Reproducibility of quantitative tractography methods applied to cerebral white matter
Open accessAbstract
Tractography based on diffusion tensor imaging (DTI) allows visualization of white matter tracts. In this study, protocols to reconstruct eleven major white matter tracts are described. The protocols were refined by several iterations of intra- and inter-rater measurements and identification of sources of variability. Reproducibility of the established protocols was then tested by raters who did not have previous experience in tractography. The protocols were applied to a DTI database of adult normal subjects to study size, fractional anisotropy (FA), and T2 of individual white matter tracts. Distinctive features in FA and T2 were found for the corticospinal tract and callosal fibers. Hemispheric asymmetry was observed for the size of white matter tracts projecting to the temporal lobe. This protocol provides guidelines for reproducible DTI-based tract-specific quantification.
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Manual streamline selection has been shown highly reproducible for specific tracts and segmentation protocols using diffusion tensor tractography.
“Methods using manual streamline selection have been shown to be highly reproducible for specific tracts and segmentation protocols using the diffusion tensor tractography (Wakana et al., 2007)”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Wakana et al., 2007
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The Measurement of Observer Agreement for Categorical Data
Landis, J. R., & Koch, G. G. (1977) · Biometrics · doi:10.2307/2529310 · Cited by 81,148 · see citing works
Diffusion Tensor Imaging and Axonal Tracking in the Human Brainstem
Stieltjes, B., Kaufmann, W. E., van Zijl, P. C. M., Fredericksen, K., Pearlson, G. D., Solaiyappan, M., & Mori, S. (2001) · NeuroImage · doi:10.1006/nimg.2001.0861 · Cited by 492 · see citing works
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- Basser PJ, Pajevic S, Pierpaoli C, Duda J, Aldroubi A. In vitro fiber tractography using DT-MRI data. Magn. Reson. Med. 2000;44:625–632. doi: 10.1002/1522-2594(200010)44:4<625::aid-mrm17>3.0.co;2-o. [DOI] [PubMed] [Google Scholar] · DOI
- Catani M, Howard RJ, Pajevic S, Jones DK. Virtual in vivo interactive dissection of white matter fasciculi in the human brain. NeuroImage. 2002;17:77–94. doi: 10.1006/nimg.2002.1136. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
- Conturo TE, Lori NF, Cull TS, Akbudak E, Snyder AZ, Shimony JS, McKinstry RC, Burton H, Raichle ME. Tracking neuronal fiber pathways in the living human brain. Proc. Natl. Acad. Sci. USA. 1999;96:10422–10427. doi: 10.1073/pnas.96.18.10422. [DOI] [PMC free article] [PubMed] [Google Scholar] · DOI · Paper page
- Farrell J, Landman B, Jones C, Smith S, Prince J, van Zijl P, Mori S. Effects of diffusion weighting scheme and SNR on DTI-derived fractional anisotropy at 1.5T. International Society of Magnetic Resonance in Medicine; Seattle: 2006. p. 1075. [Google Scholar]
- Glenn OA, Henry RG, Berman JI, Chang PC, Miller SP, Vigneron DB, Barkovich AJ. DTI-based three-dimensional tractography detects differences in the pyramidal tracts of infants and children with congenital hemiparesis. J Magn Reson Imaging. 2003;18:641–648. doi: 10.1002/jmri.10420. [DOI] [PubMed] [Google Scholar] · DOI
- Gong G, Jiang T, Zhu C, Zang Y, He Y, Xie S, Xiao J. Side and handedness effects on the cingulum from diffusion tensor imaging. Neuroreport. 2005a;16:1701–1705. doi: 10.1097/01.wnr.0000183327.98370.6a. [DOI] [PubMed] [Google Scholar] · DOI
