Name: dti of the visual pathway - white matter tracts and cerebral lesions
Uploaded: 2014-08-26T15:00:00.000+00:00
Duration: 10 min 5 s
Description: Watch this Scientific Journal Video about DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions at JoVE.com

We would like to thank the whole Service of Neuroradiology. We would like to thank Lis Prussen for her work in the library.

NOTE: This protocol follows the guidelines of the Centre Hospitalier de Luxembourg in Luxembourg.
1. Preparation of Diffusion Tensor Imaging for the Visual Pathway for Neurosurgery and Follow Up
<ol style="margin-left: 40px;">
	<li>Perform an MRI-scan at least one day before surgery strictly axial using 32 gradient directions and one b0-image. Keep in close touch with the neuroradiology unit at any moment. 
	NOTE: Make clear to the neuroradiologist that the images after surgery are the same as those before the operation.</li>
	<li>Using a 3-Tesla MRI, perform a 3DT1-weighted and DTI-sequence scans. Perform a 3DT1-weighted sequence after surgery as well.</li>
</ol>
2. Using the Planning Station
<ol>
	<li>Transfer the T2-weighted, 3DT1-weighted and DTI-sequence scan data to digital imaging and communications in medicine (DICOM). This procedure takes up to 7 min. 
	NOTE: Don`t stop the procedure before having transferred all the sequences. It is possible to stop and continue later depending on the date of surgery.</li>
	<li>Open the surgical navigation system program. Click on File and then on Import DICOM. Repeat this procedure three times for all the sequences mentioned above.
	<ol>
		<li>Click Add to view. Add every sequence separately. Don`t try to proceed with View.</li>
	</ol>
	</li>
	<li>Click on Tools. Open DTI Tensor preparation. Observe a new window in the middle of the screen.</li>
	<li>Complete the following four steps.
	<ol>
		<li>Perform Gradient Assignment as the first step.
		<ol>
			<li>Change the b-value from 1,000 to 800 s/mm&#178; on the bottom right of the window.</li>
			<li>Adjust the Threshold on the top right of the window. Do it manually by simply writing a number or moving a cursor. 20 might be an acceptable value. It is a personal experience and it is not mandatory.</li>
		</ol>
		</li>
		<li>Perform Gradient Registration as the second step.
		<ol>
			<li>Click the button All Auto. This procedure takes up to 5 min.</li>
			<li>Click Verify All Registrations. Without verifying the registrations it is not possible to continue.</li>
		</ol>
		</li>
		<li>Perform Coregistration as the third step.
		<ol>
			<li>Coregister MR1 and b0 MR2 images manually. In the end Verify All Registrations. 
			NOTE: It is possible to perform this step automatically. However, the results may not be always satisfactory in the end.</li>
		</ol>
		</li>
		<li>Perform Tensor computation as the fourth and last step,
		<ol>
			<li>Make sure FA / DEC / ADC are on. If not click ON.</li>
			<li>Click on Compute. This procedure will take only some seconds.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Save all the data and continue with fibertracking. Do not stop without saving everything.</li>
</ol>
3. Fibertracking
NOTE: Anatomic knowledge of the visual pathway is very important for the successful result.
<ol style="margin-left: 40px;">
	<li>Prepare to find the three important points where the fibers have to go through.</li>
	<li>Determine the optic chiasm using anatomical knowledge.
	<ol>
		<li>Use a ROI as a starting point and let the fibers go through. ROIs are defined by the physician.</li>
		<li>Alternatively, segment the suspected region. Click Segmentation on the bottom left and another window will appear. Segmented areas are anatomically defined areas.
		<ol>
			<li>Paint the region manually. Scroll up and down to include the whole optic chiasm. Save the procedure and go back.</li>
		</ol>
		</li>
		<li>Track the fibers either from the region of interest or from the segmented area or both.</li>
		<li>The fibers reach the left geniculate nucleus (LGN), which is the second important point of the visual pathway. The maximum angle was 50. The risk of false tracts will rise with if the angle is too high.
		<ol>
			<li>There is a possibility to segment the LGN as shown with the optic chiasm and then track the fibers. After having segmented the optic chiasm, track fibers which run from the LGN and finish in the optic chiasm or vice versa.</li>
		</ol>
		</li>
		<li>Segment the visual cortex. Proceed like in the case of the optic chiasm. This might take some time as 3DT1-weighted image contains 160 slices.</li>
		<li>Track the fibers from the visual cortex to the LGN. It is possible to track them from the LGN to the visual cortex as well.</li>
		<li>If the visual cortex is invaded by a tumor or edema then use a region of interest in place of a segmented area and then let the fibers run in direction of the LGN. 
		NOTE: If the edema is segmented it sometimes might invade the visual cortex then then the visual cortex might not be able to segmented entirely because the computer can`t distinguish between them. That`s why it is necessary to put a ROI.</li>
		<li>Repeat everything for the other hemisphere.</li>
		<li>Start with the healthy hemisphere first. 
		NOTE: It is possible to start with the other one too but it might be easier to track the fibers of the healthy hemisphere first to become a first idea about the situation. It is not mandatory, it is only an advice.</li>
	</ol>
	</li>
	<li>Segment the cerebral lesion and the edema. Proceed as mentioned above in 3.2.2.
	<ol>
		<li>Assign a color for every segmented area or lesion in order to distinguish better.</li>
	</ol>
	</li>
	<li>Save the procedure after each step in case of unforeseen events or in case of an emergency.</li>
	<li>Export the entire data locally. It is possible to export it to the operating room directly but it isn`t recommended.
	<ol>
		<li>Press File and then Export 3D-Objects. Make sure to export only the Navigation Exam.</li>
		<li>Don`t export the Hybrid Exam.</li>
	</ol>
	</li>
	<li>Enter Cranial. Choose the right patient then press Stealthmerge. Choose 3DT1-weighted images as reference exam.</li>
	<li>Create a 3D-model and insert everything.</li>
	<li>Import the data in the operation room.</li>
</ol>

