Adaptive retrospective correction of motion artifacts in cranial MRI with multicoil three-dimensional radial acquisitions

Improved motion correction in brain MRI using 3D radial trajectory and projection moment analysis

PURPOSE

To develop a generalized rigid body motion correction method in 3D radial brain MRI to deal with continuous motion pattern through projection moment analysis.

METHODS

An assumption was made that the multichannel coil moves with the head, which was achieved by using a flexible head coil. A two-step motion correction scheme was proposed to directly extract the motion parameters from the acquired k-space data using the analysis of center-of-mass with high noise robustness, which were used for retrospective motion correction. A recursive least-squares model was introduced to recursively estimate the motion parameters for every single spoke, which used the smoothness of motion and resulted in high temporal resolution and low computational cost. Five volunteers were scanned at 3 T using a 3D radial multidimensional golden-means trajectory with instructed motion patterns. The performance was tested through both simulation and in vivo experiments. Quantitative image quality metrics were calculated for comparison.

RESULTS

The proposed method showed good accuracy and precision in both translation and rotation estimation. A better result was achieved using the proposed two-step correction compared to traditional one-step correction without significantly increasing computation time. Retrospective correction showed substantial improvements in image quality among all scans, even for stationary scans.

CONCLUSIONS

The proposed method provides an easy, robust, and time-efficient tool for motion correction in brain MRI, which may benefit clinical diagnosis of uncooperative patients as well as scientific MRI researches.

Four-dimensional flow MRI for quantitative assessment of cerebrospinal fluid dynamics: Status and opportunities

Neurological disorders can manifest with altered neurofluid dynamics in different compartments of the central nervous system. These include alterations in cerebral blood flow, cerebrospinal fluid (CSF) flow, and tissue biomechanics. Noninvasive quantitative assessment of neurofluid flow and tissue motion is feasible with phase contrast magnetic resonance imaging (PC MRI). While two-dimensional (2D) PC MRI is routinely utilized in research and clinical settings to assess flow dynamics through a single imaging slice, comprehensive neurofluid dynamic assessment can be limited or impractical. Recently, four-dimensional (4D) flow MRI (or time-resolved three-dimensional PC with three-directional velocity encoding) has emerged as a powerful extension of 2D PC, allowing for large volumetric coverage of fluid velocities at high spatiotemporal resolution within clinically reasonable scan times. Yet, most 4D flow studies have focused on blood flow imaging. Characterizing CSF flow dynamics with 4D flow (i.e., 4D CSF flow) is of high interest to understand normal brain and spine physiology, but also to study neurological disorders such as dysfunctional brain metabolite waste clearance, where CSF dynamics appear to play an important role. However, 4D CSF flow imaging is challenged by the long T1 time of CSF and slower velocities compared with blood flow, which can result in longer scan times from low flip angles and extended motion-sensitive gradients, hindering clinical adoption. In this work, we review the state of 4D CSF flow MRI including challenges, novel solutions from current research and ongoing needs, examples of clinical and research applications, and discuss an outlook on the future of 4D CSF flow.

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

PURPOSE

To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-encoded FID navigator) in each radial spoke.

METHODS

A forward model was created from low-resolution calibration data to simulate the effect of relative motion between the coil sensitivity profiles and the underlying object on the self-encoded FID navigator signal. Trajectory deviations were included in the model as low spatial-order field variations. Three volunteers were imaged at 3 T using a modified 3D gradient-echo sequence acquired with a Kooshball trajectory while performing abrupt and continuous head motion. Rigid body-motion parameters were estimated from the central k-space signal of each spoke using a least-squares fitting algorithm. The accuracy of self-navigated motion parameters was assessed relative to an established external tracking system. Quantitative image quality metrics were computed for images with and without retrospective correction using external and self-navigated motion measurements.

RESULTS

Self-encoded FID navigators achieved mean absolute errors of 0.69 ± 0.82 mm and 0.73 ± 0.87° relative to external tracking for maximum motion amplitudes of 12 mm and 10°. Retrospective correction of the 3D radial data resulted in substantially improved image quality for both abrupt and continuous motion paradigms, comparable to external tracking results.

CONCLUSIONS

Accurate rigid body motion parameters can be rapidly obtained from self-encoded FID navigator signals in 3D radial MRI to continuously correct for head movements. This approach is suitable for robust neuroanatomical imaging in subjects that exhibit patterns of large and frequent motion.

Gaussian Processes for real-time 3D motion and uncertainty estimation during MR-guided radiotherapy

Respiratory motion during radiotherapy causes uncertainty in the tumor's location, which is typically addressed by an increased radiation area and a decreased dose. As a result, the treatments' efficacy is reduced. The recently proposed hybrid MR-linac scanner holds the promise to efficiently deal with such respiratory motion through real-time adaptive MR-guided radiotherapy (MRgRT). For MRgRT, motion-fields should be estimated from MR-data and the radiotherapy plan should be adapted in real-time according to the estimated motion-fields. All of this should be performed with a total latency of maximally 200 ms, including data acquisition and reconstruction. A measure of confidence in such estimated motion-fields is highly desirable, for instance to ensure the patient's safety in case of unexpected and undesirable motion. In this work, we propose a framework based on Gaussian Processes to infer 3D motion-fields and uncertainty maps in real-time from only three readouts of MR-data. We demonstrated an inference frame rate up to 69 Hz including data acquisition and reconstruction, thereby exploiting the limited amount of required MR-data. Additionally, we designed a rejection criterion based on the motion-field uncertainty maps to demonstrate the framework's potential for quality assurance. The framework was validated in silico and in vivo on healthy volunteer data (n=5) acquired using an MR-linac, thereby taking into account different breathing patterns and controlled bulk motion. Results indicate end-point-errors with a 75th percentile below 1 mm in silico, and a correct detection of erroneous motion estimates with the rejection criterion. Altogether, the results show the potential of the framework for application in real-time MR-guided radiotherapy with an MR-linac.

