K-space Trajectory Research Articles

On the correction of spiral trajectories on a preclinical MRI scanner with a high-performance gradient insert.

This study aimed to examine different trajectory correction methods for spiral imaging on a preclinical scanner with high-performance gradients with respect to image quality in a phantom and in vivo. The gold standard method of measuring the trajectories in a separate experiment is compared to an isotropic delay-correction, a correction using the gradient system transfer function (GSTF), and a combination of the two. Three different spiral trajectories, with 96, 16, and three interleaves, are considered. The best image quality is consistently achieved when determining the trajectory in a separate phantom measurement. However, especially for the spiral with 96 interleaves, the other correction methods lead to almost comparable results. Remaining imperfections in the corrected gradient waveforms and trajectories are attributed to asymmetrically occurring undulations in the actual, generated gradients, suggesting that the underlying assumption of linearity is violated. In conclusion, images of sufficient quality can be acquired on preclinical small-animal scannersusing spiral k-space trajectories without the need to carry out separate trajectory measurements each time. Depending on the trajectory, a simple isotropic delay-correction or a GSTF-based correction can provide images of similar quality.

Fuzzy ripple artifact in high resolution fMRI: identification, cause, and mitigation.

High resolution fMRI is a rapidly growing research field focused on capturing functional signal changes across cortical layers. However, the data acquisition is limited by low spatial frequency EPI artifacts; termed here as Fuzzy Ripples. These artifacts limit the practical applicability of acquisition protocols with higher spatial resolution, faster acquisition speed, and they challenge imaging in lower brain areas. We characterize Fuzzy Ripple artifacts across commonly used sequences and distinguish them from conventional EPI Nyquist ghosts, off-resonance effects, and GRAPPA artifacts. To investigate their origin, we employ dual polarity readouts. Our findings indicate that Fuzzy Ripples are primarily caused by readout-specific imperfections in k-space trajectories, which can be exacerbated by inductive coupling between third-order shims and readout gradients. We also find that these artifacts can be mitigated through complex-valued averaging of dual polarity EPI or by disconnecting the third-order shim coils. The proposed mitigation strategies allow overcoming current limitations in layer-fMRI protocols: (1)Achieving resolutions beyond 0.8mm is feasible, and even at 3T, we achieved 0.53mm voxel functional connectivity mapping.(2)Sub-millimeter sampling acceleration can be increased to allow sub-second TRs and laminar whole brain protocols with up to GRAPPA 8.(3)Sub-millimeter fMRI is achievable in lower brain areas, including the cerebellum.

Motion robust coronary MR angiography using zigzag centric ky-kz trajectory and high-resolution deep learning reconstruction.

To develop a new MR coronary angiography (MRCA) technique by employing a zigzag fan-shaped centric ky-kz k-space trajectory combined with high-resolutiondeep learning reconstruction (HR-DLR). All imaging data were acquired from 12 healthy subjects and 2 patients using two clinical 3-T MR imagers, with institutional review board approval. Ten healthy subjects underwent both standard 3D fast gradient echo (sFGE) and centric ky-kz k-space trajectory FGE (cFGE) acquisitions to compare the scan time and image quality. Quantitative measures were also performed for signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as sharpness of the vessel. Furthermore, the feasibility of the proposed cFGE sequence was assessed in two patients. For assessing the feasibility of the centric ky-kz trajectory, the navigator-echo window of a 30-mm threshold was applied in cFGE, whereas sFGE was applied using a standard 5-mm threshold. Image quality of MRCA using cFGE with HR-DLR and sFGE without HR-DLR was scored in a 5-point scale (non-diagnostic = 1, fair = 2, moderate = 3, good = 4, and excellent = 5). Image evaluation of cFGE, applying HR-DLR, was compared with sFGE without HR-DLR. Friedman test, Wilcoxon signed-rank test, or paired t tests were performed for the comparison of related variables. The actual MRCA scan time of cFGE with a 30-mm threshold was acquired in less than 5min, achieving nearly 100% efficiency, showcasing its expeditious and robustness. In contrast, sFGE was acquired with a 5-mm threshold and had an average scan time of approximately 15min. Overall image quality for MRCA was scored 3.3 for sFGE and 2.7 for cFGE without HR-DLR but increased to 3.6 for cFGE with HR-DLR and (p < 0.05). The clinical result of patients obtained within 5min showed good quality images in both patients, even with a stent, without artifacts. Quantitative measures of SNR, CNR, and sharpness of vessel presented higher in cFGE with HR-DLR. Our findings demonstrate a robust, time-efficient solution for high-quality MRCA, enhancing patient comfort and increasing clinical throughput.

