Real‐time motion and retrospective coil sensitivity correction for CEST using volumetric navigators (vNavs) at 7T

PURPOSE: To explore the impact of temporal motion-induced coil sensitivity changes on CEST-MRI at 7T and its correction using interleaved volumetric EPI navigators, which are applied for real-time motion correction. METHODS: Five healthy volunteers were scanned via CEST. A 4-fold correction pipeline allowed the mitigation of (1) motion, (2) motion-induced coil sensitivity variations, Δ B 1 - , (3) motion-induced static magnetic field inhomogeneities, ΔB0 , and (4) spatially varying transmit RF field fluctuations, ΔB 1 + . Four CEST measurements were performed per session. For the first 2, motion correction was turned OFF and then ON in absence of voluntary motion, whereas in the other 2 controlled head rotations were performed. During post-processing Δ B 1 - was removed additionally for the motion-corrected cases, resulting in a total of 6 scenarios to be compared. In all cases, retrospective ∆B0 and - ΔB 1 + corrections were performed to compute artifact-free magnetization transfer ratio maps with asymmetric analysis (MTRasym ). RESULTS: Dynamic Δ B 1 - correction successfully mitigated signal deviations caused by head motion. In 2 frontal lobe regions of volunteer 4, induced relative signal errors of 10.9% and 3.9% were reduced to 1.1% and 1.0% after correction. In the right frontal lobe, the motion-corrected MTRasym contrast deviated 0.92%, 1.21%, and 2.97% relative to the static case for Δω = 1, 2, 3 ± 0.25 ppm. The additional application of Δ B 1 - correction reduced these deviations to 0.10%, 0.14%, and 0.42%. The fully corrected MTRasym values were highly consistent between measurements with and without intended head rotations. CONCLUSION: Temporal Δ B 1 - cause significant CEST quantification bias. The presented correction pipeline including the proposed retrospective Δ B 1 - correction significantly reduced motion-related artifacts on CEST-MRI

Real-time motion and retrospective coil sensitivity correction for CEST using volumetric navigators (vNavs) at 7T

Purpose To explore the impact of temporal motion-induced coil sensitivity changes on CEST-MRI at 7T and its correction using interleaved volumetric EPI navigators, which are applied for real-time motion correction. Methods Five healthy volunteers were scanned via CEST. A 4-fold correction pipeline allowed the mitigation of (1) motion, (2) motion-induced coil sensitivity variations, Delta B1-, (3) motion-induced static magnetic field inhomogeneities, Delta B-0, and (4) spatially varying transmit RF field fluctuations, Delta B1+. Four CEST measurements were performed per session. For the first 2, motion correction was turned OFF and then ON in absence of voluntary motion, whereas in the other 2 controlled head rotations were performed. During post-processing Delta B1- was removed additionally for the motion-corrected cases, resulting in a total of 6 scenarios to be compared. In all cases, retrospective increment B-0 and -Delta B1+ corrections were performed to compute artifact-free magnetization transfer ratio maps with asymmetric analysis (MTRasym). Results Dynamic Delta B1- correction successfully mitigated signal deviations caused by head motion. In 2 frontal lobe regions of volunteer 4, induced relative signal errors of 10.9% and 3.9% were reduced to 1.1% and 1.0% after correction. In the right frontal lobe, the motion-corrected MTRasym contrast deviated 0.92%, 1.21%, and 2.97% relative to the static case for Delta omega = 1, 2, 3 +/- 0.25 ppm. The additional application of Delta B1- correction reduced these deviations to 0.10%, 0.14%, and 0.42%. The fully corrected MTRasym values were highly consistent between measurements with and without intended head rotations. Conclusion Temporal Delta B1- cause significant CEST quantification bias. The presented correction pipeline including the proposed retrospective Delta B1- correction significantly reduced motion-related artifacts on CEST-MRI.Peer reviewe

