Registration-free analysis of diffusion MRI tractography data across subjects through the human lifespan.
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ABSTRACT:
SUBMITTER: Siless V
PROVIDER: S-EPMC8482444 | 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:Diffusion MRI-based probabilistic tractography is a powerful tool for non-invasively investigating normal brain architecture and alterations in structural connectivity associated with disease states. Both voxelwise and region-of-interest methods of analysis are capable of integrating population differences in tract amplitude (streamline count or density), given proper alignment of the tracts of interest. However, quantification of tract differences (between groups, or longitudinally within individuals) has been hampered by two related features of white matter. First, it is unknown to what extent healthy individuals differ in the precise location of white matter tracts, and to what extent experimental factors influence perceived tract location. Second, white matter lacks the gross neuroanatomical features (e.g., gyri, histological subtyping) that make parcellation of grey matter plausible - determining where tracts "should" lie within larger white matter structures is difficult. Accurately quantifying tractographic connectivity between individuals is thus inherently linked to the difficulty of identifying and aligning precise tract location. Tractography is often utilized to study neurological diseases in which the precise structural and connectivity abnormalities are unknown, underscoring the importance of accounting for individual differences in tract location when evaluating the strength of structural connectivity. We set out to quantify spatial variance in tracts aligned through a standard, whole-brain registration method, and to assess the impact of location mismatch on groupwise assessments of tract amplitude. We then developed a method for tract alignment that enhances the existing standard whole brain registration, and then tested whether this method improved the reliability of groupwise contrasts. Specifically, we conducted seed-based probabilistic diffusion tractography from primary motor, supplementary motor, and visual cortices, projecting through the corpus callosum. Streamline counts decreased rapidly with movement from the tract center (-35% per millimeter); tract misalignment of a few millimeters caused substantial compromise of amplitude comparisons. Alignment of tracts "peak-to-peak" is essential for accurate amplitude comparisons. However, for all transcallosal tracts registered through the whole-brain method, the mean separation distance between an individual subject's tract and the average tract (3.2?mm) precluded accurate comparison: at this separation, tract amplitudes were reduced by 74% from peak value. In contrast, alignment of subcortical tracts (thalamo-putaminal, pallido-rubral) was substantially better than alignment for cortical tracts; whole-brain registration was sufficient for these subcortical tracts. We demonstrated that location mismatches in cortical tractography were sufficient to produce false positive and false negative amplitude estimates in both groupwise and longitudinal comparisons. We then showed that our new tract alignment method substantially reduced location mismatch and improved both reliability and statistical power of subsequent quantitative comparisons.
| S-EPMC6790978 | biostudies-literature
Project description:BackgroundKnowledge of the normal myocardial-myocyte orientation could theoretically allow the definition of relevant quantitative biomarkers in clinical routine to diagnose heart pathologies. A whole heart diffusion tensor template representative of the global myofiber organization over species is therefore crucial for comparisons across populations. In this study, we developed a groupwise registration and tractography framework to resolve the global myofiber arrangement of large mammalian sheep hearts. To demonstrate the potential application of the proposed method, a novel description of sub-regions in the intraventricular septum is presented.MethodsThree explanted sheep (ovine) hearts (size ~12×8×6 cm3, heart weight ~ 150 g) were perfused with contrast agent and fixative and imaged in a 9.4T magnet. A group-wise registration of high-resolution anatomical and diffusion-weighted images were performed to generate anatomical and diffusion tensor templates. Diffusion tensor metrics (eigenvalues, eigenvectors, fractional anisotropy …) were computed to provide a quantitative and spatially-resolved analysis of cardiac microstructure. Then tractography was performed using deterministic and probabilistic algorithms and used for different purposes: i) Visualization of myofiber architecture, ii) Segmentation of sub-area depicting the same fiber organization, iii) Seeding and Tract Editing. Finally, dissection was performed to confirm the existence of macroscopic structures identified in the diffusion tensor template.ResultsThe template creation takes advantage of high-resolution anatomical and diffusion-weighted images obtained at an isotropic resolution of 150 μm and 600 μm respectively, covering ventricles and atria and providing information on the normal myocardial architecture. The diffusion metric distributions from the template were found close to the one of the individual samples validating the registration procedure. Small new sub-regions exhibiting spatially sharp variations in fiber orientation close to the junctions of the septum and ventricles were identified. Each substructure was defined and represented using streamlines. The existence of a fiber-bundles in the posterior junction was validated by anatomical dissection. A complex structural organization of the anterior junction in comparison to the posterior junction was evidenced by the high-resolution acquisition.ConclusionsA new framework combining cardiac template generation and tractography was applied on the whole sheep heart. The framework can be used for anatomical investigation, characterization of microstructure and visualization of myofiber orientation across samples. Finally, a novel description of the ventricular junction in large mammalian sheep hearts was proposed.
