**2.1. Construction of diffusion tensor tractography (DTT)**

in both grey matter and cerebrospinal fluid (CSF). The major diffusion eigenvector is assumed

Diffusion-weighted imaging (DWI) is an important technique of functional magnetic resonance (fMR) imaging, which has the ability to assess changes in random motion of water protons in vivo. It is useful to diagnose several diseases in the central nervous system of humans and animals, specially canines [2, 22]. To detect lesions by DWI, the anisotropy is deliberately reduced using imaging techniques and processing to avoid detecting the signals

DWI can be used to detect and visualize water molecules diffusion in tissues by adding a bipolar gradient pulse called a motion-proving gradient (MPG). Diffusion-weighted MRI differs from conventional MRI in that it provides high-contrast resolution based on diffusion, which allows new information on lesions to be obtained [4]. In the 1970s, water diffusion MRI was introduced and later used for medical applications [5]. Reports on diffusion MRI of the brain for neurological disorders were first published in the 1980s [23]. In the 1990s, its use was extended [4]. With the introduction of DTI, it was proposed to represent the water diffusion coefficient distribution in all the directions of space as a tensor in each voxel. A reconstruction

DTI is an advanced technique of DWI sequence that displays vectors corresponding to the strength and direction of the movement of water molecules [2]. Recently, the DTI technique has permitted the detailed visualization of white matter structural integrity and connectivity [24]. One of the advantages of DTI is the reconstruction of axonal tracts in the brain in vivo [10]. DTI uses water diffusion anisotropy in axonal fibers allowing the analysis and tracking of said

Cerebral white matter anatomy can be studied in detail using DTI; it shows a complete anatomical and statistical fiber atlas of the white matter [15]; and it can explain, in combination with functional MRI, some anatomical and functional connectivity between different parts of

Pathologic conditions such as edema, inflammation, myelin loss, and gliosis may cause disruption in white matter tracts or changes in the membrane permeability which can alter DTI measurements, such as fractional anisotropy (FA) and apparent diffusion coefficient

Several studies have demonstrated the validity of quantitative diffusion imaging of the large white matter tracts in the brain in vivo [2]. FA provides information about the shape of the diffusion tensor at each voxel. The FA relates the differences between isotropic and anisotropic diffusion and is a scalar value between 0 and 1 indicating the degree of anisotropy in water diffusion. If FA value is close to 0, the diffusion is isotropic or random, and if it is close to 1, the diffusion is highly directional. The diffusion coefficient measured by nuclear magnetic resonance is best known as apparent diffusion coefficient (ADC). ADC depends greatly on the interactions of the diffusing molecule with the cellular structures over a given time; it could also be influenced by active processes within the tissue. ADC is calculated by acquiring two or more images with a different gradient duration and amplitudes, quantified as b-values.

to be parallel to the tract orientation in regions of homogeneous white matter [3].

of the white matter pathways was later proposed based on this tensor model [5].

from normal white matter [4].

184 Canine Medicine - Recent Topics and Advanced Research

fibers in cerebral white matter.

the brain [11].

(ADC) [25].

Methods for tracing connections in the brain have a long history, beginning with those based on lesions and the resulting retrograde or anterograde degeneration. The ensuing methods exploited the axonal transport of specific molecules like the horseradish peroxidase, and it was followed by a host of other tracers including small fluorescent molecules, lectins, neurotrophins, neurotoxins, dextrans, carbocyanine dyes, latex microspheres, and viruses. Although these methods allow the study of the brain connections, they are highly invasive. Moreover, any histological visualization of the transported substance requires sacrifice of the experimental animal [5]. Magnetic resonance images that make use of tensor analysis, such as FA maps and color maps, are collectively called DTI. A recent extension of DTI is fiber tracking, or tractography, which has been applied in the brain to noninvasively identify specific white matter pathways and connections in the brain in vivo. In the broadest sense, DTT can be considered a subtype of DTI, but it is often deliberately differentiated from DTI.

