Deterministic diffusion fiber tracking improved by quantitative anisotropy
Open accessAbstract
Diffusion MRI tractography has emerged as a useful and popular tool for mapping connections between brain regions. In this study, we examined the performance of quantitative anisotropy (QA) in facilitating deterministic fiber tracking. Two phantom studies were conducted. The first phantom study examined the susceptibility of fractional anisotropy (FA), generalized factional anisotropy (GFA), and QA to various partial volume effects. The second phantom study examined the spatial resolution of the FA-aided, GFA-aided, and QA-aided tractographies. An in vivo study was conducted to track the arcuate fasciculus, and two neurosurgeons blind to the acquisition and analysis settings were invited to identify false tracks. The performance of QA in assisting fiber tracking was compared with FA, GFA, and anatomical information from T1-weighted images. Our first phantom study showed that QA is less sensitive to the partial volume effects of crossing fibers and free water, suggesting that it is a robust index. The second phantom study showed that the QA-aided tractography has better resolution than the FA-aided and GFA-aided tractography. Our in vivo study further showed that the QA-aided tractography outperforms the FA-aided, GFA-aided, and anatomy-aided tractographies. In the shell scheme (HARDI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 30.7%, 32.6%, and 24.45% of the false tracks, respectively, while the QA-aided tractography has 16.2%. In the grid scheme (DSI), the FA-aided, GFA-aided, and anatomy-aided tractographies have 12.3%, 9.0%, and 10.93% of the false tracks, respectively, while the QA-aided tractography has 4.43%. The QA-aided deterministic fiber tracking may assist fiber tracking studies and facilitate the advancement of human connectomics.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
The deterministic fiber tracking algorithm used has been shown to accomplish 92% valid connections over an average of 54% of other algorithms.
“We used a deterministic fiber tracking algorithm (Yeh et al., 2013), which has been shown to accomplish 92% valid connections over an average of 54% of other algorithms (Maier-Hein et al., 2017).”
From Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference (2023) · cites this paper as Yeh et al., 2013
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173 · see citing works
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 · see citing works
Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging
Mori, S., Crain, B. J., Chacko, V. P., & van Zijl, P. C. M. (1999) · Annals of Neurology · doi:10.1002/1531-8249(199902)45:2 · Cited by 3,479 · see citing works
Predicting human resting-state functional connectivity from structural connectivity
Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meuli, R., & Hagmann, P. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811168106 · Cited by 3,307 · see citing works
The Human Connectome: A Structural Description of the Human Brain
Sporns, O., Tononi, G., & Kötter, R. (2005) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0010042 · Cited by 3,260 · see citing works
Tournier, J., Calamante, F., & Connelly, A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.02.016 · Cited by 2,191 · see citing works
Tuch, D. S. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20279 · Cited by 1,880 · see citing works
High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity
Tuch, D. S., Reese, T. G., Wiegell, M. R., Makris, N., Belliveau, J. W., & Wedeen, V. J. (2002) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10268 · Cited by 1,548 · cited 10× · see citing works
“The diffusion sampling schemes included the HARDI-253 (shell scheme) and DSI-203 (grid scheme) schemes that were previously documented in an optimization study [35].”
BackgroundInfluentialMapping complex tissue architecture with diffusion spectrum magnetic resonance imaging
Wedeen, V. J., Hagmann, P., Tseng, W. I., Reese, T. G., & Weisskoff, R. M. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20642 · Cited by 1,339 · see citing works
Self-citationSmith, R. E., Tournier, J.-D., Calamante, F., & Connelly, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.005 · Cited by 1,216 · see citing works
Free water elimination and mapping from diffusion MRI
Pasternak, O., Sochen, N., Gur, Y., Intrator, N., & Assaf, Y. (2009) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22055 · Cited by 1,092 · see citing works
Generalized ${ q}$-Sampling Imaging
Yeh, F.-C. F., Wedeen, V. J., & Tseng, W. I. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2010.2045126 · Cited by 1,030 · see citing works
Self-citationDiffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers
Wedeen, V. J., Wang, R., Schmahmann, J. D., Benner, T., Tseng, W. I., Dai, G., Pandya, D. Ν., Hagmann, P., D'Arceuil, H. E., & de Crespigny, A. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.036 · Cited by 941 · see citing works
Self-citationRegularized, fast, and robust analytical Q-ball imaging
Descoteaux, M., Angelino, E., Fitzgibbons, S., & Deriche, R. (2007) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21277 · Cited by 850 · see citing works
Mapping Human Whole-Brain Structural Networks with Diffusion MRI
Hagmann, P., Kurant, M., Gigandet, X., Thiran, P., Wedeen, V. J., Meuli, R., & Thiran, J.-P. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000597 · Cited by 788 · see citing works
White matter maturation reshapes structural connectivity in the late developing human brain
Hagmann, P., Sporns, O., Madan, N., Cammoun, L., Pienaar, R., Wedeen, V. J., Meuli, R., Thiran, J.-P., & Grant, P. E. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1009073107 · Cited by 700 · see citing works
Deterministic and probabilistic tractography based on complex fibre orientation distributions
Descoteaux, M., Deriche, R., Knosche, T. R., & Anwander, A. (2009) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.2004424 · Cited by 698 · see citing works
Analysis of partial volume effects in diffusion‐tensor MRI
Alexander, A. L., Hasan, K. M., Lazar, M., Tsuruda, J. S., & Parker, D. L. (2001) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1105 · Cited by 695 · see citing works
Tractography: Where Do We Go from Here?
