Retrospective Motion Correction Research Articles

Non-Water-Suppressed 1H MR Spectroscopy with Orientational Prior Knowledge Shows Potential for Separating Intra- and Extramyocellular Lipid Signals in Human Myocardium

Conditions such as type II diabetes are linked with elevated lipid levels in the heart, and significantly increased risk of heart failure; however, metabolic processes underlying the development of cardiac disease in type II diabetes are not fully understood. Here we present a non-invasive method for in vivo investigation of cardiac lipid metabolism: namely, IVS-McPRESS. This technique uses metabolite-cycled, non-water suppressed 1H cardiac magnetic resonance spectroscopy with prospective and retrospective motion correction. High-quality IVS-McPRESS data acquired from healthy volunteers allowed us to investigate the frequency shift of extramyocellular lipid signals, which depends on the myocardial fibre orientation. Assuming consistent voxel positioning relative to myofibres, the myofibre angle with the magnetic field was derived from the voxel orientation. For separation and individual analysis of intra- and extramyocellular lipid signals, the angle myocardial fibres in the spectroscopy voxel take with the magnetic field should be within ±24.5°. Metabolite and lipid concentrations were analysed with respect to BMI. Significant correlations between BMI and unsaturated fatty acids in intramyocellular lipids, and methylene groups in extramyocellular lipids were found. The proposed IVS-McPRESS technique enables non-invasive investigation of cardiac lipid metabolism and may thus be a useful tool to study healthy and pathological conditions.

Fetal cardiac cine imaging using highly accelerated dynamic MRI with retrospective motion correction and outlier rejection.

PurposeDevelopment of a MRI acquisition and reconstruction strategy to depict fetal cardiac anatomy in the presence of maternal and fetal motion.MethodsThe proposed strategy involves i) acquisition and reconstruction of highly accelerated dynamic MRI, followed by image‐based ii) cardiac synchronization, iii) motion correction, iv) outlier rejection, and finally v) cardiac cine reconstruction. Postprocessing entirely was automated, aside from a user‐defined region of interest delineating the fetal heart. The method was evaluated in 30 mid‐ to late gestational age singleton pregnancies scanned without maternal breath‐hold.ResultsThe combination of complementary acquisition/reconstruction and correction/rejection steps in the pipeline served to improve the quality of the reconstructed 2D cine images, resulting in increased visibility of small, dynamic anatomical features. Artifact‐free cine images successfully were produced in 36 of 39 acquired data sets; prolonged general fetal movements precluded processing of the remaining three data sets.ConclusionsThe proposed method shows promise as a motion‐tolerant framework to enable further detail in MRI studies of the fetal heart and great vessels. Processing data in image‐space allowed for spatial and temporal operations to be applied to the fetal heart in isolation, separate from extraneous changes elsewhere in the field of view. Magn Reson Med 79:327–338, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Tracking discrete off-resonance markers with three spokes (trackDOTS) for compensation of head motion and B0 perturbations: Accuracy and performance in anatomical imaging.

To develop a novel approach for head motion and B0 field monitoring based on tracking discrete off-resonance markers with three spokes (trackDOTS). Small markers filled with acetic acid were built and attached to a head cap. Marker positions and phase were tracked with fast MR navigators (DotNavs) consisting of three off-resonance, double-echo, orthogonal one-dimensional projections. Individual marker signals were extracted using optimized coil combinations, and used to estimate head motion and field perturbations. To evaluate the approach, DotNavs were integrated in submillimeter MP2RAGE and long-echo time gradient-echo sequences at 7 Tesla, and tested on six healthy volunteers. The DotNav-based motion estimates differed by less than 0.11 ± 0.09 mm and 0.19 ± 0.17 ° from reference estimates obtained with an existing navigator approach (FatNavs). Retrospective motion correction brought clear improvements to MP2RAGE image quality, even in cases with submillimeter involuntary motion. The DotNav-based field estimates could track deep breathing-induced oscillations, and in cases with small head motion, field correction visibly improved the gradient-echo data quality. Conversely, field estimates were less robust when strong motion was present. The trackDOTS approach is suitable for head-motion tracking and correction, with significant benefits for high-spatial-resolution MRI. With small head motion, DotNav-based field estimates also allow correcting for deep-breathing artifacts in T2 *-weighted acquisitions. Magn Reson Med 79:160-171, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Prospective motion correction in diffusion-weighted imaging using intermediate pseudo-trace-weighted images