DTI and DTT provide us with a new opportunity to investigate such structures and to assess changes due to brain disease [4, 7, 15, 27]. DTT is a method of noninvasively tracing neuronal fiber bundles, and it integrates voxel-by-voxel orientations into a pathway that connects distant brain regions. The DTT technique can be used to analyze the trajectory, shape, fiber structure, location, topology, and connectivity of neuronal fiber pathways in vivo [28–30]. DTT can be used to simultaneously delineate cerebral white matter tracts in three dimensions and to identify alterations in connectivity. By tracing fiber pathways throughout the entire brain, diffusion tractography provides information that cannot be achieved by conventional anatomical MR imaging or histology [8, 9]. DTT refers to 3D models of white matter pathways generated from diffusion weighted MRI data, most commonly diffusion tensor imaging (DTI). Here, the term DT is used to refer to all forms of tractography derived from diffusion MRI data including but not limited to DTI. Given that white matter is highly anisotropic, the nerve fibers can be tracked and visualized with DTT. To perform a DTT, parameters such the ADC and the FA must be calculated. To calculate these parameters, tensor analysis is employed [4, 27, 31]. The orientation of the component of the diagonalized diffusion tensor represents the orientation of the dominant axonal tracts, DTI provides a 3D vector field, and each vector represents the fiber orientation. Actually, there are different ways to reconstruct cerebral white matter tracts, these reconstructions are divided in two different types. The first type is based on line propagation algorithms that use local tensor information for propagation step. The main differences found throughout these techniques are due to the way they incorporate information from neighboring pixels in order to define smooth trajectories and to reduce noise contributions. The second one is based on global energy minimization to find the most favorable energetic pathway between two pixels [15]. The orientation of the diffusion tensor major eigenvector is generally assumed to be parallel to the local white matter fascicles. These directional patterns may be simply visualized using the color maps representing the major eigenvector direction. Such color maps are useful for assessing the organization of the cerebral white matter in the brain and for the identification of the major cerebral white matter tracts in 2D sections [3]. Another approach to visualize the white matter connection patrons in 3D is using diffusion tensor tractography. White matter patterns are estimated by starting at a specified location, this location is called seed point, also estimating the direction of propagation that is called major eigenvector, and moving a short distance in that direction called tract integration. The tract direction is then re-evaluated and another small step is taken until the tract is finished. Fiber tracts can be obtained using different number of regions of interest (ROIs) [3]. Diffusion tensor tractography have been used to produce anatomically fiber tract reconstruction of the most important proyection pathways. The primary applications of tractography to date have been the visualization of WM trajectories in 3D (particularly, in relation to brain pathology) and segmentation of specific brain regions [3, 32]. In human medicine, this technique has great potential for studying numerous diseases because the results of DTT and clinical symptoms can be compared directly. This technique is commonly used in human to study the anatomy and maturation of the normal, aging brain, but it also can be used to help diagnose neurological conditions, including brain ischemia, multiple sclerosis, diffuse axonal injury, epilepsy, metabolic disorders, certain mental illnesses, and brain tumors, as well as establish a prognosis for patients with these conditions [1]. FA and ADC are measurements that may be altered by disruption of white matter tracts or changes in membrane permeability as a result of pathologic conditions such as edema, inflammation, myelin loss, and gliosis. We can visualize the physical displacement of axon bundles employing tractography maps and are evaluated for surgical planning. Also, using axonal diffusivity, we can quantified noninvasively and correlate with histopathology axonal injury without demyelination [1, 2, 11, 25, 33].

#### **2.2. DTI in human medicine**

DTI is a widely used technique for the detection of several central nervous system diseases. It is the tool of choice because it is highly sensitive, highly specific, and noninvasive while providing a diagnosis within the therapeutic window [34].

It is expected to become even more useful due to the recent development of diffusion-weighted whole-body imaging with background body signal suppression, which can be used to evaluate the metastases of malignant tumors in three dimensions.

DTI is commonly used in order to study the normal anatomy of normal brain maturation and aging [11].

Normal white matter brain anatomy can be studied in detail using DTI; on one side, it shows a complete anatomical and statistical fiber atlas of the white matter, and on the other hand, it can explain in combination with functional MRI, some anatomical and functional connectivity between different parts of the brain [11, 15].

Aside detecting diseases in the central nervous system, DTI has been used for different applications in human medicine.

DTI was applied presurgically in human medicine to plan function-preserving brain surgery by saving special areas of motor and speech function, actually the application of the DTI is also possible for white matter tract reconstruction in 3D images for the spinal cord and brain [22].

Some applications of DTI in normal brain are demonstrating the relationship between the white matter structure and its function; for example, IQ has been positively correlated with anisotropy in cerebral white matter association tracts. Reading ability has been correlated with anisotropy of the left temporoparietal white matter, where tractography has localized the language areas. In visual pathways, increase in anisotropy has been correlated with improved reaction time. Tractography findings have demonstrated an excellent correlation with functional data; for example, probabilistic tractography has been used for segmentation of the thalamus according to its cortical connectivity, which corresponds well to segmentation of the thalamus.

DTI has shown additional abnormalities in patients with several types of dementia and neurodegenerative disease.

Several researches have use DTI to demonstrate a variety of white matter abnormalities often correlated with performance in neuropsychiatric test.

For demyelinating disease, the use of DTI is often used for diagnosing multiple sclerosis; several groups have demonstrated increased diffusivity and decreased anisotropy in demyelinating lesions.