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The authors declare that they have no competing financial interests.

DTI is a technique enabling the neurosurgeon to visualize white matter tracts in vivo8. The visual pathway is one of these tracts. Although this method provides physicians with new possibilities regarding the treatment of patients with lesions concerning eloquent regions of the brain we have to say that some limitations of this technique do still exist. The first and most obvious challenge is brain shift, which remains an issue under investigation4. After opening the dura mater and after manipulation in the brain by removing the tumor or the cerebrospinal fluid loss we don`t have the same conditions as before surgery. Furthermore DTI is unable to solve the crossing or kissing of fibers and to determine with accuracy the origin and destination of fibers, producing multiple artifacts and false tracts1-3. Another problem is the resolution of fibers in areas of disturbed diffusion, for example due to tumor or peritumoral edema22. Small tracts with different directions within a voxel will not be imaged due secondary to partial volume artefacts28. The possibility of false positive and false negative tracts should always be taken into account. The results might be compromised. Other algorithms have shown the VP in a more complete way, however an international standardized procedure to depict the VP doesn`t exist up to date which might be confusing additionally. The portrayal of the Meyer loop remains a challenge for this protocol. Another limitation might consist in the depiction of the Baum loop. However we couldn`t find any note of the depiction of this loop elsewhere.
As mentioned before this protocol is easily feasible for the everyday routine. However a good preparation is required for a satisfactory outcome. It is necessary to take care that the images are performed strictly axial. It might compromise the quality of the images afterwards if this is not taken into account. A 3DT1-weighted image is always needed for the navigation. The slices should be thin enough in order to have good results. For this protocol we use 2 mm slices with no gaps in between. Respecting the protocol will lead to a good portrayal of the major parts of the VP. The VP was portrayed using multiple ROIs . The VC was always segmented additionally. Others have also used a multiple ROI approach16,17. DTI-angulation has also been tried out. It might have good results for anteroposterior fiberbundles but other fibers might come in an unfortunate position12. Further methods include seeding the fiber tracking from multiple fiducials placed on the optic tract near the LGN11.
Future applications include the use of DTI in brain ischemia, multiple sclerosis, Alzheimer`s disease, portrayal of cranial nerves, gamma knife surgery and others 7, 13,28. They are being used already in some institutions but this is not a routine everywhere. Intrasurgical mapping of optic radiation using subcortical electrical stimulation is a reliable method to identify and preserve this tract during glioma surgery6. Another possibility to monitor the functional integrity of the visual pathway is the intraoperative use of cortically recorded VEPs5,10. Intraoperative use of MRI might be a possibility to reduce the problem which arises with the brain shift alternatively the application of a 3D ultrasound might present an alternative18. Other diffusion imaging and reconstruction schemes have become increasingly relevant to portray the visual pathway. The visual pathway has more fibers and the Meyer loop is more reliably displayed18.