Jbabdi, S., & Johansen-Berg, H. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0033 · Cited by 614 · see citing works
The Geometric Structure of the Brain Fiber Pathways
Wedeen, V. J., Rosene, D. L., Wang, R., Dai, G., Mortazavi, F., Hagmann, P., Kaas, J. H., & Tseng, W.-Y. I. (2012) · Science · doi:10.1126/science.1215280 · Cited by 445 · see citing works
Self-citationQuantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom
Fillard, P., Descoteaux, M., Goh, A., Gouttard, S., Jeurissen, B., Malcolm, J., Ramirez-Manzanares, A., Reisert, M., Sakaie, K., Tensaouti, F., et al. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.032 · Cited by 418 · see citing works
Ciccarelli, O., Catani, M., Johansen‐Berg, H., Clark, C. A., & Thompson, A. J. (2008) · The Lancet Neurology · doi:10.1016/s1474-4422(08)70163-7 · Cited by 408 · see citing works
How and how not to correct for CSF-contamination in diffusion MRI
Metzler-Baddeley, C., O'Sullivan, M. J., Bells, S., Pasternak, O., & Jones, D. K. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.043 · Cited by 291 · see citing works
MR connectomics: Principles and challenges
Hagmann, P., Cammoun, L., Gigandet, X., Gerhard, S., Grant, P. E., Wedeen, V. J., Meuli, R. A., Thiran, J., Honey, C. J., & Sporns, O. (2010) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2010.01.014 · Cited by 271 · see citing works
Oouchi, H., Yamada, K., Sakai, K., Kizu, O., Kubota, T., Ito, H., & Nishimura, T. (2007) · American Journal of Neuroradiology · doi:10.3174/ajnr.a0488 · Cited by 256 · see citing works
High-Definition Fiber Tractography of the Human Brain
Fernandez-Miranda, J. C., Pathak, S., Engh, J. A., Jarbo, K., Verstynen, T., Yeh, F.-C. F., Wang, Y., Mintz, A. H., Boada, F. E., Schneider, W., et al. (2012) · Neurosurgery · doi:10.1227/neu.0b013e3182592faa · Cited by 237 · see citing works
Self-citationDauguet, J., Peled, S., Berezovskii, V., Delzescaux, T., Warfield, S. K., Born, R., & Westin, C.-F. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.067 · Cited by 233 · 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
Toga, A. W., Clark, K. A., Thompson, P. M., Shattuck, D. W., & Horn, J. D. V. (2012) · Neurosurgery · doi:10.1227/neu.0b013e318258e9ff · Cited by 181 · see citing works
Optimization of diffusion spectrum imaging and q-ball imaging on clinical MRI system
Kuo, L., Chen, J., Wedeen, V. J., & Tseng, W. I. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.02.016 · Cited by 156 · see citing works
Self-citationRethinking the Role of the Middle Longitudinal Fascicle in Language and Auditory Pathways
Wang, Y., Fernandez-Miranda, J. C., Verstynen, T., Pathak, S., Schneider, W., & Yeh, F.-C. F. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs225 · Cited by 139 · see citing works
Self-citationLo, Y., Soong, W., Gau, S. S., Wu, Y.-Y., Lai, M., Yeh, F.-C. F., Chiang, W.-Y., Kuo, L., Jaw, F.-S., & Tseng, W. I. (2011) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2010.09.008 · Cited by 120 · see citing works
Self-citationIn vivo quantification of global connectivity in the human corpus callosum
Jarbo, K., Verstynen, T., & Schneider, W. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.056 · Cited by 95 · see citing works
Self-citationA review of diffusion tensor magnetic resonance imaging computational methods and software tools
Hasan, K. M., Walimuni, I. S., Abid, H., & Hahn, K. R. (2010) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2010.10.008 · Cited by 89 · see citing works
Fritzsche, K. H., Laun, F. B., Meinzer, H.-P., & Stieltjes, B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.007 · Cited by 78 · see citing works
In Vivo Mapping of Microstructural Somatotopies in the Human Corticospinal Pathways
Verstynen, T., Jarbo, K., Pathak, S., & Schneider, W. (2010) · Journal of Neurophysiology · doi:10.1152/jn.00698.2010 · Cited by 72 · see citing works
