Diffusion tensor imaging

Super resolution track-density imaging (TDI), which produces high-quality white matter images, with high spatial resolution and exquisite anatomical contrast not available from other MRI modalities. This method achieves super resolution by utilising the long-range information contained in the diffusion MRI fibre tracks. In this study, we validate the super resolution property of the TDI method by using in vivo diffusion MRI data acquired at ultra-high magnetic field strength (7 T), and in silico diffusion MRI data from a well-characterised numerical phantom. Furthermore, an alternative version of the TDI technique is described, which mitigates the track length weighting of the TDI map intensity. For the in vivo data, high-resolution diffusion images were down-sampled to simulate low-resolution data, for which the high-resolution images serve as a gold standard. For the in silico data, the gold standard is given by the known simulated structures of the numerical phantom. Both the in vivo and in silico data show that the structures that could be identified in the TDI maps only after using super resolution were consistent with the corresponding structures identified in the reference maps. This supports the claim that the structures identified by the super resolution step are accurate, thus providing further evidence for the important potential role of the super resolution TDI methodology in neuroscience 1).

An MRI technique that demonstrates white matter tracts by exploiting the difference in diffusion parallel to the nerve axons that comprise white matter tracts from diffusion perpendicular to their course.

Available only with specialized software for specific MRI scanners.

Contraindications are same as for MRI in general.

Probably most useful to permit planning surgical approaches that minimize disruption of critical white matter tracts during intraparenchymal brain surgery for deep lesions, especially when a lesion (e.g. tumor, AVM, cerebral hemorrhage…) may displace these tracts from their expected position.

The major divisions of white matter tracts demonstrable by DTT MRI are

projection fibers: tend to be oriented rostrocaudal

corticospinal tract coalesces as corona radiata funnels into internal capsule and forms pyramidal tract

commissural fibers: mediolaterally oriented, connecting the cerebral hemispheres

corpus callosum

anterior commissure

posterior commissure

association fibers: connect regions within the same hemisphere

U-fibers: connect adjacent gyri

○ long association fibers: connect more distant areas

optic radiations: connect lateral geniculate bodies to visual cortex. Pass lateral to the body of the lateral ventricles.

uncinate fasciculus: connects the anterior temporal lobe to the inferior frontal gyrus. Damage can cause language deficits

superior longitudinal fasciculus (SLF): connects regions of frontal lobe to temporal and occi- pital lobes. Injury can cause language deficits

arcuate fasciculus: part of SLF. Classic neuroanatomy teaching: connects the inferior frontal gyri (Broca’s area = motor speech) to the superior temporal gyrus (Wernicke’s area = language comprehension) and that injury causes “conduction aphasia.” DTI has suggested broader connections, including those to the premotor cortex

inferior longitudinal fasciculus (ILF): connects temporal and occipital lobes at the level of the optic radiation. Injury can cause deficits in object recognition, visual agnosias, prosopagnosia (face blindness)

cingulum: project from cingulate gyrus to the entorhinal cortex as part of the limbic system

Convention for color-coding tracts on DTI images:

● blue: superior-inferior tracts

● red: mediolateral (horizontal) tracts

● green: anterior-posterior tracts 2).

Owing to a number of technical considerations, DTI is somewhat more operator-dependent than conventional MRI.

For surgical planning, the goal is to keep the surgical trajectory roughly parallel (at < 30°angle) to the long axis of the white matter tract that one is trying to preserve (unproven hypothesis 3)). surgical “corridors” have been described taking into consideration the preservation of white matter tracts:

● anterior corridor: parallel to association fibers, between the SLF and the cingulum (e.g. can be through eyebrow or forehead incision)

● posterior corridor: enters at the parieto-occipital sulcus, passes adjacent to the optic radiations

● lateral corridor

There is no strong consensus regarding the best method for utilizing DTI for concussion diagnosis or prognosis in the individual patient but multiple studies have shown group differences in DTI parameters between mTBI and control patients 4).

The ability of diffusion tensor MRI to detect the preferential diffusion of water in cerebral white matter tracts enables neurosurgeons to noninvasively visualize the relationship of lesions to functional neural pathways.

see Intraoperative Diffusion Tensor Imaging Tractography.

Since its introduction, diffusion tensor imaging (DTI) has become an important tool in neuroscience given its unprecedented ability to image brain white matter in vivo.

It is commonly used in neurosurgical practice but is largely limited to the preoperative setting.

The interest in understanding the mechanisms of action of Deep Brain Stimulation in different targets and indications, together with the constant drive towards the improvement in long-term clinical outcomes, has found a logical complement in the application of tractography in this field. Diffusion tensor imaging has been traditionally associated with an increased susceptibility to MRI artifacts, and expensive computational resources. Recent advances have however improved these restrictions, allowing for countless applications in Neurosurgery, as demonstrated by the large number of original research papers published in the last decade 5).

Diffusion tensor imaging (DTI) for the assessment of fractional anisotropy (FA) and involving measurements of mean diffusivity (MD) and apparent diffusion coefficient (ADC) represents a, MRI-based, noninvasive technique that may delineate microstructural changes in cerebral white matter (WM).

