Download Free Medical Diffusion tensor image in neurology PowerPoint Presentation

Diffusion tensor image in neurology PowerPoint Presentation

DOWNLOAD MEDICAL POWERPOINT PRESENTATION

About This Presentation

Description : Check out this medical presentation on Radiology and Imaging, which is titled "Diffusion tensor image in neurology", to know about diffusion tensor image in neurology.

Tags : Radiology, Imaging, Diffusion tensor image, neurology

Published on : Aug 02, 2021 | Views : 2431 | Downloads : 1

Shareable Url :

Embed Code :

Comment

Transcript

Slide 1-

Diffusion tensor image in neurology Osama Ragab Neurology MD. 2017
Slide 2-

ppt slide no 2 content not found
Slide 3-

In 1826 a botanist named Robert Brown was studying the seemingly random pattern of motion that pollen grains exhibited when suspended in water through his microscope. It later became clear that the motion that he had observed was due to the buffeting of the pollen grains by water molecules surrounding them.
Slide 4-

liquids are not static and lifeless as they might appear at first glance. The atoms and molecules in constant motion, undergoing persistent collisions and energy exchanges with other molecules and atoms. This led to an intuitive understanding of phenomena of spreading of an ink drop in a glass of seemingly motionless water.
Slide 5-

Albert Einstein developed a rigorous mathematical framework, which is still in use today.
Slide 6-

Diffusion ?!!!
Slide 7-

In water at room temperature, the average distance moved of a water molecule in one second is around 100 μm. This length scale is of a similar magnitude to that of many cellular structures of central nervous system tissue. Hence if we probe the motion of water molecules at such timescales , we can probe the geometric structure of the tissue of the central nervous system at the cellular level from outside the body.
Slide 8-

DWI VS DTI A conventional DWI sequence evaluates diffusion in all directions. Diffusion tensor imaging (DTI) evaluates diffusion in multiple different directions (represented by vectors with magnitude and direction) to investigate the three-dimensional microanatomical structure of brain parenchyma. Each point of the imaged tissue is mathematically represented as a multidimensional diffusion vector that is known as a diffusion tensor.
Slide 9-

In cerebrospinal fluid, the diffusion of protons is unrestricted in all directions, and therefore isotropic, In highly organized biological tissue, diffusion often is restricted in some directions or anisotropic. and represented by an elongated ellipsoid tensor
Slide 10-

DTI The diffusion tensor can be fully characterized by calculating its “eigenvalues” (λ 1 , λ 2 , and λ 3 ), which describe the length of the three axes of the ellipsoid, and the “eigenvectors” (ε 1 , ε 2 , and ε 3 ), which describe the orientation of these axes in space. The eigenvectors provide information about the direction of maximum diffusion within a voxel .
Slide 11-

From the eigenvalues, the mean diffusivity (MD), is calculated. The most commonly used measure for diffusion anisotropy is fractional anisotropy (FA), which is calculated from the eigenvalues and gives a normalized value to the tensor's degree of anisotropy (0 is completely isotropic and 1 is completely anisotropic). Diffusion tensors are commonly visualized with color encoded FA maps, which display fiber orientation with three standard colors: red (transverse), blue (craniocaudal), and green (anteroposterior). DTI
Slide 12-

Fraction anisotropy
Slide 13-

The (Self-)Diffusion Coefficient It quantifies the freedom of movement of any single molecule of water, in the glass of water, and CSF .
Slide 14-

The Apparent Diffusion Coefficient Apparently, the self-diffusion coefficient of water has changed, just because we measured it in the grey matter. We are not interested in the ADC for the purpose of quantifying diffusion itself, but rather to investigate properties of the tissue that apparently caused the diffusion process to behave in the way that we measure
Slide 15-

Mean Diffusivity (MD) the average of the eigenvalues, it describes the overall size of the tensor and as such represents a invariant ADC measure.
Slide 16-

Hindered / Restricted Diffusion
Slide 17-

DTI-based tractography DTI tractography can be classified broadly into two methods: deterministic and probabilistic. In deterministic techniques, a starting or “seed” point is designated in three-dimensional space and tracking is terminated when “stop criteria,” such as a pixel with low FA or a predetermined trajectory angle between two contiguous vectors is attained. A distinct limitation is the inability to produce more than one reconstructed trajectory per seed point.
Slide 18-

ppt slide no 18 content not found
Slide 19-

probabilistic algorithms allow for the modelling of uncertainty of two (or more) fiber directions at each voxel. Tracking is done by launching a high number of streamlines from a seed region, and at each voxel drawing from the previously determined 3D probability distribution to propagate the tracts. After a sufficient number of samples, the output is a probabilistic mapping of the uncertainty of fiber tracts at each voxel, with the dominant streamline surfacing as most probable. DTI-based tractography
Slide 20-

ppt slide no 20 content not found
Slide 21-

Probabilistic tractography techniques incorporate uncertainty of fiber direction to create a probabilistic map of “likely” tracts, which has the benefit of allowing for branching fibers. The probabilistic method creates a three-dimensional volume of potential connectivities that may leak into unexpected regions of the brain. This makes visual interpretation of fibers more difficult and requires judgment to determine relevance. DTI-based tractography
Slide 22-

