COMPREHENSIVE 3D FIBER TRACKING AS A NEW VISUALIZATION SYSTEM IN BRAIN STUDIES

2007 ◽  
Vol 07 (04) ◽  
pp. 749-765 ◽  
Author(s):  
DANMARY SANCHEZ ◽  
MALEK ADJOUADI ◽  
NOLAN R. ALTMAN ◽  
DANIEL SANCHEZ ◽  
BYRON BERNAL
Keyword(s):  
Diffusion Tensor ◽  
3D Visualization ◽  
Fiber Tracking ◽  
Brain Images ◽  
Visualization System ◽  
Fiber Tracts ◽  
Desirable Outcome ◽  
White Matter Fiber Tracts ◽  
Magnetic Resonance Imaging Mri ◽  
Using Data

Comprehensive spatial visualization of fiber tracts from all perspectives is a highly desirable outcome in brain studies. To achieve this aim, this study establishes the foundation for a new 3D visual interface that integrates Magnetic Resonance Imaging (MRI) to Diffusion Tensor Imaging (DTI). The need for such an interface is critical for understanding brain dynamics, and for providing accurate diagnosis of key brain dysfunctions, in terms of neuronal connectivity in the human brain. Two research fronts were explored: (1) the development of new image processing techniques resulting in comprehensive visualization mechanisms that accurately establish relational positioning of neuronal fiber tracts and key landmarks in semi-transparent 3D brain images, and (2) the design of key algorithms that do not tax the computational requirements of 3D rendering and feature extraction using 2D MRI and DTI frames, remaining within practical time constraints. The system was evaluated using data from thirty patients and volunteers with the Brain Institute at Miami Children's Hospital. The highly integrated and fully embedded fiber-tracking software system provides an optimal research environment for innovative visualization mechanisms of white matter fiber tracts. This 3D visualization system reached the implementation level that makes it ready for deployment at other clinical sites.

scholarly journals Meyer’s Loop Anatomy Demonstrated Using Diffusion Tensor MR Imaging and Fiber Tractography at 3T

2014 ◽  
Vol 60 (5) ◽  
pp. 215-222 ◽  
Author(s):  
Cristina Goga ◽  
Zeynep Firat ◽  
Klara Brinzaniuc ◽  
Is Florian
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Region Of Interest ◽  
Fiber Tractography ◽  
Brain Images ◽  
3 Dimensional ◽  
Software Release ◽  
Magnetic Resonance Imaging Mri ◽  
Meyer’S Loop

Abstract Objective: The ultimate anatomy of the Meyer’s loop continues to elude us. Diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) may be able to demonstrate, in vivo, the anatomy of the complex network of white matter fibers surrounding the Meyer’s loop and the optic radiations. This study aims at exploring the anatomy of the Meyer’s loop by using DTI and fiber tractography. Methods: Ten healthy subjects underwent magnetic resonance imaging (MRI) with DTI at 3 T. Using a region-of-interest (ROI) based diffusion tensor imaging and fiber tracking software (Release 2.6, Achieva, Philips), sequential ROI were placed to reconstruct visual fibers and neighboring projection fibers involved in the formation of Meyer’s loop. The 3-dimensional (3D) reconstructed fibers were visualized by superimposition on 3-planar MRI brain images to enhance their precise anatomical localization and relationship with other anatomical structures. Results: Several projection fiber including the optic radiation, occipitopontine/parietopontine fibers and posterior thalamic peduncle participated in the formation of Meyer’s loop. Two patterns of angulation of the Meyer’s loop were found. Conclusions: DTI with DTT provides a complimentary, in vivo, method to study the details of the anatomy of the Meyer’s loop.