Subject head motion is a major challenge in diffusion-weighted imaging, which requires a precise alignment of images from different time points to allow a reliable quantification of diffusion parameters within each voxel. The technique requires long measurement times, making it highly sensitive to long-term subject motion, even when head restraint is used. Current methods of data analysis rely on retrospective motion correction, but there are potential benefits to using prospective motion correction, in which motion is tracked and compensated for during data acquisition. This technique is regularly used to enhance image quality in blood-oxygen-level dependent (BOLD) imaging, but its application to diffusion-weighted imaging has been limited by the contrast variation between images acquired with different diffusion-gradient directions. This paper describes a novel approach to this topic that exploits the rotational invariance of the trace of the diffusion tensor to reduce the effect of this contrast variation, making it possible to perform a fast image registration using a least-squares cost function. This results in an image-based motion detection algorithm that can be applied in real time during data acquisition to adapt the slice position and orientation in response to subject motion. The motion detection capabilities of the technique were evaluated in a study of ten subjects with b-values up to 3000s/mm². The resulting motion-parameter estimates were in close agreement with reference values provided by interleaved low-b-value images with a correlation coefficient of R=0.9634 for the voxel displacements measured across all subjects and b-values. The technique was also used to perform prospective motion correction on a standard clinical MRI system with b-values up to 2000s/mm². The correction was evaluated in 3 subjects using interleaved low-b-value images, retrospective image registration using the AFNI processing package and mean diffusivity histogram analysis. Compared to acquisitions without motion correction, prospective motion correction based on pseudo-trace-weighted images was found to provide a robust method for substantially reducing the level of misregistration between volumes. In most cases, misregistrations were reduced to less than 0.2mm of translation and 0.2° of rotation for an isotropic voxel size of 2mm, yielding high-quality diffusion parameter maps even in the absence of head restraint and post-acquisition image registration.

Prospective motion correction in functional MRI

Due to the intrinsic low sensitivity of BOLD-fMRI long scanning is required. Subject motion during fMRI scans reduces statistical significance of the activation maps and increases the prevalence of false activations. Motion correction is therefore an essential tool for a successful fMRI data analysis. Retrospective motion correction techniques are now commonplace and are incorporated into a wide range of fMRI analysis toolboxes. These techniques are advantageous due to robustness, sequence independence and have minimal impact on the fMRI study setup. Retrospective techniques however, do not provide an accurate intra-volume correction, nor can these techniques correct for the spin-history effects. The application of prospective motion correction in fMRI appears to be effective in reducing false positives and increasing sensitivity when compared to retrospective techniques, particularly in the cases of substantial motion. Especially advantageous in this regard is the combination of prospective motion correction with dynamic distortion correction. Nevertheless, none of the recent methods are able to recover activations in presence of motion that are comparable to no-motion conditions, which motivates further research in the area of adaptive dynamic imaging.

Coronary Atherosclerosis T1-Weighed Characterization With Integrated Anatomical Reference: Comparison With High-Risk Plaque Features Detected by Invasive Coronary Imaging