MP-RAVE: IR-Prepared T1 -Weighted Radial Stack-of-Stars 3D GRE imaging with retrospective motion correction

PURPOSE

To describe an inversion-recovery T₁ -weighted radial stack-of-stars 3D gradient echo (GRE) sequence with comparable image quality to conventional MP-RAGE and to demonstrate how the radial acquisition scheme can be utilized for additional retrospective motion correction to improve robustness to head motion.

METHODS

The proposed sequence, named MP-RAVE, has been derived from a previously described radial stack-of-stars 3D GRE sequence (RAVE) and includes a 180° inversion recovery pulse that is generated once for every stack of radial views. The sequence is combined with retrospective 3D motion correction to improve robustness. The effectiveness has been evaluated in phantoms and healthy volunteers and compared to conventional MP-RAGE acquisition.

RESULTS

MP-RAGE and MP-RAVE anatomical images were rated "good" to "excellent" in overall image quality, with artifact level between "mild" and "no artifacts", and with no statistically significant difference between methods. During head motion, MP-RAVE showed higher inherent robustness with artifacts confined to local brain regions. In combination with motion correction, MP-RAVE provided noticeably improved image quality during different head motion and showed statistically significant improvement in image sharpness.

CONCLUSION

MP-RAVE provides comparable image quality and contrast to conventional MP-RAGE with improved robustness to head motion. In combination with retrospective 3D motion correction, MP-RAVE can be a useful alternative to MP-RAGE, especially in non-cooperative or pediatric patients.

Motion-corrected 4D-Flow MRI for neurovascular applications

Neurovascular 4D-Flow MRI has emerged as a powerful tool for comprehensive cerebrovascular hemodynamic characterization. Clinical studies in at risk populations such as aging adults indicate hemodynamic markers can be confounded by motion-induced bias. This study develops and characterizes a high fidelity 3D self-navigation approach for retrospective rigid motion correction of neurovascular 4D-Flow data. A 3D radial trajectory with pseudorandom ordering was combined with a multi-resolution low rank regularization approach to enable high spatiotemporal resolution self-navigators from extremely undersampled data. Phantom and volunteer experiments were performed at 3.0T to evaluate the ability to correct for different amounts of induced motions. In addition, the approach was applied to clinical-research exams from ongoing aging studies to characterize performance in the clinical setting. Simulations, phantom and volunteer experiments with motion correction produced images with increased vessel conspicuity, reduced image blurring, and decreased variability in quantitative measures. Clinical exams revealed significant changes in hemodynamic parameters including blood flow rates, flow pulsatility index, and lumen areas after motion correction in probed cerebral arteries (Flow: P<0.001 Lt ICA, P=0.002 Rt ICA, P=0.004 Lt MCA, P=0.004 Rt MCA; Area: P<0.001 Lt ICA, P<0.001 Rt ICA, P=0.004 Lt MCA, P=0.004 Rt MCA; flow pulsatility index: P=0.042 Rt ICA, P=0.002 Lt MCA). Motion induced bias can lead to significant overestimation of hemodynamic markers in cerebral arteries. The proposed method reduces measurement bias from rigid motion in neurovascular 4D-Flow MRI in challenging populations such as aging adults.

Abdominal applications of quantitative 4D flow MRI

4D flow MRI is a quantitative MRI technique that allows the comprehensive assessment of time-resolved hemodynamics and vascular anatomy over a 3-dimensional imaging volume. It effectively combines several advantages of invasive and non-invasive imaging modalities like ultrasound, angiography, and computed tomography in a single MRI acquisition and provides an unprecedented characterization of velocity fields acquired non-invasively in vivo. Functional and morphological imaging of the abdominal vasculature is especially challenging due to its complex and variable anatomy with a wide range of vessel calibers and flow velocities and the need for large volumetric coverage. Despite these challenges, 4D flow MRI is a promising diagnostic and prognostic tool as many pathologies in the abdomen are associated with changes of either hemodynamics or morphology of arteries, veins, or the portal venous system. In this review article, we will discuss technical aspects of the implementation of abdominal 4D flow MRI ranging from patient preparation and acquisition protocol over post-processing and quality control to final data analysis. In recent years, the range of applications for 4D flow in the abdomen has increased profoundly. Therefore, we will review potential clinical applications and address their clinical importance, relevant quantitative and qualitative parameters, and unmet challenges.

Motion corrected silent ZTE neuroimaging

Purpose

To develop self‐navigated motion correction for 3D silent zero echo time (ZTE) based neuroimaging and characterize its performance for different types of head motion.

Methods

The proposed method termed MERLIN (Motion Estimation & Retrospective correction Leveraging Interleaved Navigators) achieves self‐navigation by using interleaved 3D phyllotaxis k‐space sampling. Low resolution navigator images are reconstructed continuously throughout the ZTE acquisition using a sliding window and co‐registered in image space relative to a fixed reference position. Rigid body motion corrections are then applied retrospectively to the k‐space trajectory and raw data and reconstructed into a final, high‐resolution ZTE image.

Results

MERLIN demonstrated successful and consistent motion correction for magnetization prepared ZTE images for a range of different instructed motion paradigms. The acoustic noise response of the self‐navigated phyllotaxis trajectory was found to be only slightly above ambient noise levels (<4 dBA).