Super resolution using sparse sampling at portable ultra-low field MR

Ultra-low field (ULF) magnetic resonance imaging (MRI) holds the potential to make MRI more accessible, given its cost-effectiveness, reduced power requirements, and portability. However, signal-to-noise ratio (SNR) drops with field strength, necessitating imaging with lower resolution and longer scan times. This study introduces a novel Fourier-based Super Resolution (FouSR) approach, designed to enhance the resolution of ULF MRI images with minimal increase in total scan time. FouSR combines spatial frequencies from two orthogonal ULF images of anisotropic resolution to create an isotropic T2-weighted fluid-attenuated inversion recovery (FLAIR) image. We hypothesized that FouSR could effectively recover information from under-sampled slice directions, thereby improving the delineation of multiple sclerosis (MS) lesions and other significant anatomical features. Importantly, the FouSR algorithm can be implemented on the scanner with changes to the k-space trajectory. Paired ULF (Hyperfine SWOOP, 0.064 tesla) and high field (Siemens, Skyra, 3 Tesla) FLAIR scans were collected on the same day from a phantom and a cohort of 10 participants with MS or suspected MS (6 female; mean ± SD age: 44.1 ± 4.1). ULF scans were acquired along both coronal and axial planes, featuring an in-plane resolution of 1.7 mm × 1.7 mm with a slice thickness of 5 mm. FouSR was evaluated against registered ULF coronal and axial scans, their average (ULF average) and a gold standard SR (ANTs SR). FouSR exhibited higher SNR (47.96 ± 12.6) compared to ULF coronal (36.7 ± 12.2) and higher lesion conspicuity (0.12 ± 0.06) compared to ULF axial (0.13 ± 0.07) but did not exhibit any significant differences contrast-to-noise-ratio (CNR) compared to other methods in patient scans. However, FouSR demonstrated superior image sharpness (0.025 ± 0.0040) compared to all other techniques (ULF coronal 0.021 ± 0.0037, q = 5.9, p-adj. = 0.011; ULF axial 0.018 ± 0.0026, q = 11.1, p-adj. = 0.0001; ULF average 0.019 ± 0.0034, q = 24.2, p-adj. &amp;lt; 0.0001) and higher lesion sharpness (−0.97 ± 0.31) when compared to the ULF average (−1.02 ± 0.37, t(543) = −10.174, p = &amp;lt;0.0001). Average blinded qualitative assessment by three experienced MS neurologists showed no significant difference in WML and sulci or gyri visualization between FouSR and other methods. FouSR can, in principle, be implemented on the scanner to produce clinically useful FLAIR images at higher resolution on the fly, providing a valuable tool for visualizing lesions and other anatomical structures in MS.

B0-insensitive image navigators for prospective motion-corrected MRS with localized second-order shimming.

