healthy brain. J. Magn. Reson. Imaging 37, 610-618.

Laughlin, S.B., Sejnowski, T.J. (2003). Communication in neuronal networks. Science 301, 1870-1874.

Lee, C. E., Danielian, L. E., Thomasson, D., Baker, E. H. (2009). Normal regional fractional anisotropy and apparent diffusion coefficient of the brain measured on a 3 T MR scanner. Neuroradiology 51, 3-9.

Leuthardt, E.C., Wippold, F.J., Oswood, M.C., Rich, K.M. (2002). Diffusion-weighted MR imaging in the preoperative assessment of brain abscesses. Surg. Neurol. 58, 395-402.

Liu, X., Gao, X., Zhang, L., Yuan, Z., Zhang, C., Lu, W., Cui, D., Zheng, F., Qiu, J., Xie, J. (2018). Age-related changes in fiber tracts in healthy adult brains: A generalized q-sampling and connectometry study. J. Magn. Reson. Imaging 48, 369-381.

Maldjian, J. A., Laurienti, P. J., Kraft, R. A., Burdette, J. H. (2003). An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. Neuroimage 19, 1233-1239.

Maraganore, D. M., Folger, W. N., Swanson, J. W., Ahlskog, J. E. (1992). Movement disorders as sequelae of central pontine myelinolysis: report of three cases. Mov. Disord. 7:142-148.

Maudsley, A.A., Domenig, C., Govind, V., Darkazanli, A., Studholme, C., Arheart, K., Bloomer, C. (2009). Mapping of brain metabolite distributions by volumetric proton MR spectroscopic imaging (MRSI). Magn. Reson. Med. 61, 548-559.

Maudsley, A. A., Roy, B., Gupta, R. K., Sheriff, S., Awasthi, R., Gu, M., Husain, N., Mohakud, S., Behari, S., Spielman, D. M. (2014). Association of metabolite concentrations and water diffusivity in normal appearing brain tissue with glioma grade. J. Neuroimaging 24:585-589. Maudsley, A.A., Govind, V., Saigal, G., Gold, S.G., Harris, L., Sheriff, S. (2017). Longitudinal MR Spectroscopy Shows Altered Metabolism in Traumatic Brain Injury. J. Neuroimaging 27, 562-569.

Meier-Ruge, W., Ulrich, J., Brühlmann, M., Meier, E. (1992). Age -related white matter atrophy in the human brain. Ann. N. Y. Acad. Sci. 673, 260-269.

Menzler, K., Belke, M., Wehrmann, E., Krakow, K., Lengler, U., Jansen, A., Hamer, H. M., Oertel, W. H., Rosenow, F., Knake, S. (2011). Men and women are different: diffusion tensor imaging reveals sexual dimorphism in the microstructure of the thalamus, corpus callosum and cingulum. Neuroimage 54, 2557-2562.

Mitra, P.P. (1995). Multiple wave-vector extensions of the NMR pulsed-field-gradient spin- echo diffusion measurement. Phys. Rev. B. Condens. Matter 51, 15074-15078.

Nitta, N., Shiino, A., Watanabe, T., Sakaue, Y., Nozaki, K. (2012). Buccofacial apraxia without limb apraxia or aphasia after right premotor area contusion: a case report. No Shinkei Geka 40, 985-990.

Oldfield, R.C. (1971). The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97-113.

Orimo, H. (2006). Reviewing the definition of elderly. Nihon Ronen Igakkai Zasshi. 43, 27-34. Oshida, K., Shimizu, T., Takase, M., Tamura, Y., Shimizu, T., Yamashiro, Y. (2003). Effects of dietary sphingomyelin on central nervous system myelination in developing rats. Pediatr. Res. 53, 589-593.

Owen, A. M., Stern, C. E., Look, R. B., Tracey, I., Rosen, B. R., Petrides, M. (1998). Functional organization of spatial and nonspatial working memory processing within the human lateral frontal cortex. Proc. Natl. Acad. Sci. U. S. A. 95, 7721-7726.

Ozarslan, E. (2009). Compartment shape anisotropy (CSA) revealed by double pulsed field gradient MR. J. Magn. Reson. 199, 56-67.

Panesar, S.S., Yeh, F.C., Deibert, C.P., Fernandes-Cabral, D., Rowthu, V., Celtikci, P., Celtikci, E., Hula, W.D., Pathak, S., Fernández -Miranda, J.C. (2017). A diffusion spectrum imaging- based tractographic study into the anatomical subdivision and cortical connectivity of the ventral external capsule: uncinate and inferior fronto-occipital fascicles. Neuroradiology 59, 971-987.

