Motion Correction in fMRI by Mapping Slice-to-Volume with Concurrent Field-Inhomogeneity Correction

Head motion is the major source of error in measuring intensity changes related to given stimuli in fMRI. The effects of head motion are image shifts and field inhomogeneity variations which cause local changes in geometric distortions. The previously developed motion correction method, mapping slice-to-volume (MSV), retrospectively remaps slices that are shifted by head motion to their spatially correct locations in an anatomical reference. Images exhibiting spatially varying geometric distortions require non-linear mapping solutions. An accurate field map can be used for the correction of such spatial distortions. However, field-map changes with head motion and, in practice, only one field-map is available typically. This work evaluates the improved motion correction capability of MSV with concurrent iterative field-corrected reconstruction using only an initial field-map. The results from simulated motion data show effective convergence and accuracy in image registration for the correction of image artifacts complicated by the motion induced field effects.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85942/1/Fessler206.pd

Deconvolution‐based distortion correction of EPI using analytic single‐voxel point‐spread functions

Purpose To develop a postprocessing algorithm that corrects geometric distortions due to spatial variations of the static magnetic field amplitude, B0, and effects from relaxation during signal acquisition in EPI. Theory and Methods An analytic, complex point‐spread function is deduced for k‐space trajectories of EPI variants and applied to corresponding acquisitions in a resolution phantom and in human volunteers at 3 T. With the analytic point‐spread function and experimental maps of B0 (and, optionally, the effective transverse relaxation time, urn:x-wiley:07403194:media:mrm28591:mrm28591-math-0004) as input, a point‐spread function matrix operator is devised for distortion correction by a Thikonov‐regularized deconvolution in image space. The point‐spread function operator provides additional information for an appropriate correction of the signal intensity distribution. A previous image combination algorithm for acquisitions with opposite phase blip polarities is adapted to the proposed method to recover destructively interfering signal contributions. Results Applications of the proposed deconvolution‐based distortion correction (“DecoDisCo”) algorithm demonstrate excellent distortion corrections and superior performance regarding the recovery of an undistorted intensity distribution in comparison to a multifrequency reconstruction. Examples include full and partial Fourier standard EPI scans as well as double‐shot center‐out trajectories. Compared with other distortion‐correction approaches, DecoDisCo permits additional deblurring to obtain sharper images in cases of significant urn:x-wiley:07403194:media:mrm28591:mrm28591-math-0005 effects. Conclusion Robust distortion corrections in EPI acquisitions are feasible with high quality by regularized deconvolution with an analytic point‐spread function. The general algorithm, which is publicly released on GitHub, can be straightforwardly adapted for specific EPI variants or other acquisition schemes

Generating Diffusion MRI scalar maps from T1 weighted images using generative adversarial networks

Diffusion magnetic resonance imaging (diffusion MRI) is a non-invasive microstructure assessment technique. Scalar measures, such as FA (fractional anisotropy) and MD (mean diffusivity), quantifying micro-structural tissue properties can be obtained using diffusion models and data processing pipelines. However, it is costly and time consuming to collect high quality diffusion data. Here, we therefore demonstrate how Generative Adversarial Networks (GANs) can be used to generate synthetic diffusion scalar measures from structural T1-weighted images in a single optimized step. Specifically, we train the popular CycleGAN model to learn to map a T1 image to FA or MD, and vice versa. As an application, we show that synthetic FA images can be used as a target for non-linear registration, to correct for geometric distortions common in diffusion MRI

Multiband diffusion-weighted MRI of the eye and orbit free of geometric distortions using a RARE-EPI hybrid

Diffusion-weighted imaging (DWI) provides information on tissue microstructure. Single-shot echo planar imaging (EPI) is the most common technique for DWI applications in the brain, but is prone to geometric distortions and signal voids. Rapid acquisition with relaxation enhancement [RARE, also known as fast spin echo (FSE)] imaging presents a valuable alternative to DWI with high anatomical accuracy. This work proposes a multi-shot diffusion-weighted RARE-EPI hybrid pulse sequence, combining the anatomical integrity of RARE with the imaging speed and radiofrequency (RF) power deposition advantage of EPI. The anatomical integrity of RARE-EPI was demonstrated and quantified by center of gravity analysis for both morphological images and diffusion-weighted acquisitions in phantom and in vivo experiments at 3.0 T and 7.0 T. The results indicate that half of the RARE echoes in the echo train can be replaced by EPI echoes whilst maintaining anatomical accuracy. The reduced RF power deposition of RARE-EPI enabled multiband RF pulses facilitating simultaneous multi-slice imaging. This study shows that diffusion-weighted RARE-EPI has the capability to acquire high fidelity, distortion-free images of the eye and the orbit. It is shown that RARE-EPI maintains the immunity to B0 inhomogeneities reported for RARE imaging. This benefit can be exploited for the assessment of ocular masses and pathological changes of the eye and the orbit