Diffusion tensor imaging (DTI) is used to portray WMT non-invasively in the human brain1. It has been used in the past decade to reduce the risk of harming eloquent areas of the brain during surgery1.
DTI was performed in fifty patients between March 2012 and January 2014 to portray the visual pathway. DTI might improve preservation of eloquent areas of the brain during surgery by providing important information about the anatomical location of white matter tracts. It has been incorporated into strategic planning for resection of complex brain lesions1. However, the portrayal of the visual pathway remains a challenge because there is no standard for the parameters of DTI, the placement of the seed volumes and interpretation of results12.
Different algorithms have been implemented so far 19-21. Some approaches concentrated on deterministic methods 19, 22-25. Others were using probabilistic methods,26,27,29. More recently, techniques using Q-ball tensor fields, diffusion spectral imaging and High Angular Resolution Diffusion Imaging (HARDI) are being used to depict white matter tracts among others the visual pathway 1,13-15,18 . Nevertheless, the necessary time for HARDI is significantly longer with 45 min, the software is not commercially available and emphasizes scientific applications18. The teaching period for HARDI seems to be longer than for DTI18.
The presented protocol is easy feasible and can be used for everyday routine in neurosurgical operations in order to avoid morbidity and improve the postoperative outcome. The additional time for this protocol is less than 9 min which is significantly faster than other protocols1,9,12,16. Acknowledging the fact that many sophisticated algorithms have been developed recently the paper restricts itself to the use of a commercially available and FDA approved software. However it is mandatory to take into account the limitations of this technique which are mentioned above.

<table><tbody><tr><td>3-Tesla-MRI</td><td>General Electric</td><td>Signa LX version 9.1</td><td></td></tr><tr><td>Surgical Navigation System Program</td><td>Medtronic</td><td>9734478</td><td></td></tr><tr><td>Surgical Navigation System Program</td><td>Medtronic</td><td>4500810331&amp;nbsp; 20016318</td><td></td></tr></tbody></table>

dti of the visual pathway - white matter tracts and cerebral lesions

DTI is a technique that identifies white matter tracts (WMT) non-invasively in healthy and non-healthy patients using diffusion measurements. Similar to visual pathways (VP), WMT are not visible with classical MRI or intra-operatively with microscope. DTI will help neurosurgeons to prevent destruction of the VP while removing lesions adjacent to this WMT. We have performed DTI on fifty patients before and after surgery between March 2012 to January 2014. To navigate we used a 3DT1-weighted sequence. Additionally, we performed a T2-weighted and DTI-sequences. The parameters used were, FOV: 200 x 200 mm, slice thickness: 2 mm, and acquisition matrix: 96 x 96 yielding nearly isotropic voxels of 2 x 2 x 2 mm. Axial MRI was carried out using a 32 gradient direction and one b0-image. We used Echo-Planar-Imaging (EPI) and ASSET parallel imaging with an acceleration factor of 2 and b-value of 800 s/mm&#178;. The scanning time was less than 9 min.
The DTI-data obtained were processed using a FDA approved surgical navigation system program which uses a straightforward fiber-tracking approach known as fiber assignment by continuous tracking (FACT). This is based on the propagation of lines between regions of interest (ROI) which is defined by a physician. A maximum angle of 50, FA start value of 0.10 and ADC stop value of 0.20 mm&#178;/s were the parameters used for tractography.
There are some limitations to this technique. The limited acquisition time frame enforces trade-offs in the image quality. Another important point not to be neglected is the brain shift during surgery. As for the latter intra-operative MRI might be helpful. Furthermore the risk of false positive or false negative tracts needs to be taken into account which might compromise the final results.