Real-time motion and main magnetic field correction in MR spectroscopy using an EPI volumetric navigator

In population groups where subjects do not lie still during Magnetic Resonance Spectroscopy (MRS) scans, real-time volume of interest (VOI), frequency, and main magnetic field (B0) shim correction may be necessary. This work demonstrates firstly that head movement causes significant B0 disruption in both single voxel spectroscopy and spectroscopic imaging

Real-time motion analytics during brain MRI improve data quality and reduce costs

Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional 'buffer data', an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more

Additional sampling directions improve detection range of wireless probes

PURPOSE: While MRI is enhancing our knowledge about the structure and function of the human brain, subject motion remains a problem in many clinical applications. Recently, the use of wireless radiofrequency markers with three one-dimensional (1D) navigators for prospective correction was demonstrated. This method is restricted in the range of motion that can be corrected, however, because of limited information in the 1D readouts. METHODS: Here, the limitation of techniques for disambiguating marker locations was investigated. It was shown that including more sampling directions extends the tracking range for head rotations. The efficiency of trading readout resolution for speed was explored. RESULTS: Tracking of head rotations was demonstrated from -19.2 to 34.4°, -2.7 to 10.0°, and -60.9 to 70.9° in the x-, y-, and z-directions, respectively. In the presence of excessive head motion, the deviation of marker estimates from SPM8 was reduced by 17.1% over existing three-projection methods. This was achieved by using an additional seven directions, extending the time needed for readouts by a factor of 3.3. Much of this increase may be circumvented by reducing resolution, without compromising accuracy. CONCLUSION: Including additional sampling directions extends the range in which markers can be used, for patients who move a lot. Magn Reson Med 76:913-918, 2016. © 2015 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.The project was supported by funding from the Isaac Newton Trust, the Wellcome Trust ISSF, and the Cusanuswerk funding body (Bonn, Germany).This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/mrm.2599

Retrospective Motion Correction in Magnetic Resonance Imaging of the Brain

Magnetic Resonance Imaging (MRI) is a tremendously useful diagnostic imaging modality that provides outstanding soft tissue contrast. However, subject motion is a significant unsolved problem; motion during image acquisition can cause blurring and distortions in the image, limiting its diagnostic utility. Current techniques for addressing head motion include optical tracking which can be impractical in clinical settings due to challenges associated with camera cross-calibration and marker fixation. Another category of techniques is MRI navigators, which use specially acquired MRI data to track the motion of the head. This thesis presents two techniques for motion correction in MRI: the first is spherical navigator echoes (SNAVs), which are rapidly acquired k-space navigators. The second is a deep convolutional neural network trained to predict an artefact-free image from motion-corrupted data. Prior to this thesis, SNAVs had been demonstrated for motion measurement but not motion correction, and they required the acquisition of a 26s baseline scan during which the subject could not move. In this work, a novel baseline approach is developed where the acquisition is reduced to 2.6s. Spherical navigators were interleaved into a spoiled gradient echo sequence (SPGR) on a stand-alone MRI system and a turbo-FLASH sequence (tfl) on a hybrid PET/MRI system to enable motion measurement throughout image acquisition. The SNAV motion measurements were then used to retrospectively correct the image data. While MRI navigator methods, particularly SNAVs that can be acquired very rapidly, are useful for motion correction, they do require pulse sequence modifications. A deep learning technique may be a more general solution. In this thesis, a conditional generative adversarial network (cGAN) is trained to perform motion correction on image data with simulated motion artefacts. We simulate motion in previously acquired brain images and use the image pairs (corrupted + original) to train the cGAN. MR image data was qualitatively and quantitatively improved following correction using the SNAV motion estimates. This was also true for the simultaneously acquired MR and PET data on the hybrid system. Motion corrected images were more similar than the uncorrected to the no-motion reference images. The deep learning approach was also successful for motion correction. The trained cGAN was evaluated on 5 subjects; and artefact suppression was observed in all images

