The DOI matches its Crossref record, with a small difference in title or year; 74 of the 77 references it cites were found in a registry or an index.
Is diffusion anisotropy an accurate monitor of myelination?
Abstract
We compare T2-relaxation and diffusion tensor data from normal human brain. The relationships between myelin-water fraction (MWF) and various diffusion tensor measures [e.g., fractional anisotropy (FA), perpendicular diffusivity (ADC perpendicular) and mean diffusivity ] in white matter (WM) and gray matter (GM) structures in the brain were examined in 16 normal volunteers at 1.5 T and 6 normal subjects at 3.0 T and mean diffusivity. We found some degree of linear correlation between these measurements, but by using region of interest (ROI)-based analysis, we also observed several structures which seemed to deviate significantly from a linear relationship. From all investigated relationships between various diffusion tensor measures and myelin-water content, FA and ADC perpendicular yielded the highest correlation coefficients with MWF. However, diffusion anisotropy was also significantly influenced by factors other than myelin-water content. The less operator-dependent voxel-based analysis (VBA) between myelin-water and diffusional anisotropy measures is proposed as an innovative alternative to ROI-based analysis. We confirmed that WM structures, in general, have higher diffusional anisotropy than GM structures and also have higher myelin-water content. However, our findings suggest that in the highly organized fibre arrangement of compact WM structures such as the genu of the corpus callosum, elevated degrees of diffusional anisotropies are measured, which do not necessaril…
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“in the case of ihMT and MWI likely also provide more myelin-specific information than can be obtained with more general measures based on DTI or T1w/T2w ratio metrics (Mädler et al., 2008; Ercan et al., 2018; Uddin et al., 2019).”
From Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure (2022) · cites this paper as Mädler et al., 2008
Citations
Cites
Spin Diffusion Measurements: Spin Echoes in the Presence of a Time-Dependent Field Gradient
Stejskal, E. O., & Tanner, J. E. (1965) · The Journal of Chemical Physics · doi:10.1063/1.1695690 · Cited by 8,239
Solutions of Ill-Posed Problems.
Bell, J. B., Tikhonov, A. N., & Arsenin, V. Y. (1978) · Mathematics of Computation · doi:10.2307/2006360 · Cited by 8,096
SENSE: Sensitivity encoding for fast MRI
Pruessmann, K. P., Weiger, M., Scheidegger, M. B., & Boesiger, P. (1999) · Magnetic Resonance in Medicine · doi:10.1002/(sici)1522-2594(199911)42:5 · Cited by 6,303
The basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,628
Basser, P. J., & Pierpaoli, C. (1996) · Journal of Magnetic Resonance, Series B · doi:10.1006/jmrb.1996.0086 · Cited by 4,306
Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo
Basser, P. J., Mattiello, J., & Bihan, D. L. (1994) · Journal of Magnetic Resonance Series B · doi:10.1006/jmrb.1994.1037 · Cited by 3,656
Diffusion tensor imaging: Concepts and applications
Le Bihan, D., Mangin, J., Poupon, C., Clark, C. A., Pappata, S., Molko, N., & Chabriat, H. (2001) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.1076 · Cited by 3,547
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
Song, S.-K., Sun, S.-W., Ju, W.-K., Lin, S.-J., Cross, A. H., & Neufeld, A. H. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.07.005 · Cited by 1,738
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
Flagged first, then by citations
3 of the 77 references couldn’t be matched to a known paper.
Research works printed but not linked: 5
- Mädler, 2002, Correlation of multicomponent T2-relaxation data with diffusion tensor anisotropy measures in human brain, Proc ISMRM, 9
- Bells, 2007, Comparison of linear combination filtering to DTI and MTR in whole brain myelin-water imaging, Proc ISMRM, 15, 1606
- Mädler, 2006, In-vivo 3D multi-component T2-relaxation measurements for quantitative myelin imaging at 3T, Proc ISMRM, 13, 2112
- Laidlaw, 1999, Evaluating effects of diffusion weighting choice on accuracy of diffusion tensor MRI of fixed mouse spinal cord, Proc ISMRM, 1786
- Pajevic, 1999, Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: application to white matter fiber tract mapping in the human brain, Magn Reson Med, 42, 526, 10.1002/(SICI)1522-2594(199909)42:3<526::AID-MRM15>3.0.CO;2-J · DOI
Cited by
Sorted by citations
Life-Span Changes of the Human Brain White Matter: Diffusion Tensor Imaging (DTI) and Volumetry
Westlye, L. T., Walhovd, K. B., Dale, A. M., Bjornerud, A., Due-Tonnessen, P., Engvig, A., Grydeland, H., Tamnes, C. K., Ostby, Y., & Fjell, A. M. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp280 · Cited by 765
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
Puberty and the human brain: insights into adolescent development
Vijayakumar, N., Op de Macks, Z., Shirtcliff, E. A., & Pfeifer, J. H. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.06.004 · Cited by 437
Lifespan maturation and degeneration of human brain white matter
Yeatman, J. D., Wandell, B. A., & Mezer, A. (2014) · Nature Communications · doi:10.1038/ncomms5932 · Cited by 446
Growth of white matter in the adolescent brain: Myelin or axon?
