Diffusion-based tractography atlas of the human acoustic radiation.
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ABSTRACT:
SUBMITTER: Maffei C
PROVIDER: S-EPMC6411970 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.
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Project description:Diffusion-weighted magnetic resonance imaging allows researchers and clinicians to identify individual white matter fiber tracts and map their trajectories. The reliability and interpretability of fiber-tracking procedures is improved when a priori anatomical information is used as a guide. We have developed an automated method for labeling white matter fiber tracts in individual subjects based on a probabilistic atlas of fiber tract locations and orientations. The probabilistic fiber atlas contains 23 fiber tracts and was constructed by manually identifying fiber tracts in 21 healthy controls and 21 patients with temporal lobe epilepsy (TLE). The manual tract identification method required approximately 40 h of manual editing by a trained image analyst using multiple regions of interest to select or exclude streamline fibers. Identification of fiber tracts with the atlas does not require human intervention, but nonetheless benefits from the a priori anatomical information that was used to manually identify the tracts included in the atlas. We applied this method to compare fractional anisotropy--thought to be a measure of white matter integrity--in individual fiber tracts between control subjects and patients with TLE. We found that the atlas-based and manual fiber selection methods produced a similar pattern of results. However, the between-group effect sizes using the atlas-derived fibers were generally as large or larger than those obtained with manually selected fiber tracks.
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Project description:Diffusion-weighted neuroimaging approaches provide rich evidence for estimating the structural integrity of white matter in vivo, but typically do not assess white matter integrity for connections between two specific regions of the brain. Here, we present a method for deriving tract-specific diffusion statistics, based upon predefined regions of interest. Our approach derives a population distribution using probabilistic tractography, based on the Nathan Kline Institute (NKI) Enhanced Rockland sample. We determine the most likely geometry of a path between two regions and express this as a spatial distribution. We then estimate the average orientation of streamlines traversing this path, at discrete distances along its trajectory, and the fraction of diffusion directed along this orientation for each participant. The resulting participant-wise metrics (tract-specific anisotropy; TSA) can then be used for statistical analysis on any comparable population. Based on this method, we report both negative and positive associations between age and TSA for two networks derived from published meta-analytic studies (the "default mode" and "what-where" networks), along with more moderate sex differences and age-by-sex interactions. The proposed method can be applied to any arbitrary set of brain regions, to estimate both the spatial trajectory and DWI-based anisotropy specific to those regions.
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Project description:IntroductionThe reproducibility of tractography is important to determine its sensitivity to pathological abnormalities. The reproducibility of tract morphology has not yet been systematically studied and the recently developed tractography contrast Tract Density Imaging (TDI) has not yet been assessed at the tract specific level.Materials and methodsDiffusion tensor imaging (DTI) and probabilistic constrained spherical deconvolution (CSD) tractography are performed twice in 9 healthy subjects. Tractography is based on common space seed and target regions and performed for several major white matter tracts. Tractograms are converted to tract segmentations and inter-session reproducibility of tract morphology is assessed using Dice similarity coefficient (DSC). The coefficient of variation (COV) and intraclass correlation coefficient (ICC) are calculated of the following tract metrics: fractional anisotropy (FA), apparent diffusion coefficient (ADC), volume, and TDI. Analyses are performed both for proximal (deep white matter) and extended (including subcortical white matter) tract segmentations.ResultsProximal DSC values were 0.70-0.92. DSC values were 5-10% lower in extended compared to proximal segmentations. COV/ICC values of FA, ADC, volume and TDI were 1-4%/0.65-0.94, 2-4%/0.62-0.94, 3-22%/0.53-0.96 and 8-31%/0.48-0.70, respectively, with the lower COV and higher ICC values found in the proximal segmentations.ConclusionFor all investigated metrics, reproducibility depended on the segmented tract. FA and ADC had relatively low COV and relatively high ICC, indicating clinical potential. Volume had higher COV but its moderate to high ICC values in most tracts still suggest subject-differentiating power. Tract TDI had high COV and relatively low ICC, which reflects unfavorable reproducibility.