Conclusion

Silent ZTE imaging combined with MERLIN addresses two major challenges intrinsic to MRI (i.e., subject motion and acoustic noise) in a synergistic and integrated manner without increase in scan time and thereby forms a versatile and powerful framework for clinical and research MR neuroimaging applications.

Rigid real-time prospective motion-corrected three-dimensional multiparametric mapping of the human brain

PURPOSE

To develop a rigid real-time prospective motion-corrected multiparametric mapping technique and to test the performance of quantitative estimates.

METHODS

Motion tracking and correction were performed by integrating single-shot spiral navigators into a multiparametric imaging technique, three-dimensional quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). The spiral navigator was optimized, and quantitative measurements were validated using a standard system phantom. The effect of motion correction on whole-brain T1 and T2 mapping under different types of head motion during the scan was evaluated in 10 healthy volunteers. Finally, six patients with Parkinson's disease, which is known to be associated with a high prevalence of motion artifacts, were scanned to evaluate the effectiveness of our method in the real world.

RESULTS

The phantom study demonstrated that the proposed motion correction method did not introduce quantitative bias. Improved parametric map quality and repeatability were shown in volunteer experiments with both in-plane and through-plane motions, comparable to the no-motion ground truth. In real-life validation in patients, the approach showed improved parametric map quality compared to images obtained without motion correction.

CONCLUSIONS

Real-time prospective motion-corrected multiparametric relaxometry based on 3D-QALAS provided robust and repeatable whole-brain multiparametric mapping.

Clinical Applications of 4D Flow MRI in the Portal Venous System

Evaluation of the hemodynamics in the portal venous system plays an essential role in many hepatic pathologies. Changes in portal flow and vessel morphology are often indicative of disease.Routinely used imaging modalities, such as CT, ultrasound, invasive angiography, and MRI, often focus on either hemodynamics or anatomical imaging. In contrast, 4D flow MRI facilitiates a more comprehensive understanding of pathophysiological mechanisms by simultaneously and noninvasively acquiring time-resolved flow and anatomical information in a 3D imaging volume.Though promising, 4D flow MRI in the portal venous system is especially challenging due to small vessel calibers, slow flow velocities, and breathing motion. In this review article, we will discuss how to account for these challenges when planning and conducting 4D flow MRI acquisitions in the upper abdomen. We will address patient preparation, sequence acquisition, postprocessing, quality control, and analysis of 4D flow data.In the second part of this article, we will review potential clinical applications of 4D flow MRI in the portal venous system. The most promising area for clinical utilization is the diagnosis and grading of liver cirrhosis and its complications. Relevant parameters acquired by 4D flow MRI include the detection of reduced or reversed flow in the portal venous system, characterization of portosystemic collaterals, and impaired response to a meal challenge. In patients with cirrhosis, 4D flow MRI has the potential to address the major unmet need of noninvasive detection of gastroesophageal varices at high risk for bleeding. This could replace many unnecessary, purely diagnostic, and invasive esophagogastroduodenoscopy procedures, thereby improving patient compliance with follow-up. Moreover, 4D flow MRI offers unique insights and added value for surgical planning and follow-up of multiple hepatic interventions, including transjugular intrahepatic portosystemic shunts, liver transplantation, and hepatic disease in children. Lastly, we will discuss the path to clinical implementation and remaining challenges.

Self-gated 3D stack-of-spirals UTE pulmonary imaging at 0.55T

PURPOSE

To develop an isotropic high-resolution stack-of-spirals UTE sequence for pulmonary imaging at 0.55 Tesla by leveraging a combination of robust respiratory-binning, trajectory correction, and concomitant-field corrections.

METHODS

A stack-of-spirals golden-angle UTE sequence was used to continuously acquire data for 15.5 minutes. The data was binned to a stable respiratory phase based on superoinferior readout self-navigator signals. Corrections for trajectory errors and concomitant field artifacts, along with image reconstruction with conjugate gradient SENSE, were performed inline within the Gadgetron framework. Finally, data were retrospectively reconstructed to simulate scan times of 5, 8.5, and 12 minutes. Image quality was assessed using signal-to-noise, image sharpness, and qualitative reader scores. The technique was evaluated in healthy volunteers, patients with coronavirus disease 2019 infection, and patients with lung nodules.

RESULTS

The technique provided diagnostic quality images with parenchymal lung SNR of 3.18 ± 0.0.60, 4.57 ± 0.87, 5.45 ± 1.02, and 5.89 ± 1.28 for scan times of 5, 8.5, 12, and 15.5 minutes, respectively. The respiratory binning technique resulted in significantly sharper images (p < 0.001) as measured with relative maximum derivative at the diaphragm. Concomitant field corrections visibly improved sharpness of anatomical structures away from iso-center. The image quality was maintained with a slight loss in SNR for simulated scan times down to 8.5 minutes. Inline image reconstruction and artifact correction were achieved in <5 minutes.

CONCLUSION

The proposed pulmonary imaging technique combined efficient stack-of-spirals imaging with robust respiratory binning, concomitant field correction, and trajectory correction to generate diagnostic quality images with 1.75 mm isotropic resolution in 8.5 minutes on a high-performance 0.55 Tesla system.

Free-breathing radial imaging using a pilot-tone radiofrequency transmitter for detection of respiratory motion

PURPOSE

To describe an approach for detection of respiratory signals using a transmitted radiofrequency (RF) reference signal called Pilot-Tone (PT) and to use the PT signal for creation of motion-resolved images based on 3D stack-of-stars imaging under free-breathing conditions.