- Gong G, Jiang T, Zhu C, Zang Y, Wang F, Xie S, Xiao J, Guo X. Asymmetry analysis of cingulum based on scale-invariant parameterization by diffusion tensor imaging. Hum Brain Mapp. 2005b;24:92–98. doi: 10.1002/hbm.20072. [DOI] [PMC free article] [PubMed] [Google Scholar] · DOI
- Heiervang E, Behrens TE, Mackay CE, Robson MD, Johansen-Berg H. Between session reproducibility and between subject variability of diffusion MR and tractography measures. NeuroImage. 2006;33:867–877. doi: 10.1016/j.neuroimage.2006.07.037. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
- Huang H, Zhang J, van Zijl PC, Mori S. Analysis of noise effects on DTI-based tractography using the brute-force and multi-ROI approach. Magn Reson Med. 2004;52:559–565. doi: 10.1002/mrm.20147. [DOI] [PubMed] [Google Scholar] · DOI
- Jellison BJ, Field AS, Medow J, Lazar M, Salamat MS, Alexander AL. Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR Am J Neuroradiol. 2004;25:356–369. [PMC free article] [PubMed] [Google Scholar]
- Jones DK, Horsfield MA, Simmons A. Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 1999a;42:515–525. [PubMed] [Google Scholar]
- Jones DK, Simmons A, Williams SC, Horsfield MA. Non-invasive assessment of axonal fiber connectivity in the human brain via diffusion tensor MRI. Magn. Reson. Med. 1999b;42:37–41. doi: 10.1002/(sici)1522-2594(199907)42:1<37::aid-mrm7>3.0.co;2-o. [DOI] [PubMed] [Google Scholar] · DOI
- Kinoshita M, Yamada K, Hashimoto N, Kato A, Izumoto S, Baba T, Maruno M, Nishimura T, Yoshimine T. Fiber-tracking does not accurately estimate size of fiber bundle in pathological condition: initial neurosurgical experience using neuronavigation and subcortical white matter stimulation. NeuroImage. 2005;25:424–429. doi: 10.1016/j.neuroimage.2004.07.076. [DOI] [PubMed] [Google Scholar] · DOI
- Lazar M, Weinstein DM, Tsuruda JS, Hasan KM, Arfanakis K, Meyerand ME, Badie B, Rowley HA, Haughton V, Field A, Alexander AL. White matter tractography using diffusion tensor deflection. Hum Brain Mapp. 2003;18:306–321. doi: 10.1002/hbm.10102. [DOI] [PMC free article] [PubMed] [Google Scholar] · DOI
- Makris N, Kennedy DN, McInerney S, Sorensen AG, Wang R, Caviness VS, Jr., Pandya DN. Segmentation of subcomponents within the superior longitudinal fascicle in humans: a quantitative, in vivo, DT-MRI study. Cereb Cortex. 2005;15:854–869. doi: 10.1093/cercor/bhh186. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
- Mori S, Crain BJ, Chacko VP, van Zijl PCM. Three dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Annal. Neurol. 1999;45:265–269. doi: 10.1002/1531-8249(199902)45:2<265::aid-ana21>3.0.co;2-3. [DOI] [PubMed] [Google Scholar] · DOI
- Mori S, Kaufmann WE, Davatzikos C, Stieltjes B, Amodei L, Fredericksen K, Pearlson GD, Melhem ER, Solaiyappan M, Raymond GV, Moser HW, van Zijl PCM. Imaging cortical association tracts in human brain. Magn Reson Med. 2002;47:215–223. doi: 10.1002/mrm.10074. [DOI] [PubMed] [Google Scholar] · DOI
- Mori S, Wakana S, Nagae-Poetscher LM, van Zijl PC. MRI atlas of human white matter. Elsevier; Amsterdam, The Netherlands: 2005. [Google Scholar]
- Nucifora PG, Verma R, Melhem ER, Gur RE, Gur RC. Leftward asymmetry in relative fiber density of the arcuate fasciculus. Neuroreport. 2005;16:791–794. doi: 10.1097/00001756-200505310-00002. [DOI] [PubMed] [Google Scholar] · DOI
- Pagani E, Filippi M, Rocca MA, Horsfield MA. A method for obtaining tract-specific diffusion tensor MRI measurements in the presence of disease: application to patients with clinically isolated syndromes suggestive of multiple sclerosis. NeuroImage. 2005;26:258–265. doi: 10.1016/j.neuroimage.2005.01.008. [DOI] [PubMed] [Google Scholar] · DOI