Paus, T. (2010) · Brain and Cognition · doi:10.1016/j.bandc.2009.06.002 · Cited by 424
Deoni, S. C. L., Dean, D. C., O'Muircheartaigh, J., Dirks, H., & Jerskey, B. A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.07.037 · Cited by 390
Quantification of increased cellularity during inflammatory demyelination
Wang, Y., Wang, Q., Haldar, J. P., Yeh, F.-C., Xie, M., Sun, P., Tu, T.-W., Trinkaus, K., Klein, R. S., Cross, A. H., et al. (2011) · Brain · doi:10.1093/brain/awr307 · Cited by 384
Fractional anisotropy of water diffusion in cerebral white matter across the lifespan
Kochunov, P., Williamson, D. E., Lancaster, J., Fox, P. T., Cornell, J. E., Blangero, J., & Glahn, D. C. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.01.014 · Cited by 377
SANDI: a compartment‐based model for non‐invasive apparent soma and neurite imaging by diffusion MRI
Palombo, M., Ianus, A., Guerreri, M., Nunes, D., Alexander, D. C., Shemesh, N., & Zhang, H. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116835 · Cited by 349
White Matter Microstructure and Atypical Visual Orienting in 7-Month-Olds at Risk for Autism
Elison, J. T., Paterson, S. J., Wolff, J. J., Reznick, J. S., Sasson, N. J., Gu, H., Botteron, K. N., Dager, S. R., Estes, A. M., Evans, A. C., et al. (2013) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2012.12091150 · Cited by 277
“However, there is evidence to suggest that the density and diameter of axons in a given fiber tract, in addition to myelin content, affect the diffusion of water molecules perpendicular to the primary eigenvector of a fiber tract (32).”
BackgroundDelineation of early brain development from fetuses to infants with diffusion MRI and beyond
Ouyang, M., Dubois, J., Yu, Q., Mukherjee, P., & Huang, H. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.017 · Cited by 257
Figley, C. R., Uddin, M. N., Wong, K., Kornelsen, J., Puig, J., & Figley, T. D. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.799576 · Cited by 253
Diffusion tensor imaging for understanding brain development in early life
Qiu, A., Mori, S., & Miller, M. I. (2015) · Annual Review of Psychology · doi:10.1146/annurev-psych-010814-015340 · Cited by 238
Neurodevelopmental and neurodegenerative models of schizophrenia: white matter at the center stage
Kochunov, P., & Hong, L. E. (2014) · Schizophrenia Bulletin · doi:10.1093/schbul/sbu070 · Cited by 236
De Santis, S., Drakesmith, M., Bells, S., Assaf, Y., & Jones, D. K. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.12.003 · Cited by 231
The Biological Basis of Diffusion Anisotropy
Beaulieu, C. (2009) · Elsevier eBooks · doi:10.1016/b978-0-12-374709-9.00006-7 · Cited by 240
Whole brain myelin mapping using T1- and T2-weighted MR imaging data.