This protocol enables the physician to portray adequately the major parts of the VP. It can be used with a little amount of time in order to prevent damages in patients with cerebral lesions next to eloquent areas. Postoperative controls show also good results. VP is portrayed in Figure 7 after the patient was operated from a glioblastoma. Figure 2 shows the VP after recurrence of a glioblastoma. The authors recognize the fact of the difficulties presented by this protocol to depict the Meyer loop which remains a major challenge.
<img alt="Figure 1" src="/files/ftp_upload/51946/51946fig1highres.jpg" /> 
Figure 1.&#160;VP 1: Glioblastoma before surgery. The tumor is red. Edema is shown in purple and gold represents the VP. Displacement of the VP on the other side is shown. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/51946/51946fig2highres.jpg" /> 
Figure 2.&#160;VP 2: Glioblastoma recurrence. The tumor is red. The edema (purple) surrounds the VP (gold). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/51946/51946fig3highres.jpg" /> 
Figure 3.&#160;VP 3: Glioblastoma occipital. The tumor is red. Disruption of the VP (gold) anteriorly by tumor and edema (purple). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/51946/51946fig4highres.jpg" /> 
Figure 4.&#160;VP 4: Temporal glioblastoma. The tumor (red) touches the VP (gold) anteriorly. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/51946/51946fig5highres.jpg" /> 
Figure 5.&#160;VP 5: Glioblastoma of the corpus callosum. The tumor (red) with edema (purple) surround the VP (gold). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/51946/51946fig6highres.jpg" /> 
Figure 6.&#160;VP 6: Glioblastoma anterior. The tumor (red) and the edema (purple) surround the VP (gold). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" src="/files/ftp_upload/51946/51946fig7highres.jpg" /> 
Figure 7.&#160;VP 7: VP after glioblastoma surgery. Black represents the cavity of the tumor. Edema (purple) is adjacent to the VP (gold). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" src="/files/ftp_upload/51946/51946fig8highres.jpg" /> 
Figure 8.&#160;Preparation for fibertracking. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" src="/files/ftp_upload/51946/51946fig9highres.jpg" /> 
Figure 9.&#160;Preparation for fibertracking / VP. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" src="/files/ftp_upload/51946/51946fig10highres.jpg" /> 
Figure 10.&#160;Preparation for fibertracking 3. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 11" src="/files/ftp_upload/51946/51946fig11highres.jpg" /> 
Figure 11.&#160;Preparation for fibertracking 4. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51946/51946fig11large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 12" src="/files/ftp_upload/51946/51946fig12highres.jpg" /> 
Figure 12.&#160;Preparation for fibertracking 5.

Watch this Scientific Journal Video about DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions at JoVE.com

DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Diffusion tensor imaging (DTI) was performed to try to depict the major parts of the visual pathway. The goal was to use an FDA approved standard commercial workstation which could be used for everyday routine in order to try to reduce postoperative damage of the visual pathway in the patients.

DTI is a technique that identifies white matter tracts (WMT) non-invasively in healthy and non-healthy patients using diffusion measurements. Similar to ...

dti-of-the-visual-pathway-white-matter-tracts-and-cerebral-lesions

Universidad San Sebastian

Research

JoVE Journal

Medicine

14.0K Views.  Centre Hospitalier de Luxembourg. Diffusion tensor imaging (DTI) was performed to try to depict the major parts of the visual pathway. The goal was to use an FDA approved standard commercial workstation which could be used for everyday routine in order to try to reduce postoperative damage of the visual pathway in the patients.