- Park HJ, Westin CF, Kubicki M, Maier SE, Niznikiewicz M, Baer A, Frumin M, Kikinis R, Jolesz FA, McCarley RW, Shenton ME. White matter hemisphere asymmetries in healthy subjects and in schizophrenia: a diffusion tensor MRI study. NeuroImage. 2004;23:213–223. doi: 10.1016/j.neuroimage.2004.04.036. [DOI] [PMC free article] [PubMed] [Google Scholar] · DOI · Paper page
- Parker GJ, Stephan KE, Barker GJ, Rowe JB, MacManus DG, Wheeler-Kingshott CA, Ciccarelli O, Passingham RE, Spinks RL, Lemon RN, Turner R. Initial demonstration of in vivo tracing of axonal projections in the macaque brain and comparison with the human brain using diffusion tensor imaging and fast marching tractography. NeuroImage. 2002;15:797–809. doi: 10.1006/nimg.2001.0994. [DOI] [PubMed] [Google Scholar] · DOI
- Partridge SC, Mukherjee P, Henry RG, Miller SP, Berman JI, Jin H, Lu Y, Glenn OA, Ferriero DM, Barkovich AJ, Vigneron DB. Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns. NeuroImage. 2004;22:1302–1314. doi: 10.1016/j.neuroimage.2004.02.038. [DOI] [PubMed] [Google Scholar] · DOI
- Pierpaoli C, Barnett A, Pajevic S, Chen R, Penix LR, Virta A, Basser P. Water diffusion changes in Wallerian degeneration and their dependence on white matter architecture. NeuroImage. 2001;13:1174–1185. doi: 10.1006/nimg.2001.0765. [DOI] [PubMed] [Google Scholar] · DOI · Paper page
- Poupon C, Clark CA, Frouin V, Regis J, Bloch L, Le Bihan D, Mangin JF. Regularization of diffusion-based direction maps for the tracking of brain white matter fascicules. NeuroImage. 2000;12:184–195. doi: 10.1006/nimg.2000.0607. [DOI] [PubMed] [Google Scholar] · DOI
- Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med. 1999;42:952–962. [PubMed] [Google Scholar]
- Virta A, Barnett A, Pierpaoli C. Visualizing and characterizing white matter fiber structure and architecture in the human pyramidal tract using diffusion tensor MRI. Magn.Reson.Imaging. 1999;17:1121–1133. doi: 10.1016/s0730-725x(99)00048-x. [DOI] [PubMed] [Google Scholar] · DOI
- Wakana S, Jiang H, Nagae-Poetscher LM, Van Zijl PC, Mori S. Fiber Tract-based Atlas of Human White Matter Anatomy. Radiology. 2004;230:77–87. doi: 10.1148/radiol.2301021640. [DOI] [PubMed] [Google Scholar] · DOI
- Wiegell M, Larsson H, Wedeen V. Fiber crossing in human brain depicted with diffusion tensor MR imaging. Radiology. 2000;217:897–903. doi: 10.1148/radiology.217.3.r00nv43897. [DOI] [PubMed] [Google Scholar] · DOI
- Wilson M, Tench CR, Morgan PS, Blumhardt LD. Pyramidal tract mapping by diffusion tensor magnetic resonance imaging in multiple sclerosis: improving correlations with disability. J Neurol Neurosurg Psychiatry. 2003;74:203–207. doi: 10.1136/jnnp.74.2.203. [DOI] [PMC free article] [PubMed] [Google Scholar] · DOI
- Woods RP, Grafton ST, Holmes CJ, Cherry SR, Mazziotta JC. Automated image registration: I. General methods and intrasubject, intramodality validation. J Comput Assist Tomogr. 1998;22:139–152. doi: 10.1097/00004728-199801000-00027. [DOI] [PubMed] [Google Scholar] · DOI
- Xue R, van Zijl PCM, Crain BJ, Solaiyappan M, Mori S. In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging. Magn. Reson. Med. 1999;42:1123–1127. doi: 10.1002/(sici)1522-2594(199912)42:6<1123::aid-mrm17>3.0.co;2-h. [DOI] [PubMed] [Google Scholar] · DOI
- Yagishita A, Nakano I, Oda M, Hirano A. Location of the corticospinal tract in the internal capsule at MR imaging. Radiology. 1994;191:455–460. doi: 10.1148/radiology.191.2.8153321. [DOI] [PubMed] [Google Scholar] · DOI
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Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., Bartsch, A. J., Jbabdi, S., Sotiropoulos, S. N., Andersson, J. L. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4393 · Cited by 2,020 · see citing works