Ganzetti, M., Wenderoth, N., & Mantini, D. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00671 · Cited by 225
Gadie, A., Shafto, M. A., Leng, Y., Cam-CAN, & Kievit, R. (2017) · BMJ Open · doi:10.1136/bmjopen-2016-014920 · Cited by 224
Enhanced brain connectivity in long-term meditation practitioners
Luders, E., Clark, K., Narr, K. L., & Toga, A. W. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.075 · Cited by 209
Billiet, T., Vandenbulcke, M., Mädler, B., Peeters, R., Dhollander, T., Zhang, H., Deprez, S., Van den Bergh, B. R. H., Sunaert, S., & Emsell, L. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.02.029 · Cited by 203
Self-citationNoninvasive mapping of water diffusional exchange in the human brain using filter‐exchange imaging
Nilsson, M., Lätt, J., van Westen, D., Brockstedt, S., Lasič, S., Ståhlberg, F., & Topgaard, D. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24395 · Cited by 189
White matter integrity in adolescents with histories of marijuana use and binge drinking
Jacobus, J., McQueeny, T. M., Bava, S., Schweinsburg, B. C., Frank, L. R., Yang, T. T., & Tapert, S. F. (2009) · Neurotoxicology and Teratology · doi:10.1016/j.ntt.2009.07.006 · Cited by 194
Anterior thalamic radiation integrity in schizophrenia: A diffusion-tensor imaging study
Mamah, D., Conturo, T. E., Harms, M. P., Akbudak, E., Wang, L., McMichael, A. R., Gado, M. H., Barch, D. M., & Csernansky, J. G. (2010) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2010.04.013 · Cited by 185
White matter development and early cognition in babies and toddlers
O'Muircheartaigh, J., Dean, D. C., Ginestet, C. E., Walker, L., Waskiewicz, N., Lehman, K., Dirks, H., Piryatinsky, I., & Deoni, S. C. L. (2014) · Human Brain Mapping · doi:10.1002/hbm.22488 · Cited by 183
Characterizing longitudinal white matter development during early childhood
Dean, D. C., O’Muircheartaigh, J., Dirks, H., Waskiewicz, N., Walker, L., Doernberg, E., Piryatinsky, I., & Deoni, S. C. L. (2015) · Brain Structure and Function · doi:10.1007/s00429-014-0763-3 · Cited by 174
Govindan, R. M., Behen, M. E., Helder, E., Makki, M. I., & Chugani, H. T. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp122 · Cited by 172
A digital 3D atlas of the marmoset brain based on multi-modal MRI
Liu, C., Ye, F. Q., Yen, C. C., Newman, J. D., Glen, D., Leopold, D. A., & Silva, A. C. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.004 · Cited by 170
Sleep variability in adolescence is associated with altered brain development
Telzer, E. H., Goldenberg, D., Fuligni, A. J., Lieberman, M. D., & Galván, A. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.05.007 · Cited by 171
Modeling healthy male white matter and myelin development: 3 through 60months of age
Dean, D. C., O'Muircheartaigh, J., Dirks, H., Waskiewicz, N., Lehman, K., Walker, L., Han, M., & Deoni, S. C. L. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.09.058 · Cited by 163
Kochunov, P., Glahn, D. C., Lancaster, J. L., Thompson, P. M., Kochunov, V., Rogers, B. G., Fox, P. T., Blangero, J., & Williamson, D. E. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.050 · Cited by 165
Genetics of microstructure of cerebral white matter using diffusion tensor imaging
Kochunov, P., Glahn, D. C., Lancaster, J. L., Winkler, A. M., Smith, S. M., Thompson, P. M., Almasy, L. A., Duggirala, R., Fox, P. T., & Blangero, J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.078 · Cited by 158
White matter architecture rather than cortical surface area correlates with the EEG alpha rhythm
Valdes-Hernandez, P. A., Ojeda, A., Martínez‐Montes, E., Lage‐Castellanos, A., Virues-Alba, T. A., Valdés-Urrutia, L., & Valdes-Sosa, P. A. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.030 · Cited by 153
Thomas, A. G., Dennis, A., Rawlings, N. B., Stagg, C. J., Matthews, L., Morris, M., Kolind, S. H., Foxley, S., Jenkinson, M., Nichols, T. E., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.090 · Cited by 152
“…and FA which have been used in other studies to draw conclusions about axonal orientation, integrity, and myelination within white matter regions where fibers are bundled with coherent orientation (Scholz et al., 2009) though aspects of this interpretation are controversial (Mädler et al., 2008).”
