Confirmation of a gyral bias in diffusion MRI fiber tractography.
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ABSTRACT:
SUBMITTER: Schilling K
PROVIDER: S-EPMC5807146 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In recent years, several new diffusion MRI approaches have been proposed to explore microstructural properties of the white matter, such as Q-ball imaging and spherical deconvolution-based techniques to estimate the orientation distribution function. These methods can describe the estimated diffusion profile with a higher accuracy than the more conventional second-rank diffusion tensor imaging technique. Despite many important advances, there are still inconsistent findings between different models that investigate the "crossing fibers" issue. Due to the high information content and the complex nature of the data, it becomes virtually impossible to interpret and compare results in a consistent manner. In this work, we present novel fiber tractography visualization approaches that provide a more complete picture of the microstructural architecture of fiber pathways: multi-fiber hyperstreamlines and streamribbons. By visualizing, for instance, the estimated fiber orientation distribution along the reconstructed tract in a continuous way, information of the local fiber architecture is combined with the global anatomical information derived from tractography. Facilitating the interpretation of diffusion MRI data, this approach can be useful for comparing different diffusion reconstruction techniques and may improve our understanding of the intricate white matter network.
| S-EPMC3839966 | biostudies-literature
Project description:BackgroundDiffusion tensor imaging (DTI) has been applied in the lumbar and sacral nerves in vivo, but information about the reproducibility of this method is needed before DTI can be used reliably in clinical practice across centers.PurposeIn this multicenter study the reproducibility of DTI of the lumbosacral nerves in healthy volunteers was investigated.Study typeProspective control series.SubjectsTwenty healthy subjects.Field strength/sequence3T MRI. 3D turbo spin echo, and 3.0 mm isotropic DTI scan.AssessmentThe DTI scan was performed three times (twice in the same session, intrascan reproducibility, and once after an hour, interscan reproducibility). At site 2, 1 week later, the protocol was repeated (interweek reproducibility). Fiber tractography (FT) of the lumbar and sacral nerves (L3-S2) was performed to obtain values for fractional anisotropy, mean, axial, and radial diffusivity.Statistical testsReproducibility was determined using the intraclass correlation coefficient (ICC), and power calculations were performed.ResultsFT was successful and reproducible in all datasets. ICCs for all diffusion parameters were high for intrascan (ranging from 0.70-0.85), intermediate for interscan (ranging from 0.61-0.73), and interweek reliability (ranging from 0.58-0.62). There were small but significant differences between the interweek diffusivity values (P < 0.0005). Depending on the effect size, nerve location, and parameter of interest, power calculations showed that sample sizes between 10 and 232 subjects are needed for cross-sectional studies.Data conclusionWe found that DTI and FT of the lumbosacral nerves have intermediate to high reproducibility within and between scans. Based on these results, 10-58 subjects are needed to find a 10% change in parameters in cross-sectional studies of the lumbar and sacral nerves. The small significant differences of the interweek comparison suggest that results from longitudinal studies need to be interpreted carefully, since small differences may also be caused by factors other than disease progression or therapeutic effects.Level of evidence1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:951-963.
| S-EPMC6221026 | biostudies-literature
Project description:There are two popular approaches for automated white matter parcellation using diffusion MRI tractography, including fiber clustering strategies that group white matter fibers according to their geometric trajectories and cortical-parcellation-based strategies that focus on the structural connectivity among different brain regions of interest. While multiple studies have assessed test-retest reproducibility of automated white matter parcellations using cortical-parcellation-based strategies, there are no existing studies of test-retest reproducibility of fiber clustering parcellation. In this work, we perform what we believe is the first study of fiber clustering white matter parcellation test-retest reproducibility. The assessment is performed on three test-retest diffusion MRI datasets including a total of 255 subjects across genders, a broad age range (5-82 years), health conditions (autism, Parkinson's disease and healthy subjects), and imaging acquisition protocols (three different sites). A comprehensive evaluation is conducted for a fiber clustering method that leverages an anatomically curated fiber clustering white matter atlas, with comparison to a popular cortical-parcellation-based method. The two methods are compared for the two main white matter parcellation applications of dividing the entire white matter into parcels (i.e., whole brain white matter parcellation) and identifying particular anatomical fiber tracts (i.e., anatomical fiber tract parcellation). Test-retest reproducibility is measured using both geometric and diffusion features, including volumetric overlap (wDice) and relative difference of fractional anisotropy. Our experimental results in general indicate that the fiber clustering method produced more reproducible white matter parcellations than the cortical-parcellation-based method.
| S-EPMC6548665 | biostudies-literature
Project description:Visual neuroscience has traditionally focused much of its attention on understanding the response properties of single neurons or neuronal ensembles. The visual white matter and the long-range neuronal connections it supports are fundamental in establishing such neuronal response properties and visual function. This review article provides an introduction to measurements and methods to study the human visual white matter using diffusion MRI. These methods allow us to measure the microstructural and macrostructural properties of the white matter in living human individuals; they allow us to trace long-range connections between neurons in different parts of the visual system and to measure the biophysical properties of these connections. We also review a range of findings from recent studies on connections between different visual field maps, the effects of visual impairment on the white matter, and the properties underlying networks that process visual information supporting visual face recognition. Finally, we discuss a few promising directions for future studies. These include new methods for analysis of MRI data, open datasets that are becoming available to study brain connectivity and white matter properties, and open source software for the analysis of these data.