Strategies of DTI Analysis
Slide 23-

ppt slide no 23 content not found
Slide 24-

Applications in Neurology
Slide 25-

Brain Tumors
Slide 26-

Pre-surgical planning and intraoperative guidance in regions adjacent to functional tracts. In addition to diffusion MRI, high-resolution T1- and T2-weighted anatomic images must be acquired to coregister with the FA map and DTI tractography for use with an intraoperative navigation system . Numerous arbitrary technical factors such as FA and angle of trajectory thresholds can significantly alter the tract trajectories generated. This may result in artifactual delineation of spurious fibers or in nonvisualization of intact fibers within the area in question.
Slide 27-

White matter shifts and deformation significantly limit accuracy of this technique when DTI tractography is used intraoperatively, with fiber tract shifts ranging from −8 to +15 mm during tumor resection. Brain shift may occur after dura mater opening as well as during tumor resection and is more likely when peritumoral edema is present. This has resulted in recommendations that continuous stimulation be applied when the planned resection is within 1 cm of the DTI estimated tracts
Slide 28-

( A ) Coronal gadolinium-enhanced image shows a melanoma metastasis to the brain. ( B ) Coronal functional MRI shows the metastasis results in medial displacement of the motor activation area. ( C ) Color-coded axial fractional anisotropy map reveals less-robust anisotropy in the posterior left centrum semiovale. ( D ) Tractography demonstrates displacement of the fiber tracts medially surrounding the area of motor activation.
Slide 29-

In summary, DTI tractography should not be used as the sole technique for presurgical planning. Instead, directional color-coded FA map and conventional MRI should be used in conjunction with tractography to improve visualization of distorted, infiltrated tracts .
Slide 30-

DTI metrics also have been used for diagnostic characterization of brain masses to differentiate solitary metastatic lesions from gliomas. Measured mean peritumoral MD of metastatic lesions was found to be significantly greater than that of gliomas. however, FA values were similar or slightly decreased for gliomas.
Slide 31-

FA values also have been used to try to assess tissue differentiation between low- and high-grade gliomas. Some authors have shown no significant difference in FA values between low- and high-grade gliomas ,whereas others have found a correlation between decreasing FA and increasing glioma grade .
Slide 32-

Spinal Cord
Slide 33-

The spinal cord is frequently involved by multiple sclerosis with the dorsal and lateral columns most commonly affected. Decreased FA has been shown not only in the cord lesions themselves but also in adjacent normal-appearing white matter (NAWM) on conventional MRI in the cervical cord as compared with healthy controls . Good correlation has also been found between the average FA and MD and the severity of disability
Slide 34-

Differentiate a spinal cord ependymoma from an astrocytoma . FA values have been shown to be astrocytomas and do not similar in ependymomas and help characterize the tumor. However, the use of fiber tractography has proven to be useful because it often shows displacement of fibers around ependymomas and infiltration of fibers in astrocytomas
Slide 35-

DTI in cervical spondylotic myelopathy, demonstrating correlation between decrease in cord FA and clinical disease severity . DWI and DTI has been used to study multiple other diseases of the spinal cord, including HIV-associated spinal cord abnormalities, transverse myelitis, spinal cord injury, and spinal cord ischemia
Slide 36-

Epilepsy
Slide 37-

Diffusion imaging has great potential value in epileptogenic localization. In the peri- and postictal state, cortical changes in the apparent diffusion coefficient (ADC) and MD are similar to those seen in cerebral ischemia, with early decrease, followed by normalization and subsequent elevation of these parameters
Slide 38-

Diffusion changes typically normalize by day 14 . Chronic repetition of seizures may then result in irreversible elevation of ADC and MD, reflecting development of gliosis and cellular loss.
Slide 39-

In cryptogenic temporal lobe epilepsy, findings of decreased FA and increased ADC were noted in hippocampi and temporal lobe white matter ipsilateral to the seizure onset in a significant number of patients with normal MRI . Similarly, decreased FA and increased MD have been shown in the normal-appearing subcortical white matter adjacent to focal cortical dysplasia, identifying these occult abnormalities
Slide 40-

Finally, because seizures can induce neuronal injury, chronic refractory epilepsy may result in synaptic reorganization and altered connectivity . Tractography can be used to help delineate these chronic effects such as structural reorganization of higher cortical functions such as language and memory . Thus, tractography may play a significant role in longitudinal studies of the chronic effects of epilepsy on the brain.
Slide 41-