MethodSelf-citationHypomyelinating leukodystrophies: Translational research progress and prospects
Pouwels, P. J. W., Vanderver, A. L., Bernard, G., Wolf, N. I., Dreha‐Kulaczewski, S. F., Deoni, S., Bertini, E., Kohlschütter, A., Richardson, W. D., ffrench‐Constant, C., et al. (2014) · Annals of Neurology · doi:10.1002/ana.24194 · Cited by 153
Uddin, M. N., Figley, T. D., Solar, K. G., Shatil, A. S., & Figley, C. R. (2019) · Scientific Reports · doi:10.1038/s41598-019-39199-x · Cited by 151
Bound pool fractions complement diffusion measures to describe white matter micro and macrostructure
Stikov, N., Perry, L. M., Mezer, A., Rykhlevskaia, E. I., Wandell, B. A., Pauly, J. M., & Dougherty, R. F. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.068 · Cited by 145
Sacchet, M. D., & Gotlib, I. H. (2017) · Scientific Reports · doi:10.1038/s41598-017-02062-y · Cited by 153
Lim, S. I., Han, C. E., Uhlhaas, P. J., & Kaiser, M. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht333 · Cited by 154
Quantitative MRI and ultrastructural examination of the cuprizone mouse model of demyelination
Thiessen, J. D., Zhang, Y., Zhang, H., Wang, L., Buist, R., Del Bigio, M. R., Kong, J., Li, X., & Martin, M. (2013) · NMR in Biomedicine · doi:10.1002/nbm.2992 · Cited by 148
Inferring brain tissue composition and microstructure via MR relaxometry
Does, M. D. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.087 · Cited by 137
Friedrich, P., Fraenz, C., Schlüter, C., Ocklenburg, S., Mädler, B., Güntürkün, O., & Genç, E. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz221 · Cited by 133
Self-citationTamnes, 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
Arshad, M., Stanley, J. A., & Raz, N. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.047 · Cited by 115
Brouwer, R. M., Mandl, R. C. W., Schnack, H. G., van Soelen, I. L. C., van Baal, G. C., Peper, J. S., Kahn, R. S., Boomsma, D. I., & Pol, H. E. H. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032316 · Cited by 107
Babaeeghazvini, P., Rueda‐Delgado, L. M., Gooijers, J., Swinnen, S. P., & Daffertshofer, A. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.721206 · Cited by 125
fMRI Functional Connectivity Applied to Adolescent Neurodevelopment
Ernst, M., Torrisi, S., Balderston, N. L., Grillon, C., & Hale, E. A. (2015) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-032814-112753 · Cited by 111
Diffusion tensor imaging segments the human amygdala in vivo
Solano-Castiella, E., Anwander, A., Lohmann, G., Weiß, M., Docherty, C., Geyer, S., Reimer, E., Friederici, A. D., & Turner, R. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.027 · Cited by 107
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
Alterations of Myelin Content in Parkinson’s Disease: A Cross-Sectional Neuroimaging Study
Dean, D., Sojkova, J., Hurley, S. A., Kecskemeti, S., Okonkwo, O. C., Bendlin, B. B., Theisen, F., Johnson, S. C., Alexander, A. L., & Gallagher, C. L. (2016) · PLoS ONE · doi:10.1371/journal.pone.0163774 · Cited by 103
Mandl, R. C. W., Schnack, H. G., Luigjes, J., van den Heuvel, M. P., Cahn, W., Kahn, R. S., & Pol, H. E. H. (2008) · Schizophrenia Bulletin · doi:10.1093/schbul/sbn161 · Cited by 100
Khodanovich, M. Y., Sorokina, I. V., Glazacheva, V., Евгеньевич, А. А., Nemirovich-Danchenko, N. M., Romashchenko, A. V., Tolstikova, T. G., Mustafina, L. R., & Yarnykh, V. L. (2017) · Scientific Reports · doi:10.1038/srep46686 · Cited by 97
White matter abnormalities in adolescents with major depressive disorder
Bessette, K. L., Nave, A. M., Caprihan, A., & Stevens, M. C. G. (2013) · Brain Imaging and Behavior · doi:10.1007/s11682-013-9274-8 · Cited by 98
Quantitative myelin imaging with MRI and PET: an overview of techniques and their validation status
van der Weijden, C. W. J., Biondetti, E., Gutmann, I. W., Dijkstra, H., McKerchar, R., Faria, D. D. P., de Vries, E. F. J., Meilof, J. F., Dierckx, R., Prévost, V., et al. (2022) · Brain · doi:10.1093/brain/awac436 · Cited by 95