Video: DTI of the Visual Pathway - White Matter Tracts and Cerebral Lesions

Dissection of Human Vitreous Body Elements for Proteomic Analysis

The vitreous is an optically clear, collagenous extracellular matrix that fills the inside of the eye and overlies the retina. 1,2 Abnormal interactions between vitreous substructures and the retina underlie several vitreoretinal diseases, including retinal tear and detachment, macular pucker, macular hole, age-related macular degeneration, vitreomacular traction, proliferative vitreoretinopathy, proliferative diabetic retinopathy, and inherited vitreoretinopathies. 1,2 The molecular composition of the vitreous substructures is not known. Since the vitreous body is transparent with limited surgical access, it has been difficult to study its substructures at the molecular level. We developed a method to separate and preserve these tissues for proteomic and biochemical analysis. The dissection technique in this experimental video shows how to isolate vitreous base, anterior hyaloid, vitreous core, and vitreous cortex from postmortem human eyes. One-dimensional SDS-PAGE analyses of each vitreous component showed that our dissection technique resulted in four unique protein profiles corresponding to each substructure of the human vitreous body. Identification of differentially compartmentalized proteins will reveal candidate molecules underlying various vitreoretinal diseases.

This video shows an effective technique for differentiating and dissecting the various semi-transparent structures of the human vitreous body in post mortem eyes.

The vitreous is an optically clear, collagenous extracellular matrix that fills the inside of the eye and overlies the retina. 1,2 Abnormal interactions ...

The Application Of Permanent Middle Cerebral Artery Ligation in the Mouse

Focal cerebral ischemia is among the most common type of stroke seen in patients. Due to the clinical significance there has been a prolonged effort to develop suitable animal models to study the events that unfold during ischemic insult. These techniques include transient or permanent, focal or global ischemia models using many different animal models, with the most common being rodents.
The permanent MCA ligation method which is also referred as pMCAo in the literature is used extensively as a focal ischemia model in rodents 1-6. This method was originally described for rats by Tamura et al. in 1981 7. In this protocol a craniotomy was used to access the MCA and the proximal regions were occluded by electrocoagulation. The infarcts involve mostly cortical and sometimes striatal regions depending on the location of the occlusion. This technique is now well established and used in many laboratories 8-13. Early use of this technique led to the definition and description of &#x201C;infarct core&#x201D; and &#x201C;penumbra&#x201D; 14-16, and it is often used to evaluate potential neuroprotective compounds 10, 12, 13, 17. Although the initial studies were performed in rats, permanent MCA ligation has been used successfully in mice with slight modifications 18-20 .
This model yields reproducible infarcts and increased post-survival rates. Approximately 80% of the ischemic strokes in humans happen in the MCA area 21 and thus this is a very relevant model for stroke studies. Currently, there is a paucity of effective treatments available to stroke patients, and thus there is a need for good models to test potential pharmacological compounds and evaluate physiological outcomes. This method can also be used for studying intracellular hypoxia response mechanisms in vivo. 
Here, we present the MCA ligation surgery in a C57/BL6 mouse. We describe the pre-surgical preparation, MCA ligation surgery and 2,3,5 Triphenyltetrazolium chloride (TTC) staining for quantification of infarct volumes.

Middle cerebral artery (MCA) ligation is a technique to study focal cerebral ischemia in animal models. In this method, the middle cerebral artery is exposed by craniotomy and ligated by cauterization. This method gives highly reproducible infarct volumes and increased post-operative survival rates compared to other methods available.

Focal cerebral ischemia is among the most common type of stroke seen in patients. Due to the clinical significance there has been a prolonged effort to ...