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Project description:Despite the importance of pelvic floor muscles, significant controversy still exists about the true structural details of these muscles. We provide an objective analysis of the architecture and orientation of the superficial muscles of the perineum using a novel approach. Magnetic Resonance Diffusion Tensor Images (MR-DTI) were acquired in 10 healthy asymptomatic nulliparous women, and 4 healthy males. Global tractography was then used to generate the architecture of the muscles. Micro-CT imaging of a male cadaver was performed for validation of the fiber tracking results. Results show that muscles fibers of the external anal sphincter, from the right and left side, cross midline in the region of the perineal body to continue as transverse perinea and bulbospongiosus muscles of the opposite side. The morphology of the external anal sphincter resembles that of the number '8' or a "purse string". The crossing of muscle fascicles in the perineal body was supported by micro-CT imaging in the male subject. The superficial muscles of the perineum, and external anal sphincter are frequently damaged during child birth related injuries to the pelvic floor; we propose the use of MR-DTI based global tractography as a non-invasive imaging technique to assess damage to these muscles.
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Project description:Diffusion Tensor Imaging (DTI) and fiber tractography are important tools to map the cerebral white matter microstructure in vivo and to model the underlying axonal pathways in the brain with three-dimensional fiber tracts. As the fast and consistent extraction of anatomically correct fiber bundles for multiple datasets is still challenging, we present a novel atlas-guided clustering framework for exploratory data analysis of large tractography datasets. The framework uses an hierarchical cluster analysis approach that exploits the inherent redundancy in large datasets to time-efficiently group fiber tracts. Structural information of a white matter atlas can be incorporated into the clustering to achieve an anatomically correct and reproducible grouping of fiber tracts. This approach facilitates not only the identification of the bundles corresponding to the classes of the atlas; it also enables the extraction of bundles that are not present in the atlas. The new technique was applied to cluster datasets of 46 healthy subjects. Prospects of automatic and anatomically correct as well as reproducible clustering are explored. Reconstructed clusters were well separated and showed good correspondence to anatomical bundles. Using the atlas-guided cluster approach, we observed consistent results across subjects with high reproducibility. In order to investigate the outlier elimination performance of the clustering algorithm, scenarios with varying amounts of noise were simulated and clustered with three different outlier elimination strategies. By exploiting the multithreading capabilities of modern multiprocessor systems in combination with novel algorithms, our toolkit clusters large datasets in a couple of minutes. Experiments were conducted to investigate the achievable speedup and to demonstrate the high performance of the clustering framework in a multiprocessing environment.
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Project description:Diffusion Tensor Magnetic Resonance Imaging (DTI) allows to decode the mobility of water molecules in cerebral tissue, which is highly directional along myelinated fibers. By integrating the direction of highest water diffusion through the tissue, DTI Tractography enables a non-invasive dissection of brain fiber bundles. As such, this technique is a unique probe for in vivo characterization of white matter architecture. Unraveling the principal brain texture features of preclinical models that are advantageously exploited in experimental neuroscience is crucial to correctly evaluate investigational findings and to correlate them with real clinical scenarios. Although structurally similar to the human brain, the gyrencephalic ovine model has not yet been characterized by a systematic DTI study. Here we present the first in vivo sheep (ovis aries) tractography atlas, where the course of the main white matter fiber bundles of the ovine brain has been reconstructed. In the context of the EU's Horizon EDEN2020 project, in vivo brain MRI protocol for ovine animal models was optimized on a 1.5T scanner. High resolution conventional MRI scans and DTI sequences (b-value = 1,000 s/mm2, 15 directions) were acquired on ten anesthetized sheep o. aries, in order to define the diffusion features of normal adult ovine brain tissue. Topography of the ovine cortex was studied and DTI maps were derived, to perform DTI tractography reconstruction of the corticospinal tract, corpus callosum, fornix, visual pathway, and occipitofrontal fascicle, bilaterally for all the animals. Binary masks of the tracts were then coregistered and reported in the space of a standard stereotaxic ovine reference system, to demonstrate the consistency of the fiber bundles and the minimal inter-subject variability in a unique tractography atlas. Our results determine the feasibility of a protocol to perform in vivo DTI tractography of the sheep, providing a reliable reconstruction and 3D rendering of major ovine fiber tracts underlying different neurological functions. Estimation of fiber directions and interactions would lead to a more comprehensive understanding of the sheep's brain anatomy, potentially exploitable in preclinical experiments, thus representing a precious tool for veterinaries and researchers.
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