| S-EPMC9292118 | 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:The verification and validation of segmentation and registration methods is a necessary assessment in the development of new processing methods. However, verification and validation of diffusion MRI (dMRI) processing methods is challenging for the lack of gold-standard data. The data described here are related to the research article entitled "Surface-driven registration method for the structure-informed segmentation of diffusion MR images" [1], in which publicly available data are used to derive golden-standard reference-data to validate and evaluate segmentation and registration methods in dMRI.
| S-EPMC4957576 | biostudies-literature
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:Registration of subject and control brains to a common anatomical space or template is the basis for quantitatively delineating regions of abnormality in an individual brain. Normally, a brain atlas is chosen as the template. Limitations in the registration process result in persistent differences between individual subject brains and template, which can be a source of error in an analysis. We propose a new approach to the registration process where the subject of interest is the registration template. Through this change, we eliminate errors due to differences between a brain template and a subject's brain. We applied this method to the analysis of FA values derived from DTI data of 20 individual mTBI patients as compared to 48 healthy controls. Subject-centered analysis resulted in identification of significantly fewer regions of abnormally low FA compared to two separate atlas-centered analyses, with subject-centered abnormalities essentially representing the common subset of abnormal low FA regions detected by the two atlas-centered methods. Whereas each atlas-centered approach demonstrated abnormalities in nearly every subject (19/20 and 20/20), the subject-centered approach demonstrated abnormalities in fewer than half the subjects (9/20). This reduction of diffusion abnormalities observed using the subject-centered approach is due to elimination of misregistration errors that occur when registering the subject of interest to a template. Evaluation of atlas-centered analyses demonstrated that 9.8% to 13.3% of subject GM and CSF was misregistered onto the WM of the brain atlas, resulting in the observation of additional low FA clusters compared to the subject-centered approach. Without careful evaluation, these misregistrations could be misinterpreted as pathology. An additional benefit of the subject-centered approach is that diffusion abnormalities can now be visualized directly in the subject's anatomical space, rather than interpolating results from the brain atlas space, and can thereby enhance correlation with other components of an imaging protocol.
| S-EPMC4651497 | biostudies-literature
Project description:Diffusion MRI (dMRI)-based tractography offers unique abilities to map whole-brain structural connections in human and animal brains. However, dMRI-based tractography indirectly measures white matter tracts, with suboptimal accuracy and reliability. Recently, sophisticated methods including constrained spherical deconvolution (CSD) and global tractography have been developed to improve tract reconstructions through modeling of more complex fiber orientations. Our study aimed to determine the accuracy of connectome reconstruction for three dMRI-based tractography approaches: diffusion tensor (DT)-based, CSD-based and global tractography. Therefore, we validated whole brain structural connectome reconstructions based on ten ultrahigh-resolution dMRI rat brain scans and 106 cortical regions, from which varying tractography parameters were compared against standardized neuronal tracer data. All tested tractography methods generated considerable numbers of false positive and false negative connections. There was a parameter range trade-off between sensitivity: 0.06-0.63 interhemispherically and 0.22-0.86 intrahemispherically; and specificity: 0.99-0.60 interhemispherically and 0.99-0.23 intrahemispherically. Furthermore, performance of all tractography methods decreased with increasing spatial distance between connected regions. Similar patterns and trade-offs were found, when we applied spherical deconvolution informed filtering of tractograms, streamline thresholding and group-based average network thresholding. Despite the potential of CSD-based and global tractography to handle complex fiber orientations at voxel level, reconstruction accuracy, especially for long-distance connections, remains a challenge. Hence, connectome reconstruction benefits from varying parameter settings and combination of tractography methods to account for anatomical variation of neuronal pathways.
| S-EPMC5968063 | biostudies-literature
Project description:Recently proposed tractography and connectomics approaches often require a very large number of streamlines, in the order of millions. Generating, storing and interacting with these datasets is currently quite difficult, since they require a lot of space in memory and processing time. Compression is a common approach to reduce data size. Recently such an approach has been proposed consisting in removing collinear points in the streamlines. Removing points from streamlines results in files that cannot be robustly post-processed and interacted with existing tools, which are for the most part point-based. The aim of this work is to improve visualization, interaction and tractometry algorithms to robustly handle compressed tractography datasets. Our proposed improvements are threefold: (i) An efficient loading procedure to improve visualization (reduce memory usage up to 95% for a 0.2 mm step size); (ii) interaction techniques robust to compressed tractograms; (iii) tractometry techniques robust to compressed tractograms to eliminate biased in tract-based statistics. The present work demonstrates the need of correctly handling compressed streamlines to avoid biases in future tractometry and connectomics studies.
| S-EPMC5483435 | 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