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Cited by 574Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesAdvanced MRI Techniques and Applications

Diffusion MRI fiber tractography of the brain

Open access
Jeurissen, Ben, Descoteaux, Maxime, Mori, Susumu, Leemans, Alexander·2019·NMR in Biomedicine
DOI 10.1002/nbm.3785
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Abstract

The ability of fiber tractography to delineate non-invasively the white matter fiber pathways of the brain raises possibilities for clinical applications and offers enormous potential for neuroscience. In the last decade, fiber tracking has become the method of choice to investigate quantitative MRI parameters in specific bundles of white matter. For neurosurgeons, it is quickly becoming an invaluable tool for the planning of surgery, allowing for visualization and localization of important white matter pathways before and even during surgery. Fiber tracking has also claimed a central role in the field of "connectomics," a technique that builds and studies comprehensive maps of the complex network of connections within the brain, and to which significant resources have been allocated worldwide. Despite its unique abilities and exciting applications, fiber tracking is not without controversy, in particular when it comes to its interpretation. As neuroscientists are eager to study the brain's connectivity, the quantification of tractography-derived "connection strengths" between distant brain regions is becoming increasingly popular. However, this practice is often frowned upon by fiber-tracking experts. In light of this controversy, this paper provides an overview of the key concepts of tractography, the technical considerations at play, and the different types of tractography algorithm, as well as the common misconceptions and mistakes that surround them. We also highlight the ongoing challenges related to fiber tracking. While recent methodological developments have vastly increased the biological accuracy of fiber tractograms, one should be aware that, even with state-of-the-art techniques, many issues that severely bias the resulting structural "connectomes" remain unresolved.

AI snapshot

Written from the paper’s full text.

TL;DR

This review explains diffusion MRI fiber tractography, its technical steps, algorithm families, and common misinterpretations. It argues that tractography is valuable for qualitative white matter delineation but remains severely limited for quantitative connectivity and connectomics, even with state-of-the-art methods.

Key findings

  • DTI-based tractography remains dominant in clinical neurosurgery: roughly 98% of 160 neurosurgical tractography studies reported DTI-based tractography, despite growing consensus that it should be deprecated in favor of higher-order models.
  • Tractography is biased toward short, straight, simple trajectories; long, curving, or complex-fiber tracks are more likely to terminate prematurely, and whole-brain seeding overrepresents long bundles while underrepresenting short ones.
  • In the ISMRM 2015 Tractography Challenge, 96 tractograms from 21 international groups contained on average four false-positive bundles for every valid bundle recovered.
  • Practical resolution limits remain: clinical whole-brain diffusion MRI is limited to at best 2 mm³, angular resolution levels off around b = 3000 s/mm² with as few as 45 unique gradient orientations, and inter-fiber angles below 30° are rarely resolved.

Methods

  • Narrative review of diffusion MRI fiber tractography, covering key concepts, terminology, local fiber orientation estimation, integration, interpolation, seeding, stopping criteria, virtual dissection, and algorithm families.
  • No primary empirical sample is analyzed; the paper synthesizes prior literature and cites examples including 160 neurosurgical tractography studies, the ISMRM 2015 Tractography Challenge, simulation studies, and Human Connectome Project data.
  • Main analysis is conceptual and technical: it compares deterministic vs probabilistic, local vs global, and streamline vs filtering/shortest-path approaches, and discusses common misconceptions about quantification.

Limitations

  • The authors state their focus on challenges and limitations may appear pessimistic, but they intend it as a reflection on intrinsic tractography limitations and inspiration for next-generation algorithms.
  • The paper notes that even advanced higher-order models are simplified approximations whose assumptions may not always hold, and that global methods rely on stochastic optimization without guaranteed convergence to a globally optimal solution.
  • Evident from the text: this is a review, not a systematic meta-analysis or primary validation study; it also focuses on brain white matter tractography, with non-brain fibrous tissues mentioned only briefly.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1002/nbm.3785

Cites

126 of 126 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 84 cited sources checked · 0 supported · 0 flagged

  • Findingnone given

    As we move away from the seed point, errors made by nearest-neighbor interpolation accumulate.