In the case of ischemic disease, DTI is used for the detection of early acute ischemia into the domain of prognosis and long-term management of ischemic sequelae.

DTI has important implications in the delineation of tumor margins beyond what is currently demonstrated with conventional MRI [21].

## **2.3. DTI in animals**

including but not limited to DTI. Given that white matter is highly anisotropic, the nerve fibers can be tracked and visualized with DTT. To perform a DTT, parameters such the ADC and the FA must be calculated. To calculate these parameters, tensor analysis is employed [4, 27, 31]. The orientation of the component of the diagonalized diffusion tensor represents the orientation of the dominant axonal tracts, DTI provides a 3D vector field, and each vector represents the fiber orientation. Actually, there are different ways to reconstruct cerebral white matter tracts, these reconstructions are divided in two different types. The first type is based on line propagation algorithms that use local tensor information for propagation step. The main differences found throughout these techniques are due to the way they incorporate information from neighboring pixels in order to define smooth trajectories and to reduce noise contributions. The second one is based on global energy minimization to find the most favorable energetic pathway between two pixels [15]. The orientation of the diffusion tensor major eigenvector is generally assumed to be parallel to the local white matter fascicles. These directional patterns may be simply visualized using the color maps representing the major eigenvector direction. Such color maps are useful for assessing the organization of the cerebral white matter in the brain and for the identification of the major cerebral white matter tracts in 2D sections [3]. Another approach to visualize the white matter connection patrons in 3D is using diffusion tensor tractography. White matter patterns are estimated by starting at a specified location, this location is called seed point, also estimating the direction of propagation that is called major eigenvector, and moving a short distance in that direction called tract integration. The tract direction is then re-evaluated and another small step is taken until the tract is finished. Fiber tracts can be obtained using different number of regions of interest (ROIs) [3]. Diffusion tensor tractography have been used to produce anatomically fiber tract reconstruction of the most important proyection pathways. The primary applications of tractography to date have been the visualization of WM trajectories in 3D (particularly, in relation to brain pathology) and segmentation of specific brain regions [3, 32]. In human medicine, this technique has great potential for studying numerous diseases because the results of DTT and clinical symptoms can be compared directly. This technique is commonly used in human to study the anatomy and maturation of the normal, aging brain, but it also can be used to help diagnose neurological conditions, including brain ischemia, multiple sclerosis, diffuse axonal injury, epilepsy, metabolic disorders, certain mental illnesses, and brain tumors, as well as establish a prognosis for patients with these conditions [1]. FA and ADC are measurements that may be altered by disruption of white matter tracts or changes in membrane permeability as a result of pathologic conditions such as edema, inflammation, myelin loss, and gliosis. We can visualize the physical displacement of axon bundles employing tractography maps and are evaluated for surgical planning. Also, using axonal diffusivity, we can quantified noninvasively and correlate with histopathology axonal injury without

186 Canine Medicine - Recent Topics and Advanced Research

DTI is a widely used technique for the detection of several central nervous system diseases. It is the tool of choice because it is highly sensitive, highly specific, and noninvasive while

demyelination [1, 2, 11, 25, 33].

**2.2. DTI in human medicine**

providing a diagnosis within the therapeutic window [34].

DTI has been used in an experimental model in cats, rats, mice, dogs, pigs, and marmosets [2, 5, 8–10, 12, 17, 20, 30, 31, 34]. DTI has generally been used following the creation of spinal cord trauma to serve as a model to aid in evaluating human spinal cord trauma victims [4, 35–37].

In dogs, it has been used for the evaluation of the spinal cord and its pathologies, providing statistically and visually different images when evaluating fractional anisotropy and ADC in normal dogs compared against dogs with lesions localized in the spinal cord using different types of scanners and software [19, 22, 24, 38–40].

DTI technique has also been applied to image animal brains in vivo and ex vivo [1, 10, 11, 20, 34]. Previous work shows consistent results between diffusion anisotropy of in vivo and ex vivo formalin-fixed mouse brains. This offers a new opportunity to study the brain microstructure with ex vivo DTI, as it avoids motion artifacts and allows for longer imaging time [20].

The use of DTI in white matter tracts found in dog and human brains has the potential for studying several pathologies by correlating DTI findings with clinical symptoms [11].

The corpus callosum has been also studied in dogs with DTI because its aging and pathologies are similar of those found in the human corpus callosum. In Pierce's work, the corpus callosum was segmentated into six major White matter tracts, which will provide grounds for new research in both species [34].

Tracing tracts by DTI is relative new, and it is expected that further research will develop new technologies soon. However, recent studies have demonstrated that even simple methodologies are able to visualize cerebral white matter tracts connections in situ for both human and animals [15].
