Multi-fiber tractography visualizations for diffusion MRI data.
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ABSTRACT:
SUBMITTER: Vos SB
PROVIDER: S-EPMC3839966 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Diffusion MRI fiber tractography has been increasingly used to map the structural connectivity of the human brain. However, this technique is not without limitations; for example, there is a growing concern over anatomically correlated bias in tractography findings. In this study, we demonstrate that there is a bias for fiber tracking algorithms to terminate preferentially on gyral crowns, rather than the banks of sulci. We investigate this issue by comparing diffusion MRI (dMRI) tractography with equivalent measures made on myelin-stained histological sections. We begin by investigating the orientation and trajectories of axons near the white matter/gray matter boundary, and the density of axons entering the cortex at different locations along gyral blades. These results are compared with dMRI orientations and tract densities at the same locations, where we find a significant gyral bias in many gyral blades across the brain. This effect is shown for a range of tracking algorithms, both deterministic and probabilistic, and multiple diffusion models, including the diffusion tensor and a high angular resolution diffusion imaging technique. Additionally, the gyral bias occurs for a range of diffusion weightings, and even for very high-resolution datasets. The bias could significantly affect connectivity results using the current generation of tracking algorithms.
| S-EPMC5807146 | biostudies-literature
Project description:BACKGROUND:Diffusion 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. PURPOSE:In this multicenter study the reproducibility of DTI of the lumbosacral nerves in healthy volunteers was investigated. STUDY TYPE:Prospective control series. SUBJECTS:Twenty healthy subjects. FIELD STRENGTH/SEQUENCE:3T MRI. 3D turbo spin echo, and 3.0?mm isotropic DTI scan. ASSESSMENT:The 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 TESTS:Reproducibility was determined using the intraclass correlation coefficient (ICC), and power calculations were performed. RESULTS:FT 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 CONCLUSION:We 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 EVIDENCE:1 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: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-other
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:Diffusion MRI tractography produces massive sets of streamlines that need to be clustered into anatomically meaningful white-matter bundles. Conventional clustering techniques group streamlines based on their proximity in Euclidean space. We have developed AnatomiCuts, an unsupervised method for clustering tractography streamlines based on their neighboring anatomical structures, rather than their coordinates in Euclidean space. In this work, we show that the anatomical similarity metric used in AnatomiCuts can be extended to find corresponding clusters across subjects and across hemispheres, without inter-subject or inter-hemispheric registration. Our proposed approach enables group-wise tract cluster analysis, as well as studies of hemispheric asymmetry. We evaluate our approach on data from the pilot MGH-Harvard-USC Lifespan Human Connectome project, showing improved correspondence in tract clusters across 184 subjects aged 8-90. Our method shows up to 38% improvement in the overlap of corresponding clusters when comparing subjects with large age differences. The techniques presented here do not require registration to a template and can thus be applied to populations with large inter-subject variability, e.g., due to brain development, aging, or neurological disorders.
| S-EPMC8482444 | biostudies-literature
Project description:Interest in structural brain connectivity has grown with the understanding that abnormal neural connections may play a role in neurologic and psychiatric diseases. Small animal connectivity mapping techniques are particularly important for identifying aberrant connectivity in disease models. Diffusion magnetic resonance imaging tractography can provide nondestructive, 3D, brain-wide connectivity maps, but has historically been limited by low spatial resolution, low signal-to-noise ratio, and the difficulty in estimating multiple fiber orientations within a single image voxel. Small animal diffusion tractography can be substantially improved through the combination of ex vivo MRI with exogenous contrast agents, advanced diffusion acquisition and reconstruction techniques, and probabilistic fiber tracking. Here, we present a comprehensive, probabilistic tractography connectome of the mouse brain at microscopic resolution, and a comparison of these data with a neuronal tracer-based connectivity data from the Allen Brain Atlas. This work serves as a reference database for future tractography studies in the mouse brain, and demonstrates the fundamental differences between tractography and neuronal tracer data.
| S-EPMC4715247 | 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:While magnetic resonance imaging (MRI) data is itself 3D, it is often difficult to adequately present the results papers and slides in 3D. As a result, findings of MRI studies are often presented in 2D instead. A solution is to create figures that include perspective and can convey 3D information; such figures can sometimes be produced by standard functional magnetic resonance imaging (fMRI) analysis packages and related specialty programs. However, many options cannot provide functionality such as visualizing activation clusters that are both cortical and subcortical (i.e., a 3D glass brain), the production of several statistical maps with an identical perspective in the 3D rendering, or animated renderings. Here I detail an approach for creating 3D visualizations of MRI data that satisfies all of these criteria. Though a 3D 'glass brain' rendering can sometimes be difficult to interpret, they are useful in showing a more overall representation of the results, whereas the traditional slices show a more local view. Combined, presenting both 2D and 3D representations of MR images can provide a more comprehensive view of the study's findings.
| S-EPMC4648228 | 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