Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia
Abstract
Both axon and myelin degeneration have significant impact on the long-term disability of patients with white matter disorder. However, the clinical manifestations of the neurological dysfunction caused by white matter disorders are not sufficient to determine the origin of neurological deficits. A noninvasive biological marker capable of detecting and differentiating axon and myelin degeneration would be a significant addition to currently available tools. Directional diffusivities derived from diffusion tensor imaging (DTI) have been previously proposed by this group as potential biological markers to detect and differentiate axon and myelin degeneration. To further test the hypothesis that axial (lambdaparallel) and radial (lambdaperpendicular) diffusivities reflect axon and myelin pathologies, respectively, the optic nerve was examined serially using DTI in a mouse model of retinal ischemia. A significant decrease of lambdaparallel, the putative DTI axonal marker, was observed 3 days after ischemia without concurrently detectable changes in lambdaperpendicular, the putative myelin marker. This result is consistent with histological findings of significant axonal degeneration with no detectable demyelination at 3 days after ischemia. The elevation of lambdaperpendicular observed 5 days after ischemia is consistent with histological findings of myelin degeneration at this time. These results support the hypothesis that lambdaparallel and lambdaperpendicular hold promise as s…
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Recent studies using animal models suggested that measures of directional diffusivity other than FA may be able to distinguish between axonal degeneration (increased axial diffusivity; normal radial diffusivity) and loss of myelin per se, at least in early phase of myelin breakdown (increased radial diffusivity; normal axial diffusivity).
“Recent studies using animal models suggested that measures of directional diffusivity other than FA may be able to distinguish between axonal degeneration (increased axial diffusivity; normal radial diffusivity) (Song et al., 2003) and loss of myelin per se, at least in the early phase of myelin breakdown (increased radial diffusivity; normal axial diffusivity) (Song et al., 2002).”
From Diffusion tensor imaging of post mortem multiple sclerosis brain (2007) · cites this paper as Song et al., 2003
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Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
Song, S.-K., Sun, S.-W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002) · NeuroImage · doi:10.1006/nimg.2002.1267 · Cited by 2,582 · see citing works
Self-citationDiffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis
Werring, D. J., Clark, C. A., Barker, G. J., Thompson, A. J., & Miller, D. H. (1999) · Neurology · doi:10.1212/wnl.52.8.1626 · Cited by 621 · see citing works
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Demyelination increases radial diffusivity in corpus callosum of mouse brain
Song, S.-K., Yoshino, J., Le, T. Q., Lin, S.-J., Sun, S.-W., Cross, A. H., & Armstrong, R. C. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.01.028 · Cited by 1,658 · see citing works
Self-citationAbout “axial” and “radial” diffusivities
Wheeler‐Kingshott, C. A. M., & Cercignani, M. (2009) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21965 · Cited by 885 · see citing works
Tamnes, C. K., Østby, Y., Fjell, A. M., Westlye, L. T., Due-Tønnessen, P., & Walhovd, K. B. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp118 · Cited by 779 · see citing works
Age-related changes in grey and white matter structure throughout adulthood
Giorgio, A., Santelli, L., Tomassini, V., Bosnell, R., Smith, S., De Stefano, N., & Johansen-Berg, H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.004 · Cited by 532 · see citing works
Voss, M. W., Heo, S., Prakash, R. S., Erickson, K. I., Alves, H., Chaddock, L., Szabo, A. N., Mailey, E. L., Wójcicki, T. R., White, S. M., et al. (2013) · Human Brain Mapping · doi:10.1002/hbm.22119 · Cited by 553 · see citing works
Douaud, G., Jbabdi, S., Behrens, T. E. J., Menke, R. A., Gass, A., Monsch, A. U., Rao, A., Whitcher, B., Kindlmann, G., Matthews, P. M., et al. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.008 · Cited by 514 · see citing works
Mapping Infant Brain Myelination with Magnetic Resonance Imaging
Deoni, S. C. L., Mercure, E., Blasi, A., Gasston, D., Thomson, A., Johnson, M., Williams, S. C. R., & Murphy, D. G. M. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.2106-10.2011 · Cited by 497 · see citing works
Frontostriatal Microstructure Modulates Efficient Recruitment of Cognitive Control
Liston, C., Watts, R., Tottenham, N., Davidson, M. C., Niogi, S., Ulug, A. M., & Casey, B. J. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhj003 · Cited by 477 · see citing works
Understanding the Physiopathology Behind Axial and Radial Diffusivity Changes—What Do We Know?
