The DOI matches its Crossref record; 292 of the 292 references it cites were found in a registry or an index.
Diffusion MRI tractography for neurosurgery: the basics, current state, technical reliability and challenges
Open accessAbstract
Diffusion magnetic resonance imaging (dMRI) tractography is currently the only imaging technique that allows for non-invasive delineation and visualisation of white matter (WM) tracts in vivo, prompting rapid advances in related fields of brain MRI research in recent years. One of its major clinical applications is for pre-surgical planning and intraoperative image guidance in neurosurgery, where knowledge about the location of WM tracts nearby the surgical target can be helpful to guide surgical resection and optimise post-surgical outcomes. Surgical injuries to these WM tracts can lead to permanent neurological and functional deficits, making the accuracy of tractography reconstructions paramount. The quality of dMRI tractography is influenced by many modifiable factors, ranging from MRI data acquisition through to the post-processing of tractography output, with the potential of error propagation based on decisions made at each and subsequent processing steps. Research over the last 25 years has significantly improved the anatomical accuracy of tractography. An updated review about tractography methodology in the context of neurosurgery is now timely given the thriving research activities in dMRI, to ensure more appropriate applications in the clinical neurosurgical realm. This article aims to review the dMRI physics, and tractography methodologies, highlighting recent advances to provide the key concepts of tractography-informed neurosurgery, with a focus on the general considerations, the current state of practice, technical challenges, potential advances, and future demands to this field.
Overview
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
Verification
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 source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Tractography is increasingly used to estimate the relationship between tumors and eloquent pathways before surgery (Kamagata et al., 2024; Yang et al., 2021), but infiltration, edema, mass effect, crossing fibers, reduced anisotropy, algorithmic choices, and intraoperative brain shift may generate false-positive or false-negative reconstructions.”
From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Yang et al., 2021
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“It has reoriented neurosurgical planning (Yang et al., 2021), enabled in vivo studies of language and motor pathways, and provided a framework for rethinking neurological and psychiatric disorders as disorders of networks (Berkovitch et al., 2021).”
From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Yang et al., 2021
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
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
MR diffusion tensor spectroscopy and imaging
Basser, P. J., Mattiello, J., & LeBihan, D. (1994) · Biophysical Journal · doi:10.1016/s0006-3495(94)80775-1 · Cited by 5,970
The minimal preprocessing pipelines for the Human Connectome Project
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.127 · Cited by 5,253
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
PENFIELD, W., & BOLDREY, E. (1937) · Brain · doi:10.1093/brain/60.4.389 · Cited by 4,188
Bloch, F. (1946) · Physical Review · doi:10.1103/physrev.70.460 · Cited by 4,041
Le Bihan, D., Breton, E., Lallemand, D., Grenier, P., Cabanis, E., & Laval-Jeantet, M. (1986) · Radiology · doi:10.1148/radiology.161.2.3763909 · Cited by 3,912
Research works printed but not linked: 2
- Dhollander, 2016, A novel iterative approach to reap the benefits of multi-tissue CSD from just single-shell (+b = 0) diffusion MRI data, Proc. Int. Soc. Mag. Reson. Med., 24, 3010
- Maier-Hein, 2017, The challenge of mapping the human connectome based on diffusion tractography, Nat. Commun., 8, 1349, 10.1038/s41467-017-01285-x · DOI
Cited by
Sorted by citations
Schilling, K. G., Rheault, F., Petit, L., Hansen, C. B., Nath, V., Yeh, F.-C., Girard, G., Barakovic, M., Rafael-Patino, J., Yu, T., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118502 · Cited by 182
Self-citationAdvancements in diffusion MRI tractography for neurosurgery
Kamagata, K., Andica, C., Uchida, W., Takabayashi, K., Saito, Y., Lukies, M., Hagiwara, A., Fujita, S., Akashi, T., Wada, A., et al. (2024) · Investigative Radiology · doi:10.1097/rli.0000000000001015 · Cited by 50
Feltrin, F. S., Chopra, R., Pouratian, N., Elkurd, M. T., El‐Nazer, R., Lanford, L., Dauer, W. T., & Shah, B. (2022) · Brain Communications · doi:10.1093/braincomms/fcac273 · Cited by 46
Diffusion MRI with machine learning
Karimi, D., & Warfield, S. K. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00353 · Cited by 23
Research Progress in Diffusion Spectrum Imaging
Sun, F., Huang, Y., Wang, J., Hong, W., & Zhao, Z. (2023) · Brain Sciences · doi:10.3390/brainsci13101497 · Cited by 20
Metadata
- Authors
- Yang, J. Y.-M., Yeh, C.-H., Poupon, C., & Calamante, F.
- Affiliations
- Royal Children's Hospital (AU)
- Chang Gung University (TW)
- Centre National de la Recherche Scientifique (FR)
- The University of Sydney (AU)
- Corresponding author
- Yeh, Chun-Hung
- Venue
- Physics in Medicine & Biology
- Publisher
- IOP Publishing
- Published
- 2021-07-22
- Volume
- 66
- Issue
- 15
- Pages
- 15TR01
- ISSN
- 0031-9155 (ISSN-L)
- 1361-6560
- OpenAlex
- W3173443563
- Cited by
- 80
- References
- 292
- Citations by year
- 2026: 16 · 2025: 25 · 2024: 14 · 2023: 15 · 2022: 8 · 2021: 2
- FWCI
- 1.59
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Physics in Medicine and Biology (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Funders
- Taiwan Ministry of Science and Technology (109-2222-E-182-001-MY3)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Physical Sciences › Engineering › Biomedical Engineering › Anatomy and Medical Technology
- Keywords
- diffusion MRI, tractography, white matter tracts, neurosurgery, surgical planning, intraoperative image guidance, error propagation, surgical resection
- MeSH terms
- Magnetic Resonance Imaging, Neurosurgery, Reproducibility of Results, Diffusion Magnetic Resonance Imaging, 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