    “Note that, as we move away from the seed point, the errors made by the nearest-neighbor interpolation accumulate”
    Quote in the paperNot a substantial claim
  • Findingown data

    Inspection of tracking endpoints in standard probabilistic fODF tracking reveals numerous biologically implausible terminals.

    “Although all tractograms appear great, inspection of the tracking endpoints reveals numerous biologically implausible terminals (left).”
    Quote in the paperSubstantial claim
  • Interpretationreasoning

    The mapping from diffusion signal to fiber orientations is ill posed because a single white matter voxel can contain hundreds of thousands of fibers and other microstructural tissue constituents.

    “Given that a single white matter voxel can contain hundreds of thousands of fibers, as well as other microstructural tissue constituents, the mapping from diffusion signal to fiber orientations is ill posed.”
    Quote in the paperSubstantial claim
  • Premisecitation

    dMRI can probe white matter fiber orientations only indirectly by looking at the associated average diffusion pattern of the water molecules.

    “in contrast to several imaging techniques such as (polarized-)light microscopy 24 and electron microscopy, 25 where individual fibers can be visualized directly, dMRI can probe white matter fiber orientations only indirectly by looking at the associated average diffusion pattern of the water molecules.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [24]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [25]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Interpretationreasoning

    Different tracking approaches will produce very different tractograms given the same connectome.

    “different tracking approaches will produce very different tractograms given the same connectome”
    Quote in the paperNot a substantial claim
  • May combine two claims. 49
  • Classified as probably not a substantial claim. 18

  • May combine two claims.

    Findingown data

    Filtering the tractogram makes the distribution of endpoints more uniform but does not prevent the many implausible terminals.

    “Filtering the tractogram makes the distribution of endpoints more uniform, but does not prevent the many implausible terminals (middle).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Trajectories in standard probabilistic fODF tracking end prematurely in regions containing complex white matter configurations or at the cerebrospinal fluid interface.

    “In particular, trajectories end prematurely in regions containing complex white matter configurations (green arrows) or at the cerebrospinal fluid interface (cyan arrows).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Fiber tracks or streamlines obtained with fiber tracking are virtual entities that encompass no physical volume and are related only indirectly to the nerve fibers.

    “while the white matter”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Euler integration is a first-order integration method that assumes the orientation v(r_i) is constant at the length scale of step size Δ, making it highly susceptible to overshoots in highly curved regions, especially for larger step sizes.

    “Note that Euler integration is a first-order integration method and assumes that the orientation v(r i ) is constant at the length scale of step size Δ, which will make this method highly susceptible to overshoots in highly curved regions, especially for larger step sizes (see Figure 3).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    There is a growing consensus in the dMRI community that diffusion tensor tractography should be deprecated, but this wisdom has not been fully translated into clinical practice.

    “Although there seems to be a growing consensus in the dMRI community that diffusion tensor tractography should be deprecated, 6,34,37,38 this wisdom does not seem to have been fully translated into clinical practice.”
    Quote in the paperNot a substantial claim0 of 4 sources checked
    • cites [6]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [34]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [37]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [38]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationcitation

    Higher-order numerical integration schemes such as Runge-Kutta integration take into account variations of v between r_i and r_i+1 and are much less susceptible to integration errors than Euler integration.

    “Higherorder numerical integration schemes, such as Runge-Kutta integration, take into account the variations of v between r i and r i + 1 and are much less susceptible to these integration errors.23,39”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [23]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [39]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    Even when using higher-order integration methods, the step-by-step nature of streamline fiber tracking makes it extremely susceptible to error propagation, so small local errors can accumulate and cause tracks to veer off course, jump to unrelated adjacent tracts, or stop prematurely.

    “It should be clear at this point that, even when using higher-order integration methods, the sheer step-by-step nature of such a procedure makes streamline fiber tracking extremely susceptible to error propagation: indeed, even small local errors can accumulate along the way, causing tracks to veer off course and jump to unrelated adjacent tracts or to stop prematurely.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    DTI-based tractography can result in systematically unreliable and clinically misleading information.

    “Recent studies have shown that DTI-based tractography can result in systematically unreliable and clinically misleading information, while higher-order tractography approaches, using the same dMRI data, clearly demonstrate fiber trajectories that are biologically much more plausible.32,36”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [32]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [36]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationnone given

    Even the most advanced higher-order models are still only models, i.e., simplified approximations of the physical reality, and some of the assumptions behind these models might not always hold.

