Retrospective head motion correction approaches for diffusion tensor imaging: Effects of preprocessing choices on biases and reproducibility of scalar diffusion metrics

2015 ◽  
Vol 43 (1) ◽  
pp. 99-106 ◽  
Author(s):  
Barbara A.K. Kreilkamp ◽  
Domenico Zacà ◽  
Nico Papinutto ◽  
Jorge Jovicich
Keyword(s):  
Diffusion Tensor Imaging ◽  
Motion Correction ◽  
Diffusion Tensor ◽  
Head Motion ◽  
Scalar Diffusion

scholarly journals In utero diffusion tensor imaging of the fetal brain: a reproducibility study

2017 ◽  
Author(s):  
András Jakab ◽  
Ruth O`Gorman Tuura ◽  
Christian Kellenberger ◽  
Ianina Scheer
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Corpus Callosum ◽  
Coefficient Of Variation ◽  
Motion Correction ◽  
Diffusion Tensor ◽  
Structural Similarity ◽  
Image Correlation ◽  
Normal Brain ◽  
Slice Thickness

AbstractOur purpose was to evaluate the within-subject reproducibility of in utero diffusion tensor imaging (DTI) metrics and the visibility of major white matter structures.Images for 30 fetuses (20-33. postmenstrual weeks, normal neurodevelopment: 6 cases, cerebral pathology: 24 cases) were acquired on 1.5T or 3.0T MRI. DTI with 15 diffusion-weighting directions was repeated three times for each case, TR/TE: 2200/63 ms, voxel size: 1*1 mm, slice thickness: 3-5 mm, b-factor: 700 s/mm2. Reproducibility was evaluated from structure detectability, variability of DTI measures using the coefficient of variation (CV), image correlation and structural similarity across repeated scans for six selected structures. The effect of age, scanner type, presence of pathology was determined using Wilcoxon rank sum test.White matter structures were detectable in the following percentage of fetuses in at least two of the three repeated scans: corpus callosum genu 76%, splenium 64%, internal capsule, posterior limb 60%, brainstem fibers 40% and temporooccipital association pathways 60%. The mean CV of DTI metrics ranged between 3% and 14.6% and we measured higher reproducibility in fetuses with normal brain development. Head motion was negatively correlated with reproducibility, this effect was partially ameliorated by motion-correction algorithm using image registration. Structures on 3.0 T had higher variability both with- and without motion correction.Fetal DTI is reproducible for projection and commissural bundles during mid-gestation, however, in 16-30% of the cases, data were corrupted by artifacts, resulting in impaired detection of white matter structures. To achieve robust results for the quantitative analysis of diffusivity and anisotropy values, fetal-specific image processing is recommended and repeated DTI is needed to ensure the detectability of fiber pathways.AbbreviationsADaxial diffusivity;CCAcorpus callosum agenesis;CVcoefficient of variation,DTIdiffusion tensor imaging;FAfractional anisotropy;GWgestational week;MDmean diffusivity;RDradial diffusivity;ROIregion of interest;SSIMstructural similarity index

Motion correction algorithms for pediatric spinal cord diffusion tensor imaging

2012 ◽  
Author(s):  
Devon M. Middleton ◽  
Feroze B. Mohamed ◽  
Nadia Barakat ◽  
Louis N. Hunter ◽  
Jurgen Finsterbusch ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Diffusion Tensor Imaging ◽  
Motion Correction ◽  
Diffusion Tensor

scholarly journals Understanding Diffusion MR Imaging Techniques: From Scalar Diffusion-weighted Imaging to Diffusion Tensor Imaging and Beyond

Radiographics ◽  
2006 ◽  
Vol 26 (suppl_1) ◽  
pp. S205-S223 ◽  
Author(s):  
Patric Hagmann ◽  
Lisa Jonasson ◽  
Philippe Maeder ◽  
Jean-Philippe Thiran ◽  
Van J. Wedeen ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Mr Imaging ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Imaging Techniques ◽  
Diffusion Mr ◽  
Diffusion Weighted ◽  
Scalar Diffusion ◽  
Diffusion Mr Imaging

scholarly journals The Impact of In-Scanner Head Motion on Structural Connectivity Derived from Diffusion Tensor Imaging