Winklewski, P. J., Sabisz, A., Naumczyk, P., Jodzio, K., Szurowska, E., & Szarmach, A. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00092 · Cited by 463 · see citing works
A prospective diffusion tensor imaging study in mild traumatic brain injury
Mayer, A. R., Ling, J., Mannell, M. V., Gasparovic, C., Phillips, J. P., Doezema, D., Reichard, R., & Yeo, R. A. (2010) · Neurology · doi:10.1212/wnl.0b013e3181d0ccdd · Cited by 459 · see citing works
Developmental Changes in Cognitive Control through Adolescence
Luna, B. (2009) · Advances in Child Development and Behavior · doi:10.1016/s0065-2407(09)03706-9 · Cited by 419 · see citing works
Budde, M. D., Janes, L., Gold, E., Turtzo, L. C., & Frank, J. A. (2011) · Brain · doi:10.1093/brain/awr161 · Cited by 408 · see citing works
Early-stage visual processing and cortical amplification deficits in schizophrenia
Butler, P. D., Zemon, V., Schechter, I., Saperstein, A. M., Hoptman, M. J., Lim, K. O., Revheim, N., Silipo, G., & Javitt, D. C. (2005) · Archives of General Psychiatry · doi:10.1001/archpsyc.62.5.495 · Cited by 362 · see citing works
Effectiveness of regional DTI measures in distinguishing Alzheimer’s disease, MCI, and normal aging
Nir, T. M., Jahanshad, N., Villalon-Reina, J. E., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2013.07.006 · Cited by 348 · see citing works
Diffusion tensor imaging of post mortem multiple sclerosis brain
Schmierer, K., Wheeler-Kingshott, C. A. M., Boulby, P. A., Scaravilli, F., Altmann, D. R., Barker, G. J., Tofts, P. S., & Miller, D. H. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.12.010 · Cited by 395 · see citing works
Measuring macroscopic brain connections in vivo
Jbabdi, S., Sotiropoulos, S. N., Haber, S. N., Van Essen, D. C., & Behrens, T. E. (2015) · Nature Neuroscience · doi:10.1038/nn.4134 · Cited by 334 · see citing works
Mechanisms of white matter changes induced by meditation
Tang, Y.-Y., Lu, Q., Fan, M., Yang, Y., & Posner, M. I. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1207817109 · Cited by 335 · see citing works
Magnetic Resonance Imaging of Myelin
Laule, C., Vavasour, I. M., Kolind, S. H., Li, D. K. B., Traboulsee, T. L., Moore, G. R. W., & MacKay, A. L. (2007) · Neurotherapeutics · doi:10.1016/j.nurt.2007.05.004 · Cited by 334 · see citing works
Current clinical applications of diffusion-tensor imaging in neurological disorders
Tae, W.-S., Ham, B.-J., Pyun, S.-B., Kang, S.-H., & Kim, B.-J. (2018) · Journal of Clinical Neurology · doi:10.3988/jcn.2018.14.2.129 · Cited by 302 · see citing works
Zhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R. E., Yeh, C.-H., Zhao, T., & O’Donnell, L. J. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2021.118870 · Cited by 302 · see citing works
“cal accuracy, researchers should be cautious when interpreting results in research and clinical applications by considering prior anatomical knowledge learned from studies in histology [207, 290, 407, 506] and animals [421, 422].”
BackgroundWhite matter pathology isolates the hippocampal formation in Alzheimer's disease
Salat, D. H., Tuch, D. S., van der Kouwe, A. J. W., Greve, D. N., Pappu, V., Lee, S. Y., Hevelone, N. D., Zaleta, A. K., Growdon, J. H., Corkin, S., et al. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.03.013 · Cited by 279 · see citing works
Cerebral White Matter Integrity Mediates Adult Age Differences in Cognitive Performance
Madden, D. J., Spaniol, J., Costello, M. C., Bucur, B., White, L. E., Cabeza, R., Davis, S. W., Dennis, N. A., Provenzale, J. M., & Huettel, S. A. (2008) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21047 · Cited by 265 · see citing works
Neurodevelopment and executive function in autism
O'Hearn, K., Asato, M., Ordaz, S., & Luna, B. (2008) · Development and Psychopathology · doi:10.1017/s0954579408000527 · Cited by 274 · see citing works
Frontostriatal connectivity and its role in cognitive control in parent-child dyads with ADHD
Casey, B. J., Epstein, J. N., Buhle, J., Liston, C., Davidson, M. C., Tonev, S. T., Spicer, J., Niogi, S., Millner, A. J., Reiss, A., et al. (2007) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2007.06101754 · Cited by 258 · see citing works
Ivanova, M. V., Isaev, D. Y., Dragoy, O. V., Akinina, Y. S., Petrushevskiy, A. G., Fedina, O. N., Shklovsky, V. M., & Dronkers, N. F. (2016) · Cortex · doi:10.1016/j.cortex.2016.04.019 · Cited by 221 · see citing works
Is diffusion anisotropy an accurate monitor of myelination?