METHODS

This work explores the use of a reference RF signal generated by a small RF transmitter, placed outside the MR bore. The reference signal is received in parallel to the MR signal during each readout. Because the received PT amplitude is modulated by the subject's breathing pattern, a respiratory signal can be obtained by detecting the strength of the received PT signal over time. The breathing-induced PT signal modulation can then be used for reconstructing motion-resolved images from free-breathing scans. The PT approach was tested in volunteers using a radial stack-of-stars 3D gradient echo (GRE) sequence with golden-angle acquisition.

RESULTS

Respiratory signals derived from the proposed PT method were compared to signals from a respiratory cushion sensor and k-space-center-based self-navigation under different breathing conditions. Moreover, the accuracy was assessed using a modified acquisition scheme replacing the golden-angle scheme by a zero-angle acquisition. Incorporating the PT signal into eXtra-Dimensional (XD) motion-resolved reconstruction led to improved image quality and clearer anatomical depiction of the lung and liver compared to k-space-center signal and motion-averaged reconstruction, when binned into 6, 8, and 10 motion states.

CONCLUSION

PT is a novel concept for tracking respiratory motion. Its small dimension (8 cm), high sampling rate, and minimal interaction with the imaging scan offers great potential for resolving respiratory motion.

Self-Navigated Three-Dimensional Ultrashort Echo Time Technique for Motion-Corrected Skull MRI

Ultrashort echo time (UTE) MRI is capable of detecting signals from protons with very short T₂ relaxation times, and thus has potential for skull-selective imaging as a radiation-free alternative to computed tomography. However, relatively long scan times make the technique vulnerable to artifacts from involuntary subject motion. Here, we developed a self-navigated, three-dimensional (3D) UTE pulse sequence, which builds on dual-RF, dual-echo UTE imaging, and a retrospective motion correction scheme for motion-resistant skull MRI. Full echo signals in the second readout serve as a self-navigator that yields a time-course of center of mass, allowing for adaptive determination of motion states. Furthermore, golden-means based k-space trajectory was employed to achieve a quasi-uniform distribution of sampling views on a spherical k-space surface for any subset of the entire data collected, thereby allowing reconstruction of low-resolution images pertaining to each motion state for subsequent estimation of rigid-motion parameters. Finally, the extracted trajectory of the head was used to make the whole k-space datasets motion-consistent, leading to motion-corrected, high-resolution images. Additionally, we posit that hardware-related k-space trajectory errors, if uncorrected, result in obscured bone contrast. Thus, a calibration scan was performed once to measure k-space encoding locations, subsequently used during image reconstruction of actual imaging data. In vivo studies were performed to evaluate the effectiveness of the proposed correction schemes in combination with approaches to accelerated bone-selective imaging. Results illustrating effective removal of motion artifacts and clear depiction of skull bone voxels suggest that the proposed method is robust to intermittent head motions during scanning.

Sharpness in motion corrected quantitative imaging at 7T

Sub-millimeter imaging at 7T has opened new possibilities for qualitatively and quantitatively studying brain structure as it evolves throughout the life span. However, subject motion introduces image blurring on the order of magnitude of the spatial resolution and is thus detrimental to image quality. Such motion can be corrected for, but widespread application has not yet been achieved and quantitative evaluation is lacking. This raises a need to quantitatively measure image sharpness throughout the brain. We propose a method to quantify sharpness of brain structures at sub-voxel resolution, and use it to assess to what extent limited motion is related to image sharpness. The method was evaluated in a cohort of 24 healthy volunteers with a wide and uniform age range, aiming to arrive at results that largely generalize to larger populations. Using 3D fat-excited motion navigators, quantitative R₁, R₂^* and Quantitative Susceptibility Maps and T₁-weighted images were retrospectively corrected for motion. Sharpness was quantified in all modalities for selected regions of interest (ROI) by fitting the sigmoidally shaped error function to data within locally homogeneous clusters. A strong, almost linear correlation between motion and sharpness improvement was observed, and motion correction significantly improved sharpness. Overall, the Full Width at Half Maximum reduced from 0.88 mm to 0.70 mm after motion correction, equivalent to a 2.0 times smaller voxel volume. Motion and sharpness were not found to correlate with the age of study participants. We conclude that in our data, motion correction using fat navigators is overall able to restore the measured sharpness to the imaging resolution, irrespective of the amount of motion observed during scanning.

Three-dimensional motion-corrected T1 relaxometry with MPnRAGE

PURPOSE

To test the performance of the MPnRAGE motion-correction algorithm on quantitative relaxometry estimates.

METHODS

Twelve children (9.4 ± 2.6 years, min = 6.5 years, max = 13.8 years) were imaged 3 times in a session without sedation. Stabilization padding was not used for the second and third scans. Quantitative T₁ values were estimated in each voxel on images reconstructed with and without motion correction. Mean T₁ values were assessed in various regions determined from automated segmentation algorithms. Statistical tests were performed on mean values and the coefficient of variation across the measurements. Accuracy of T₁ estimates were determined by scanning the High Precision Devices (Boulder, CO) MRI system phantom with the same protocol.

RESULTS

The T₁ values obtained with MPnRAGE agreed within 4% of the reference values of the High Precision Devices phantom. The best fit line was T₁ (MPnRAGE) = 1.02 T₁ (reference)-0.9 ms, R²  = 0.9999. For in vivo studies, motion correction reduced the coefficients of variation of mean T₁ values in whole-brain tissue regions determined by FSL FAST by 74% ± 7%, and subcortical regions determined by FIRST and FreeSurfer by 32% ± 21% and 33% ± 26%, respectively. Across all participants, the mean coefficients of variation ranged from 0.8% to 2.0% for subcortical regions and 0.6% ± 0.5% for cortical regions when motion correction was applied.

CONCLUSION

The MPnRAGE technique demonstrated highly accurate values in phantom measurements. When combined with retrospective motion correction, MPnRAGE demonstrated highly reproducible T₁ values, even in participants who moved during the acquisition.

