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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.
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“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
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“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
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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 ›
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