| S-EPMC5317208 | biostudies-literature
Project description:Brain atlases have proven to be valuable neuroscience tools for localizing regions of interest and performing statistical inferences on populations. Although many human brain atlases exist, most do not contain information about white matter structures, often neglecting them completely or labelling all white matter as a single homogenous substrate. While few white matter atlases do exist based on diffusion MRI fiber tractography, they are often limited to descriptions of white matter as spatially separate "regions" rather than as white matter "bundles" or fascicles, which are well-known to overlap throughout the brain. Additional limitations include small sample sizes, few white matter pathways, and the use of outdated diffusion models and techniques. Here, we present a new population-based collection of white matter atlases represented in both volumetric and surface coordinates in a standard space. These atlases are based on 2443 subjects, and include 216 white matter bundles derived from 6 different automated state-of-the-art tractography techniques. This atlas is freely available and will be a useful resource for parcellation and segmentation.
| S-EPMC8124084 | biostudies-literature
Project description:Advances in diffusion-weighted magnetic resonance imaging (DW-MRI) have led to many alternative diffusion sampling strategies and analysis methodologies. A common objective among methods is estimation of white matter fiber orientations within each voxel, as doing so permits in-vivo fiber-tracking and the ability to study brain connectivity and networks. Knowledge of how DW-MRI sampling schemes affect fiber estimation accuracy, tractography and the ability to recover complex white-matter pathways, differences between results due to choice of analysis method, and which method(s) perform optimally for specific data sets, all remain important problems, especially as tractography-based studies become common. In this work, we begin to address these concerns by developing sets of simulated diffusion-weighted brain images which we then use to quantitatively evaluate the performance of six DW-MRI analysis methods in terms of estimated fiber orientation accuracy, false-positive (spurious) and false-negative (missing) fiber rates, and fiber-tracking. The analysis methods studied are: 1) a two-compartment "ball and stick" model (BSM) (Behrens et al., 2003); 2) a non-negativity constrained spherical deconvolution (CSD) approach (Tournier et al., 2007); 3) analytical q-ball imaging (QBI) (Descoteaux et al., 2007); 4) q-ball imaging with Funk-Radon and Cosine Transform (FRACT) (Haldar and Leahy, 2013); 5) q-ball imaging within constant solid angle (CSA) (Aganj et al., 2010); and 6) a generalized Fourier transform approach known as generalized q-sampling imaging (GQI) (Yeh et al., 2010). We investigate these methods using 20, 30, 40, 60, 90 and 120 evenly distributed q-space samples of a single shell, and focus on a signal-to-noise ratio (SNR = 18) and diffusion-weighting (b = 1000 s/mm(2)) common to clinical studies. We found that the BSM and CSD methods consistently yielded the least fiber orientation error and simultaneously greatest detection rate of fibers. Fiber detection rate was found to be the most distinguishing characteristic between the methods, and a significant factor for complete recovery of tractography through complex white-matter pathways. For example, while all methods recovered similar tractography of prominent white matter pathways of limited fiber crossing, CSD (which had the highest fiber detection rate, especially for voxels containing three fibers) recovered the greatest number of fibers and largest fraction of correct tractography for complex three-fiber crossing regions. The synthetic data sets, ground-truth, and tools for quantitative evaluation are publically available on the NITRC website as the project "Simulated DW-MRI Brain Data Sets for Quantitative Evaluation of Estimated Fiber Orientations" at http://www.nitrc.org/projects/sim_dwi_brain.
| S-EPMC4600612 | biostudies-literature
Project description:Diffusion-tensor MRI fiber tractography has been used to reconstruct skeletal muscle architecture, but remains a specialized technique using custom-written data processing routines. In this work, we describe the public release of a software toolbox having the following design objectives: accomplish the pre-processing tasks of file input, image registration, denoising, and diffusion-tensor calculation; allow muscle-specific methods for defining seed points; make fiber-tract architectural measurements referenced to tendinous structures; visualize fiber tracts and other muscle structures of interest; analyze the goodness of outcomes; and provide a programming structure that allows the addition of new capabilities in future versions. The proper function of the code was verified using simulated datasets. The toolbox capabilities for characterizing human muscle structure in vivo were demonstrated in a case study. These capabilities included measurements of muscle morphology; contractile and non-contractile tissue volumes; fiber-tract length, pennation angle, curvature; and the physiological cross-sectional area,. The free public release of this software is a first step in creating of a community of users who use these tools in studies of muscle physiology and biomechanics. Users may further contribute to code development. Along with simulated and actual datasets for benchmarking, these tools will further create mechanisms for enhancing scientific rigor and developing and validating new code features. Planned future developments include additional options for image pre-processing, development of a graphical user interface, analysis of architectural patterns during muscle contraction, and integration of functional imaging data.