Relevant Biophysical Parameters Discrimination along Corticospinal Tract in Patients with Stroke Using Convolutional Neural Networks

2021 ◽  
Vol 51 ◽  
pp. 95-103
Author(s):  
Abderrazek Zeraii ◽  
Amine Ben Slama ◽  
Lazhar Rmili ◽  
Cyrine Drissi ◽  
Mokhtar Mars ◽  
...  
Keyword(s):  
Motor Neurons ◽  
Corticospinal Tract ◽  
Diffusion Tensor ◽  
Biophysical Parameters ◽  
Spinal Motor Neurons ◽  
Fiber Tracts ◽  
Subacute Stroke ◽  
Quantitative Metrics ◽  
White Matter Fiber Tracts

Stroke remains the leading source of long-term disability. As the only direct descending motor pathway, the corticospinal tract (CST) is the primary pathway to innervate spinal motor neurons and one of the most well studied tracts in human neuroanatomy. Its clinical significance can be demonstrated in many distinguished traumatic situations and diseases such as stroke. Along‐tract statistics analysis enables the extraction of quantitative diffusion metrics along specific white matter fiber tracts. Besides quantitative metrics derived from classical diffusion tensor imaging (DTI), such as fractional anisotropy and diffusivities. In this study, we extracted DTI derived quantitative microstructural diffusion metrics along the CST tract in patients with moderate to severe subacute stroke. Respectively DTI metric of individual patient's fiber tract was then plotted. This approach may be useful for future studies that may compare in two different time (acute and chronic). The contribution of this work presents a totally computerized method of DTI image recognition based on conventional neural network (CNN) in order to supply quantitative appraisal of clinical characteristics. The obtained results have achieved an important classification (Accuracy=94.12%) when applying the CNN. The proposed methodology enables us to assess the classification of the used DTI images database within a reduced processing time. Experimental results prove the success of the proposed rating system for a suitable analysis of microstructural diffusion when compared to previous work.

scholarly journals Quantitative diffusion tensor MRI-based fiber tracking of human skeletal muscle

2007 ◽  
Vol 103 (2) ◽  
pp. 673-681 ◽  
Author(s):  
Drew A. Lansdown ◽  
Zhaohua Ding ◽  
Megan Wadington ◽  
Jennifer L. Hornberger ◽  
Bruce M. Damon
Keyword(s):  
Muscle Fiber ◽  
Diffusion Tensor ◽  
Fiber Tracking ◽  
Laboratory Frame ◽  
Mean Value ◽  
Pennation Angle ◽  
Frame Of Reference ◽  
Fiber Tracts ◽  
Angle Measurements ◽  
The Mean

Diffusion-tensor magnetic resonance imaging (DT-MRI) offers great potential for understanding structure-function relationships in human skeletal muscles. The purposes of this study were to demonstrate the feasibility of using in vivo human DT-MRI fiber tracking data for making pennation angle measurements and to test the hypothesis that heterogeneity in the orientation of the tibialis anterior (TA) muscle's aponeurosis would lead to heterogeneity in pennation angle. Eight healthy subjects (5 male) were studied. T1-weighted anatomical MRI and DT-MRI data were acquired of the TA muscle. Fibers were tracked from the TA's aponeurosis by following the principal eigenvector. The orientations of the aponeurosis and muscle fiber tracts in the laboratory frame of reference and the orientation of the fiber tracts with respect to the aponeurosis [i.e., the pennation angle (θ)] were determined. The muscle fiber orientations, when expressed relative to the laboratory frame of reference, did not change as functions of superior-to-inferior position. The sagittal and coronal orientations of the aponeurosis did not change in practically significant manners either, but the aponeurosis′ axial orientation changed by ∼40°. As a result, the mean value for θ decreased from 16.3 (SD 6.9) to 11.4° (SD 5.0) along the muscle's superior-to-inferior direction. The mean value of θ was greater in the deep than in the superficial compartment. We conclude that pennation angle measurements of human muscle made using DT-MRI muscle fiber tracking are feasible and reveal that in the foot-head direction, there is heterogeneity in the pennation properties of the human TA muscle.

scholarly journals Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

2017 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Node Degree ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
Structural Brain Network ◽  
Structural Networks

AbstractIn diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

Diffusion Tensor Imaging and Fiber Tractography

2009 ◽  
pp. 229-246
Author(s):  
Evanthia E. Tripoliti ◽  
Dimitrios I. Fotiadis ◽  
Konstantia Veliou
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Cerebral White Matter ◽  
Tissue Microstructure ◽  
Diffusion Weighted Images ◽  
Fiber Tracts ◽  
Diffusion Weighted ◽  
Magnetic Resonance Imaging Mri

Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) modality which can significantly improve our understanding of the brain structures and neural connectivity. DTI measures are thought to be representative of brain tissue microstructure and are particularly useful for examining organized brain regions, such as white matter tract areas. DTI measures the water diffusion tensor using diffusion weighted pulse sequences which are sensitive to microscopic random water motion. The resulting diffusion weighted images (DWI) display and allow quantification of how water diffuses along axes or diffusion encoding directions. This can help to measure and quantify the tissue’s orientation and structure, making it an ideal tool for examining cerebral white matter and neural fiber tracts. In this chapter the authors discuss the theoretical aspects of DTI, the information that can be extracted from DTI data, and the use of the extracted information for the reconstruction of fiber tracts and the diagnosis of a disease. In addition, a review of known fiber tracking algorithms is presented.

scholarly journals Motor cortex gliomas induces microstructural changes of large fiber tracts revealed by TBSS

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Xiangdong Wang ◽  
Chunyao Zhou ◽  
Lei Wang ◽  
Yinyan Wang ◽  
Tao Jiang
Keyword(s):  
White Matter ◽  
Motor Cortex ◽  
Diffusion Tensor ◽  
Early Stage ◽  
Mean Diffusivity ◽  
Cerebral White Matter ◽  
Control Group ◽  
Fiber Tracts ◽  
3.0 T ◽  
White Matter Fiber Tracts

Abstract Gliomas grow and invade along white matter fiber tracts. This study assessed the effects of motor cortex gliomas on the cerebral white matter fiber bundle skeleton. The motor cortex glioma group included 21 patients, and the control group comprised 14 healthy volunteers. Both groups underwent magnetic resonance imaging-based 3.0 T diffusion tensor imaging. We used tract-based spatial statistics to analyze the characteristics of white matter fiber bundles. The left and right motor cortex glioma groups were analyzed separately from the control group. Results were statistically corrected by the family-wise error rate. Compared with the controls, patients with left motor cortex gliomas exhibited significantly reduced fractional anisotropy and an increased radial diffusivity in the corpus callosum. The alterations in mean diffusivity (MD) and the axial diffusivity (AD) were widely distributed throughout the brain. Furthermore, atlas-based analysis showed elevated MD and AD in the contralateral superior fronto-occipital fasciculus. Motor cortex gliomas significantly affect white matter fiber microstructure proximal to the tumor. The range of affected white matter fibers may extend beyond the tumor-affected area. These changes are primarily related to early stage tumor invasion.

scholarly journals Endoscopic Surgery for Supratentorial Deep Cavernous Malformation Adjacent to Cortical Spinal Tract: Preliminary Experience and Technical Note

2021 ◽  
Vol 12 ◽  
Author(s):  
Fuxin Lin ◽  
Chunwang Li ◽  
Xiaorong Yan ◽  
Dengliang Wang ◽  
Yuanxiang Lin ◽  
...  
Keyword(s):  
Endoscopic Surgery ◽  
Diffusion Tensor ◽  
Mean Value ◽  
Technical Note ◽  
Motor Deficits ◽  
Cavernous Malformations ◽  
Fiber Tracts ◽  
Fiber Number ◽  
Magnetic Resonance Imaging Mri ◽  
Poor Outcomes

In this study, we aimed to introduce a technical note and to explore the efficacy of endoscopic surgery combined with diffusion tensor imaging (DTI) navigation for supratentorial deep cerebral cavernous malformations (CCM). A prospectively maintained database of CCM patients was reviewed to identify all CCM patients treated by endoscopic surgery. The sagittal T1-weighted anatomical magnetic resonance imaging (MRI) and DTI were acquired before surgery. Endoscopic surgery was planned and performed based on preoperative DTI images and intraoperative DTI navigation. All patients were followed up more than 6 months. Motor function deficit and modified Rankin scale (mRS) scores were documented on follow-up. A final mRS score of 0–2 was considered a good outcome, and a final mRS score >2 was considered a poor outcome. Second DTI and 3DT1 were performed at 3 months after surgery. We tracked the ipsilateral corticospinal tract (CST) on pre- and postoperative DTI images. The overall mean FA values and the number of fibers of tracked CST were compared on pre- and postoperative DTI images. Risk factors associated with motor deficits and poor outcomes were analyzed. Seven patients with deep CCM and treated by endoscopic surgery were enrolled in this study. The mean value of preoperative mRS was 1.5 ± 0.98, but that score recovered to 0.86 ± 1.22 3 months later. The mRS scores were improved significantly according to statistical analysis (p = 0.012). According to the Spearman non-parametric test, only the fiber number of ipsilateral CST on postoperative DTI was significantly associated with muscle strength 6 months after surgery (p = 0.032). Compared with preoperative CST characteristics on DTI, the change of FA value (p = 0.289) and fiber number (p = 0.289) of ipsilateral CST on postoperative DTI was not significant It meant that the CST was protected during endoscopic surgery. Endoscopic surgery based on DTI navigation might be an effective method to protect fiber tracts in supratentorial deep CCM patients and improve long-term outcomes. However, more studies and cases are needed to confirm our findings.

