Real-time multislice-to-volume motion correction for task-based EPI-fMRI at 7T.

Prospective motion correction in functional MRI using simultaneous multislice imaging and multislice-to-volume image registration

Functional magnetic resonance imaging (fMRI) is a unique window to the brain, enabling scientists to follow changes in brain activity in response to hormones, ageing, environment, drugs of abuse and other stimuli. There are two features that make fMRI unique when compared with other imaging modalities used in behavioural neuroscience. First, it can be entirely noninvasive: each animal can serve as its own control over the natural course of its life, vital for following neuroadaptation and other developmental processes critical to understanding behaviour. Second, fMRI has the spatial and temporal resolution to observe patterns of neuronal activity across the entire brain in less than a minute. Although fMRI does not have the cellular spatial resolution of immunostaining, nor the millisecond temporal resolution of electrophysiology, synchronised changes in neuronal activity across multiple brain areas seen with functional MRI can be viewed as functional neuroanatomical circuits coordinating the thoughts, memories and emotions for particular behaviours. Thus, fMRI affords a systems approach to the study of the brain, complementing and building from other neurobiological techniques to understand how behaviour is organised across multiple brain regions. In this review, we present a general background to fMRI and the different imaging modalities that can be used in fMRI studies. Included are examples of the application of fMRI in behavioural neuroscience research, along with discussion of the advantages and disadvantages of this technology.

Functional magnetic resonance spectroscopy (fMRS) is a powerful tool for investigating neurometabolic dynamics in response to physiological stimuli in vivo. However, fMRS is challenging due to the low SNR of the spectrum and small neurochemical changes. Many existing studies were conducted at ultrahigh field strength (7T). To translate fMRS studies to the more common 3T clinical field strength, averaging more transients can improve SNR. However, this results in a long scan time compounds physiological motion which incurs degradations in spectrum quality and consistency. Investigate the feasibility of PRESS fMRS studies at 3T assisted by the combination of prospective motion correction (PMC) system and frequency navigator. A combination of markerless PMC system and frequency navigator was applied to an fMRS study during motor activation with a clinical PRESS protocol at 3T. Twenty-one volunteers were involved in the study. The functional task paradigm consisted of three blocks REST-TASK-REST. During the TASK period, the volunteer was asked to squeeze a hand-hold balloon according to a red rectangle flashing at 2Hz shown centered in a black background. The same motor task was repeated twice, once with PMC ON and once with PMC OFF. The data were processed and quantified by in-house VDI software. The following two analyses were performed: a motion pattern analysis and a metabolite dynamics analysis. The motion analysis was used to compare the motion states when PMC was ON and OFF. The metabolite dynamic change was a key assessment for the fMRS study. It was estimated via . p-values < 0.05 were considered significant. A statistically significant increase in Glx of 5.73% when the PMC was switched on was observed. No statistically significant increase in any of the metabolites with PMC OFF was observed. The major singlets (tCho, tCr, and tNAA) for both PMC ON and OFF keep constant. With a markerless PMC system and frequency navigator, PRESS fMRS at 3T is capable of detecting small changes of a few percent in Glx concentration during functional activation.

Revealing Brain Activity and White Matter Structure Using Functional and Diffusion-Weighted Magnetic Resonance Imaging