Self-citationEffect of head size on diffusion tensor imaging
Takao, H., Hayashi, N., Inano, S., & Ohtomo, K. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.019 · Cited by 55 · see citing works
Tang, P., Ko, Y.-T., Luo, Z.-A., Yeh, F.-C. F., Chen, S. A., & Tseng, W. I. (2010) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1981 · Cited by 44 · see citing works
Self-citationQuantitative and reproducibility study of four tractography algorithms used in clinical routine
Tensaouti, F., Lahlou, I., Clarisse, P., Lotterie, J. A., & Berry, I. (2011) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.22584 · Cited by 36 · see citing works
Investigation of resolution effects using a specialized diffusion tensor phantom
Bach, M., Fritzsche, K. H., Stieltjes, B., & Laun, F. B. (2014) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24774 · Cited by 32 · see citing works
Kim, Y. B., Kalthoff, D., Po, C., et al. (2012) · NMR in Biomedicine · doi:10.1002/nbm.1815 · Cited by 20 · see citing works
The human connectome: just another 'ome?
Williams, R. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(10)70046-6 · Cited by 17 · see citing works
Basser (2000) · doi:10.1002/1522-2594(200010)44:4
Flagged first, then by citations
Research works printed but not linked: 1
- [21]Girard G, Descoteaux M. Online Filtering Tractography: Tracking with anatomical priors; 2013; Proceedings 21th Scientific Meeting. Salt Lake City, USA: International Society for Magnetic Resonance in Medicine.
Cited by
Sorted by citations
The connectomics of brain disorders
Fornito, A., Zalesky, A., & Breakspear, M. (2015) · Nature Reviews Neuroscience · doi:10.1038/nrn3901 · Cited by 1,734 · see citing works
A gut-derived metabolite alters brain activity and anxiety behaviour in mice
Needham, B. D., Funabashi, M., Adame, M. D., Wang, Z., Boktor, J. C., Haney, J., Wu, W.-L., Rabut, C., Ladinsky, M. S., Hwang, S.-J., et al. (2022) · Nature · doi:10.1038/s41586-022-04396-8 · Cited by 489 · see citing works
Baum, G. L., Ciric, R., Roalf, D. R., Betzel, R. F., Moore, T. M., Shinohara, R. T., Kahn, A. E., Vandekar, S. N., Rupert, P. E., Quarmley, M., et al. (2017) · Current Biology · doi:10.1016/j.cub.2017.04.051 · Cited by 401 · see citing works
A Synergistic Core for Human Brain Evolution and Cognition
Luppi, A. I., Mediano, P. A. M., Rosas, F. E., Holland, N., Fryer, T. D., O’Brien, J. T., Rowe, J. B., Menon, D. K., Bor, D., & Stamatakis, E. A. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01070-0 · Cited by 314 · 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
Structural disconnections explain brain network dysfunction after stroke
Griffis, J. C., Metcalf, N. V., Corbetta, M., & Shulman, G. L. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.07.100 · Cited by 213 · see citing works
Yeh, F.-C., Vettel, J. M., Singh, A., Poczos, B., Grafton, S. T., Erickson, K. I., Tseng, W.-Y. I., & Verstynen, T. D. (2016) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005203 · Cited by 151 · see citing works
Self-citationThe impact of in-scanner head motion on structural connectivity derived from diffusion MRI
Baum, G. L., Roalf, D. R., Cook, P. A., Ciric, R., Rosen, A. F. G., Xia, C., Elliott, M. A., Ruparel, K., Verma, R., Tunç, B., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.02.041 · Cited by 116 · see citing works
Yang, R., Walder-Christensen, K. K., Kim, N., Wu, D., Lorenzo, D. N., Badea, A., Jiang, Y.-H., Yin, H. H., Wetsel, W. C., & Bennett, V. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1904348116 · Cited by 99 · see citing works
Damage to white matter bottlenecks contributes to language impairments after left hemispheric stroke
Griffis, J. C., Nenert, R., Allendorfer, J. B., & Szaflarski, J. P. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.02.019 · Cited by 87 · see citing works
Neurite orientation dispersion and density imaging of mouse brain microstructure