Motion-corrected MRI with DISORDER: Distributed and incoherent sample orders for reconstruction deblurring using encoding redundancy

PURPOSE

To enable rigid body motion-tolerant parallel volumetric magnetic resonance imaging by retrospective head motion correction on a variety of spatiotemporal scales and imaging sequences.

THEORY AND METHODS

Tolerance against rigid body motion is based on distributed and incoherent sampling orders for boosting a joint retrospective motion estimation and reconstruction framework. Motion resilience stems from the encoding redundancy in the data, as generally provided by the coil array. Hence, it does not require external sensors, navigators or training data, so the methodology is readily applicable to sequences using 3D encodings.

RESULTS

Simulations are performed showing full inter-shot corrections for usual levels of in vivo motion, large number of shots, standard levels of noise and moderate acceleration factors. Feasibility of inter- and intra-shot corrections is shown under controlled motion in vivo. Practical efficacy is illustrated by high-quality results in most corrupted of 208 volumes from a series of 26 clinical pediatric examinations collected using standard protocols.

CONCLUSIONS

The proposed framework addresses the rigid motion problem in volumetric anatomical brain scans with sufficient encoding redundancy which has enabled reliable pediatric examinations without sedation.

Reducing motion sensitivity in 3D high-resolution T2*-weighted MRI by navigator-based motion and nonlinear magnetic field correction

T₂*-weighted gradient echo (GRE) MRI at high field is uniquely sensitive to the magnetic properties of tissue and allows the study of brain and vascular anatomy at high spatial resolution. However, it is also sensitive to B₀ field changes induced by head motion and physiological processes such as the respiratory cycle. Conventional motion correction techniques do not take these field changes into account, and consequently do not fully recover image quality in T₂*-weighted MRI. Here, a novel approach was developed to address this by monitoring the B₀ field with a volumetric EPI phase navigator. The navigator was acquired at a shorter echo time than that of the (higher resolution) T₂*-weighted GRE imaging data and accelerated with parallel imaging for high temporal resolution. At 4 ​mm isotropic spatial resolution and 0.54 ​s temporal resolution, the accuracy for estimation of rotation and translation was better than 0.2° and 0.1 ​mm, respectively. The 10% and 90% percentiles of B₀ measurement error using the navigator were -1.8 and 1.5 Hz  at 7 T, respectively. A fast retrospective reconstruction algorithm correcting for both motion and nonlinear B₀ changes was also developed. The navigator and reconstruction algorithm were evaluated in correcting motion-corrupted high-resolution T₂*-weighted GRE MRI on healthy human subjects at 7 ​T. Excellent image quality was demonstrated with the proposed correction method.

Motion robust respiratory-resolved 3D radial flow MRI and its application in neonatal congenital heart disease

PURPOSE

To test and implement a motion-robust and respiratory-resolved 3D Radial Flow framework that addresses the need for rapid, high resolution imaging in neonatal patients with congenital heart disease.

METHODS

A 4-point velocity encoding and 3D radial trajectory with double-golden angle ordering was combined with bulk motion correction (from projection center of mass) and respiration phase detection (from principal component analysis of heartbeat-averaged data) to create motion-robust 3D velocity cardiac time-averaged data. This framework was tested in a whole-chest digital phantom with simulated bulk and realistic physiological motion. In vivo imaging was performed in 20 congenital heart disease infants under feed-and-sleep with submillimeter isotropic resolution in ~3 min. Flows were validated against clinical 2D PCMRI and whole-heart visualizations of blood flow were performed.

RESULTS

The proposed framework resolved all simulated digital phantom motion states (mean ± standard error: rotation - azimuthal = 0.29 ± 0.02°; translation - T_y = 1.29 ± 0.12 mm, T_z = -0.27 ± 0.13 mm; rotation+translation - polar = 0.49 ± 0.16°, T_x = -2.47 ± 0.51 mm, T_z = 5.78 ± 1.33 mm). Measured timing errors of peak expiration across all signal-to-noise ratio values were 22% of the true respiratory period (range = [404-489 ± 298-334] ms). For in vivo imaging, motion correction improved 3D Radial Flow measurements (no correction: R² = 0.62, root mean square error = 0.80 L/min/m² , Bland-Altman bias [limits of agreement] = -0.21 [-1.40, 0.94] L/min/m² ; motion corrected, expiration: R² = 0.90, root mean square error = 0.46 L/min/m² , bias [limits of agreement] = 0.06 [-0.49, 0.62] L/min/m² ). Respiratory-resolved 3D velocity visualizations were achieved in various neonatal pathologies pre- and postsurgical correction.

CONCLUSION

3D cardiac flow may be visualized and accurately quantified in neonatal subjects using the proposed framework. This technique may enable more comprehensive hemodynamic studies in small infants.