To develop a patient-specific respiratory motion correction technique with true 100% acquisition efficiency. A short training scan consisting of a series of single heartbeat images, each acquired with a preceding diaphragmatic navigator, was performed to fit a model relating the patient-specific 3D respiratory motion of the heart-to-diaphragm position. The resulting motion model was then used to update the imaging plane in real-time to correct for translational motion based on respiratory position provided by the navigator. The method was tested in a group of 11 volunteers with 5 separate free-breathing acquisitions: FB, no motion correction; FB-TF, free breathing with a linear tracking factor; Nav Gate, navigator gating; Nav Gate-TF, navigator gating with a tracking factor; and PROCO, prospective motion correction (proposed). Each acquisition lasted for 50 accepted heartbeats, where non-gated scans had a 100% acceptance rate, and gated scans accepted data only within a ±4 mm navigator window. Retrospective image registration was used to measure residual motion and determine the effectiveness of each method. PROCO reduced the range/RMSE of residual motion to 4.08 ± 1.4/0.90 ± 0.3 mm, compared to 10.78 ± 6.9/2.97 ± 2.2 mm for FB, 5.32 ± 2.92/1.24 ± 0.8 mm for FB-TF, 4.08 ± 1.6/0.93 ± 0.4 mm for Nav Gate, and 2.90 ± 1.0/0.63 ± 0.2 mm for Nav Gate-TF. Nav Gate and Nav Gate-TF reduced scan efficiency to 48.84 ± 9.31% and 54.54 ± 10.12%, respectively. PROCO successfully limited the residual motion in single-shot imaging to the level of traditional navigator gating while maintaining 100% acquisition efficiency.

To determine whether the blood flow abnormalities frequently associated with arteriovenous malformations (AVMs) can alter functional magnetic resonance (MR) imaging evaluation of language lateralization and whether reorganization of language function occurs in patients with brain AVMs. Eleven patients with left-hemisphere brain AVMs and 10 age-matched control subjects were examined with 1.5-T blood oxygen level-dependent (BOLD) functional MR imaging. Verbal fluency, sentence repetition, and story listening tasks were performed. The functional MR imaging laterality index in the frontal and temporal lobes was defined as the (L - R)/(L + R) ratio, where L and R are the numbers of activated pixels in the left and right hemispheres, respectively. Statistical analyses were performed with Wilcoxon signed rank, Fisher exact, and Kruskal-Wallis tests. Control subjects had left-sided language dominance, although symmetric pixel counts were observed in the frontal lobes in two subjects and in the temporal lobes in one subject. Six patients had left-sided language dominance similar to that observed in control subjects. Five of these patients had AVMs outside frontal or temporal language areas, without flow abnormalities. Five patients had abnormally right-sided asymmetric indexes (below mean control subject value - 2 SDs), which suggested language reorganization (P <.05). Results of Wada examination and/or postembolization functional MR imaging performed in two of these patients showed that the abnormal laterality indexes were at least partly due to severe flow abnormalities that impaired detection of BOLD MR imaging signal intensity. These data suggest that flow abnormalities may interfere with language lateralization assessment with functional MR imaging.

To evaluate prospective motion correction using the pilot tone (PT) as a quantitative respiratory motion signal with high temporal resolution for cardiac cine images during free breathing. Before cine data acquisition, a short prescan was performed, calibrating the PT to the respiratory-induced heart motion using respiratory-resolved real-time images. The calibrated PT was then applied for nearly real-time prospective motion correction of cine MRI through slice tracking (ie, updating the slice position before every readout). Additionally, in-plane motion correction was performed retrospectively also based on the calibrated PT data. The proposed method was evaluated in a moving phantom and 10 healthy volunteers. The PT showed very good correlation to the phantom motion. In volunteer studies using a long-term scan over 7.96 ± 1.40 min, the mean absolute error between registered and predicted motion from the PT was 1.44 ± 0.46 mm in head-feet and 0.46 ± 0.07 mm in anterior-posterior direction. Irregular breathing could also be corrected well with the PT. The PT motion correction leads to a significant improvement of contrast-to-noise ratio by 68% (P ≤ .01) between blood pool and myocardium and sharpness of endocardium by 24% (P = .04) in comparison to uncorrected data. The image score, which refers to the cine image quality, has improved with the utilization of the proposed PT motion correction. The proposed approach provides respiratory motion-corrected cine images of the heart with improved image quality and a high scan efficiency using the PT. The PT is independent of the MR acquisition, making this a very flexible motion-correction approach.