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral symptoms displayed by individuals with autism. While structural neuroimaging findings have provided some insights into brain abnormalities in autism, the consistency of such findings is questionable. Functional neuroimaging, on the other hand, has been more fruitful in this regard because autism is a disorder of dynamic processing and allows examination of communication between cortical networks, which appears to be where the underlying problem occurs in autism. Functional connectivity is defined as the temporal correlation of spatially separate neurological events1. Findings from a number of recent fMRI studies have supported the idea that there is weaker coordination between different parts of the brain that should be working together to accomplish complex social or language problems2,3,4,5,6. One of the mysteries of autism is the coexistence of deficits in several domains along with relatively intact, sometimes enhanced, abilities. Such complex manifestation of autism calls for a global and comprehensive examination of the disorder at the neural level. A compelling recent account of the brain functioning in autism, the cortical underconnectivity theory,2,7 provides an integrating framework for the neurobiological bases of autism. The cortical underconnectivity theory of autism suggests that any language, social, or psychological function that is dependent on the integration of multiple brain regions is susceptible to disruption as the processing demand increases. In autism, the underfunctioning of integrative circuitry in the brain may cause widespread underconnectivity. In other words, people with autism may interpret information in a piecemeal fashion at the expense of the whole. Since cortical underconnectivity among brain regions, especially the frontal cortex and more posterior areas 3,6, has now been relatively well established, we can begin to further understand brain connectivity as a critical component of autism symptomatology.
A logical next step in this direction is to examine the anatomical connections that may mediate the functional connections mentioned above. Diffusion Tensor Imaging (DTI) is a relatively novel neuroimaging technique that helps probe the diffusion of water in the brain to infer the integrity of white matter fibers. In this technique, water diffusion in the brain is examined in several directions using diffusion gradients. While functional connectivity provides information about the synchronization of brain activation across different brain areas during a task or during rest, DTI helps in understanding the underlying axonal organization which may facilitate the cross-talk among brain areas. This paper will describe these techniques as valuable tools in understanding the brain in autism and the challenges involved in this line of research.

Neuroimaging techniques, such as functional MRI and Diffusion Tensor Imaging have become increasingly useful in characterizing the cognitive and neural deficits in autism. An examination of brain connectivity in autism at a network level along with adaptations for scanning children with developmental disabilities is presented.

Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral ...

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)1, 2 protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for the purpose of monitoring task-relevant brain activity in networks of interest.

We describe a novel approach for simultaneous analysis of brain function and structure using magnetic resonance imaging (MRI). We assess brain structure with high-resolution diffusion-weighted imaging and white-matter fiber tractography. Unlike standard structural MRI, these techniques allow us to directly relate anatomical connectivity to functional properties of brain networks.

The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when ...

Neuroscience

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. 	
DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels.	
In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.

Diffusion tensor imaging (DTI) basically serves as an MRI-based tool to identify in vivo the microstructure of the brain and pathological processes due to neurological disorders within the cerebral white matter. DTI-based analyses allow for application to brain diseases both at the group level and in single subject data.

Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present ...

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography

In albinism, the number of ipsilaterally projecting retinal ganglion cells (RGCs) is significantly reduced. The retina and optic chiasm have been proposed as candidate sites for misrouting. Since a correlation between the number of lateral geniculate nucleus (LGN) relay neurons and LGN size has been shown, and based on previously reported reductions in LGN volumes in human albinism, we suggest that fiber projections from LGN to the primary visual cortex (V1) are also reduced. Studying structural differences in the visual system of albinism can improve the understanding of the mechanism of misrouting and subsequent clinical applications. Diffusion data and tractography are useful for mapping the OR (optic radiation). This manuscript describes two algorithms for OR reconstruction in order to compare brain connectivity in albinism and controls.An MRI scanner with a 32-channel head coil was used to acquire structural scans. A T1-weighted 3D-MPRAGE sequence with 1 mm3 isotropic voxel size was used to generate high-resolution images for V1 segmentation. Multiple proton density (PD) weighted images were acquired coronally for right and left LGN localization. Diffusion tensor imaging (DTI) scans were acquired with 64 diffusion directions. Both deterministic and probabilistic tracking methods were run and compared, with LGN as the seed mask and V1 as the target mask. Though DTI provides relatively poor spatial resolution, and accurate delineation of OR may be challenging due to its low fiber density, tractography has been shown to be advantageous both in research and clinically. Tract based spatial statistics (TBSS) revealed areas of significantly reduced white matter integrity within the OR in patients with albinism compared to controls. Pairwise comparisons revealed a significant reduction in LGN to V1 connectivity in albinism compared to controls. Comparing both tracking algorithms revealed common findings, strengthening the reliability of the technique.

