SIFT: Spherical-deconvolution informed filtering of tractograms

Smith, Robert E.; Tournier, Jacques‐Donald; Calamante, Fernando; Connelly, Alan

doi:10.1016/j.neuroimage.2012.11.049

Cited by 665 publications

(629 citation statements)

References 25 publications

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“…Streamlines were terminated when they either reached the cortical or subcortical grey‐matter mask or exited the foreground mask. The spherical deconvolution informed filtering of tractograms algorithm [Smith et al, 2013] was used to reduce biases. The resulting set of streamlines was used to construct the structural brain network.…”

Section: Methodsmentioning

confidence: 99%

Structural and functional brain network correlates of depressive symptoms in premanifest Huntington's disease

McColgan¹,

Razi

Gregory

et al. 2017

Human Brain Mapping

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Depression is common in premanifest Huntington's disease (preHD) and results in significant morbidity. We sought to examine how variations in structural and functional brain networks relate to depressive symptoms in premanifest HD and healthy controls. Brain networks were constructed using diffusion tractography (70 preHD and 81 controls) and resting state fMRI (92 preHD and 94 controls) data. A sub‐network associated with depression was identified in a data‐driven fashion and network‐based statistics was used to investigate which specific connections correlated with depression scores. A replication analysis was then performed using data from a separate study. Correlations between depressive symptoms with increased functional connectivity and decreased structural connectivity were seen for connections in the default mode network (DMN) and basal ganglia in preHD. This study reveals specific connections in the DMN and basal ganglia that are associated with depressive symptoms in preHD. Hum Brain Mapp 38:2819–2829, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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Section: Methodsmentioning

confidence: 99%

Structural and functional brain network correlates of depressive symptoms in premanifest Huntington's disease

McColgan¹,

Razi

Gregory

et al. 2017

Human Brain Mapping

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“…is based on a nonlinear gradient descent method called spherical‐deconvolution informed filtering of tractograms (SIFT). This approach removes fibers of an initially large fiber population to improve the fit between the streamline distribution in each voxel and the fiber ODF (Smith, Tournier, Calamante, & Connelly, 2013). Thereby, a cost function describing the deviation between fiber densities and FOD lobe integrals is minimized by iteratively removing fibers.…”

Section: Introductionmentioning

confidence: 99%

Fiber up‐sampling and quality assessment of tractograms – towards quantitative brain connectivity

et al. 2016

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Background and PurposeDiffusion MRI tractography enables to investigate white matter pathways noninvasively by reconstructing estimated fiber pathways. However, such tractograms remain biased and nonquantitative. Several techniques have been proposed to reestablish the link between tractography and tissue microstructure by modeling the diffusion signal or fiber orientation distribution (FOD) with the given tractogram and optimizing each fiber or compartment contribution according to the diffusion signal or FOD. Nevertheless, deriving a reliable quantification of connectivity strength between different brain areas is still a challenge. Moreover, evaluating the quality of a tractogram and measuring the possible error sources contained in a specific reconstructed fiber bundle also remains difficult. Lastly, all of these optimization techniques fail if specific fiber populations within a tractogram are underrepresented, for example, due to algorithmic constraints, anatomical properties, fiber geometry or seeding patterns.MethodsIn this work, we propose an approach which enables the inspection of the quality of a tractogram optimization by evaluating the residual error signal and its FOD representation. The automated fiber quantification (AFQ) is applied, whereby the framework is extended to reflect not only scalar diffusion metrics along a fiber bundle, but also directionally dependent FOD amplitudes along and perpendicular to the fiber direction. Furthermore, we also present an up‐sampling procedure to increase the number of streamlines of a given fiber population. The introduced error metrics and fiber up‐sampling method are tested and evaluated on single‐shell diffusion data sets of 16 healthy volunteers.Results and ConclusionAnalyzing the introduced error measures on specific fiber bundles shows a considerable improvement in applying the up‐sampling method. Additionally, the error metrics provide a useful tool to spot and identify potential error sources in tractograms.