MR Relaxation in Multiple Sclerosis
MacKay, A. L., Vavasour, I. M., Rauscher, A., Kolind, S., Mädler, B., Moore, G. R. W., Traboulsee, A. L., Li, D. K. B., & Laule, C. (2008) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2008.09.007 · Cited by 95
Self-citationIdentifying population differences in whole-brain structural networks: A machine learning approach
Robinson, E. C., Hammers, A., Ericsson, A. B., Edwards, A. D., & Rueckert, D. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.019 · Cited by 92
Dynamics of the human structural connectome underlying working memory training
Caeyenberghs, K., Metzler-Baddeley, C., Foley, S., & Jones, D. K. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.1973-15.2016 · Cited by 91
Evaluation of diffusion kurtosis imaging in ex vivo hypomyelinated mouse brains
Kelm, N. D., West, K. L., Carson, R. P., Gochberg, D. F., Ess, K. C., & Does, M. D. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.09.028 · Cited by 84
White Matter Integrity in Veterans With Mild Traumatic Brain Injury
Sorg, S. F., Delano‐Wood, L., Luc, N., Schiehser, D. M., Hanson, K. L., Nation, D. A., Lanni, E., Jak, A. J., Lu, K., Meloy, M. J., et al. (2013) · Journal of Head Trauma Rehabilitation · doi:10.1097/htr.0b013e31828a1aa4 · Cited by 87
Evaluation of white matter myelin water fraction in chronic stroke
Borich, M. R., MacKay, A. L., Vavasour, I. M., Rauscher, A., & Boyd, L. A. (2013) · NeuroImage Clinical · doi:10.1016/j.nicl.2013.04.006 · Cited by 83
Self-citationWhite-matter relaxation time and myelin water fraction differences in young adults with autism
Deoni, S., Zinkstok, J., Daly, E., Ecker, C., Williams, S., & Murphy, D. (2014) · Psychological Medicine · doi:10.1017/s0033291714001858 · Cited by 83
Hypomyelination following deletion of Tsc2 in oligodendrocyte precursors
Carson, R. P., Kelm, N. D., West, K. L., Does, M. D., Fu, C., Weaver, G., McBrier, E., Parker, B., Grier, M. D., & Ess, K. C. (2015) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.254 · Cited by 79
Deficient MWF mapping in multiple sclerosis using 3D whole-brain multi-component relaxation MRI
Kitzler, H. H., Su, J., Zeineh, M., Harper-Little, C., Leung, A., Kremenchutzky, M., Deoni, S., & Rutt, B. K. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.052 · Cited by 77
Heritability of DTI and MTR in nine-year-old children
Brouwer, R. M., Mandl, R. C. W., Peper, J. S., van Baal, G. C. M., Kahn, R. S., Boomsma, D. I., & Pol, H. E. H. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.017 · Cited by 74
Chopra, S., Shaw, M. E., Shaw, T. B., Sachdev, P. S., Anstey, K. J., & Cherbuin, N. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.069 · Cited by 68
Faizy, T. D., Thaler, C. P., Broocks, G., Flottmann, F., Leischner, H., Kniep, H. C., Nawabi, J., Schön, G., Stellmann, J., Kemmling, A., et al. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00136 · Cited by 70
Rose, S., Pannek, K., Bell, C., Baumann, F., Hutchinson, N. M., Coulthard, A., McCombe, P., & Henderson, R. D. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.054 · Cited by 73
Croteau-Chonka, E. C., Dean, D. C., Remer, J., Dirks, H., O'Muircheartaigh, J., & Deoni, S. C. L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.038 · Cited by 70
Tullo, S., Patel, R., Devenyi, G. A., Salaciak, A., Bedford, S. A., Farzin, S., Wlodarski, N., Tardif, C. L., Breitner, J. C. S., & Chakravarty, M. M. (2019) · Human Brain Mapping · doi:10.1002/hbm.24771 · Cited by 63
Magnetic resonance microdynamic imaging reveals distinct tissue microenvironments
Benjamini, D., & Basser, P. J. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.09.033 · Cited by 68
The Biological Basis of Diffusion Anisotropy
Beaulieu, C. (2014) · Diffusion MRI · doi:10.1016/b978-0-12-396460-1.00008-1 · Cited by 66
Diffusion Tensor Imaging and Neuromodulation