ObjectivesThe aim of this work is the development of coronary atherosclerosis T1-weighted characterization with integrated anatomical reference (CATCH) technique and the validation by comparison with high-risk plaque features (HRPF) observed on intracoronary optical coherence tomography (OCT) and invasive coronary angiography. BackgroundT1-weighted cardiac magnetic resonance with or without contrast media has been used for characterizing coronary atherosclerosis showing promising prognostic value. Several limitations include: 1) coverage is limited to proximal coronary segments; 2) spatial resolution is low and often anisotropic; and 3) a separate magnetic resonance angiography acquisition is needed to localize lesions. MethodsCATCH acquired dark-blood T1-weighted images and bright-blood anatomical reference images in an interleaved fashion. Retrospective motion correction with 100% respiratory gating efficiency was achieved. Reference control subjects (n = 13) completed both pre- and post-contrast scans. Stable angina patients (n = 30) completed pre-contrast scans, among whom 26 eligible patients also completed post-contrast scans. After cardiac magnetic resonance, eligible patients (n = 22) underwent invasive coronary angiography and OCT for the interrogation of coronary atherosclerosis. OCT images were assessed and scored for HRPF (lipid-richness, macrophages, cholesterol crystals, and microvessels) by 2 experienced analysts blinded to magnetic resonance results. ResultsPer-subject analysis showed none of the 13 reference control subjects had coronary hyperintensive plaques (CHIP) in either pre-contrast or post-contrast CATCH. Five patients had CHIP on pre-contrast CATCH and 5 patients had CHIP on post-contrast CATCH. Patients with CHIP had greater lipid abnormality than those without. Per-segment analysis showed elevated pre- and post-contrast plaque to myocardium signal ratio in the lesions with HRPF versus those without. Positive correlation was observed between plaque to myocardium signal ratio and OCT HRPF scoring. CHIP on pre-contrast CATCH were associated with significantly higher stenosis level than non-CHIP on invasive coronary angiography. ConclusionsCATCH provided accelerated whole heart coronary plaque characterization with simultaneously acquired anatomical reference. CHIP detected by CATCH showed positive association with high-risk plaque features on invasive imaging studies.

A dedicated neonatal brain imaging system.

PurposeThe goal of the Developing Human Connectome Project is to acquire MRI in 1000 neonates to create a dynamic map of human brain connectivity during early development. High‐quality imaging in this cohort without sedation presents a number of technical and practical challenges.MethodsWe designed a neonatal brain imaging system (NBIS) consisting of a dedicated 32‐channel receive array coil and a positioning device that allows placement of the infant's head deep into the coil for maximum signal‐to‐noise ratio (SNR). Disturbance to the infant was minimized by using an MRI‐compatible trolley to prepare and transport the infant and by employing a slow ramp‐up and continuation of gradient noise during scanning. Scan repeats were minimized by using a restart capability for diffusion MRI and retrospective motion correction. We measured the 1) SNR gain, 2) number of infants with a completed scan protocol, and 3) number of anatomical images with no motion artifact using NBIS compared with using an adult 32‐channel head coil.ResultsThe NBIS has 2.4 times the SNR of the adult coil and 90% protocol completion rate.ConclusionThe NBIS allows advanced neonatal brain imaging techniques to be employed in neonatal brain imaging with high protocol completion rates. Magn Reson Med 78:794–804, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

Assessing the performance of different DTI motion correction strategies in the presence of EPI distortion correction.

Diffusion tensor imaging (DTI) is susceptible to several artifacts due to eddy currents, echo planar imaging (EPI) distortion and subject motion. While several techniques correct for individual distortion effects, no optimal combination of DTI acquisition and processing has been determined. Here, the effects of several motion correction techniques are investigated while also correcting for EPI distortion: prospective correction, using navigation; retrospective correction, using two different popular packages (FSL and TORTOISE); and the combination of both methods. Data from a pediatric group that exhibited incidental motion in varying degrees are analyzed. Comparisons are carried while implementing eddy current and EPI distortion correction. DTI parameter distributions, white matter (WM) maps and probabilistic tractography are examined. The importance of prospective correction during data acquisition is demonstrated. In contrast to some previous studies, results also show that the inclusion of retrospective processing also improved ellipsoid fits and both the sensitivity and specificity of group tractographic results, even for navigated data. Matches with anatomical WM maps are highest throughout the brain for data that have been both navigated and processed using TORTOISE. The inclusion of both prospective and retrospective motion correction with EPI distortion correction is important for DTI analysis, particularly when studying subject populations that are prone to motion. Hum Brain Mapp 37:4405-4424, 2016. © 2016 Wiley Periodicals, Inc.