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Maier-Hein, K. H., Neher, P., Houde, J.-C., Côté, M.-A., Garyfallidis, E., Zhong, J., Chamberland, M., Yeh, F.-C., Lin, Y.-C., Ji, Q., et al. (2016) · doi:10.1101/084137 · Cited by 1,361 · 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
Thiebaut de Schotten, M., ffytche, D. H., Bizzi, A., Dell'Acqua, F., Allin, M., Walshe, M., Murray, R., Williams, S. C., Murphy, D. G. M., & Catani, M. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.055 · Cited by 656 · see citing works
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Rojkova, K., Volle, E., Urbanski, M., Humbert, F., Dell’Acqua, F., & Thiebaut de Schotten, M. (2016) · Brain Structure and Function · doi:10.1007/s00429-015-1001-3 · Cited by 361 · 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
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Ahluwalia, V., Wade, J. B., Heuman, D. M., Hammeke, T. A., Sanyal, A. J., Sterling, R. K., Stravitz, R. T., Luketic, V., Siddiqui, M. S., Puri, P., et al. (2014) · Metabolic Brain Disease · doi:10.1007/s11011-014-9507-6 · Cited by 92 · see citing works
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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
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Phillips, O. R., Nuechterlein, K. H., Clark, K. A., Hamilton, L. S., Asarnow, R. F., Hageman, N. S., Toga, A. W., & Narr, K. L. (2009) · Schizophrenia Research · doi:10.1016/j.schres.2008.10.019 · Cited by 80 · see citing works
Taylor, W. D., Boyd, B., McQuoid, D. R., Kudra, K., Saleh, A., & MacFall, J. R. (2015) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2015.05.001 · Cited by 79 · see citing works
Lynch, K. M., Cabeen, R. P., Toga, A. W., & Clark, K. A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116672 · Cited by 79 · 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
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PETERS, S. U., KAUFMANN, W. E., BACINO, C. A., ANDERSON, A. W., ADAPA, P., CHU, Z., YALLAMPALLI, R., TRAIPE, E., HUNTER, J. V., & WILDE, E. A. (2011) · Developmental Medicine & Child Neurology · doi:10.1111/j.1469-8749.2010.03838.x · Cited by 69 · see citing works
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Landrigan, J.-F., Zhang, F., & Mirman, D. (2021) · Brain · doi:10.1093/brain/awab010 · Cited by 54 · see citing works
Beer, A. L., Plank, T., Meyer, G., & Greenlee, M. W. (2013) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2013.00005 · Cited by 53 · see citing works
Taylor, W. D., Zhao, Z., Ashley‐Koch, A., Payne, M. E., Steffens, D. C., Krishnan, R. R., Hauser, E., & MacFall, J. R. (2013) · Human Brain Mapping · doi:10.1002/hbm.21445 · Cited by 50 · see citing works
Surova, Y., Lampinen, B., Nilsson, M., Lätt, J., Hall, S., Widner, H., study, S. B., van Westen, D., & Hansson, O. (2016) · PLOS ONE · doi:10.1371/journal.pone.0157755 · Cited by 51 · see citing works
White-matter tract integrity in late-life depression: associations with severity and cognition
Charlton, R. A., Lamar, M., Zhang, A., Yang, S., Ajilore, O., & Kumar, A. (2014) · Psychological Medicine · doi:10.1017/s0033291713001980 · Cited by 49 · see citing works
Liu, Y., Metens, T., Absil, J., De Maertelaer, V., Balériaux, D., David, P., Denolin, V., Van Overmeire, B., Avni, F., Van Bogaert, P., et al. (2011) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2690 · Cited by 44 · 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
“The JHU-ICBM-tract atlas [Wakana et al., 2007] was used to define regions of interest (ROI) for major fiber bundles that have previously demonstrated importance in ADHD [Chuang et al., 2013; Lawrence et al., 2013; Silk et al., 2009; Tamm et al., 2012].”