Mädler, B., Drabycz, S. A., Kolind, S. H., Whittall, K. P., & MacKay, A. L. (2008) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2008.01.047 · Cited by 227 · see citing works
Effects of age and gender on white matter integrity
Inano, S., Takao, H., Hayashi, N., Abe, O., & Ohtomo, K. (2011) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2785 · Cited by 213 · see citing works
Quantitative tract-based white matter development from birth to age 2 years
Geng, X., Gouttard, S., Sharma, A., Gu, H., Styner, M., Lin, W., Gerig, G., & Gilmore, J. H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.057 · Cited by 212 · see citing works
Liston, C., Cohen, M. M., Teslovich, T., Levenson, D., & Casey, B. J. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.03.022 · Cited by 216 · see citing works
Functional implications of hippocampal volume and diffusivity in mild cognitive impairment
Müller, M. J., Greverus, D., Dellani, P. R., Weibrich, C., Wille, P. R., Scheurich, A., Stoeter, P., & Fellgiebel, A. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.06.029 · Cited by 210 · see citing works
Korgaonkar, M. S., Grieve, S. M., Koslow, S. H., Gabrieli, J. D. E., Gordon, E., & Williams, L. M. (2011) · Human Brain Mapping · doi:10.1002/hbm.21178 · Cited by 205 · see citing works
Ryan, N. S., Keihaninejad, S., Shakespeare, T. J., Lehmann, M., Crutch, S. J., Malone, I. B., Thornton, J. S., Mancini, L., Hyare, H., Yousry, T., et al. (2013) · Brain · doi:10.1093/brain/awt065 · Cited by 205 · see citing works
Sex differences in the growth of white matter during adolescence
Perrin, J. S., Leonard, G., Perron, M., Pike, G. B., Pitiot, A., Richer, L., Veillette, S., Pausova, Z., & Paus, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.023 · Cited by 197 · see citing works
Lowe, M. J., Beall, E. B., Sakaie, K. E., Koenig, K. A., Stone, L., Marrie, R. A., & Phillips, M. D. (2008) · Human Brain Mapping · doi:10.1002/hbm.20576 · Cited by 196 · see citing works
Vestergaard, M., Madsen, K. S., Baaré, W. F. C., Skimminge, A., Ejersbo, L. R., Ramsøy, T. Z., Gerlach, C., Åkeson, P., Paulson, O. B., & Jernigan, T. L. (2011) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2010.21592 · Cited by 181 · see citing works
Crossing fibres in tract-based spatial statistics
Jbabdi, S., Behrens, T. E. J., & Smith, S. M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.08.039 · Cited by 187 · see citing works
Chang, E. H., Argyelan, M., Aggarwal, M., Chandon, T.-S. S., Karlsgodt, K. H., Mori, S., & Malhotra, A. K. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.068 · Cited by 186 · see citing works
Bartzokis, G., Lu, P. H., Heydari, P., Couvrette, A., Lee, G. J., Kalashyan, G., Freeman, F., Grinstead, J. W., Villablanca, P., Finn, J. P., et al. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.07.010 · Cited by 152 · see citing works
Walhovd, K. B., Johansen-Berg, H., & Káradóttir, R. T. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.06.058 · Cited by 156 · see citing works
Burzynska, A. Z., Jiao, Y., Knecht, A. M., Fanning, J., Awick, E. A., Chen, T., Gothe, N., Voss, M. W., McAuley, E., & Kramer, A. F. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00059 · Cited by 150 · see citing works
Lawrence, A. J., Patel, B., Morris, R. G., MacKinnon, A. D., Rich, P. M., Barrick, T. R., & Markus, H. S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061014 · Cited by 140 · see citing works
