Diffusion Tensor Imaging Tractography
Diffusion magnetic resonance imaging (dMRI) is a non-invasive neuroimaging technique that uses magnetic resonance imaging (MRI) to measure the diffusion of water molecules in brain tissue. The diffusion of water molecules in biological tissues is affected by the presence of barriers, such as cell membranes and myelin, as well as by the direction and alignment of fibers. By measuring the diffusion of water in different directions, dMRI can provide information about the microstructure of brain tissue.
To perform dMRI, a magnetic field is applied to the brain tissue, causing the water molecules to align with the field. A series of diffusion-weighted images are then acquired, in which the strength and direction of the magnetic field are varied. These images are used to compute a diffusion tensor, which describes the diffusion of water in each voxel (a 3D pixel) of the brain.
The diffusion tensor can be used to compute several parameters, including fractional anisotropy (FA), which measures the degree of directional diffusion in a voxel and mean diffusivity (MD), which measures the overall diffusion in a voxel. These parameters can provide insights into the microstructure of white matter, such as the density, orientation, and integrity of axonal fibers.
dMRI has many potential applications in neuroscience and clinical research. For example, it can be used to study the effects of brain injury or disease on white matter microstructure, to investigate the development of the brain during infancy and childhood, and to identify biomarkers for neurodegenerative disorders.
It is extensively used in preoperative planning for brain tumors, epilepsy, and functional neurosurgical procedures such as deep brain stimulation. Over the past 25 years, significant advancements have been made in imaging acquisition, fiber direction estimation, and tracking methods, resulting in considerable improvements in tractography accuracy. The technique enables the mapping of functionally critical pathways around surgical sites to avoid permanent functional disability. When the limitations are adequately acknowledged and considered, tractography can serve as a valuable tool to safeguard critical white matter tracts and provide insight regarding changes in normal white matter and structural connectivity of the whole brain beyond local lesions. In functional neurosurgical procedures such as deep brain stimulation, it plays a significant role in optimizing stimulation sites and parameters to maximize therapeutic efficacy and can be used as a direct target for therapy 1).
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
● 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).
Indications
Limitations
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).