    “It should be noted that even the most advanced higher-order models are still only models, i.e. simplified approximations of the physical reality, and that some of the assumptions behind these models might not always hold.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning

    Even the most advanced tracking algorithms are bound to produce only very crude approximations to the actual connectome.

    “even the most advanced tracking algorithms are bound to produce only very crude approximations to the actual connectome.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    In voxels of complex fiber architecture, the diffusion tensor is often a poor representation of the underlying fiber orientations, causing false negatives or false positives in tracking.

    “In voxels of complex fiber architecture (e.g.crossing fiber populations or partial volume effect between adjacent fiber populations) the diffusion tensor is often a poor representation of the underlying fiber orientations, [28][29][30] causing false negatives, in which tracking can terminate prematurely, 31,32 or false positives, in which tracking can switch to an unrelated adjacent tract.32,33”
    Quote in the paperSubstantial claim0 of 6 sources checked
    • cites [28]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [29]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [30]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [31]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [32]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [33]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    As tracks grow longer, the chance of encountering local tractography errors and the extent of error accumulation increases, making premature termination more likely.

    “Indeed, it is easy to see that, as tracks grow longer, the chance of encountering local tractography errors as well as the extent of error accumulation increases, making it more likely for trajectories to terminate prematurely.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    Using cortical activation maps from functional MRI for ROI definition may suffer from ill-defined fiber orientations present in gray matter regions.

    “While this latter approach is particularly appealing as it allows for correlation analyses between structural and functional connectivity, it may suffer from ill-defined fiber orientations present in gray matter regions.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Probabilistic tractography makes it possible to track through regions of high uncertainty where deterministic techniques would usually stop, but the probability of connection beyond this region is lower.

    “By treating the problem in a probabilistic fashion, it also becomes possible to track through regions of high uncertainty, where deterministic techniques would usually stop, acknowledging, however, that the probability of”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    Combining the two approaches could potentially provide both types of information simultaneously.

    “As previously suggested by Behrens et al., 100 combining the two approaches could potentially provide both types of information simultaneously.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Behrens et al., 100

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Local fiber orientations are subject to noise and model errors, resulting in a distribution of possible fiber orientations known as the uODF.

    “These local fiber orientations are subject to noise and model errors, resulting in a distribution of possible fiber orientations also known as the uODF.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    Virtual dissection relies heavily on prior anatomical knowledge.

    “While this technique is very powerful, it relies heavily on prior anatomical knowledge.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Specification of prior knowledge that is too strong might lead to inconsistencies with the actual data, potentially resulting in non-existent fiber trajectories; specification that is too weak might lead to fiber tracks that perfectly match the underlying data but make little sense anatomically.

    “Specification of prior knowledge that is too strong might lead to inconsistencies with the actual data, potentially resulting in non-existent fiber trajectories.On the other hand, specification of prior knowledge that is too weak might lead to fiber tracks that perfectly match the underlying data, but that make little sense anatomically.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationnone given

    Shortest-path methods construct globally optimal pathways from a given seed point that do not necessarily always align with the locally estimated fiber orientation, but they do not consider pathways from all seed points simultaneously.

    “These methods construct globally optimal pathways from a given seed point, which do not necessarily always align with the locally estimated fiber orientation.However, they do not consider the pathways from all seed points simultaneously, setting them apart from the purely global methods.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Increased architectural complexity increases local fiber orientation uncertainty, resulting in fewer tracks making it from start to finish.

    “It is also easy to see that increased architectural complexity will increase the local fiber orientation uncertainty, resulting in fewer tracks making it from start to finish.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    In streamline tractography, measurement uncertainty can propagate, making these errors especially important.

    “These errors are especially important in the context of streamline tractography, as measurement uncertainty can propagate.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Diffusion from closely aligned fiber orientations is blurred together, implying that only a single fiber population is present.

    “As a consequence, diffusion from closely aligned fiber orientations will be blurred together, implying that only a single fiber population is present.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    TDI can provide maps with high anatomical contrast, and when combined with a super-resolution voxel grid can potentially resolve sub-voxel anatomical details.