| S-EPMC9673086 | biostudies-literature
Project description:Background and purposePatients with craniosynostosis syndromes caused by mutations in FGFR-2, FGFR-3, and TWIST1 genes are characterized by having prematurely fused skull sutures and skull base synchondroses, which result in a skull deformity and are accompanied by brain anomalies, including altered white matter microarchitecture. In this study, the reliability and reproducibility of DTI fiber tractography was investigated in these patients. The outcomes were compared with those of controls.Materials and methodsDTI datasets were acquired with a 1.5T MR imaging system with 25 diffusion gradient orientations (voxel size = 1.8 × 1.8 × 3.0 mm(3), b-value = 1000 s/mm(2)). White matter tracts studied included the following: corpus callosum, cingulate gyrus, fornix, corticospinal tracts, and medial cerebellar peduncle. Tract pathways were reconstructed with ExploreDTI in 58 surgically treated patients with craniosynostosis syndromes and 7 controls (age range, 6-18 years).ResultsBecause of the brain deformity and abnormal ventricular shape and size, DTI fiber tractography was challenging to perform in patients with craniosynostosis syndromes. To provide reliable tracts, we adapted standard tracking protocols. Fractional anisotropy was equal to that in controls (0.44 versus 0.45 ± 0.02, P = .536), whereas mean, axial, and radial diffusivity parameters of the mean white matter were increased in patients with craniosynostosis syndromes (P < .001). No craniosynostosis syndrome-specific difference in DTI properties was seen for any of the fiber tracts studied in this work.ConclusionsPerforming DTI fiber tractography in patients with craniosynostosis syndromes was difficult due to partial volume effects caused by an anisotropic voxel size and deformed brain structures. Although these patients have a normal fiber organization, increased diffusivity parameters suggest abnormal microstructural tissue properties of the investigated white matter tracts.
| S-EPMC7964691 | biostudies-literature
Project description:Executive function (EF) and cognitive processing speed (CPS) are two cognitive performance domains that decline with advanced age. Reduced EF and CPS are known to correlate with age-related frontal-lobe volume loss. However, it remains unclear whether white matter microstructure in these regions is associated with age-related decline in EF and/or CPS. We utilized quantitative tractography metrics derived from diffusion-tensor MRI to investigate the relationship between the mean fiber bundle lengths (FBLs) projecting to different lobes, and EF/CPS performance in 73 healthy aging adults. We measured aspects of EF and CPS with the Trail Making Test (TMT), Color-Word Interference Test, Letter-Number Sequencing (L-N Seq), and Symbol Coding. Results revealed that parietal and occipital FBLs explained a significant portion of variance in EF. Frontal, temporal, and occipital FBLs explained a significant portion of variance in CPS. Shorter occipital FBLs were associated with poorer performance on the EF tests TMT-B and CWIT 3. Shorter frontal, parietal, and occipital FBLs were associated with poorer performance on L-N Seq and Symbol Coding. Shorter frontal and temporal FBLs were associated with lower performance on CPS tests TMT-A and CWIT 1. Shorter FBLs were also associated with increased age. Results suggest an age-related FBL shortening in specific brain regions related to poorer EF and CPS performance among older adults. Overall, results support both the frontal aging hypothesis and processing speed theory, suggesting that each mechanism is contributing to age-related cognitive decline.
| S-EPMC4424188 | biostudies-literature
Project description:Objective.The use of non-invasive techniques for the estimation of structural brain networks (i.e. connectomes) opened the door to large-scale investigations on the functioning and the architecture of the brain, unveiling the link between neurological disorders and topological changes of the brain network. This study aims at assessing if and how the topology of structural connectomes estimated non-invasively with diffusion MRI is affected by the employment of tractography filtering techniques in structural connectomic pipelines. Additionally, this work investigates the robustness of topological descriptors of filtered connectomes to the common practice of density-based thresholding.Approach.We investigate the changes in global efficiency, characteristic path length, modularity and clustering coefficient on filtered connectomes obtained with the spherical deconvolution informed filtering of tractograms and using the convex optimization modelling for microstructure informed tractography. The analysis is performed on both healthy subjects and patients affected by traumatic brain injury and with an assessment of the robustness of the computed graph-theoretical measures with respect to density-based thresholding of the connectome.Main results.Our results demonstrate that tractography filtering techniques change the topology of brain networks, and thus alter network metrics both in the pathological and the healthy cases. Moreover, the measures are shown to be robust to density-based thresholding.Significance.The present work highlights how the inclusion of tractography filtering techniques in connectomic pipelines requires extra caution as they systematically change the network topology both in healthy subjects and patients affected by traumatic brain injury. Finally, the practice of low-to-moderate density-based thresholding of the connectomes is confirmed to have negligible effects on the topological analysis.
| S-EPMC8053736 | biostudies-literature