Coenen, V. A., Schlaepfer, T. E., Allert, N., & Mädler, B. (2012) · International review of neurobiology · doi:10.1016/b978-0-12-404706-8.00011-5 · Cited by 66
Self-citationLiu, F., Vidarsson, L., Winter, J. D., Tran, H., & Kassner, A. (2010) · Brain Research · doi:10.1016/j.brainres.2010.04.064 · Cited by 65
Genetic Analysis of Cortical Thickness and Fractional Anisotropy of Water Diffusion in the Brain
Kochunov, P., Glahn, D. C., Nichols, T. E., Winkler, A. M., Hong, E. L., Holcomb, H. H., Stein, J. L., Thompson, P. M., Curran, J. E., Carless, M. A., et al. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00120 · Cited by 61
Kochunov, P., Ganjgahi, H., Winkler, A. M., Kelly, S., Shukla, D. K., Du, X. M., Jahanshad, N., Rowland, L. M., Sampath, H., Patel, B., et al. (2016) · Human Brain Mapping · doi:10.1002/hbm.23336 · Cited by 63
Diffusion magnetic resonance imaging in preterm brain injury
Pandit, A. S., Ball, G., Edwards, A. D., & Counsell, S. J. (2013) · Neuroradiology · doi:10.1007/s00234-013-1242-x · Cited by 63
Developmental differences in diffusion tensor imaging parameters in borderline personality disorder
New, A. S., Carpenter, D. M., Pérez-Rodríguez, M. M., Ripoll, L. H., Avedon, J., Patil, U., Hazlett, E. A., & Goodman, M. S. (2013) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2013.03.021 · Cited by 60
Bender, A. R., & Raz, N. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.02.001 · Cited by 65
White matter and memory in healthy adults: Coupled changes over two years
Bender, A. R., Prindle, J., Brandmaier, A. M., & Raz, N. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.085 · Cited by 61
Atypical age‐dependent effects of autism on white matter microstructure in children of 2–7 years
Ouyang, M., Cheng, H., Mishra, V. R., Gong, G., Mosconi, M. W., Sweeney, J. A., Peng, Y., & Huang, H. (2015) · Human Brain Mapping · doi:10.1002/hbm.23073 · Cited by 63
Assessing structure and function of myelin in cervical spondylotic myelopathy
Liu, H., MacMillian, E. L., Jutzeler, C. R., Ljungberg, E., MacKay, A. L., Kolind, S., Mädler, B., Li, D. K. B., Dvorak, M. F., Curt, A. E. P., et al. (2017) · Neurology · doi:10.1212/wnl.0000000000004197 · Cited by 60
Self-citationJann, K., Federspiel, A., Giezendanner, S., Andreotti, J., Kottlow, M., Dierks, T., & Koenig, T. W. (2012) · Brain Connectivity · doi:10.1089/brain.2011.0063 · Cited by 59
Insights into human cerebral white matter maturation and degeneration across the adult lifespan
Kiely, M., Triebswetter, C., Cortina, L. E., Gong, Z., Alsameen, M. H., Spencer, R. G. S., & Bouhrara, M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118727 · Cited by 54
Comparing MRI metrics to quantify white matter microstructural damage in multiple sclerosis
Lipp, I., Jones, D. K., Bells, S., Sgarlata, E., Foster, C., Stickland, R., Davidson, A. E., Tallantyre, E. C., Robertson, N. P., Wise, R. G., et al. (2019) · Human Brain Mapping · doi:10.1002/hbm.24568 · Cited by 52
Hybrid multidimensional T2 and diffusion‐weighted MRI for prostate cancer detection
Wang, S., Peng, Y., Medved, M., Yousuf, A. N., Ivancevic, M. K., Karademir, İ., Jiang, Y., Antic, T., Sammet, S., Oto, A., et al. (2013) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24212 · Cited by 53
A Magnetization Transfer Imaging Study of Corpus Callosum Myelination in Young Children with Autism
Gozzi, M., Nielson, D. M., Lenroot, R., Ostuni, J. L., Luckenbaugh, D. A., Thurm, A. E., Giedd, J. N., & Swedo, S. E. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.01.026 · Cited by 53
Balamoody, S., Williams, T. G., Wolstenholme, C., Waterton, J. C., Bowes, M. A., Hodgson, R. J., Zhao, S., Scott, M. L. J., Taylor, C., & Hutchinson, C. E. (2012) · Skeletal Radiology · doi:10.1007/s00256-012-1511-5 · Cited by 49
Gonçalves, F. G., Serai, S. D., & Zuccoli, G. (2018) · Topics in Magnetic Resonance Imaging · doi:10.1097/rmr.0000000000000189 · Cited by 48