2017 ◽  
Author(s):  
Graham L. Baum ◽  
David R. Roalf ◽  
Philip A. Cook ◽  
Rastko Ciric ◽  
Adon F.G. Rosen ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Data Quality ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Structural Connectivity ◽  
Head Motion ◽  
Dependent Manner ◽  
Assessment Protocol ◽  
The Impact ◽  
Structural Brain

ABSTRACTMultiple studies have shown that data quality is a critical confound in the construction of brain networks derived from functional MRI. This problem is particularly relevant for studies of human brain development where important variables (such as participant age) are correlated with data quality. Nevertheless, the impact of head motion on estimates of structural connectivity derived from diffusion tractography methods remains poorly characterized. Here, we evaluated the impact of in-scanner head motion on structural connectivity using a sample of 949 participants (ages 8-23 years old) who passed a rigorous quality assessment protocol for diffusion tensor imaging (DTI) acquired as part of the Philadelphia Neurodevelopmental Cohort. Structural brain networks were constructed for each participant using both deterministic and probabilistic tractography. We hypothesized that subtle variation in head motion would systematically bias estimates of structural connectivity and confound developmental inference, as observed in previous studies of functional connectivity. Even following quality assurance and retrospective correction for head motion, eddy currents, and field distortions, in-scanner head motion significantly impacted the strength of structural connectivity in a consistency-and length-dependent manner. Specifically, increased head motion was associated with reduced estimates of structural connectivity for high-consistency network edges, which included both short-and long-range connections. In contrast, motion inflated estimates of structural connectivity for low-consistency network edges that were primarily shorter-range. Finally, we demonstrate that age-related differences in head motion can both inflate and obscure developmental inferences on structural connectivity. Taken together, these data delineate the systematic impact of head motion on structural connectivity, and provide a critical context for identifying motion-related confounds in studies of structural brain network development.

scholarly journals Volumetric navigators for real-time motion correction in diffusion tensor imaging

2012 ◽  
Vol 68 (4) ◽  
pp. 1097-1108 ◽  
Author(s):  
A. Alhamud ◽  
M. Dylan Tisdall ◽  
Aaron T. Hess ◽  
Khader M. Hasan ◽  
Ernesta M. Meintjes ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Real Time ◽  
Motion Correction ◽  
Diffusion Tensor ◽  
Time Motion

scholarly journals Real-time optical motion correction for diffusion tensor imaging

2011 ◽  
Vol 66 (2) ◽  
pp. 366-378 ◽  
Author(s):  
Murat Aksoy ◽  
Christoph Forman ◽  
Matus Straka ◽  
Stefan Skare ◽  
Samantha Holdsworth ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Real Time ◽  
Motion Correction ◽  
Diffusion Tensor ◽  
Optical Motion

scholarly journals Head injury or head motion? Assessment and quantification of motion artifacts in diffusion tensor imaging studies

2011 ◽  
Vol 33 (1) ◽  
pp. 50-62 ◽  
Author(s):  
Josef Ling ◽  
Flannery Merideth ◽  
Arvind Caprihan ◽  
Amanda Pena ◽  
Terri Teshiba ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Head Injury ◽  
Diffusion Tensor ◽  
Motion Artifacts ◽  
Head Motion ◽  
Imaging Studies ◽  
Motion Assessment

scholarly journals Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging

2012 ◽  
Vol 36 (4) ◽  
pp. 961-971 ◽  
Author(s):  
Samantha J. Holdsworth ◽  
Murat Aksoy ◽  
Rexford D. Newbould ◽  
Kristen Yeom ◽  
Anh T. Van ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Motion Correction ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Pediatric Imaging ◽  
Diffusion Tensor Imaging Dti
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