Park, H.J., Westin, C.F., Kubicki, M., Maier, S.E., Niznikiewicz, M., Baer, A., Frumin, M., Kikinis, R., Jolesz, F.A., McCarley, R.W., et al. (2004). White matter hemisphere asymmetries in healthy subjects and in schizophrenia: a diffusion tensor MRI study. Neuroimage 1, 213-223. Petit, L., Zago, L., Mellet, E., Jobard, G., Crivello, F., Joliot, M., Mazoyer, B., Tzourio- Mazoyer, N. (2015). Strong rightward lateralization of the dorsal attentional network in left- handers with right sighting-eye: an evolutionary advantage. Hum. Brain Mapp. 36, 1151-1164. Pierpaoli, C., Basser, P.J. (1996). Toward a quantitative assessment of diffusion anisotropy. Magn. Reson. Med. 36, 893-906.

Pouwels, P.J., Frahm, J. (1998). Regional metabolite concentrations in human brain as determined by quantitative localized proton MRS. Magn. Reson. Med. 39, 53-60.

Rebok, G.W., Ball, K., Guey, L.T., Jones, R.N., Kim, H.Y., King, J.W., Marsiske, M., Morris, J.N., Tennstedt, S.L., Unverzagt, F.W., et al. (2014). Ten-year effects of the advanced cognitive training for independent and vital elderly cognitive training trial on cognition and everyday functioning in older adults. J. Am. Geriatr. Soc. 62, 16-24.

Rochefort, C., Lefort, J. M., Rondi-Reig, L. (2013). The cerebellum: a new key structure in the navigation system. Front. Neural Circuits 7, 35.

Rorden, C., Karnath, H.O., Bonilha, L. (2007). Improving lesion-symptom mapping. J. Cogn. Neurosci. 19, 1081-1088.

Rueda, M. R., Checa, P., Cómbita, L. M. (2012). Enhanced efficiency of the executive attention network after training in preschool children: immediate changes and effects after two months. Dev. Cogn. Neurosci. 2 Suppl 1(Suppl 1), S192–S204.

Salminen, T., Strobach, T., Schubert, T. (2012). On the impacts of working memory training on executive functioning. Front. Hum. Neurosci. 6, 166.

Sandell, J.H., Peters, A. (2003). Disrupted myelin and axon loss in the anterior commissure of the aged rhesus monkey. J. Comp. Neurol. 466, 14-30.

Schneider, C.A., Rasband, W.S., Eliceiri, K.W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nat. Methods. 9, 671-675.

Shemesh, N., Cohen, Y. (2011). Microscopic and compartment shape anisotropies in gray and white matter revealed by angular bipolar double-PFG MR. Magn. Reson. Med. 65, 1216-1227. Sun, T., Walsh, C.A. (2006). Molecular approaches to brain asymmetry and handedness. Nat. Rev. Neurosci. 7, 655-662.

Szczepankiewicz, F., Lasič, S., van Westen, D., Sundgren, P.C., Englund, E., Westin, C.F., Ståhlberg, F., Lätt, J., Topgaard, D., Nilsson, M. (2015). Quantification of microscopic diffusion anisotropy disentangles effects of orientation dispersion from microstructure: applications in healthy volunteers and in brain tumors. Neuroimage 104, 241-252.

Takao, H., Abe, O., Yamasue, H., Aoki, S., Sasaki, H., Kasai, K., Yoshioka, N., Ohtomo, K. (2011). Gray and white matter asymmetries in healthy individuals aged 21-29 years: a voxel- based morphometry and diffusion tensor imaging study. Hum. Brain Mapp. 10, 1762-1773.

Takao, H., Hayashi, N., Ohtomo, K. (2014). Sex dimorphism in the white matter: fractional anisotropy and brain size. J. Magn. Reson. Imaging 39, 917-923.

Teipel, S.J., Lerche, M., Kilimann, I., O'Brien, K., Grothe, M., Meyer, P., Li, X., Sänger, P., Hauenstein, K. (2014). Decline of fiber tract integrity over the adult age range: a diffusion spectrum imaging study. J. Magn. Reson. Imaging 40, 348-359.