Retrospective 3D motion correction using spherical navigator echoes

PurposeTo develop and evaluate a rapid spherical navigator echo (SNAV) motion correction technique, then apply it for retrospective correction of brain images. MethodsThe pre-rotated, template matching SNAV method (preRot-SNAV) was developed in combination with a novel hybrid baseline strategy, which includes acquired and interpolated templates. Specifically, the SNAV templates are only rotated around X- and Y-axis; for each rotated SNAV, simulated baseline templates that mimic object rotation about the Z-axis were interpolated.The new method was first evaluated with phantom experiments. Then, a customized SNAV-interleaved gradient echo sequence was used to image three volunteers performing directed head motion. The SNAV motion measurements were used to retrospectively correct the brain images. Experiments were performed using a 3.0T whole-body MRI scanner and both single and 8-channel head coils. ResultsPhantom rotations and translations measured using the hybrid baselines agreed to within 0.9° and 1mm compared to those measured with the original preRot-SNAV method. Retrospective motion correction of in vivo images using the hybrid preRot-SNAV effectively corrected for head rotation up to 4° and 4mm. ConclusionsThe presented hybrid approach enables the acquisition of pre-rotated baseline templates in as little as 2.5s, and results in accurate measurement of rotations and translations. Retrospective 3D motion correction successfully reduced motion artifacts in vivo.

Compressive Sensing Based Q-Space Resampling for Handling Fast Bulk Motion in Hardi Acquisitions.

Diffusion-weighted (DW) MRI has become a widely adopted imaging modality to reveal the underlying brain connectivity. Long acquisition times and/or non-cooperative patients increase the chances of motion-related artifacts. Whereas slow bulk motion results in inter-gradient misalignment which can be handled via retrospective motion correction algorithms, fast bulk motion usually affects data during the application of a single diffusion gradient causing signal dropout artifacts. Common practices opt to discard gradients bearing signal attenuation due to the difficulty of their retrospective correction, with the disadvantage to lose full gradients for further processing. Nonetheless, such attenuation might only affect limited number of slices within a gradient volume. Q-space resampling has recently been proposed to recover corrupted slices while saving gradients for subsequent reconstruction. However, few corrupted gradients are implicitly assumed which might not hold in case of scanning unsedated infants or patients in pain. In this paper, we propose to adopt recent advances in compressive sensing based reconstruction of the diffusion orientation distribution functions (ODF) with under sampled measurements to resample corrupted slices. We make use of Simple Harmonic Oscillator based Reconstruction and Estimation (SHORE) basis functions which can analytically model ODF from arbitrary sampled signals. We demonstrate the impact of the proposed resampling strategy compared to state-of-art resampling and gradient exclusion on simulated intra-gradient motion as well as samples from real DWI data.

Retrospective correction of involuntary microscopic head movement using highly accelerated fat image navigators (3D FatNavs) at 7T

PurposeThe goal of the present study was to use a three‐dimensional (3D) gradient echo volume in combination with a fat‐selective excitation as a 3D motion navigator (3D FatNav) for retrospective correction of microscopic head motion during high‐resolution 3D structural scans of extended duration. The fat excitation leads to a 3D image that is itself sparse, allowing high parallel imaging acceleration factors – with the additional advantage of a minimal disturbance of the water signal used for the host sequence.MethodsA 3D FatNav was inserted into two structural protocols: an inversion‐prepared gradient echo at 0.33 × 0.33 × 1.00 mm resolution and a turbo spin echo at 600 μm isotropic resolution.ResultsMotion estimation was possible with high precision, allowing retrospective motion correction to yield clear improvements in image quality, especially in the conspicuity of very small blood vessels.ConclusionThe highly accelerated 3D FatNav allowed motion correction with noticeable improvements in image quality, even for head motion which was small compared with the voxel dimensions of the host sequence. Magn Reson Med 75:1030–1039, 2016. © 2015 Wiley Periodicals, Inc.

Motion correction and frequency stabilization for MRS of the human spinal cord.