    “TDI can provide maps with high anatomical contrast, and when combined with a super-resolution voxel grid can potentially resolve sub-voxel anatomical details. 102”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [101]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [102]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    Seed dependence and non-commutativity are confounding factors for quantification of brain connectivity.

    “Both issues are not only of practical importance when trying to qualitatively reconstruct a particular tract; they are also a confounding factor when it comes to quantification of brain connectivity.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    Probabilistic uODF tracking says nothing about accuracy; even the most reproducible fiber pathways can be highly inaccurate.

    “It should be noted at this point that, while probabilistic uODF tracking gives an indication of the precision of the tracking result, it says nothing about accuracy: even the most reproducible fiber pathways can be highly inaccurate.10”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [10]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationnone given

    Global tracking methods have many solutions, and selecting a suitable one requires prior knowledge about expected properties of the trajectories such as local smoothness.

    “In general, this problem has many solutions and selecting a suitable one requires prior knowledge about the expected properties of the trajectories such as local smoothness.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given

    Convincing results based on combining the two approaches have not been published to date.

    “However, convincing results based on this combination have not been published to date.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Probabilistic tractography algorithms typically build on the deterministic streamline approach and are subject to the same limitations.

    “Typically, probabilistic tractography algorithms build on the deterministic streamline approach described in the previous section, and as such are subject to the same limitations.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given

    Global tracking promises better stability with respect to noise and imaging artifacts and better agreement with the actual dMRI data that was acquired.

    “Global tracking promises a better stability with respect to noise and imaging artifacts and a better agreement with the actual dMRI data that was acquired.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given

    Streamline tractograms are typically a very poor predictor of the dMRI data that was actually measured, resulting in fiber tracks that have little to no quantitative or biological meaning.

    “Another, lesser-known downside is that streamline tractograms are typically a very poor predictor of the dMRI data that was actually measured, resulting in fiber tracks that have little to no quantitative or biological meaning (this issue is further discussed in section 5.4).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationnone given

    ROI definition by the user requires anatomical knowledge and is subject to inter-operator variability.

    “Typically, these ROIs are defined by the user.This task requires anatomical knowledge and is subject to inter-operator variability.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisereasoning

    Whole-brain tracking can be achieved either by seeding from all white matter voxels or by seeding solely from voxels close to the gray matter-white matter interface, because fibers are known to originate from there.

    “Note that whole-brain tracking can be achieved either by seeding from all white matter voxels or by seeding solely from those voxels that are close to the gray matter-white matter interface, as this is where fibers are known to originate from (see Figure 5).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Local tractography methods are fast and widely used but have important drawbacks, the most apparent being that minor errors in local fiber orientations can accumulate and significantly affect the final result.

    “Local methods are fast and used widely but have important drawbacks.The most apparent is probably that minor errors in the local fiber orientations can accumulate and significantly affect the final result.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given

    Shortest-path frameworks are not widely adopted in software packages and their use in practical studies has been limited.

    “While these frameworks are often mathematically elegant, they are not widely adopted in software packages and their use in practical studies has been limited.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Seeding at the gray matter-white matter interface can reduce overrepresentation of long bundles, but it is not guaranteed that these trajectories will cover the whole of the white matter because tracks typically end prematurely due to errors.

    “The overrepresentation of long bundles can be reduced by seeding at the gray matter-white matter interface; however, it is not guaranteed that these trajectories will be able to cover the whole of the white matter, as tracks typically end prematurely due to errors.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given

    There are many misconceptions surrounding fiber tracking, and not recognizing its technological pitfalls can easily lead to big mistakes, particularly in interpretation of fiber-tracking results.

    “There are many misconceptions that surround fiber tracking, and not recognizing its many technological pitfalls can easily lead to big mistakes, in particular when it comes to interpretation of fiber-tracking results.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    The fODF approach can be regarded as providing more biophysically meaningful tractograms because it is driven by anatomical dispersion rather than noise characteristics and model inaccuracies.

    “In a sense, this approach can be regarded as providing more biophysically meaningful tractograms, as it is driven by anatomical dispersion rather than noise characteristics and model inaccuracies.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Introducing anatomical constraints during fiber tracking prevents premature stopping within white matter and evenly covers the white matter-gray matter interface.