Robust Motion Correction Strategy for Structural MRI in Unsedated Children Demonstrated with Three-dimensional Radial MPnRAGE

Purpose To develop and evaluate a retrospective method to minimize motion artifacts in structural MRI. Materials and Methods The motion-correction strategy was developed for three-dimensional radial data collection and demonstrated with MPnRAGE, a technique that acquires high-resolution volumetric magnetization-prepared rapid gradient-echo, or MPRAGE, images with multiple tissue contrasts. Forty-four pediatric participants (32 with autism spectrum disorder [mean age ± standard deviation, 13 years ± 3] and 12 age-matched control participants [mean age, 12 years ± 3]) were imaged without sedation. Images with and images without retrospective motion correction were scored by using a Likert scale (0-4 for unusable to excellent) by two experienced neuroradiologists. The Tenengrad metric (a reference-free measure of image sharpness) and statistical analyses were performed to determine the effects of performing retrospective motion correction. Results MPnRAGE T1-weighted images with retrospective motion correction were all judged to have good or excellent quality. In some cases, retrospective motion correction improved the image quality from unusable (Likert score of 0) to good (Likert score of 3). Overall, motion correction improved mean Likert scores from 3.0 to 3.8 and reduced standard deviations from 1.1 to 0.4. Image quality was significantly improved with motion correction (Mann-Whitney U test; P < .001). Intraclass correlation coefficients for absolute agreement of Tenengrad scores with reviewers 1 and 2 were 0.92 and 0.88 (P < .0005 for both), respectively. In no cases did the retrospective motion correction induce severe image degradation. Conclusion Retrospective motion correction of MPnRAGE data were shown to be highly effective for consistently improving image quality of T1-weighted MRI in unsedated pediatric participants, while also enabling multiple tissue contrasts to be reconstructed for structural analysis. © RSNA, 2018 Online supplemental material is available for this article.

Adaptive bulk motion exclusion for improved robustness of abdominal magnetic resonance imaging

Non-Cartesian magnetic resonance imaging (MRI) sequences have shown great promise for abdominal examination during free breathing, but break down in the presence of bulk patient motion (i.e. voluntary or involuntary patient movement resulting in translation, rotation or elastic deformations of the body). This work describes a data-consistency-driven image stabilization technique that detects and excludes bulk movements during data acquisition. Bulk motion is identified from changes in the signal intensity distribution across different elements of a multi-channel receive coil array. A short free induction decay signal is acquired after excitation and used as a measure to determine alterations in the load distribution. The technique has been implemented on a clinical MR scanner and evaluated in the abdomen. Six volunteers were scanned and two radiologists scored the reconstructions. To show the applicability to other body areas, additional neck and knee images were acquired. Data corrupted by bulk motion were successfully detected and excluded from image reconstruction. An overall increase in image sharpness and reduction of streaking and shine-through artifacts were seen in the volunteer study, as well as in the neck and knee scans. The proposed technique enables automatic real-time detection and exclusion of bulk motion during MR examinations without user interaction. It may help to improve the reliability of pediatric MRI examinations without the use of sedation.

Trimmed autocalibrating k-space estimation based on structured matrix completion

PURPOSE

Parallel imaging allows the reconstruction of undersampled data from multiple coils. This provides a means to reject and regenerate corrupt data (e.g. from motion artefact). The purpose of this work is to approach this problem using the SAKE parallel imaging method.

THEORY AND METHODS

Parallel imaging methods typically require calibration by fully sampling the center of k-space. This is a challenge in the presence of corrupted data, since the calibration data may be corrupted which leads to an errors-in-variables problem that cannot be solved by least squares or even iteratively reweighted least squares. The SAKE method, based on matrix completion and structured low rank approximation, was modified to detect and trim these errors from the data.

RESULTS

Simulated and actual corrupted datasets were reconstructed with SAKE, the proposed approach and a more standard reconstruction method (based on solving a linear equation) with a data rejection criterion. The proposed approach was found to reduce artefacts considerably in comparison to the other two methods.

CONCLUSION

SAKE with data trimming improves on previous methods for reconstructing images from grossly corrupted data.

Three-dimensional motion corrected sensitivity encoding reconstruction for multi-shot multi-slice MRI: Application to neonatal brain imaging

PURPOSE

To introduce a methodology for the reconstruction of multi-shot, multi-slice magnetic resonance imaging able to cope with both within-plane and through-plane rigid motion and to describe its application in structural brain imaging.

THEORY AND METHODS

The method alternates between motion estimation and reconstruction using a common objective function for both. Estimates of three-dimensional motion states for each shot and slice are gradually refined by improving on the fit of current reconstructions to the partial k-space information from multiple coils. Overlapped slices and super-resolution allow recovery of through-plane motion and outlier rejection discards artifacted shots. The method is applied to T₂ and T₁ brain scans acquired in different views.

RESULTS

The procedure has greatly diminished artifacts in a database of 1883 neonatal image volumes, as assessed by image quality metrics and visual inspection. Examples showing the ability to correct for motion and robustness against damaged shots are provided. Combination of motion corrected reconstructions for different views has shown further artifact suppression and resolution recovery.

CONCLUSION

The proposed method addresses the problem of rigid motion in multi-shot multi-slice anatomical brain scans. Tests on a large collection of potentially corrupted datasets have shown a remarkable image quality improvement. Magn Reson Med 79:1365-1376, 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.

Role of MRI for detecting micro cracks in teeth

OBJECTIVES

To evaluate the limit of tooth crack width visualization by two MRI pulse sequences in comparison with CBCT.

METHODS

Two extracted human teeth with known crack locations and dimensions, as determined by reference standard microCT, were selected for experimental imaging. Crack location/dimension and the presence of common dental restorative materials such as amalgam were typical of that found clinically. Experimental imaging consisted of conventional CBCT scans and MRI scans with two pulse sequences including Sweep Imaging with Fourier Transformation (SWIFT) and gradient echo (GRE). CBCT and MR images of extracted teeth were acquired using acquisition parameters identical to those used for in vivo imaging. Experimental and reference standard images were registered and the limit of tooth crack visualization was determined.

RESULTS

Collected images indicate that SWIFT could demonstrate cracks with 20-µm width, which is 10 times narrower than the imaging voxel size. Cracks of this size were not visible in GRE images, even with a short echo time of 2.75 ms. The CBCT images were distorted by artefacts owing to close location of metallic restorations.