Hasan, K. M., Walimuni, I. S., Kramer, L. A., & Frye, R. E. (2010) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22515 · Cited by 47
Kumar, A., Behen, M. E., Singsoonsud, P., Veenstra, A. L., Wolfe-Christensen, C., Helder, E., & Chugani, H. T. (2014) · Journal of Child Neurology · doi:10.1177/0883073812474098 · Cited by 46
Kennedy, K. M., & Raz, N. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00068-3 · Cited by 48
Separate lanes for adding and reading in the white matter highways of the human brain
Grotheer, M., Zhen, Z., Lerma‐Usabiaga, G., & Kalanit Grill-spector, A. (2019) · Nature Communications · doi:10.1038/s41467-019-11424-1 · Cited by 44
Eminian, S., Hajdu, S. D., Meuli, R. A., Maeder, P. P., & Hagmann, P. (2018) · PLoS ONE · doi:10.1371/journal.pone.0198250 · Cited by 43
Petkoski, S., Ritter, P., & Jirsa, V. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac500 · Cited by 43
Dalton, C. M., Bodini, B., Samson, R. S., Battaglini, M., Fisniku, L., Thompson, A. J., Ciccarelli, O., Miller, D., & Chard, D. (2011) · Multiple Sclerosis Journal · doi:10.1177/1352458511420269 · Cited by 41
Acheson, A., Wijtenburg, S. A., Rowland, L. M., Winkler, A. M., Gaston, F. E., Mathias, C. W., Fox, P. T., Lovallo, W. R., Wright, S. N., Hong, L. E., et al. (2014) · Human Brain Mapping · doi:10.1002/hbm.22559 · Cited by 45
A multisample study of longitudinal changes in brain network architecture in 4–13‐year‐old children
Wierenga, L. M., van den Heuvel, M. P., Oranje, B., Giedd, J. N., Durston, S., Peper, J. S., Brown, T. T., Crone, E. A., & The Pediatric Longitudinal Imaging, N. (2017) · Human Brain Mapping · doi:10.1002/hbm.23833 · Cited by 44
Abel, S., Vavasour, I. M., Lee, L. E., Johnson, P., Ristow, S., Ackermans, N., Chan, J., Cross, H., Laule, C., Dvorak, A. V., et al. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.14220 · Cited by 43
Self-citationErcan, E., Varma, G., Mädler, B., Dimitrov, I. E., Pinho, M. C., Xi, Y., Wagner, B. C., Davenport, E. M., Maldjian, J. A., Alsop, D. C., et al. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27211 · Cited by 40
Self-citationWijtenburg, S. A., McGuire, S., Rowland, L. M., Sherman, P. M., Lancaster, J. L., Tate, D. F., Hardies, L. J., Patel, B., Glahn, D. C., Hong, L. E., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.014 · Cited by 42
Subtle white matter alterations in schizophrenia identified with a new measure of fiber density
Stämpfli, P., Sommer, S., Manoliu, A., Burrer, A., Schmidt, A., Herdener, M., Seifritz, E., Kaiser, S., & Kirschner, M. (2019) · Scientific Reports · doi:10.1038/s41598-019-40070-2 · Cited by 40
Metadata
- Authors
- Mädler, B., Drabycz, S. A., Kolind, S. H., Whittall, K. P., & MacKay, A. L.
- Affiliations
- University of British Columbia Hospital (CA)
- University of Calgary (CA)
- Corresponding author
- Mädler, Burkhard
- Venue
- Magnetic Resonance Imaging
- Publisher
- Elsevier BV
- Published
- 2008-09
- Volume
- 26
- Issue
- 7
- Pages
- 874-888
- ISSN
- 0730-725X (ISSN-L)
- OpenAlex
- W2008655880
- Cited by
- 227
- References
- 77
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 5 · 2023: 6 · 2022: 10 · 2021: 18 · 2020: 11 · 2019: 14 · 2018: 18 · 2017: 14 · 2016: 12 · 2015: 22 · 2014: 13 · 2013: 22 · 2012: 10
- FWCI
- 11.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Magnetic Resonance Imaging (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Bundesministerium für Bildung und Forschung
- Killam Trusts
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- diffusion anisotropy, myelination, myelin water fraction, fractional anisotropy, white matter, gray matter, T2 relaxation, mean diffusivity, corpus callosum, forceps minor, forceps major, voxel-based analysis, restricted diffusion
- MeSH terms
- Adolescent, Adult, Brain, Brain Mapping, Female, Humans, Male, Middle Aged, Nerve Fibers, Myelinated, Water, Linear Models, Anisotropy, Diffusion Magnetic Resonance Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review