Combined prospective and retrospective correction to reduce motion‐induced image misalignment and geometric distortions in EPI

Ooi, Melvyn B.; Muraskin, Jordan; Zou, Xiaowei; Thomas, William J.; Krueger, Sascha; Aksoy, Murat; Bammer, Roland; Brown, Truman R.

doi:10.1002/mrm.24285

Cited by 36 publications

(42 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our previous study analyzed PRAMMO not only by a quality metric but also by simulating an fMRI experiment, which showed PRAMMO increased statistical significance in activated regions of interest over retrospective techniques in the “deliberate motion” case [32]. We subsequently confirmed these results in an actual fMRI experiment involving a breath-holding task [33]. One study by Speck et al showed that their optical correction system increases the number of activated voxels while decreasing both false positives and false negatives in an in-vivo visual fMRI paradigm [42].…”

Section: Discussionsupporting

confidence: 54%

“…Broadly speaking they can be classified into image-based methods [46] which can only correct for inter-volume movements, navigator-based methods [11], which acquire extra data along various three-dimensional k-space trajectories to estimate the 6-df [35,51,52,48,53], and marker-based methods which follow in real time the position of external markers attached to the head either by optical tracking [54,42,36,14,27] or using MRI [10,55,13,12,25,7,31,32]. Our group has developed prospective active-marker motion correction (PRAMMO) for structural [31] and echo-planar brain scans and demonstrated potential advantages of the approach for functional imaging [32,33]. However, our initial experiments were done assuming substantial and highly controlled motion as well as results reported for individual subjects.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prospective active marker motion correction improves statistical power in BOLD fMRI

et al. 2013

Self Cite

View full text Add to dashboard Cite

Group level statistical maps of blood oxygenation level dependent (BOLD) signals acquired using functional magnetic resonance imaging (fMRI) have become a basic measurement for much of systems, cognitive and social neuroscience. A challenge in making inferences from these statistical maps is the noise and potential confounds that arise from the head motion that occurs within and between acquisition volumes. This motion results in the scan plane being misaligned during acquisition, ultimately leading to reduced statistical power when maps are constructed at the group level. In most cases, an attempt is made to correct for this motion through the use of retrospective analysis methods. In this paper, we use a prospective active marker motion correction (PRAMMO) system that uses radio frequency markers for real-time tracking of motion, enabling on-line slice plane correction. We show that the statistical power of the activation maps is substantially increased using PRAMMO compared to conventional retrospective correction. Analysis of our results indicates that the PRAMMO acquisition reduces the variance without decreasing the signal component of the BOLD (beta). Using PRAMMO could thus improve the overall statistical power of fMRI based BOLD measurements, leading to stronger inferences of the nature of processing in the human brain.

show abstract

Section: Discussionsupporting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Prospective active marker motion correction improves statistical power in BOLD fMRI

et al. 2013

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, in most of the brain these changes are typically smaller than partial volume and spin history motion effects, and for a relatively homogeneous coil both are likely to be smaller than the effect of motion on the phase-encode warping, which SimPACE does produce accurately. Furthermore, these can be accounted for or simulated retrospectively (Hartwig et al, 2011; Ooi et al, 2013; Xu et al, 2007), although this is outside the scope of the present study. Additionally, SimPACE does not produce within-slice acquisition motion or motion between excitation and completion of EPI readout and thus is limited to between-slice motion.…”

Section: Discussionmentioning

confidence: 99%

SimPACE: Generating simulated motion corrupted BOLD data with synthetic-navigated acquisition for the development and evaluation of SLOMOCO: A new, highly effective slicewise motion correction