Clerx, L., Visser, P. J., Verhey, F., & Aalten, P. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2011-110797 · Cited by 132 · see citing works
Tamnes, C. K., Østby, Y., Walhovd, K. B., Westlye, L. T., Due‐Tønnessen, P., & Fjell, A. M. (2010) · Human Brain Mapping · doi:10.1002/hbm.20962 · Cited by 126 · see citing works
White matter microstructure in opiate addiction
Bora, E., Yücel, M., Fornito, A., Pantelis, C., Harrison, B. J., Cocchi, L., Pell, G., & Lubman, D. I. (2012) · Addiction Biology · doi:10.1111/j.1369-1600.2010.00266.x · Cited by 130 · see citing works
Zhang, A., Leow, A., Ajilore, O., Lamar, M., Yang, S., Joseph, J., Medina, J., Zhan, L., & Kumar, A. (2012) · Neuropsychopharmacology · doi:10.1038/npp.2011.279 · Cited by 121 · see citing works
Douet, V., & Chang, L. (2015) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00343 · Cited by 122 · see citing works
Nowrangi, M. A., Lyketsos, C. G., Leoutsakos, J. S., Oishi, K., Albert, M., Mori, S., & Mielke, M. M. (2013) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2012.05.2186 · Cited by 120 · see citing works
O'Dwyer, L., Lamberton, F., Bokde, A. L. W., Ewers, M., Faluyi, Y. O., Tanner, C., Mazoyer, B., O'Neill, D., Bartley, M., Collins, D. R., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021745 · Cited by 119 · see citing works
Kochunov, P., Glahn, D. C., Rowland, L. M., Olvera, R. L., Winkler, A., Yang, Y.-H., Sampath, H., Carpenter, W. T., Duggirala, R., Curran, J., et al. (2013) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.10.002 · Cited by 118 · see citing works
Neuroprotection in Glaucoma: Animal Models and Clinical Trials
Almasieh, M., & Levin, L. A. (2017) · Annual Review of Vision Science · doi:10.1146/annurev-vision-102016-061422 · Cited by 111 · see citing works
White matter lesions defined by diffusion tensor imaging in older adults
Back, S. A., Kroenke, C. D., Sherman, L. S., Lawrence, G., Gong, X., Taber, E. N., Sonnen, J. A., Larson, E. B., & Montine, T. J. (2011) · Annals of Neurology · doi:10.1002/ana.22484 · Cited by 109 · see citing works
Associations between white matter microstructure and infants' working memory
Short, S. J., Elison, J. T., Goldman, B. D., Styner, M., Gu, H., Connelly, M., Maltbie, E., Woolson, S., Lin, W., Gerig, G., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.021 · Cited by 105 · see citing works
Response inhibition is associated with white matter microstructure in children.
Madsen, K. S., Baaré, W. F. C., Vestergaard, M., Skimminge, A., Ejersbo, L. R., Ramsøy, T. Z., Gerlach, C., Åkeson, P., Paulson, O. B., & Jernigan, T. L. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2009.11.001 · Cited by 104 · see citing works
Sensitivity of multi-shell NODDI to multiple sclerosis white matter changes: a pilot study
Schneider, T. (2017) · Functional Neurology · doi:10.11138/fneur/2017.32.2.097 · Cited by 104 · see citing works
Zavaliangos-Petropulu, A., Nir, T. M., Thomopoulos, S. I., Reid, R. I., Bernstein, M. A., Borowski, B., Jack Jr., C. R., Weiner, M. W., Jahanshad, N., & Thompson, P. M. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00002 · Cited by 101 · see citing works
“…more coherent intact axons, while lower anisotropy and higher diffusivity may reflect factors such as axonal injury and demyelination, among other factors (Beaulieu, 2002; Song et al., 2003, 2005; Harsan et al., 2006; Le Bihan and Johansen-Berg, 2012; Kantarci et al., 2017; Moore et al., 2018).”