scholarly journals QUANTITATIVE EXAMINATION OF A NOVEL CLUSTERING METHOD USING MAGNETIC RESONANCE DIFFUSION TENSOR TRACTOGRAPHY

2008 ◽  
Vol 31 (4) ◽  
pp. 24
Author(s):  
Aristotle N Voineskos ◽  
L J O’Donnell ◽  
N J Lobaugh ◽  
D Markant ◽  
M Niethammer ◽  
...  
Keyword(s):  
Diffusion Tensor ◽  
A Priori ◽  
Region Of Interest ◽  
Clustering Method ◽  
Fiber Tracts ◽  
Clustering Approach ◽  
White Matter Fiber Tracts ◽  
Highly Correlated ◽  
High Level

Introduction: MR diffusion tensor imaging (DTI) is the most powerful and currentlythe only way to visualize the organization of white matter fiber tracts in vivo. As this is a relatively newimaging technique, new tools are developed for quantifying fiber tracts, andrequire evaluation. We examined scalar indices of the diffusion tensor with two different tractography methods. We compared a novel clustering approach with a multiple region of interest (MROI) approach in a healthy and disease (schizophrenia) population. Methods: DTI images were acquired in 12 participants (n=6 patients withschizophrenia: 58 ± 12 years; n=6 controls: 57 ± 21 years) on a 1.5 Tesla GE system with diffusion gradients applied in 23 non-collinear directions, repeated three times. Tractography andfiber tract creation was performed using 3D Slicer software. Interraterreliability of the clustering approach and its similarity to the MROI methodwere evaluated. Results: The clustering approach was reliable both quantitatively and spatially (k > 0.8 for all tracts). There was high spatial(voxel-based) agreement between the clustering and MROI methods. Fractionalan isotropy and trace values were highly correlated between the clustering and MROI methods (p < 0.001 for all tracts). Discussion: Our clustering method has excellent interrater reliability and thereis a high level of agreement between our clustering method and the MROI method, both quantitatively and spatially. The clustering method is less susceptible touser bias. Moreover, not limited by a priori predictions, our clustering method may be a more robust and efficient way to identify and measure fiber tracts of interest. (colour figure available in PDF version)

Differences in Analysis Methods of the Human Uncinate Fasciculus Using Diffusion Tensor MRI

2013 ◽  
pp. 162-170
Author(s):  
Tetsuo Sato ◽  
Kotaro Minato
Keyword(s):  
Magnetic Resonance Imaging ◽  
Functional Role ◽  
Diffusion Tensor ◽  
Region Of Interest ◽  
Fiber Tracking ◽  
Uncinate Fasciculus ◽  
Temporal Lobes ◽  
Analysis Methods ◽  
Magnetic Resonance Imaging Mri

The human uncinate fasciculus is an important cortico-cortical white matter pathway that directly connects the frontal and temporal lobes, but its exact functional role is not yet known. Using diffusion tensor Magnetic Resonance Imaging (MRI), the uncinate fasciculus can be extracted and its volume calculated. DTI metrics such as fractional anisotropy for the uncinate fasciculus can also be analyzed, but there are currently three different methods for this analysis. DTI reports on the uncinate fasciculus are conducted using region of interest, voxel-based, and fiber tracking deterministic approaches. Due to these differences in analysis methods, prior studies report conflicting levels of uncinate asymmetry measured with diffusion anisotropy. Here, the authors briefly introduce these three different methods for measuring uncinate asymmetry values and compare the results. This result can lead to a better understanding of the role of the uncinate fasciculus in future behavioral and clinical studies.

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