Diffuse Axonal Injury (DAI)
Slide 42-

DAI is the result of shear-strain deformation of the brain tissue with disruption of the axonal membranes and cytoskeletal network. DTI may detect microstructural injury implicated in DAI that is linked to persisting symptoms in patients after mild traumatic brain injury (TBI).
Slide 43-

( A ) Axial gradient-recalled echo image demonstrates focal areas of hypointensity within the bilateral centrum semiovale consistent with microhemorrhage associated with DAI. ( B ) Axial fluid-attenuated inversion recovery image ( C ) Axial diffusion-weighted image shows several areas of restricted diffusion near the gray-white junction bilaterally compatible with DAI. ( D ) Axial fractional anisotropy (FA) map demonstrates decreased FA (0.494) in the posterior body of the right corpus collosum (black arrow) compared with the same region on the left (0.646). however, the other conventional MR sequences (white arrows) show no abnormality in this region.
Slide 44-

Multiple Sclerosis
Slide 45-

MS lesions typically demonstrate increased MD and decreased FA compared with contralateral normal appearing white matter . These abnormalities correlate with axonal and myelin disruption. The greatest MD values and lowest FA values are seen in lesions that are hypointense on T1WI, which represent chronic destructive changes where diffusion is least restricted
Slide 46-

DTI also has been used to differentiate acute lesions and chronic lesions. FA values were found to be relatively lower in enhancing lesions (especially in lesions with ring enhancement) compared with non- enhancing lesions . It is important to recognize that DTI metrics, including FA and MD, do not differentiate axonal disruption from demyelination or from focal tissue edema, which are frequently seen in MS.
Slide 47-

Normal-appearing gray matter (NAGM), including the basal ganglia in patients with MS, has also been shown to demonstrate DTI abnormalities . A recent study demonstrated correlation between increased FA in NAGM, cortical lesion volume, and clinical disability in patients with MS .
Slide 48-

DTI can distinguish MS from other secondary demyelinating white matter diseases such as acute disseminated encephalomyelitis and neurosarcoidosis. Increased ADC values in the corpus callosum of patients with MS, with no significant corresponding ADC elevation in the corpus callosum of patients with secondary demyelinating disorders.
Slide 49-

Alzheimer Disease (AD)
Slide 50-

In addition to evaluation of patients with clinical AD, DTI has been investigated for detection of incipient AD, which is commonly clinically classified as amnestic mild cognitive impairment (MCI) . DTI has demonstrated decreased FA values in white matter of frontal and occipital lobes in patients with a diagnosis of MCI and AD . This finding likely corresponds to microarchitectural derangements in NAWM of patients with AD and also has been shown recently to correlate with executive function tests in AD and MCI patients
Slide 51-

DTI evaluation of hippocampal formations correlates more consistently with MCI and AD . These abnormalities include increased MD and decreased FA in hippocampal formations (especially left hippocampus) of AD and MCI patients. Furthermore, these DTI abnormalities in hippocampi were detected in MCI before significant atrophy was detected .
Slide 52-

Comparison of conventional T1- (A) and T2- (B) weighted images, and DTI-derived mean diffusivity (MD) (C), fractional anisotropy (FA) (D), and color-coded orientation (E) maps of cognitively normal 72-year-old woman (upper row) and 70- year-old woman with Alzheimer’s disease. The areas surrounded by yellow rectangles in (E) are magnified and shown in (F) [left (F-1): from the cognitively normal woman; right (F-2): the Alzheimer’s disease patient]. The yellow arrows indicate the cingulum hippocampal part.
Slide 53-

Ischemic Stroke
Slide 54-

ADC values decrease within minutes after onset of cerebral ischemia, allowing the region of infarction to be delineated within the first 3−6 hours after the onset of symptoms when therapeutic interventions are most effective . A potential application for DTI in early stroke is using directionally encoded color anisotropy images and fiber tractography to delineate the location of functionally important white matter pathways in relation to the acute infarct. For example, studies have shown that the severity of damage to the arcuate fasciculus as estimated by DTI may predict language function in the chronic stage after an acute infarct.
Slide 55-

DTI has also been used to characterize Wallerian degeneration of white matter tracts that appear normal on conventional MRI. A decrease in FA can be detected in the pyramidal tract as early as 2 weeks after an infarct, and such applications may also provide useful prognostic information
Slide 56-

Directionally encoded color (DEC) map of DTI images and the PLIC white-matter tract. A DTI image of a representative patient (CI001) with damage to PLIC. Color codes to give diffusion tensor directions: red represents tracts running left to right; green is anterior to posterior; blue is superior to inferior. Axial view of the PLIC white-matter tract (in red) of patient CI001. A DEC map of DTI image of a representative patient (CI003) with no damage to PLIC. Color also represents diffusion tensor directions. Axial view of the PLIC white-matter tract (in red) of patient CI003.
Slide 57-

ppt slide no 57 content not found
Slide 58-

ppt slide no 58 content not found
Slide 59-

ppt slide no 59 content not found