This manuscript describes deterministic and probabilistic algorithms for white matter (WM) reconstruction, used to examine differences in optic radiation (OR) connectivity between albinism and controls. Although probabilistic tractography follows the true course of nerve fibers more closely, deterministic tractography was run to compare the reliability and reproducibility of both techniques.

In albinism, the number of ipsilaterally projecting retinal ganglion cells (RGCs) is significantly reduced. The retina and optic chiasm have been proposed ...

Fiber Connections of the Supplementary Motor Area Revisited: Methodology of Fiber Dissection, DTI, and Three Dimensional Documentation

The purpose of this study is to show the methodology for the examination of the white matter connections of the supplementary motor area (SMA) complex (pre-SMA and SMA proper) using a combination of fiber dissection techniques on cadaveric specimens and magnetic resonance (MR) tractography. The protocol will also describe the procedure for a white matter dissection of a human brain, diffusion tensor tractography imaging, and three-dimensional documentation. The fiber dissections on human brains and the 3D documentation were performed at the University of Minnesota, Microsurgery and Neuroanatomy Laboratory, Department of Neurosurgery. Five postmortem human brain specimens and two whole heads were prepared in accordance with Klingler's method. Brain hemispheres were dissected step by step from lateral to medial and medial to lateral under an operating microscope, and 3D images were captured at every stage. All dissection results were supported by diffusion tensor imaging. Investigations on the connections in line with Meynert's fiber tract classification, including association fibers (short, superior longitudinal fasciculus I and frontal aslant tracts), projection fibers (corticospinal, claustrocortical, cingulum, and frontostriatal tracts), and commissural fibers (callosal fibers) were also conducted.

The purpose of this study is to show each step of the fiber dissection technique on human cadaveric brains, the 3D documentation of these dissections, and the diffusion tensor imaging of the anatomically dissected fiber pathways.

The purpose of this study is to show the methodology for the examination of the white matter connections of the supplementary motor area (SMA) complex ...

Diffusion Tensor Magnetic Resonance Imaging in Chronic Spinal Cord Compression

Chronic spinal cord compression is the most common cause of spinal cord impairment in patients with nontraumatic spinal cord damage. Conventional magnetic resonance imaging (MRI) plays an important role in both confirming the diagnosis and evaluating the degree of compression. However, the anatomical detail provided by conventional MRI is not sufficient to accurately estimate neuronal damage and/or assess the possibility of neuronal recovery in chronic spinal cord compression patients. In contrast, diffusion tensor imaging (DTI) can provide quantitative results according to the detection of water molecule diffusion in tissues. In the present study, we develop a methodological framework to illustrate the application of DTI in chronic spinal cord compression disease. DTI fractional anisotropy (FA), apparent diffusion coefficients (ADCs), and eigenvector values are useful for visualizing microstructural pathological changes in the spinal cord. Decreased FA and increases in ADCs and eigenvector values were observed in chronic spinal cord compression patients compared to healthy controls. DTI could help surgeons understand spinal cord injury severity and provide important information regarding prognosis and neural functional recovery. In conclusion, this protocol provides a sensitive, detailed, and noninvasive tool to evaluate spinal cord compression.

Here, we present a protocol for the application of diffusion tensor imaging parameters to evaluate spinal cord compression.

Chronic spinal cord compression is the most common cause of spinal cord impairment in patients with nontraumatic spinal cord damage. Conventional magnetic ...

Advanced Diffusion Imaging in The Hippocampus of Rats with Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is the most common type of acquired brain injury. Since patients with traumatic brain injury show a tremendous variability and heterogeneity (age, gender, type of trauma, other possible pathologies, etc.), animal models play a key role in unraveling factors that are limitations in clinical research. They provide a standardized and controlled setting to investigate the biological mechanisms of injury and repair following TBI. However, not all animal models mimic the diffuse and subtle nature of mTBI effectively. For example, the commonly used controlled cortical impact (CCI) and lateral fluid percussion injury (LFPI) models make use of a craniotomy to expose the brain and induce widespread focal trauma, which are not commonly seen in mTBI. Therefore, these experimental models are not valid to mimic mTBI. Thus, an appropriate model should be used to investigate mTBI. The Marmarou weight drop model for rats induces similar microstructural alterations and cognitive impairments as seen in patients who sustain mild trauma; therefore, this model was selected for this protocol. Conventional computed tomography and magnetic resonance imaging (MRI) scans commonly show no damage following a mild injury, because mTBI induces often only subtle and diffuse injuries. With diffusion weighted MRI, it is possible to investigate microstructural properties of brain tissue, which can provide more insight into the microscopic alterations following mild trauma. Therefore, the goal of this study is to obtain quantitative information of a selected region-of-interest (i.e., hippocampus) to follow up disease progression after obtaining a mild and diffuse brain injury.