2014

View full text Add to dashboard Cite

Head motion in functional MRI and resting-state MRI is a major problem. Existing methods do not robustly reflect the true level of motion artifact for in vivo fMRI data. The primary issue is that current methods assume motion is synchronized to the volume acquisition and thus ignore intra-volume motion. This manuscript covers three sections in the use of gold-standard motion-corrupted data to pursue an intra-volume motion correction. First, we present a way to get motion corrupted data with accurately known motion at the slice acquisition level. This technique simulates important data acquisition-related motion artifacts while acquiring real BOLD MRI data. It is based on a novel motion-injection pulse sequence that introduces known motion independently for every slice: Simulated Prospective Acquisition CorrEction (SimPACE). Secondly, with data acquired using SimPACE, we evaluate several motion correction and characterization techniques, including several commonly used BOLD signal- and motion parameter-based metrics. Finally, we introduce and evaluate a novel, slice-based motion correction technique. Our novel method, SLice-Oriented MOtion COrrection (SLOMOCO) performs better than the volumetric methods and, moreover, accurately detects the motion of independent slices, in this case equivalent to the known injected motion. We demonstrate that SLOMOCO can model and correct for nearly all effects of motion in BOLD data. Also, none of the commonly used motion metrics was observed to robustly identify motion corrupted events, especially in the most realistic scenario of sudden head movement. For some popular metrics, performance was poor even when using the ideal known slice motion instead of volumetric parameters. This has negative implications for methods relying on these metrics, such as recently proposed motion correction methods such as data censoring and global signal regression.

show abstract

“…Thus, tissue movements between these short intervals reflect contiguous deformation in the cell sheet. To calculate deformation we apply differential image correlation techniques (36) using custom image processing programs [from the NIH ImageJ plug-in bUnwarpJ (37)]. Because this method uses betasplines the resulting deformations are "smooth."…”

Section: Methodsmentioning

confidence: 99%

Mechanochemical actuators of embryonic epithelial contractility

Kim

Hazar

Vijayraghavan

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Spatiotemporal regulation of cell contractility coordinates cell shape change to construct tissue architecture and ultimately directs the morphology and function of the organism. Here we show that contractility responses to spatially and temporally controlled chemical stimuli depend much more strongly on intercellular mechanical connections than on biochemical cues in both stimulated tissues and adjacent cells. We investigate how the cell contractility is triggered within an embryonic epithelial sheet by local ligand stimulation and coordinates a long-range contraction response. Our custom microfluidic control system allows spatiotemporally controlled stimulation with extracellular ATP, which results in locally distinct contractility followed by mechanical strain pattern formation. The stimulationresponse circuit exposed here provides a better understanding of how morphogenetic processes integrate responses to stimulation and how intercellular responses are transmitted across multiple cells. These findings may enable one to create a biological actuator that actively drives morphogenesis.microfluidics | multicellular | mechanotransduction | signaling P hysiological control systems have evolved diverse strategies to sense the environment, transduce signals, and actuate contractile responses. One such strategy involves the actuation of nonmuscle cell contractility to drive a wide range of developmental processes as well as normal physiological and pathological disease states (1-5). The contractile behaviors of cells and their interactions in multicellular arrays are not only critical in shaping and guiding tissue formation (e.g., epithelial folding) for the successful outcome of development programs (6, 7), but also play a major role in the pathology of tumor growth, the invasionmetastasis cascade, wound healing, and tissue regeneration (8,9).From a signaling standpoint, embryonic development is a dynamic process where cells interact and coordinate force generation as their identities are patterned by spatiotemporally applied chemical stimuli. There has been considerable debate over the effectiveness of intra-versus intercellular signaling during development (10, 11); nevertheless, the cell-cell signaling and the coordination of a variety of multicellular responses are known to be mediated by gap-junction-dependent intercellular communication (12, 13). However, recent findings from studies of cell mechanics indicate that mechanical cues can be as potent as chemical factors in directing cell differentiation and behaviors and suggest a role in modulating signal transduction pathways (14, 15). Less clear is whether signal transduction can be modulated by mechanical connections during morphogenesis. Results and DiscussionTo investigate the complex integrated response of a multicellular system and investigate the mechanochemical response and actuation, we cultured an intact epithelial sheet adhered to a fibronectin extracellular matrix substrate within a custom microfluidic chamber and exposed a narrow band of 4-5 cells...

show abstract

Combined prospective and retrospective correction to reduce motion‐induced image misalignment and geometric distortions in EPI

Cited by 36 publications

References 32 publications

Prospective active marker motion correction improves statistical power in BOLD fMRI

Prospective active marker motion correction improves statistical power in BOLD fMRI

SimPACE: Generating simulated motion corrupted BOLD data with synthetic-navigated acquisition for the development and evaluation of SLOMOCO: A new, highly effective slicewise motion correction

Mechanochemical actuators of embryonic epithelial contractility

Contact Info

Product

Resources

About