Quan, M., Lee, S.-H., Kubicki, M., Kikinis, Z., Rathi, Y., Seidman, L. J., Mesholam-Gately, R. I., Goldstein, J. M., McCarley, R. W., Shenton, M. E., et al. (2013) · Schizophrenia Research · doi:10.1016/j.schres.2012.11.028 · Cited by 97 · see citing works
Lam, B. Y. K., Halliday, G. M., Irish, M., Hodges, J. R., & Piguet, O. (2014) · Human Brain Mapping · doi:10.1002/hbm.22420 · Cited by 90 · see citing works
Zhang, J., Jones, M. V., McMahon, M. T., Mori, S., & Calabresi, P. A. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.23032 · Cited by 88 · see citing works
The Fornix in Mild Cognitive Impairment and Alzheimer’s Disease
Nowrangi, M. A., & Rosenberg, P. B. (2015) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2015.00001 · Cited by 87 · see citing works
Increased diffusivity in acute multiple sclerosis lesions predicts risk of black hole
Naismith, R. T., Xu, J., Tutlam, N. T., Scully, P. T., Trinkaus, K., Snyder, A. Z., Song, S.-K., & Cross, A. H. (2010) · Neurology · doi:10.1212/wnl.0b013e3181e042c4 · Cited by 85 · see citing works
Self-citationLin, F., Wu, G., Zhu, L., & Lei, H. (2013) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2012.09.013 · Cited by 79 · see citing works
Sex-linked white matter microstructure of the social and analytic brain
Chou, K.-H., Cheng, Y., Chen, I.-Y., Lin, C.-P., & Chu, W.-C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.010 · Cited by 81 · see citing works
Walhovd, K. B., Westlye, L. T., Moe, V., Slinning, K., Due-Tønnessen, P., Bjørnerud, A., van der Kouwe, A., Dale, A. M., & Fjell, A. M. (2010) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1957 · Cited by 82 · see citing works
Lawrence, K. E., Levitt, J. G., Loo, S. K., Ly, R., Yee, V., O’Neill, J., Alger, J., & Narr, K. L. (2013) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2013.01.010 · Cited by 77 · see citing works
Structural insights into the rodent CNS via diffusion tensor imaging.
Zhang, J., Aggarwal, M., & Mori, S. (2012) · Trends in Neurosciences · doi:10.1016/j.tins.2012.04.010 · Cited by 73 · see citing works
Vuoksimaa, E., Panizzon, M. S., Hagler Jr, D. J., Hatton, S. N., Fennema‐Notestine, C., Rinker, D., Eyler, L. T., Franz, C. E., Lyons, M. J., Neale, M. C., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23502 · Cited by 58 · see citing works
White matter degeneration in subjective cognitive decline: a diffusion tensor imaging study
Li, X.-Y., Tang, Z.-C., Sun, Y., Tian, J., Liu, Z.-Y., & Han, Y. (2016) · Oncotarget · doi:10.18632/oncotarget.10091 · Cited by 65 · see citing works
Brain neuroplasticity related to lateral ankle ligamentous injuries: A systematic review
Maricot, A., Dick, E., Walravens, A., Pluym, B., Lathouwers, E., De Pauw, K., Verschueren, J., Roelands, B., Meeusen, R., & Tassignon, B. (2023) · Sports Medicine · doi:10.1007/s40279-023-01834-z · Cited by 62 · see citing works
Qiu, Y., Jiang, G., Su, H., Lv, X., Zhang, X., Tian, J., & Zhuo, F. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063212 · Cited by 58 · see citing works
White Matter Heritability Using Diffusion Tensor Imaging in Neonatal Brains
Geng, X., Prom-Wormley, E. C., Perez, J., Kubarych, T., Styner, M., Lin, W., Neale, M. C., & Gilmore, J. H. (2012) · Twin Research and Human Genetics · doi:10.1017/thg.2012.14 · Cited by 53 · see citing works
Lista, S., Molinuevo, J. L., Cavedo, E., Rami, L., Amouyel, P., Teipel, S. J., Garaci, F., Toschi, N., Habert, M.-O., Blennow, K., et al. (2015) · Journal of Alzheimer's Disease · doi:10.3233/jad-150202 · Cited by 53 · see citing works
Dubois, J., Adibpour, P., Poupon, C., Hertz-Pannier, L., & Dehaene-Lambertz, G. (2016) · Brain Plasticity · doi:10.3233/bpl-160031 · Cited by 40 · see citing works
Wright, D. K., O'Brien, T. J., Mychasiuk, R., & Shultz, S. R. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2018.01.033 · Cited by 46 · see citing works
Unique white matter microstructural patterns in ADHD presentations—a diffusion tensor imaging study
Svatkova, A., Nestrasil, I., Rudser, K., Goldenring Fine, J., Bledsoe, J., & Semrud‐Clikeman, M. (2016) · Human Brain Mapping · doi:10.1002/hbm.23243 · Cited by 44 · see citing works
“According to the tensor model theory, radial diffusivity value is associated with myelin sheath thickness [Song et al., 2003].”