Terry, R. D., DeTeresa, R., Hansen, L. A. (1987). Neocortical cell counts in normal human adult aging. Ann. Neurol. 21, 530-539.

Tha, K.K., Terae, S., Yabe, I., Miyamoto, T., Soma, H., Zaitsu, Y., Fujima, N., Kudo, K., Sasaki, H., Shirato, H. (2010). Microstructural white matter abnormalities of multiple system atrophy: in vivo topographic illustration by using diffusion-tensor MR imaging. Radiology 255, 563- 569.

Tha, K.K., Terae, S., Nakagawa, S., Inoue, T., Kitagawa, N., Kako, Y., Nakato, Y., Akter Popy, K., Fujima, N., Zaitsu, Y., et al. (2013). Impaired integrity of the brain parenchyma in non-geriatric patients with major depressive disorder revealed by diffusion tensor imaging. Psychiatry Res. 212, 208-215.

Thiebaut de Schotten, M., Ffytche, D.H., Bizzi, A., Dell'Acqua, F., Allin, M., Walshe, M., Murray, R., Williams, S.C., Murphy, D.G., Catani, M. (2011). Atlasing location, asymmetry and inter-subject variability of white matter tracts in the human brain with MR diffusion tractography. Neuroimage 54, 49-59.

Thiel, C.M., Zilles, K., Fink, G.R. (2004). Cerebral correlates of alerting, orienting and reorienting of visuospatial attention: an event-related fMRI study. Neuroimage 21, 318-328.

Tuch, D.S. (2004). Q-ball imaging. Magn. Reson. Med. 52, 1358-1372.

Turkeltaub, P.E., Coslett, H.B. (2010). Localization of sublexical speech perception components. Brain Lang. 114, 1-15.

Uylings, H.B.M., Jacobsen, A.M., Zilles, K., Amunts, K. (2006). Left-Right Asymmetry in Volume and Number of Neurons in Adult Broca's Area. Cortex 42, 652-658.

Van Paesschen, W., Connelly, A., King, M.D., Jackson, G.D., Duncan, J.S. (1997). The spectrum of hippocampal sclerosis: a quantitative magnetic resonance imaging study. Ann. Neurol. 41, 41‐51.

Verhelst, H., Giraldo, D., Vander Linden, C., Vingerhoets, G., Jeurissen, B., Caeyenberghs, K. (2019). Cognitive Training in Young Patients With Traumatic Brain Injury: A Fixel-Based Analysis. Neurorehabil. Neural Repair 33, 813-824.

Wakana, S., Caprihan, A., Panzenboeck, M.M., Fallon, J.H., Perry, M., Gollub, R.L., Hua, K., Zhang, J., Jiang, H., Dubey, P., et al. (2007). Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 36, 630-644.

Wang, Z.M., Wei, P.H., Shan, Y., Han, M., Zhang, M., Liu, H., Gao, J.H., Lu, J. (2020). Identifying and characterizing projections from the subthalamic nucleus to the cerebellum in humans. Neuroimage 210, 116573.

Wedeen, V. J., Hagmann, P., Tseng, W. Y., Reese, T. G., Weisskoff, R. M. (2005). Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn. Reson. Med. 54, 1377-1386.

Wedeen, V.J., Wang, R.P., Schmahmann, J.D., Benner, T., Tseng, W.Y., Dai, G., Pandya, D.N., Hagmann, P., D'Arceuil, H., de Crespigny, A.J. (2008). Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. Neuroimage 41, 1267-1277.

Yang, G., Tian, Q., Leuze, C., Wintermark, M., McNab, J.A. (2018). Double diffusion encoding MRI for the clinic. Magn. Reson. Med. 80, 507-520.

Yeh, F.C., Wedeen, V.J., Tseng, W.Y. (2010). Generalized q-sampling imaging. IEEE. Trans. Med. Imaging 29, 1626-1635.

Zhang, H., Schneider, T., Wheeler-Kingshott, C.A., Alexander, D.C. (2012). NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 61, 1000-1016.

Zhang, Y., Taub, E., Salibi, N., Uswatte, G., Maudsley, A.A., Sheriff, S., Womble, B., Mark, V.W., Knight, D.C. (2018). Comparison of reproducibility of single voxel spectroscopy and whole-brain magnetic resonance spectroscopy imaging at 3T. NMR. Biomed. 31, e3898.

参考文献をもっと見る

全国の大学の
卒論・修論・学位論文
を
一発検索！

この論文の関連論文を見る