Literature DB >> 23540269

White matter fiber tractography: why we need to move beyond DTI.

Shawna Farquharson1, J-Donald Tournier, Fernando Calamante, Gavin Fabinyi, Michal Schneider-Kolsky, Graeme D Jackson, Alan Connelly.   

Abstract

OBJECT: Diffusion-based MRI tractography is an imaging tool increasingly used in neurosurgical procedures to generate 3D maps of white matter pathways as an aid to identifying safe margins of resection. The majority of white matter fiber tractography software packages currently available to clinicians rely on a fundamentally flawed framework to generate fiber orientations from diffusion-weighted data, namely diffusion tensor imaging (DTI). This work provides the first extensive and systematic exploration of the practical limitations of DTI-based tractography and investigates whether the higher-order tractography model constrained spherical deconvolution provides a reasonable solution to these problems within a clinically feasible timeframe.
METHODS: Comparison of tractography methodologies in visualizing the corticospinal tracts was made using the diffusion-weighted data sets from 45 healthy controls and 10 patients undergoing presurgical imaging assessment. Tensor-based and constrained spherical deconvolution-based tractography methodologies were applied to both patients and controls.
RESULTS: Diffusion tensor imaging-based tractography methods (using both deterministic and probabilistic tractography algorithms) substantially underestimated the extent of tracks connecting to the sensorimotor cortex in all participants in the control group. In contrast, the constrained spherical deconvolution tractography method consistently produced the biologically expected fan-shaped configuration of tracks. In the clinical cases, in which tractography was performed to visualize the corticospinal pathways in patients with concomitant risk of neurological deficit following neurosurgical resection, the constrained spherical deconvolution-based and tensor-based tractography methodologies indicated very different apparent safe margins of resection; the constrained spherical deconvolution-based method identified corticospinal tracts extending to the entire sensorimotor cortex, while the tensor-based method only identified a narrow subset of tracts extending medially to the vertex.
CONCLUSIONS: This comprehensive study shows that the most widely used clinical tractography method (diffusion tensor imaging-based tractography) results in systematically unreliable and clinically misleading information. The higher-order tractography model, using the same diffusion-weighted data, clearly demonstrates fiber tracts more accurately, providing improved estimates of safety margins that may be useful in neurosurgical procedures. We therefore need to move beyond the diffusion tensor framework if we are to begin to provide neurosurgeons with biologically reliable tractography information.

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Year:  2013        PMID: 23540269     DOI: 10.3171/2013.2.JNS121294

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  134 in total

1.  Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited.

Authors:  Cibu Thomas; Frank Q Ye; M Okan Irfanoglu; Pooja Modi; Kadharbatcha S Saleem; David A Leopold; Carlo Pierpaoli
Journal:  Proc Natl Acad Sci U S A       Date:  2014-11-03       Impact factor: 11.205

2.  Assessment of a method to determine deep brain stimulation targets using deterministic tractography in a navigation system.

Authors:  Josué M Avecillas-Chasin; Fernando Alonso-Frech; Olga Parras; Nayade Del Prado; Juan A Barcia
Journal:  Neurosurg Rev       Date:  2015-05-12       Impact factor: 3.042

3.  Comparison of seeding methods for visualization of the corticospinal tracts using single tensor tractography.

Authors:  Alireza Radmanesh; Amir A Zamani; Stephen Whalen; Yanmei Tie; Ralph O Suarez; Alexandra J Golby
Journal:  Clin Neurol Neurosurg       Date:  2014-12-08       Impact factor: 1.876

Review 4.  Tractography for Surgical Neuro-Oncology Planning: Towards a Gold Standard.

Authors:  Sandip S Panesar; Kumar Abhinav; Fang-Cheng Yeh; Timothée Jacquesson; Malie Collins; Juan Fernandez-Miranda
Journal:  Neurotherapeutics       Date:  2019-01       Impact factor: 7.620

Review 5.  Diffusion MRI as a complementary assessment to cognition, emotion, and motor dysfunction after sports-related concussion: a systematic review and critical appraisal of the literature.

Authors:  Sarah C Hellewell; Thomas Welton; Alan J Pearce; Jerome J Maller; Stuart M Grieve
Journal:  Brain Imaging Behav       Date:  2021-06       Impact factor: 3.978

6.  High-resolution diffusion imaging: ready to become more than just a research tool in psychiatry?

Authors:  S M Grieve; J J Maller
Journal:  Mol Psychiatry       Date:  2016-10-11       Impact factor: 15.992

Review 7.  Track-weighted imaging methods: extracting information from a streamlines tractogram.

Authors:  Fernando Calamante
Journal:  MAGMA       Date:  2017-02-08       Impact factor: 2.310

8.  Characterizing White Matter Tract Organization in Polymicrogyria and Lissencephaly: A Multifiber Diffusion MRI Modeling and Tractography Study.

Authors:  F Arrigoni; D Peruzzo; S Mandelstam; G Amorosino; D Redaelli; R Romaniello; R Leventer; R Borgatti; M Seal; J Y-M Yang
Journal:  AJNR Am J Neuroradiol       Date:  2020-07-30       Impact factor: 3.825

9.  Comparing prognostic strength of acute corticospinal tract injury measured by a new diffusion tensor imaging based template approach versus common approaches.

Authors:  Kelsi K Hirai; Benjamin N Groisser; William A Copen; Aneesh B Singhal; Judith D Schaechter
Journal:  J Neurosci Methods       Date:  2015-09-16       Impact factor: 2.390

10.  Rotationally-invariant mapping of scalar and orientational metrics of neuronal microstructure with diffusion MRI.

Authors:  Dmitry S Novikov; Jelle Veraart; Ileana O Jelescu; Els Fieremans
Journal:  Neuroimage       Date:  2018-03-12       Impact factor: 6.556

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