CONCLUSIONS

The successful visualization of cracks with the SWIFT MRI sequence compared with other clinical modalities suggests that SWIFT MRI can effectively detect microcracks in teeth and therefore may have potential to be a non-invasive method for the in vivo detection of cracks in human teeth.

Optimizing the acceleration and resolution of three-dimensional fat image navigators for high-resolution motion correction at 7T

PURPOSE

To investigate the effect of spatial resolution and parallel imaging acceleration factor on the quality of the motion estimates derived from image navigators with a three-dimensional (3D) gradient-recalled echo (GRE) acquisition with fat excitation (3D FatNavs) for neuroimaging at 7T.

METHODS

Six healthy subjects were scanned for 10 min, during which time repeated GRE volumes were acquired during small movements-alternating between fat and water excitations (WaterNavs)-allowing retrospective decimation of the data to simulate a variety of combinations of image resolution and acceleration factor. Bias and error in the motion estimates were then compared across navigator parameters.

RESULTS

The 2-mm, 4 × 4 accelerated data (TR_volume  = 1.2 s) provided motion estimates that were almost indistinguishable from those from the full original acquisition (2 mm, 2 × 2, TR_volume  = 5.2 s). For faster navigators, it was found that good accuracy and precision were achievable with TR_volume  = 144 ms, using a lower spatial resolution (4 mm, 6 × 6 acceleration) to avoid the bias observed at exceptionally high acceleration factors (8 × 8 or higher). Parameter estimates from WaterNavs and FatNavs showed close agreement with FatNavs, with better performance at exceptionally high acceleration factors.

CONCLUSION

Our data help to guide the parameter choice for 3D FatNavs when a compromise must be reached between the quality of the motion estimates and the available scan time. Magn Reson Med 77:547-558, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Optical tracking with two markers for robust prospective motion correction for brain imaging

OBJECTIVE

Prospective motion correction (PMC) during brain imaging using camera-based tracking of a skin-attached marker may suffer from problems including loss of marker visibility due to the coil and false correction due to non-rigid-body facial motion, such as frowning or squinting. A modified PMC system is introduced to mitigate these problems and increase the robustness of motion correction.

MATERIALS AND METHODS

The method relies on simultaneously tracking two markers, each providing six degrees of freedom, that are placed on the forehead. This allows us to track head motion when one marker is obscured and detect skin movements to prevent false corrections. Experiments were performed to compare the performance of the two-marker motion correction technique to the previous single-marker approach.

RESULTS

Experiments validate the theory developed for adaptive marker tracking and skin movement detection, and demonstrate improved image quality during obstruction of the line-of-sight of one marker when subjects squint or when subjects squint and move simultaneously.

CONCLUSION

The proposed methods eliminate two common failure modes of PMC and substantially improve the robustness of PMC, and they can be applied to other optical tracking systems capable of tracking multiple markers. The methods presented can be adapted to the use of more than two markers.

MPnRAGE: A technique to simultaneously acquire hundreds of differently contrasted MPRAGE images with applications to quantitative T1 mapping

PURPOSE

To introduce a new technique called MPnRAGE, which produces hundreds of images with different T1 contrasts and a B1 corrected T1 map.

THEORY AND METHODS

An interleaved three-dimensional radial k-space trajectory with a sliding window reconstruction is used in conjunction with magnetization preparation pulses. This work modifies the SNAPSHOT-FLASH T1 fitting equations for radial imaging with view-sharing and develops a new rapid B1 correction procedure. MPnRAGE is demonstrated in phantoms and volunteers, including two volunteers with eight scans each and eight volunteers with two scans each. T1 values from MPnRAGE were compared with those from fast spin echo inversion recovery (FSE-IR) in phantoms and a healthy human brain at 3 Tesla (T).

RESULTS

The T1 fit for human white and gray matter was T1MPnRAGE = 1.00 · T1FSE-IR + 24 ms, r(2) = 0.990. Voxel-wise coefficient of variation in T1 measurements across eight time points was between 0.02 and 0.08. Region of interest-based T1 values were reproducible to within 2% and agree well with literature values.

CONCLUSION

In the same amount of time as a traditional MPRAGE exam (7.5 min), MPnRAGE was shown to produce hundreds of images with alternate T1 contrasts as well as an accurate and reproducible T1 map that is robust to B1 errors.

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

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Motion artifacts in MRI: A complex problem with many partial solutions

Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artifacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artifacts, but no single method can be applied in all imaging situations. Instead, a "toolbox" of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artifacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artifacts, with the aim of aiding artifact detection and mitigation in particular clinical situations.

Removal of cerebrospinal fluid partial volume effects in quantitative magnetization transfer imaging using a three-pool model with nonexchanging water component

PURPOSE

Parameters of the two-pool model describing magnetization transfer (MT) in macromolecule-rich tissues may be significantly biased in partial volume (PV) voxels containing cerebrospinal fluid (CSF). The purpose of this study was to develop a quantitative MT (qMT) method that provides indices insensitive to CSF PV averaging.

THEORY AND METHODS

We propose a three-pool MT model, in which PV macro-compartment is modeled as an additional nonexchanging water pool. We demonstrate the feasibility of model parameter estimation from several MT-weighted spoiled gradient echo datasets. We validated the three-pool model in numerical, phantom, and in vivo studies.

RESULTS

PV averaging with the free water compartment reduces all qMT parameters, most significantly affecting macromolecular proton fraction (MPF) and cross-relaxation rate. Monte-Carlo simulations confirmed stability of the three-pool model fit. Unlike the standard two-pool model, the three-pool model qMT parameters were not affected by PV averaging in simulations and phantom studies. The three-pool model fit allowed CSF PV correction in brain PV voxels and resulted in good correlation with standard two-pool model parameters in non-PV voxels.