    “However, by introducing anatomical constraints during fiber tracking, the resulting fiber trajectories no longer stop prematurely within white matter, but evenly cover the white matter-gray matter interface.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationnone given

    Whole-brain seeding will potentially overrepresent long fibers, resulting in biased connectivity matrices with little biophysical meaning.

    “Also, when studying connection strengths for the entire brain (aka connectomics), whole-brain seeding will potentially overrepresent long fibers, which will result in biased connectivity matrices with little biophysical meaning.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    TDI does not necessarily yield accuracy, and some structures observed in TDI have been shown to be caused by noise rather than anatomy.

    “However, this approach does not necessarily yield accuracy, and some structures observed in TDI have been shown to be caused by noise rather than anatomy.103,104”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [103]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [104]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisereasoning

    Whole-brain seeding procedures cause overrepresentation of long fiber tracks and underrepresentation of short fiber tracks.

    “Finally, and most importantly, the seeding procedures associated with whole-brain tracking are known to cause overrepresentation of long fiber tracks and underrepresentation of short fiber tracks.45,105”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [45]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [105]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    It is possible to test whether local geometries are supported by the local neighborhood and use this information to make better-informed decisions during fiber tracking.

    “While there is no information in the voxel-wise data to disambiguate these local geometries, it is possible to test whether they are supported by the local neighborhood and use this information to make better-informed decisions during fiber tracking.26”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [26]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    Fiber-tracking algorithms have a hard time penetrating into the gyri, and if they do they tend to propagate more often towards the crowns of the gyri than towards the gyral walls.

    “More specifically, fiber-tracking algorithms have a hard time penetrating into the gyri, and if they do manage they tend to propagate more often towards the crowns of the gyri than towards the gyral walls.88”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [88]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    The fODF approach is in theory closer to an actual measure for quantification, but in practice the same limitations that plagued local track counts come into play.

    “When adopting the fODF approach, at least in theory, we are closer to an actual measure for quantification; however, in practice we still have to curb our enthusiasm, as pretty much exactly the same limitations that plagued local track counts come into play.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    This requirement can be met by using a global tracking approach or by applying filtering approaches that remove or weight fiber tracks to fit the measured dMRI signal.

    “This requirement can be met either by using a global tracking approach, 71,73 which satisfies this requirement by its very definition, or by applying filtering approaches that will remove or weight fiber tracks, such that the sum of their contributions fits the measured dMRI signal best.45,[74][75][76][77]”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [71]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [73]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [45]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationcitation

    Artificial bundles approximate true anatomical structures very well: they connect cortical areas and appear dense and well structured.

    “What is alarming is that these artificial bundles approximate true anatomical structures very well: they connect cortical areas and appear to be dense and well structured.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    TDI is very sensitive to noise, accumulation of noise-induced errors, and model imperfections.

    “First, as TDI is based on fiber tracking, it is very sensitive to noise, the accumulation of noise-induced errors, and model imperfections.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning

    In fanning fiber configurations, one should take into account the polarity of the fanning.

    “Matters become even more complicated in the case of fanning fiber configurations, as one should also take into account the polarity of the fanning.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Premisenone given

    Techniques that disambiguate local fiber geometries do not seem to have found their way into popular fiber-tracking software yet and remain inaccessible to most researchers.

    “In general, techniques that disambiguate local fiber geometries do not seem to have found their way into popular fiber-tracking software yet and remain inaccessible to most researchers.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    In theory, global tractography methods should be able to resolve local ambiguities by their very definition, especially when combined with microstructural continuity priors.

    “In theory, global tractography methods should already be able to resolve these local ambiguities by their very definition, as they search for the set of continuous trajectories that best explain the full dMRI data, in particular when they are combined with microstructural continuity priors.113”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [113]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning

    Each local fiber geometry may require different decisions during track propagation, and failing to distinguish between these cases could adversely affect fiber-tracking outcomes.

    “However, each of these geometries may require different decisions to be taken during track propagation, and failing to distinguish between these cases could adversely affect fiber-tracking outcomes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    High-order local fiber models can provide high-quality fiber orientation estimates in pure white matter voxels, but in voxels partially containing grey matter they may no longer be appropriate and are known to produce unreliable, noisy estimates.