Subject motion is challenging for MRS, because it can falsify results. For spinal cord MRS in particular, subject movement is critical, since even a small movement > 1 mm) can lead to a voxel shift out of the desired measurement region. Therefore, the identification of motion corrupted MRS scans is essential. In this investigation, MR navigators acquired simultaneously with the MRS data are used to identify a displacement of the spinal cord due to subject motion. It is shown that navigators are able to recognize substantial subject motion (>1 mm) without impairing the MRS measurement. In addition, navigators are easy to apply to the measurement, because no additional hardware and just a minor additional user effort are needed. Moreover, no additional scan time is required, because navigators can be applied in the deadtime of the MRS sequence. Furthermore, in this work, retrospective motion correction combined with frequency stabilization is presented by combining navigators with non-water-suppressed (1)H-MRS, resulting in an improved spectral quality of the spinal cord measurements.

Automatic EEG-assisted retrospective motion correction for fMRI (aE-REMCOR)

Head motions during functional magnetic resonance imaging (fMRI) impair fMRI data quality and introduce systematic artifacts that can affect interpretation of fMRI results. Electroencephalography (EEG) recordings performed simultaneously with fMRI provide high-temporal-resolution information about ongoing brain activity as well as head movements. Recently, an EEG-assisted retrospective motion correction (E-REMCOR) method was introduced. E-REMCOR utilizes EEG motion artifacts to correct the effects of head movements in simultaneously acquired fMRI data on a slice-by-slice basis. While E-REMCOR is an efficient motion correction approach, it involves an independent component analysis (ICA) of the EEG data and identification of motion-related ICs. Here we report an automated implementation of E-REMCOR, referred to as aE-REMCOR, which we developed to facilitate the application of E-REMCOR in large-scale EEG-fMRI studies. The aE-REMCOR algorithm, implemented in MATLAB, enables an automated preprocessing of the EEG data, an ICA decomposition, and, importantly, an automatic identification of motion-related ICs. aE-REMCOR has been used to perform retrospective motion correction for 305 fMRI datasets from 16 subjects, who participated in EEG-fMRI experiments conducted on a 3T MRI scanner. Performance of aE-REMCOR has been evaluated based on improvement in temporal signal-to-noise ratio (TSNR) of the fMRI data, as well as correction efficiency defined in terms of spike reduction in fMRI motion parameters. The results show that aE-REMCOR is capable of substantially reducing head motion artifacts in fMRI data. In particular, when there are significant rapid head movements during the scan, a large TSNR improvement and high correction efficiency can be achieved. Depending on a subject's motion, an average TSNR improvement over the brain upon the application of aE-REMCOR can be as high as 27%, with top ten percent of the TSNR improvement values exceeding 55%. The average correction efficiency over the 305 fMRI scans is 18% and the largest achieved efficiency is 71%. The utility of aE-REMCOR on the resting state fMRI connectivity of the default mode network is also examined. The motion-induced position-dependent error in the DMN connectivity analysis is shown to be reduced when aE-REMCOR is utilized. These results demonstrate that aE-REMCOR can be conveniently and efficiently used to improve fMRI motion correction in large clinical EEG-fMRI studies.

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

To evaluate how retrospective head motion correction strategies affect the estimation of scalar metrics commonly used in clinical diffusion tensor imaging (DTI) studies along with their across-session reproducibility errors. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and their respective across-session reproducibility errors were measured on a 4T test-retest dataset of healthy participants using five processing pipelines. These differed in: 1) the number of b0 volumes used for motion correction reference (one or five); 2) the estimations of the gradient matrix rotation (based on 6 or 12 degrees of freedom derived from coregistration); and 3) the software packages used (FSL or DTIPrep). Biases and reproducibility were evaluated in three regions of interest (ROIs) (bilateral arcuate fasciculi, cingula, and the corpus callosum) and also at the full brain level with tract based skeleton images. Preprocessing choices affected DTI measures and their reproducibility. The DTIPrep pipeline exhibited higher DTI metrics: FA/MD and AD (P < 0.05) relative to FSL pipelines both at the ROI and full brain level, and lower RD estimates (P < 0.05) at the ROI level. Within FSL pipelines no such effects were found (P-values ranging between 0.25 and 0.97). The DTIPrep pipeline showed the highest number of white matter skeleton voxels, with significantly higher reproducibility (P < 0.001) relative to the other pipelines (tested on P < 0.01 uncorrected maps). The use of an iteratively averaged b0 image as motion correction reference (as performed by DTIPrep) affects both scalar values and improves test-retest reliability relative to the other tested pipelines. These considerations are potentially relevant for data analysis in longitudinal DTI studies.