Prospective motion correction using data from optical tracking systems has been previously shown to reduce motion artifacts in MR imaging of the head. We evaluate a novel optical embedded tracking system. The home-built optical embedded tracking system performs image processing within a 7 T scanner bore, enabling high speed tracking. Corrected and uncorrected in vivo MR volumes are acquired interleaved using a modified 3D FLASH sequence, and their image quality is assessed and compared. The latency between motion and correction of the slice position was measured to be (19 ± 5) ms, and the tracking noise has a standard deviation no greater than 10 μm/0.005° during conventional MR scanning. Prospective motion correction improved the edge strength by 16 % on average, even though the volunteers were asked to remain motionless during the acquisitions. Using a novel method for validating the effectiveness of in vivo prospective motion correction, we have demonstrated that prospective motion correction using motion data from the embedded tracking system considerably improved image quality.

Robust localization and lateralization of human language function: an optimized clinical functional magnetic resonance imaging protocol

Magnetic resonance (MR) acquisitions of the torso are frequently affected by respiratory motion with detrimental effects on signal quality. The motion of organs inside the body is typically decoupled from surface motion and is best captured using rapid MR imaging (MRI). We propose a pipeline for prospective motion correction of the target organ using MR image navigators providing absolute motion estimates in millimeters. Our method is designed to feature multi-nuclear interleaving for non-proton MR acquisitions and to tolerate local transmit coils with inhomogeneous field and sensitivity distributions. OpenCV object tracking was introduced for rapid estimation of in-plane displacements in 2D MR images. A full three-dimensional translation vector was derived by combining displacements from slices of multiple and arbitrary orientations. The pipeline was implemented on 3 T and 7 T MR scanners and tested in phantoms and volunteers. Fast motion handling was achieved with low-resolution 2D MR image navigators and direct implementation of OpenCV into the MR scanner’s reconstruction pipeline. Motion-phantom measurements demonstrate high tracking precision and accuracy with minor processing latency. The feasibility of the pipeline for reliable in-vivo motion extraction was shown on heart and kidney data. Organ motion was manually assessed by independent operators to quantify tracking performance. Object tracking performed convincingly on 7774 navigator images from phantom scans and different organs in volunteers. In particular the kernelized correlation filter (KCF) achieved similar accuracy (74%) as scored from inter-operator comparison (82%) while processing at a rate of over 100 frames per second. We conclude that fast 2D MR navigator images and computer vision object tracking can be used for accurate and rapid prospective motion correction. This and the modular structure of the pipeline allows for the proposed method to be used in imaging of moving organs and in challenging applications like cardiac magnetic resonance spectroscopy (MRS) or magnetic resonance imaging (MRI) guided radiotherapy.

Functional magnetic resonance (MR) imaging is a complex, specialized examination that is able to noninvasively measure information critical to patient care such as hemispheric language lateralization ( 1 ). Diagnostic functional MR imaging requires extensive patient interaction as well as the coordinated efforts of the entire health care team. We observed in our practice at an academic center that the times to perform functional MR imaging examinations were excessively lengthy, making scheduling of the examination difficult. The purpose of our project was to reduce functional MR imaging acquisition times by increasing the efficiency of our workflow, using specific quality tools to drive improvement of functional MR imaging. We assembled a multidisciplinary team and retrospectively reviewed all functional MR imaging examinations performed at our institution from January 2013 to August 2015. We identified five key drivers: (a) streamlined protocols, (b) consistent patient monitoring, (c) clear visual slides and audio, (d) improved patient understanding, and (e) minimized patient motion. We then implemented four specific interventions over a period of 10 months: (a) eliminating intravenous contrast medium, (b) reducing repeated language paradigms, (c) updating technologist and physician checklists, and (d) updating visual slides and audio. Our mean functional MR imaging acquisition time was reduced from 76.3 to 53.2 minutes, while our functional MR imaging examinations remained of diagnostic quality. As a result, we reduced our routine scheduling time for functional MR imaging from 2 hours to 1 hour, improving patient comfort and satisfaction as well as saving time for additional potential MR imaging acquisitions. Our efforts to optimize functional MR imaging workflow constitute a practice quality improvement project that is beneficial for patient care and can be applied broadly to other functional MR imaging practices. ©RSNA, 2017.