    “While most high-order local fiber models can provide high-quality fiber orientation estimates in voxels containing pure white matter, in voxels partially containing grey matter tissue these models may no longer be appropriate and are known to produce unreliable, noisy fiber orientation estimates.47”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [47]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationreasoning

    Fiber tracking is a complicated endeavor involving many steps, each incurring potential errors.

    “It should be clear that fiber tracking is a complicated endeavor involving many steps (local fiber orientation modeling, interpolation, integration/ propagation, seeding, masking, stopping criteria, etc.), each incurring potential errors.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Angular black hole effects can veer a track off course and create completely artificial fiber trajectories.

    “Such effects can potentially veer a track off course and create completely artificial fiber trajectories.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    By using a proper high-order model, applying realistic anatomical priors, and ensuring fidelity of the tractograms to the data, the biological accuracy of connectomes can be vastly increased and useful connectivity information can potentially be derived.

    “By using a proper high-order model, by applying realistic anatomical priors, and by ensuring fidelity of the tractograms to the data, the biological accuracy can be vastly increased and one could potentially start to derive useful connectivity information.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationreasoning

    Without a proper high-order model, without anatomical constraints, and without enforcing fidelity of the fiber tracks to the raw dMRI data, quantifying connections using fiber tracking yields connectomes riddled with false positives and false negatives, and connection strengths severely biased by the size, shape, and complexity of the underlying fiber bundle configuration, making the biological准确性

    “Without a proper high-order model, without anatomical constraints, and without enforcing fidelity of the fiber tracks to the raw dMRI data, quantifying connections using fiber tracking is the equivalent of opening Pandora's box: the resulting”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Experimental evidence suggests that the angular frequency content of the dMRI signal in brain white matter levels off at a b-value of approximately 3000 s/mm^2, suggesting this b-value achieves the highest practically available angular resolution.

    “Experimental evidence suggests that the angular frequency content of the dMRI signal in the brain white matter levels off at a b-value of approximately b = 3000 s/mm 2 , suggesting that this b-value achieves the highest practically available angular resolution.122”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [122]

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    Increasing spatial resolution typically goes hand in hand with either a significant drop in SNR or a significant increase in acquisition time.

    “Increasing spatial resolution is challenging, as it typically goes hand in hand with either a significant drop in SNR or a significant increase in acquisition time, resulting in either poor-quality data or impractically long scan times.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Even with state-of-the-art high-angular-resolution diffusion imaging and cutting-edge fiber orientation estimation, inter-fiber angles below 30° are rarely resolved and are a potential source of inaccurate and/or artifactual fiber trajectories.

    “As a consequence, even with state-of-the-art high-angularresolution diffusion imaging and cutting-edge fiber orientation estimation techniques, inter-fiber angles below 30° are rarely resolved, and are a potential source of inaccurate and/or completely artifactual fiber trajectories.”
    Quote in the paperSubstantial claim
59 of 59

  • The authors state this as an assumption.

    When a number of nerve fibers align along a common orientation, the diffusion of water molecules is hindered to a greater extent across this orientation than along it.

    “These models all rely on one fundamental assumption: when a number of nerve fibers align themselves along a common orientation, the diffusion of water molecules will be hindered to a greater extent across this orientation than along it.3”

  • The authors state this as an assumption.

    Connection strength directly relates to the proportion of white matter fibers connecting different regions, with regions connected by a larger proportion of fibers deemed more strongly connected.

    “While there are many possible definitions of connection strength, one typically assumes that it directly relates to the proportion of white matter fibers connecting different regions, with regions that are connected by a larger proportion of fibers deemed to be more strongly connected.”

  • The authors state this as an assumption.

    Fiber densities and/or axon diameters remain consistent along their trajectory.

    “For example, by assuming that fiber densities and/or axon diameters remain consistent along their trajectory, one can potentially disambiguate e.g.crossing and kissing fibers (assuming that each of the interacting fiber bundles exhibits a significantly distinct microstructural signature).”

  • The authors state this as an assumption.

    Each of the interacting fiber bundles exhibits a significantly distinct microstructural signature.

    “For example, by assuming that fiber densities and/or axon diameters remain consistent along their trajectory, one can potentially disambiguate e.g.crossing and kissing fibers (assuming that each of the interacting fiber bundles exhibits a significantly distinct microstructural signature).”