MethodClark, D. L., Johnson, K. A., Butson, C. R., Lebel, C., Gobbi, D., Ramasubbu, R., & Kiss, Z. H. T. (2020) · Brain stimulation · doi:10.1016/j.brs.2020.03.006 · Cited by 36 · see citing works
Automated tractography of the cingulate bundle in Alzheimer's disease: a multicenter DTI study
Fischer, F. U., Scheurich, A., Wegrzyn, M., Schermuly, I., Bokde, A. L. W., Klöppel, S., Pouwels, P. J. W., Teipel, S., Yakushev, I., & Fellgiebel, A. (2012) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.23621 · Cited by 34 · see citing works
Stone, 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
Kreilkamp, B. A. K., Lisanti, L., Glenn, G. R., Wieshmann, U. C., Das, K., Marson, A. G., & Keller, S. S. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.102024 · Cited by 27 · see citing works
- Authors
- Wakana, S., Caprihan, A., Panzenboeck, M. M., Fallon, J. H., Perry, M., Gollub, R. L., Hua, K., Zhang, J., Jiang, H., Dubey, P., Blitz, A., van Zijl, P., & Mori, S.
- Affiliations
- Kennedy Krieger Institute (US)
- New Mexico Resonance (US)
- University of California, Irvine (US)
- University of California San Diego (US)
- Massachusetts General Hospital (US)
- Johns Hopkins University (US)
- Corresponding author
- Mori, Susumu
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2007-07
- Volume
- 36
- Issue
- 3
- Pages
- 630-644
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2350213
- OpenAlex
- W2081237186
- Cited by
- 1,686
- References
- 2
- Citations by year
- 2026: 67 · 2025: 86 · 2024: 99 · 2023: 76 · 2022: 91 · 2021: 131 · 2020: 116 · 2019: 107 · 2018: 110 · 2017: 100 · 2016: 91 · 2015: 111 · 2014: 96 · 2013: 115 · 2012: 82
- FWCI
- 32.86
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute on Aging (R01AG020012, R01-AG20012)
- National Institute of Biomedical Imaging and Bioengineering (P41EB015909)
- National Center for Research Resources (P41RR15241, P41RR015241, U24RR021382)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- diffusion tensor imaging, white matter tracts, reproducibility, fractional anisotropy, T2 relaxation time, corticospinal tract, corpus callosum, hemispheric lateralization, interobserver variability
- MeSH terms
- Adult, Brain, Cell Count, Female, Gyrus Cinguli, Hippocampus, Humans, Image Processing, Computer-Assisted, Male, Nerve Fibers, Neural Pathways, Pyramidal Tracts, Reference Values, Thalamus, Reproducibility of Results, Observer Variation, Databases, Factual, Anisotropy, Diffusion Magnetic Resonance Imaging
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