The Human Connectome Project's neuroimaging approach

Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease

Double volumetric navigators for real-time simultaneous shim and motion measurement and correction in Glycogen Chemical Exchange Saturation Transfer (GlycoCEST) MRI

Glycogen is the primary glucose storage mechanism in in living systems and plays a central role in systemic glucose homeostasis. The study of muscle glycogen concentrations in vivo still largely relies on tissue sampling methods via needle biopsy. However, muscle biopsies are invasive and limit the frequency of measurements and the number of sites that can be assessed. Non-invasive methods for quantifying glycogen in vivo are therefore desirable in order to understand the pathophysiology of common diseases with dysregulated glycogen metabolism such as obesity, insulin resistance, and diabetes, as well as glycogen metabolism in sports physiology. Chemical Exchange Saturation Transfer (CEST) MRI has emerged as a non-invasive contrast enhancement technique that enables detection of molecules, like glycogen, whose concentrations are too low to impact the contrast of standard MR imaging. CEST imaging is performed by selectively saturating hydrogen nuclei of the metabolites that are in chemical exchange with those of water molecules and detecting a reduction in MRI signal in the water pool resulting from continuous chemical exchange. However, CEST signal can easily be compromised by artifacts. Since CEST is based on chemical shift, it is very sensitive to field inhomogeneity which may arise from poor initial shimming, subject respiration, heating of shim iron, mechanical vibrations or subject motion. This is a particular problem for molecules that resonate close to water, such as - OH protons in glycogen, where small variations in chemical shift cause misinterpretation of CEST data. The purpose of this thesis was to optimize the CEST MRI sequence for glycogen detection and implement a real-time simultaneous motion and shim correction and measurement method. First, analytical solution of the Bloch-McConnell equations was used to find optimal continuous wave RF pulse parameters for glycogen detection, and results were validated on a phantom with varying glycogen concentrations and in vivo on human calf muscle. Next, the CEST sequence was modified with double volumetric navigators (DvNavs) to measure pose changes and update field of view and zero- and first-order shim parameters. Finally, the impact of B0 field fluctuations on the scan-rescan reproducibility of CEST was evaluated in vivo in 9 volunteers across 10 different scans. Simulation results showed an optimal RF saturation power of 1.5µT and duration of 1s for glycoCEST. These parameters were validated experimentally in vivo and the ability to detect varying glycogen concentrations was demonstrated in a phantom. Phantom data showed that the DvNav-CEST sequence accurately estimates system frequency and linear shim gradient changes due to motion and corrects resulting image distortions. In addition, DvNav-CEST was shown to yield improved CEST quantification in vivo in the presence of motion and motion-induced field inhomogeneity. B0 field fluctuations were found to lower the reproducibility of CEST measures: the mean coefficient of variation (CoV) for repeated scans was 83.70 ± 70.79 % without shim correction. However, the DvNav-CEST sequence was able to measure and correct B0 variations, reducing the CoV to 2.6 ± 1.37 %. The study confirms the possibility of detecting glycogen using CEST MRI at 3 T and shows the potential of the real-time shim and motion navigated CEST sequence for producing repeatable results in vivo by reducing the effect of B0 field fluctuations

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works

Implementation of anatomical navigators for real time motion correction in diffusion tensor imaging

Includes bibliographical references.Prospective motion correction methods using an optical system, diffusion-weighted prospective acquisition correction, or a free induction decay navigator have recently been applied to correct for motion in diffusion tensor imaging. These methods have some limitations and drawbacks. This article describes a novel technique using a three-dimensional-echo planar imaging navigator, of which the contrast is independent of the b-value, to perform prospective motion correction in diffusion weighted images, without having to reacquire volumes during which motion occurred, unless motion exceeded some preset thresholds. Water phantom and human brain data were acquired using the standard and navigated diffusion sequences, and the mean and whole brain histogram of the fractional anisotropy and mean diffusivity were analyzed