CONCLUSION

Quantitative MT imaging based on a three-pool model with a non-exchanging water component yields a set of CSF-insensitive qMT parameters, which may improve MPF-based assessment of myelination in structures strongly affected by CSF PV averaging such as brain gray matter.

Fast susceptibility-weighted imaging with three-dimensional short-axis propeller (SAP)-echo-planar imaging

BACKGROUND

Susceptibility-weighted imaging (SWI) in neuroimaging can be challenging due to long scan times of three-dimensional (3D) gradient recalled echo (GRE), while faster techniques such as 3D interleaved echo-planar imaging (iEPI) are prone to motion artifacts. Here we outline and implement a 3D short-axis propeller echo-planar imaging (SAP-EPI) trajectory as a faster, motion-correctable approach for SWI.

METHODS

Experiments were conducted on a 3T MRI system. The 3D SAP-EPI, 3D iEPI, and 3D GRE SWI scans were acquired on two volunteers. Controlled motion experiments were conducted to test the motion-correction capability of 3D SAP-EPI. The 3D SAP-EPI SWI data were acquired on two pediatric patients as a potential alternative to 2D GRE used clinically.

RESULTS

The 3D GRE images had a better target resolution (0.47 × 0.94 × 2 mm, scan time = 5 min), iEPI and SAP-EPI images (resolution = 0.94 × 0.94 × 2 mm) were acquired in a faster scan time (1:52 min) with twice the brain coverage. SAP-EPI showed motion-correction capability and some immunity to undersampling from rejected data.

CONCLUSION

While 3D SAP-EPI suffers from some geometric distortion, its short scan time and motion-correction capability suggest that SAP-EPI may be a useful alternative to GRE and iEPI for use in SWI, particularly in uncooperative patients.

Speech MRI: morphology and function

Magnetic Resonance Imaging (MRI) plays an increasing role in the study of speech. This article reviews the MRI literature of anatomical imaging, imaging for acoustic modelling and dynamic imaging. It describes existing imaging techniques attempting to meet the challenges of imaging the upper airway during speech and examines the remaining hurdles and future research directions.

Diffusion-weighted imaging of the sellar region: a comparison study of BLADE and single-shot echo planar imaging sequences

PURPOSE

The purpose of this study is to compare BLADE diffusion-weighted imaging (DWI) with single-shot echo planar imaging (EPI) DWI on the aspects of feasibility of imaging the sellar region and image quality.

METHODS

A total of 3 healthy volunteers and 52 patients with suspected lesions in the sellar region were included in this prospective intra-individual study. All exams were performed at 3.0T with a BLADE DWI sequence and a standard single-shot EP-DWI sequence. Phantom measurements were performed to measure the objective signal-to-noise ratio (SNR). Two radiologists rated the image quality according to the visualisation of the internal carotid arteries, optic chiasm, pituitary stalk, pituitary gland and lesion, and the overall image quality. One radiologist measured lesion sizes for detecting their relationship with the image score.

RESULTS

The SNR in BLADE DWI sequence showed no significant difference from the single-shot EPI sequence (P>0.05). All of the assessed regions received higher scores in BLADE DWI images than single-shot EP-DWI.

Aggregated motion estimation for real-time MRI reconstruction

PURPOSE

In real-time MRI serial images are generally reconstructed from highly undersampled datasets as the iterative solutions of an inverse problem. While practical realizations based on regularized nonlinear inversion (NLINV) have hitherto been surprisingly successful, strong assumptions about the continuity of image features may affect the temporal fidelity of the estimated reconstructions.

THEORY AND METHODS

The proposed method for real-time image reconstruction integrates the deformations between nearby frames into the data consistency term of the inverse problem. The aggregated motion estimation (AME) is not required to be affine or rigid and does not need additional measurements. Moreover, it handles multi-channel MRI data by simultaneously determining the image and its coil sensitivity profiles in a nonlinear formulation which also adapts to non-Cartesian (e.g., radial) sampling schemes. The new method was evaluated for real-time MRI studies using highly undersampled radial gradient-echo sequences.

RESULTS

AME reconstructions for a motion phantom with controlled speed as well as for measurements of human heart and tongue movements demonstrate improved temporal fidelity and reduced residual undersampling artifacts when compared with NLINV reconstructions without motion estimation.

CONCLUSION

Nonlinear inverse reconstructions with aggregated motion estimation offer improved image quality and temporal acuity for visualizing rapid dynamic processes by real-time MRI.

Comparison of mouse brain DTI maps using K-space average, image-space average, or no average approach

Diffusion tensor imaging (DTI) is achieved by collecting a series of diffusion-weighted images (DWIs). Signal averaging of multiple repetitions can be performed in the k-space (k-avg) or in the image space (m-avg) to improve the image quality. Alternatively, one can treat each acquisition as an independent image and use all of the data to reconstruct the DTI without doing any signal averaging (no-avg). To compare these three approaches, in this study, in vivo DTI data were collected from five normal mice. Noisy data with signal-to-noise ratios (SNR) that varied between five and 30 (before averaging) were then simulated. The DTI indices, including relative anisotropy (RA), trace of diffusion tensor (TR), axial diffusivity (λ║), and radial diffusivity (λ⊥), derived from the k-avg, m-avg, and no-avg, were then compared in the corpus callosum white matter, cortex gray matter, and the ventricles. We found that k-avg and m-avg enhanced the SNR of DWI with no significant differences. However, k-avg produced lower RA in the white matter and higher RA in the gray matter, compared to the m-avg and no-avg, regardless of SNR. The latter two produced similar DTI quantifications. We concluded that k-avg is less preferred for DTI brain imaging.