Diffusion tensor imaging (DTI) provides a measure of the directional diffusion of water molecules in tissues and can noninvasively detect in vivo white matter (WM) abnormalities on the basis of anisotropic diffusion properties.

From the diffusion tensor, the principal direction of the diffusion tensor can be used to infer the white-matter connectivity of the brain (i.e. tractography; trying to see which part of the brain is connected to which other part).

see Neuronavigation with diffusion tensor imaging.

DTI, has limitations that include its inability to resolve multiple crossing fibers and its susceptibility to partial volume effects.

Therefore, recent focus has shifted to more advanced WM imaging techniques such as high-definition fiber tractography (HDFT).

Abhinav et al. illustrate the application of HDFT, which in their preliminary experience has enabled accurate depiction of perilesional tracts in a 3-dimensional manner in multiple anatomical compartments including edematous zones around high-grade gliomas. This has facilitated accurate surgical planning. This is illustrated by using case examples of patients with glioblastoma multiforme. They also discuss future directions in the role of these techniques in surgery for gliomas 6).

Diffusion tensor imaging tractography is the mapping of neural fiber pathways based on diffusion tensor imaging (DTI) of tissue diffusion anisotropy.

It has become a popular tool for delineating white matter tracts for neurosurgical procedures.

It uses special techniques of magnetic resonance imaging (MRI), and computer-based image analysis. The results are presented in two- and three-dimensional images.

In addition to the long tracts that connect the brain to the rest of the body, there are complicated neural networks formed by short connections among different cortical and subcortical regions. The existence of these bundles has been revealed by histochemistry and biological techniques on post-mortem specimens. Brain tracts are not identifiable by direct exam, CT, or MRI scans. This difficulty explains the paucity of their description in neuroanatomy atlases and the poor understanding of their functions.

The MRI sequences used look at the symmetry of brain water diffusion. Bundles of fiber tracts make the water diffuse asymmetrically in a tensor, the major axis parallel to the direction of the fibers. The asymmetry here is called anisotropy. There is a direct relationship between the number of fibers and the degree of anisotropy.

White matter tractography is limited by biological variables such as edema, mass effect, and tract infiltration or selection biases related to region of interest or fractional anisotropy values.

An automated tract identification paradigm was developed and evaluated for glioma surgery. A fiber bundle atlas was generated from 6 healthy participants. Fibers of a test set (including 3 healthy participants and 10 patients with brain tumors) were clustered adaptively with this atlas. Reliability of the identified tracts in both groups was assessed by comparison with 2 experts with the Cohen κ used to quantify concurrence. We evaluated 6 major fiber bundles: cingulum bundle, fornix, uncinate fasciculus, arcuate fasciculus, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus, the last 3 tracts mediating language function.

The automated paradigm demonstrated a reliable and practical method to identify white mater tracts, despite mass effect, edema, and tract infiltration. When the tumor demonstrated significant mass effect or shift, the automated approach was useful for providing an initialization to guide the expert with identification of the specific tract of interest.

Tunç et al., report a reliable paradigm for the automated identification of white matter pathways in patients with gliomas. This approach should enhance the neurosurgical objective of maximal safe resections 7).

Calamante F, Tournier JD, Heidemann RM, Anwander A, Jackson GD, Connelly A. Track density imaging (TDI): validation of super resolution property. Neuroimage. 2011 Jun 1;56(3):1259-66. doi: 10.1016/j.neuroimage.2011.02.059. Epub 2011 Feb 24. PubMed PMID: 21354314.
Douek P, Turner R, Pekar J, Patronas N, Le Bihan D. MR color mapping of myelin fiber orientation. J Comput Assist Tomogr. 1991 Nov-Dec;15(6):923-9. PubMed PMID: 1939769.
Kassam AB, Labib MA, Bafaquh M, et al. Part I: The challenge of functional preservation: an integrated systems approach using diffusion-weighted, image guided, exoscopic-assisted, transsulcal radial corri- dors. Innovative Neurosurgery. 2015
Yuh EL, Hawryluk GW, Manley GT. Imaging concus- sion: a review. Neurosurgery. 2014; 75 Suppl 4: S50–S63
Sammartino F, Hodaie M. Diffusion Tensor Imaging of the Basal Ganglia for Functional Neurosurgery Applications. Prog Neurol Surg. 2018;33:62-79. doi: 10.1159/000480766. Epub 2018 Jan 12. PubMed PMID: 29332074.
Abhinav K, Yeh FC, Mansouri A, Zadeh G, Fernandez-Miranda JC. High-definition fiber tractography for the evaluation of perilesional white matter tracts in high-grade glioma surgery. Neuro Oncol. 2015 Jun 27. pii: nov113. [Epub ahead of print] Review. PubMed PMID: 26117712.
Tunç B, Ingalhalikar M, Parker D, Lecoeur J, Singh N, Wolf RL, Macyszyn L, Brem S, Verma R. Individualized Map of White Matter Pathways: Connectivity-Based Paradigm for Neurosurgical Planning. Neurosurgery. 2016 Oct;79(4):568-77. doi: 10.1227/NEU.0000000000001183. PubMed PMID: 26678299; PubMed Central PMCID: PMC4911597.
  • diffusion_tensor_imaging.txt
  • Last modified: 2023/01/09 21:18
  • by administrador