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“…T1 co-registration to the diffusion imaging series, and subsequent FSL BET/FAST/FIRST processing on structural data as per the MRtrix3 'act_anat_prepare_fsl' script were conducted to produce a 'five tissue types' mask, to generate whole brain tractograms comprising fifty million streamlines. 59 Whole brain tractograms were subsequently processed using the Spherical-deconvolution Informed Filtering of Tractograms (SIFT) procedure introduced in MRtrix3, resulting in twenty-five million streamlines, 64 to reduce false positive streamlines. The MRtrix package was used to select regions-of-interest (ROIs) to enable extraction of the CPC, CTC, CST and somatosensory fibre tracks from SIFTed whole brain tractograms.…”

Section: Tractographymentioning

confidence: 99%

Investigating neural connectivity of corticomotor networks in ataxia telangiectasia: improving our understanding of the clinical phenotype

Sahama¹

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The human genetic disorder ataxia-telangiectasia (A-T) is an autosomal recessive neurodegenerative condition occurring in 3 per million live births. The disease is characterised by neurodegeneration, immunodeficiency, radiosensitivity, cell cycle checkpoint defects, genomic instability and cancer predisposition among patients. The most debilitating aspect of the disease is progressive cerebellar ataxia, which represents the hallmark neuropathological condition of A-T.At present, long term therapy to cure or prevent progressive symptoms of A-T are not currently available. While short term treatment to alleviate symptoms associated with immunodeficiency and deficient lung function are available to patients, the predisposition to cancer and the progressive neurodegeneration associated with A-T cannot be prevented with such efforts. To gain a more informed understanding of the A-T condition, research has focused on clinical, genetic and immunological aspects of the disorder; however, minimal attention has been directed towards identifying altered brain structure and function using imaging modalities such as magnetic resonance imaging (MRI).Imaging studies in A-T are limited to structural MRI imaging, where various radiological anomalies in patients are reported as clinical case studies. While these studies provide a detailed focus on the morphological and histopathological conditions of A-T, they provide limited insight into the mechanisms of neurodegeneration and loss of neural motor network connectivity among patients. In other ataxic diseases such as Friedrich's ataxia and spinocerebellar ataxia, the use of high-resolution MRI and diffusion-weighted imaging (DWI) has given valuable insight into the microstructural tissue environment, and the loss of white matter integrity of motor networks due to abnormal neurodevelopmental and/or progressive neurodegenerative conditions associated with the disease.Such imaging approaches have not yet been extended to the study of A-T, and could provide important new information regarding the relationship between the ataxia-telangiectasia gene mutation (ATM) and loss of motor pathway integrity in A-T patients. ivThe key objective of this PhD programme was to investigate white matter integrity and grey matter volume changes associated with A-T using a combination of structural MRI and diffusion-weighted imaging, to pinpoint potential neurodegenerative biomarkers that can be targeted for therapeutic use among young A-T patients. Performing diffusion imaging in children with A-T presents a significant challenge, as spontaneous movement at resting positions form part of the A-T condition, and nonsedated imaging procedures will contribute to excessive motion artefact and limited image quality in diffusion-weighted images. To effectively detect and correct for motion artefacts, a series of data preprocessing and correction steps were introduced to the DWI processing pipeline of A-T images in this project. Whole brain imaging analysis, specifically voxel-based morphometry (based...

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SIFT: Spherical-deconvolution informed filtering of tractograms

Cited by 665 publications

References 25 publications

Structural and functional brain network correlates of depressive symptoms in premanifest Huntington's disease

Structural and functional brain network correlates of depressive symptoms in premanifest Huntington's disease

Fiber up‐sampling and quality assessment of tractograms – towards quantitative brain connectivity

Investigating neural connectivity of corticomotor networks in ataxia telangiectasia: improving our understanding of the clinical phenotype

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