Retrospective correction of involuntary microscopic head movement using highly accelerated fat image navigators (3D FatNavs) at 7T

The goal of the present study was to use a three-dimensional (3D) gradient echo volume in combination with a fat-selective excitation as a 3D motion navigator (3D FatNav) for retrospective correction of microscopic head motion during high-resolution 3D structural scans of extended duration. The fat excitation leads to a 3D image that is itself sparse, allowing high parallel imaging acceleration factors--with the additional advantage of a minimal disturbance of the water signal used for the host sequence. A 3D FatNav was inserted into two structural protocols: an inversion-prepared gradient echo at 0.33 × 0.33 × 1.00 mm resolution and a turbo spin echo at 600 μm isotropic resolution. Motion estimation was possible with high precision, allowing retrospective motion correction to yield clear improvements in image quality, especially in the conspicuity of very small blood vessels. The highly accelerated 3D FatNav allowed motion correction with noticeable improvements in image quality, even for head motion which was small compared with the voxel dimensions of the host sequence.

A survey of patient motion in disorders of consciousness and optimization of its retrospective correction

Functional magnetic resonance imaging (fMRI) can be seriously impaired by patient motion. The purpose of this study was to characterize the typical motion in a clinical population of patients in disorders of consciousness and compare the performance of retrospective correction with rigid-body realignment as implemented in widely used software packages. 63 subjects were scanned with an fMRI visual checkerboard paradigm using a 3T scanner. Time series were corrected for motion, and the resulting transformations were used to calculate a motion score. SPM, FSL, AFNI and AIR were evaluated by comparing the motion obtained by re-running the tool on the corrected data. A publicly available sample fMRI dataset was modified with the motion detected in each patient with each tool. The performance of each tool was measured by comparing the number of supra-threshold voxels after standard fMRI analysis, both in the sample dataset and in simulated fMRI data. We assessed the effect of user-changeable parameters on motion correction in SPM. We found the equivalent motion in the patient population to be 1.4mm on average. There was no significant difference in performance between SPM, FSL and AFNI. AIR was considerably worse, and took more time to run. We found that in SPM the quality factor and interpolation method have no effect on the cluster size, while higher separation and smoothing reduce it. We showed that the main packages SPM, FSL and AFNI are equally suitable for retrospective motion correction of fMRI time series. We show that typically only 80% of activated voxels are recovered by retrospective motion correction.

Free-breathing, zero-TE MR lung imaging.

The investigation of three-dimensional radial, zero-echo time (TE) imaging for high-resolution, free-breathing magnetic resonance (MR) lung imaging using prospective and retrospective motion correction. Zero-TE was implemented similarly to the rotating-ultra-fast-imaging-sequence, providing 3D, isotropic, radial imaging with proton density contrast. Respiratory motion was addressed using prospective triggering (PT), prospective gating (PG) and retrospective gating (RG) with physiological signals obtained from a respiratory belt and interleaved pencil beam and DC navigators. The methods were demonstrated on four healthy volunteers at 3T. 3D, radial zero-TE imaging with high imaging bandwidth and nominally zero echo-time enables efficient capture of short-lived signals from the lung parenchyma and the vessels. Compared to Cartesian encoding, unaccounted for free-breathing respiration resulted in only benign blurring artifacts confined to the origin of motion. Breath holding froze respiration but achieved only limited image resolution (~1.8 mm, 30 s). PT and PG obtained similar quality expiratory-phase images at 1.2 mm resolution in ~6 min scan time. RG allowed multi-phase imaging in ~15 min, derived from eight individually stored averages. Zero-TE appears to be an attractive pulse sequence for 3D isotropic lung imaging. Prospective and retrospective approaches provide high-quality, free-breathing MR lung imaging within reasonable scan time.

Intraoperative laser speckle contrast imaging with retrospective motion correction for quantitative assessment of cerebral blood flow.