  • The paper relies on this without support.

    Water molecules are most likely to diffuse along the fiber orientation, but diffusion along other, even perpendicular, orientations is still common.

    “Although water molecules are most likely to diffuse along the fiber orientation, diffusion along other, even perpendicular, orientations is still common.”
5 of 5

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?

  • Seeding only from gray matter avoids known tract-length connectivity biases.

    “For the data used in this study, we took the approach of seeding only from the gray matter to avoid known tract-length connectivity biases (Girard et al., 2014; Jeurissen et al., 2019), and normalized the streamline counts by the volumes of each node-pair in order to better match the normalized connection density metric used in the Knox et al. model.”

    From The role of spatial embedding in mouse brain networks constructed from diffusion tractography and tracer injections (2021) · cites this paper as Jeurissen et al., 2019

    Section 3.4 says seeding at the gray matter–white matter interface can reduce the overrepresentation of long bundles caused by seeding throughout white matter. It does not say that seeding only from gray matter eliminates tract-length connectivity bias; it also warns that gray-matter regions may have ill-defined fiber orientations. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Because tractography, network analysis, and NODDI each have limitations, caution is required when interpreting NODDI connectomics data.

    “Tractography and network analysis both have their own limitations (Jeurissen et al., 2019;Sotiropoulos and Zalesky, 2019), which, in combination with the limitations of NODDI, means that caution is required when interpreting the data.”

    From NODDI in clinical research (2020) · cites this paper as Jeurissen et al., 2019

  • Reconstructed streamlines are only simulated entities and do not correspond directly to nerve fibers.

    “The reconstructed streamlines are only simulated entities that do not correspond directly to nerve fibers (Jeurissen et al., 2019; Yeh et al., 2020)”

    From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Jeurissen et al., 2019

Cites

Flagged first, then by citations

Research works printed but not linked: 6

  1. Dell'Acqua F, Reconstructing fiber orientations with diffusion MRI, NMR Biomed
  2. Bells S, 2011, Tractometry—comprehensive multi‐modal quantitative assessment of white matter along specific tracts, Proc Int Soc Magn Reson Med, 19, 678
  3. Basser PJ, 1998, Fiber‐tractography via diffusion tensor MRI (DT‐MRI), Proc Int Soc Magn Reson Med, 6, 1226
  4. 10.1016/j.neuroimage.2008.05.002 · DOI
  5. Farquharson S, 2013, Beyond Diffusion Tensor Imaging Response
  6. Holdsworth SJ, Pulse sequences and hardware considerations for brain diffusion MRI, NMR Biomed

Cited by

Sorted by citations

Related

Authors
Jeurissen, B., Descoteaux, M., Mori, S., & Leemans, A.
Affiliations
  • University of Antwerp (BE)
  • Université de Sherbrooke (CA)
  • Kennedy Krieger Institute (US)
  • Utrecht University (NL)
Corresponding author
Jeurissen, Ben
ORCID
Venue
NMR in Biomedicine
Publisher
Wiley
Published
2017-09-25
Volume
32
Issue
4
Pages
e3785-e3785
ISSN
  • 0952-3480 (ISSN-L)
  • 1099-1492
DOI
10.1002/nbm.3785
OpenAlex
W2758113150
Semantic Scholar
dba9b3e437792c297753d84a35092ea06ac599ea
Cited by
574
References
119
Citations by year
2026: 63 · 2025: 84 · 2024: 72 · 2023: 70 · 2022: 75 · 2021: 78 · 2020: 64 · 2019: 42 · 2018: 24 · 2017: 2
FWCI
25.00
Type
journal article
Language
en
Open access
Licence
Locations
  • NMR in Biomedicine (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • Utrecht University Repository (Utrecht University) (submittedVersion)
Funders
  • Fonds Wetenschappelijk Onderzoek (12M3116N)
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VIDI Grant 639.072.411)
  • Natural Sciences and Engineering Research Council of Canada (Discovery Grant)
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 MRI, fiber tractography, connectomics, structural connectome, neurosurgical planning, structural bias
MeSH terms
Algorithms, Brain, Humans, Image Processing, Computer-Assisted, Terminology as Topic, Diffusion Tensor Imaging, Connectome

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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-18.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-18.

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.

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