A framework for continuous target tracking during MR-guided high intensity focused ultrasound thermal ablations in the abdomen

Scatterplot showing percentage changes in stroke volume index (ΔSVI, %) and functional hemodynamic markers, Stroke Volume Variation (SVV, %) Pulse Pressure Variation (PPV, %), with the three tested tidal volumes (V T ), 6, 12 and 18 ml/kg during intra-abdominal hypertension. Solid line shows regression line between variables. (PDF 56 kb

Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T

Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI

Neural activity associated with the passive prediction of ambiguity and risk for aversive events

In economic decision making, outcomes are described in terms of risk (uncertain outcomes with certain probabilities) and ambiguity (uncertain outcomes with uncertain probabilities). Humans are more averse to ambiguity than to risk, with a distinct neural system suggested as mediating this effect. However, there has been no clear disambiguation of activity related to decisions themselves from perceptual processing of ambiguity. In a functional magnetic resonance imaging (fMRI) experiment, we contrasted ambiguity, defined as a lack of information about outcome probabilities, to risk, where outcome probabilities are known, or ignorance, where outcomes are completely unknown and unknowable.Wemodified previously learned pavlovian CSstimuli such that they became an ambiguous cue and contrasted evoked brain activity both with an unmodified predictive CS(risky cue), and a cue that conveyed no information about outcome probabilities (ignorance cue). Compared with risk, ambiguous cues elicited activity in posterior inferior frontal gyrus and posterior parietal cortex during outcome anticipation. Furthermore, a similar set of regions was activated when ambiguous cues were compared with ignorance cues. Thus, regions previously shown to be engaged by decisions about ambiguous rewarding outcomes are also engaged by ambiguous outcome prediction in the context of aversive outcomes. Moreover, activation in these regions was seen even when no actual decision is made. Our findings suggest that these regions subserve a general function of contextual analysis when search for hidden information during outcome anticipation is both necessary and meaningful

Diffusion-weighted renal MRI at 9.4 Tesla using RARE to improve anatomical integrity

Diffusion-weighted magnetic resonance imaging (DWI) is a non-invasive imaging technique sensitive to tissue water movement. By enabling a discrimination between tissue properties without the need of contrast agent administration, DWI is invaluable for probing tissue microstructure in kidney diseases. DWI studies commonly make use of single-shot Echo-Planar Imaging (ss-EPI) techniques that are prone to suffering from geometric distortion. The goal of the present study was to develop a robust DWI technique tailored for preclinical magnetic resonance imaging (MRI) studies that is free of distortion and sensitive to detect microstructural changes. Since fast spin-echo imaging techniques are less susceptible to B(0) inhomogeneity related image distortions, we introduced a diffusion sensitization to a split-echo Rapid Acquisition with Relaxation Enhancement (RARE) technique for high field preclinical DWI at 9.4 T. Validation studies in standard liquids provided diffusion coefficients consistent with reported values from the literature. Split-echo RARE outperformed conventional ss-EPI, with ss-EPI showing a 3.5-times larger border displacement (2.60 vs. 0.75) and a 60% higher intra-subject variability (cortex = 74%, outer medulla = 62% and inner medulla = 44%). The anatomical integrity provided by the split-echo RARE DWI technique is an essential component of parametric imaging on the way towards robust renal tissue characterization, especially during kidney disease

Accelerated mapping of magnetic susceptibility using 3D planes-on-a-paddlewheel (POP) EPI at ultra-high field strength

With the advent of ultra-high field MRI scanners in clinical research, susceptibility based MRI has recently gained increasing interest because of its potential to assess subtle tissue changes underlying neurological pathologies/disorders. Conventional, but rather slow, three-dimensional (3D) spoiled gradient-echo (GRE) sequences are typically employed to assess the susceptibility of tissue. 3D echo-planar imaging (EPI) represents a fast alternative but generally comes with echo-time restrictions, geometrical distortions and signal dropouts that can become severe at ultra-high fields. In this work we assess quantitative susceptibility mapping (QSM) at 7T using non-Cartesian 3D EPI with a planes-on-a-paddlewheel (POP) trajectory, which is created by rotating a standard EPI readout train around its own phase encoding axis. We show that the threefold accelerated non-Cartesian 3D POP EPI sequence enables very fast, whole brain susceptibility mapping at an isotropic resolution of 1mm and that the high image quality has sufficient signal-to-noise ratio in the phase data for reliable QSM processing. The susceptibility maps obtained were comparable with regard to QSM values and geometric distortions to those calculated from a conventional 4min 3D GRE scan using the same QSM processing pipeline