Although multiple intraoperative cerebral blood flow (CBF) monitoring techniques are currently available, a quantitative method that allows for continuous monitoring and that can be easily integrated into the surgical workflow is still needed. Laser speckle contrast imaging (LSCI) is an optical imaging technique with a high spatiotemporal resolution that has been recently demonstrated as feasible and effective for intraoperative monitoring of CBF during neurosurgical procedures. This study demonstrates the impact of retrospective motion correction on the quantitative analysis of intraoperatively acquired LSCI images. LSCI images were acquired through a surgical microscope during brain tumor resection procedures from 10 patients under baseline conditions and after a cortical stimulation in three of those patients. The patient's electrocardiogram (ECG) was recorded during acquisition for postprocess correction of pulsatile artifacts. Automatic image registration was retrospectively performed to correct for tissue motion artifacts, and the performance of rigid and nonrigid transformations was compared. In baseline cases, the original images had [Formula: see text] noise across 16 regions of interest (ROIs). ECG filtering moderately reduced the noise to [Formula: see text], while image registration resulted in a further noise reduction of [Formula: see text]. Combined ECG filtering and image registration significantly reduced the noise to [Formula: see text] ([Formula: see text]). Using the combined motion correction, accuracy and sensitivity to small changes in CBF were improved in cortical stimulation cases. There was also excellent agreement between rigid and nonrigid registration methods (15/16 ROIs with [Formula: see text] difference). Results from this study demonstrate the importance of motion correction for improved visualization of CBF changes in clinical LSCI images.

Motion artifact reduction in pediatric diffusion tensor imaging using fast prospective correction

To evaluate the patterns of head motion in scans of young children and to examine the influence of corrective techniques, both qualitatively and quantitatively. We investigate changes that both retrospective (with and without diffusion table reorientation) and prospective (implemented with a short navigator sequence) motion correction induce in the resulting diffusion tensor measures. Eighteen pediatric subjects (aged 5-6 years) were scanned using 1) a twice-refocused, 2D diffusion pulse sequence, 2) a prospectively motion-corrected, navigated diffusion sequence with reacquisition of a maximum of five corrupted diffusion volumes, and 3) a T1 -weighted structural image. Mean fractional anisotropy (FA) values in white and gray matter regions, as well as tractography in the brainstem and projection fibers, were evaluated to assess differences arising from retrospective (via FLIRT in FSL) and prospective motion correction. In addition to human scans, a stationary phantom was also used for further evaluation. In several white and gray matter regions retrospective correction led to significantly (P < 0.05) reduced FA means and altered distributions compared to the navigated sequence. Spurious tractographic changes in the retrospectively corrected data were also observed in subject data, as well as in phantom and simulated data. Due to the heterogeneity of brain structures and the comparatively low resolution (∼2 mm) of diffusion data using 2D single shot sequencing, retrospective motion correction is susceptible to distortion from partial voluming. These changes often negatively bias diffusion tensor imaging parameters. Prospective motion correction was shown to produce smaller changes.

Blind multirigid retrospective motion correction of MR images.

Physiological nonrigid motion is inevitable when imaging, e.g., abdominal viscera, and can lead to serious deterioration of the image quality. Prospective techniques for motion correction can handle only special types of nonrigid motion, as they only allow global correction. Retrospective methods developed so far need guidance from navigator sequences or external sensors. We propose a fully retrospective nonrigid motion correction scheme that only needs raw data as an input. Our method is based on a forward model that describes the effects of nonrigid motion by partitioning the image into patches with locally rigid motion. Using this forward model, we construct an objective function that we can optimize with respect to both unknown motion parameters per patch and the underlying sharp image. We evaluate our method on both synthetic and real data in 2D and 3D. In vivo data was acquired using standard imaging sequences. The correction algorithm significantly improves the image quality. Our compute unified device architecture (CUDA)-enabled graphic processing unit implementation ensures feasible computation times. The presented technique is the first computationally feasible retrospective method that uses the raw data of standard imaging sequences, and allows to correct for nonrigid motion without guidance from external motion sensors.