Wang, N., Zhang, J., Cofer, G., Qi, Y., Anderson, R. J., White, L. E., & Allan Johnson, G. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01877-x · Cited by 69 · see citing works
Humphreys, K. L., Camacho, M. C., Roth, M. C., & Estes, E. C. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100877 · Cited by 67 · see citing works
Adewale, Q., Khan, A. F., Carbonell, F., Iturria-Medina, Y., & Initiative, A. D. N. (2021) · eLife · doi:10.7554/elife.62589 · Cited by 44 · see citing works
Wang, D., Luo, Y., Mok, V. C. T., Chu, W. C. W., & Shi, L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.032 · Cited by 33 · see citing works
Wang, X., Cuzon Carlson, V. C., Studholme, C., Newman, N., Ford, M. M., Grant, K. A., & Kroenke, C. D. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1919048117 · Cited by 31 · see citing works
Diffusion tractography of the rat knee at microscopic resolution
Wang, N., Mirando, A. J., Cofer, G., Qi, Y., Hilton, M. J., & Johnson, G. A. (2019) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27652 · Cited by 30 · see citing works
Khan, A. F., Adewale, Q., Lin, S.-J., Baumeister, T. R., Zeighami, Y., Carbonell, F., Palomero-Gallagher, N., & Iturria-Medina, Y. (2023) · Nature Communications · doi:10.1038/s41467-023-41677-w · Cited by 28 · see citing works
Chien, Y.-L., Lin, H.-Y., Tung, Y.-H., Hwang, T.-J., Chen, C.-L., Wu, C.-S., Shang, C.-Y., Hwu, H.-G., Tseng, W.-Y. I., Liu, C.-M., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01636-1 · Cited by 24 · see citing works
Self-citationLuo, Q., Zhang, L., Huang, C.-C., Zheng, Y., Kanen, J. W., Zhao, Q., Yao, Y., Quinlan, E. B., Jia, T., Banaschewski, T., et al. (2020) · BMC Medicine · doi:10.1186/s12916-020-01743-2 · Cited by 26 · see citing works
Ni, H.-C., Lin, H.-Y., Tseng, W.-Y. I., & Gau, S. S.-F. (2020) · Scientific Reports · doi:10.1038/s41598-020-70836-y · Cited by 13 · see citing works
Self-citationHan, X., Maharjan, S., Chen, J., Zhao, Y., Qi, Y., White, L. E., Johnson, G. A., & Wang, N. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120734 · Cited by 15 · see citing works
Gonzalez-Gomez, R., Ibañez, A., & Moguilner, S. (2023) · Network Neuroscience · doi:10.1162/netn_a_00285 · Cited by 10 · see citing works
- Authors
- Yeh, F.-C., Verstynen, T. D., Wang, Y., Fernández-Miranda, J. C., & Tseng, W.-Y. I.
- Affiliations
- Carnegie Mellon University (US)
- University of Pittsburgh (US)
- National Taiwan University (TW)
- Corresponding author
- Tseng, Wen-Yih Isaac
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-11-15
- Volume
- 8
- Issue
- 11
- Pages
- e80713
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3858183
- OpenAlex
- W1999890357
- Cited by
- 1,121
- References
- 43
- Citations by year
- 2026: 106 · 2025: 121 · 2024: 116 · 2023: 104 · 2022: 132 · 2021: 132 · 2020: 98 · 2019: 84 · 2018: 79 · 2017: 60 · 2016: 44 · 2015: 31 · 2014: 14
- FWCI
- 22.98
- Type
- journal article
- Language
- en
- Update notices
- correction (2014-01-02)
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- D-Scholarship@Pitt (University of Pittsburgh) (acceptedVersion)
- KiltHub Repository (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- KiltHub Repository (cc-by)
- Funders
- National Science Council (NSC100-2321-B-002-015, NSC 100, NSC100-3112-B-002-016)
- National Institutes of Health
- National Institute of Mental Health (U01MH093765)
- 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
- quantitative anisotropy, deterministic fiber tracking, diffusion MRI tractography, fractional anisotropy, generalized fractional anisotropy, partial volume effect, crossing fibers, spatial resolution, arcuate fasciculus, high angular resolution diffusion imaging, diffusion spectrum imaging
- MeSH terms
- Adult, Brain Mapping, Humans, Magnetic Resonance Imaging, Neural Pathways, Anisotropy, Diffusion Tensor 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