The overall goal of this procedure is to obtain quantitative microstructural information of the hippocampus in a rat with mild traumatic brain injury. This is done using an advanced diffusion-weighted magnetic resonance imaging protocol and region-of-interest based analysis of parametric diffusion maps.

Mild traumatic brain injury (mTBI) is the most common type of acquired brain injury. Since patients with traumatic brain injury show a tremendous ...

Using Diffusion Tensor Imaging in Traumatic Brain Injury

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212;University of Southern California
Traditional brain imaging techniques using MRI are very good at visualizing the gross structures of the brain. A structural brain image made with MRI provides high contrast of the borders between gray and white matter, and information about the size and shape of brain structures. However, these images do not detail the underlying structure and integrity of white matter networks in the brain, which consist of axon bundles that interconnect local and distant brain regions.
Diffusion MRI uses pulse sequences that are sensitive to the diffusion of water molecules. By measuring the direction of diffusion, it is possible to make inferences about the structure of white matter networks in the brain. Water molecules within an axon are constrained in their movements by the cell membrane; instead of randomly moving in every direction with equal probability (isotropic movement), they are more likely to move in certain directions, in parallel with the axon (anisotropic movement; Figure 1). Therefore, measures of diffusion anisotropy are thought to reflect properties of the white matter such as fiber density, axon thickness, and degree of myelination. One common measure is fractional anisotropy (FA). FA values range from 0, which represents completely isotropic movement, to 1, reflecting maximum anisotropy.
<img alt="Figure 1" src="/files/ftp_upload/10276/10276fig1.jpg" /> 
Figure 1: Diffusion anisotropy. When the direction of diffusion is unconstrained and random, movement is measured in all directions equally. This is isotropic diffusion (A). When water molecules are contained within the axon of a neuron, diffusion is anisotropic, tending to occur more frequently along the direction of the axon (B). <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/10276/10276fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In this experiment we will use diffusion tensor imaging (DTI) to measure white matter integrity in traumatic brain injury (TBI). TBI occurs when an external force injures the brain, such as a blow to the head or a sudden movement like the kind that might occur in a car accident. This type of brain injury from mechanical forces is associated with diffuse axonal injury-damage to white matter throughout the brain. Because it is an injury affecting white matter integrity, standard neuroimaging techniques may not reveal the damage. However, measures of diffusion are especially sensitive to these anatomical changes. Following a study by Kraus et al.1, we compare a group of healthy controls to a group of people with TBI and use diffusion imaging to measure the effect of TBI on cerebral white matter. Furthermore, we will test the relationship between white matter integrity and cognitive function using an attention task.2 This study uses a region of interest (ROI) approach focusing on three white matter tracts: the splenium of the corpus callosum, the anterior corona radiata, and the superior longitudinal fasciculus (Figure 2).
<img alt="Figure 2" src="/files/ftp_upload/10276/10276fig2.jpg" /> 
Figure 2: Regions of interest. The three ROIs, defined from the ICBM DTI-81 atlas, are shown here in horizontal slices through the brain. In green is the splenium of the corpus callosum. The splenium is the most posterior part of the corpus callosum. In blue is the anterior corona radiata. The superior longitudinal fasciculus is shown in red. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/10276/10276fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Diffusion Tensor Imaging in Traumatic Brain Injury

Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel&#8212;University of Southern California
Traditional brain imaging techniques using MRI are ...