Motion correction of echo-planar imaging (EPI) data used in functional MRI (fMRI) is an essential pre-processing step performed prior to statistical analysis. At ultra-high resolution fMRI, current requirements regarding translational and rotational motion may no longer be acceptable. This prompts the need for a systematic investigation of the effects of motion correction procedures with in-vivo fMRI data. Here we systematically evaluated the effect of retrospective motion correction with freely available fMRI analysis software packages (FSL, AFNI and SPM) on activation maps using fMRI data acquired with prospective motion detection, to identify and quantify confounding effects of retrospective motion correction, and to evaluate its dependence on spatial resolution and motion correction algorithms.Brain activation maps were obtained for two different resolutions, an ultra-high, i.e. 0.653 mm3, and a more widely used 2.03 mm3 isotropic resolutions at 7T. The EPI data were acquired using simultaneous non-image-based optical moiré phase tracking (MPT) of physical motion. The results showed that image-based motion detection, performed by SPM8 software package, may be erroneous in high-field fMRI data with partial brain coverage and can introduce spurious motion leading to false-positive and false-negative activation. Further analyses demonstrated that limited acquisition field of view has the dominant influence on the effect.

Chapter 46 - Functional Magnetic Resonance Imaging in the Neuromodulation of Pain

HomeRadiologyVol. 231, No. 3 PreviousNext EditorialsMR Imaging: Its Development and the Recent Nobel PrizeStephen J. RiedererStephen J. RiedererAuthor Affiliations1From the MR Laboratory, Mayo Clinic, 200 First Street SW, Rochester, MN 55905. Received January 19, 2004; accepted January 21. Address correspondence to the author (e-mail: [email protected]).Stephen J. RiedererPublished Online:Jun 1 2004https://doi.org/10.1148/radiol.2313040114MoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References 1 Lauterbur PC. Image formation by induced local interactions: examples employing nuclear magnetic resonance. Nature 1973; 242:190-191. Crossref, Google Scholar2 USA MRI market Mountain View, Calif: Frost and Sullivan Market Research, 2002. Google Scholar3 Mansfield P, Grannell PK. NMR “diffraction” in solids? J Phys C Solid State Phys 1973; 6:L422. Crossref, Google Scholar4 Mansfield P. 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In magnetic resonance imaging (MRI), susceptibility-induced distortions pose a significant challenge for images acquired using echo planar imaging (EPI). Classical methods use two EPI images acquired in reverse phaseencoding (PE) directions to correct susceptibility artifacts. However, these methods suffer from long computation times, making them impractical for clinical usage. Recently, deep learning-based approaches have been proposed to enable a leap in computation efficiency for EPI susceptibility artifact correction. A vital consideration in reverse-PE-based correction is the need to take into account any potential subject motion between reversed-PE acquisitions. In this work, we propose an alignment-guided forward distortion network (agFD-Net) that accounts for subject motion during correction of susceptibility artifacts. Similar to its predecessor FD-Net, agFD-Net is trained in a physics-driven unsupervised fashion to estimate a single corrected image and a displacement field. In agFD-Net, a new pre-trained alignment network called AlignNet is plugged into the network architecture to facilitate motion correction. The results on experimental NIH dataset featuring realistic levels of motion demonstrate that agFD-Net provides rapid and high-fidelity artifact correction, while successfully accounting for subject motion.Clinical Relevance-EPI is the most commonly used sequence for diffusion MRI and functional MRI. While susceptibility artifacts in EPI require correction before any downstream evaluation, the long computation time of classical correction methods make them impractical for use in clinical settings. The proposed agFD-Net provides more than two orders of magnitude speed up in computational efficiency, making it a highly promising approach for use in clinical settings.