BackgroundMethodKolind, S. H., Laule, C., Vavasour, I. M., Li, D. K. B., Traboulsee, A. L., Mädler, B., Moore, G. R. W., & MacKay, A. L. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.11.033 · Cited by 44 · see citing works
Voxel-based diffusion tensor imaging of an APP/PS1 mouse model of Alzheimer’s disease.
Shu, X., Qin, Y.-Y., Zhang, S., Jiang, J.-J., Zhang, Y., Zhao, L.-Y., Shan, D., & Zhu, W.-Z. (2013) · Molecular Neurobiology · doi:10.1007/s12035-013-8418-6 · Cited by 41 · see citing works
Diffusion MRI quantifies early axonal loss in the presence of nerve swelling
Lin, T.-H., Chiang, C.-W., Perez-Torres, C. J., Sun, P., Wallendorf, M., Schmidt, R. E., Cross, A. H., & Song, S.-K. (2017) · Journal of Neuroinflammation · doi:10.1186/s12974-017-0852-3 · Cited by 42 · see citing works
Self-citationStone, D. B., Ryman, S. G., Hartman, A. P., Wertz, C. J., Vakhtin, A. A., & Initiative, A. D. N. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.711579 · Cited by 28 · see citing works
Jamieson, D., Shan, Z., Lagopoulos, J., & Hermens, D. F. (2021) · Sleep Medicine Reviews · doi:10.1016/j.smrv.2021.101450 · Cited by 28 · see citing works
In vivo diffusion tensor imaging of amyloid‐β‐induced white matter damage in mice
Sun, S.-W., Liang, H.-F., Mei, J., Xu, D., & Shi, W.-X. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-130236 · Cited by 27 · see citing works
Self-citationWhite Matter Alterations in Cognitively Normal apoE ɛ2 Carriers: Insight into Alzheimer Resistance?
Chiang, G. C., Zhan, W., Schuff, N., & Weiner, M. W. (2012) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2984 · Cited by 25 · see citing works
Diffusion tensor magnetic resonance imaging of the brain in app transgenic mice: A cohort study.
Müller, H.-P., Kassubek, J., Vernikouskaya, I., Ludolph, A. C., Stiller, D., & Rasche, V. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067630 · Cited by 22 · see citing works
Meijboom, R., Steketee, R. M. E., Ham, L. S., van der Lugt, A., van Swieten, J. C., & Smits, M. (2017) · Journal of Alzheimer’s Disease · doi:10.3233/jad-160564 · Cited by 17 · see citing works
Reveley, C., Ye, F. Q., & Leopold, D. A. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00368 · Cited by 14 · see citing works
Den Braber, A., Van ‘t Ent, D., Stoffers, D., Linkenkaer-Hansen, K., I. Boomsma, D., & J.C. de Geus, E. (2013) · International Journal of Psychological Research · doi:10.21500/20112084.712 · Cited by 11 · see citing works
- Authors
- Song, S.-K., Sun, S.-W., Ju, W.-K., Lin, S.-J., Cross, A. H., & Neufeld, A. H.
- Affiliations
- Washington University in St. Louis (US)
- Corresponding author
- Song, Sheng-Kwei
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2003-11
- Volume
- 20
- Issue
- 3
- Pages
- 1714-1722
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1994972002
- Cited by
- 1,738
- References
- 2
- Citations by year
- 2026: 37 · 2025: 56 · 2024: 42 · 2023: 54 · 2022: 71 · 2021: 86 · 2020: 79 · 2019: 108 · 2018: 102 · 2017: 97 · 2016: 118 · 2015: 121 · 2014: 126 · 2013: 131 · 2012: 116
- FWCI
- 8.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Eye Institute (R01EY012017, EY12017)
- National Cancer Institute (R24CA083060, R24-CA83060)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Ophthalmology › Glaucoma and retinal disorders
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Keywords
- axonal degeneration, myelin degeneration, retinal ischemia, optic nerve, diffusion tensor imaging, axial diffusivity, radial diffusivity, white matter disease, biomarkers, demyelination, mouse model
- MeSH terms
- Animals, Axons, Myelin Basic Protein, Immunohistochemistry, Ischemia, Models, Neurological, Myelin Sheath, Nerve Degeneration, Optic Nerve, Retinal Degeneration, Retinal Vessels, Wallerian Degeneration, Neurofilament Proteins, Diffusion Magnetic Resonance Imaging, Mice
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