Localized shimming in single-voxel MRS often results in large B0 inhomogeneity outside the volume-of-interest. This causes unacceptable degradation in motion navigator images. Switching back and forth between whole-brain shim and localized shim is possible for linear shims, but not for higher-order shims. Here we propose motion navigators largely insensitive to B0 inhomogeneity for prospective motion-corrected MRS with localized higher-order shimming. A recent fast high-resolution motion navigator based on spiral-in/out k-space trajectories and multislice-to-volume registration was modified by splitting the readout into multiple shot interleaves which shortened the echo time and reduced the effect of B0 inhomogeneity. The performance of motion correction was assessed in healthy subjects in the prefrontal cortex using a sLASER sequence at 3T (N = 5) and 7T (N = 5). With multiple spatial interleaves, excellent quality navigator images were acquired in the whole brain in spite of large B0 inhomogeneity outside the MRS voxel. The total duration of the navigator in sLASER remained relatively short even with multiple shots (3T: 10 spatial interleaves 94 ms per slice; 7T: 15 spatial interleaves 103 ms per slice). Prospective motion correction using the multi-shot navigators yielded comparable spectral quality (water linewidth and metabolite SNR) with and without subject motion. B0-insensitive motion navigators enable prospective motion correction for MRS with all first- and second-order shims adjusted in the MRS voxel, providing optimal spectral linewidth.

Simulation of time-intensity curve based on k-space filling in breast dynamic contrast-enhanced three-dimensional magnetic resonance imaging.

This study elucidated the effects of a three-dimensional k-space trajectory incorporating the partial Fourier (PF) technique on a time-intensity curve (TIC) in a dynamic contrast-enhanced magnetic resonance imaging of a typical malignant breast tumor using a digital phantom. Images were obtained from the Cancer Imaging Archive Open Data for Breast Cancer, and 1-min scans with high temporal resolution were analyzed. The order of the k-space trajectory was set as Linear (sequential), Low-High (centric), PF (62.5%; Z-, Y-, and both directions), and Low-High Radial. k0 (center of the k-space) timing and TIC shape were affected by the chosen k-space trajectory and implementation of the PF technique. A small TIC gradient was obtained using a Low-High Radial order. If the k-space filling method (particularly the radial method) produces a gentle TIC gradient, misinterpretation could arise during the assessment of tumor malignancy status.

3D balanced SSFP UTE MRI for multiple contrasts whole brain imaging.

This study aimed to develop a new high-resolution MRI sequence for the imaging of the ultra-short transverse relaxation time (uT2) components in the brain, while simultaneously providing proton density (PD) contrast for reference and quantification. The sequence combines low flip angle balanced SSFP (bSSFP) and UTE techniques, together with a 3D dual-echo rosette k-space trajectory for readout. The expected image contrast was evaluated by simulations. A study cohort of six healthy volunteers and eight multiple sclerosis (MS) patients was recruited to test the proposed sequence. Subtraction between two TEs was performed to extract uT2 signals. In addition, conventional longitudinal relaxation time (T1) weighted, T2-weighted, and PD-weighted MRI sequences were also acquired for comparison. Typical PD-contrast was found in the second TE images, while uT2 signals were selectively captured in the first TE images. The subtraction images presented signals primarily originating from uT2 components, but only if the first TE is short enough. Lesions in the MS subjects showed hyperintense signals in the second TE images but were hypointense signals in the subtraction images. The lesions had significantly lower signal intensity in subtraction images than normal white matter (WM), which indicated a reduction of uT2 components likely associated with myelin. 3D isotropic sub-millimeter (0.94 mm) spatial resolution images were acquired with the novel bSSFP UTE sequence within 3 min. It provided easy extraction of uT2 signals and PD-contrast for reference within a single acquisition.

Fast online spectral-spatial pulse design for subject-specific fat saturation in cervical spine and foot imaging at 1.5 T

ObjectiveTo compensate subject-specific field inhomogeneities and enhance fat pre-saturation with a fast online individual spectral-spatial (SPSP) single-channel pulse design.MethodsThe RF shape is calculated online using subject-specific field maps and a predefined excitation k-space trajectory. Calculation acceleration options are explored to increase clinical viability. Four optimization configurations are compared to a standard Gaussian spectral selective pre-saturation pulse and to a Dixon acquisition using phantom and volunteer (N = 5) data at 1.5 T with a turbo spin echo (TSE) sequence. Measurements and simulations are conducted across various body parts and image orientations.ResultsPhantom measurements demonstrate up to a 3.5-fold reduction in residual fat signal compared to Gaussian fat saturation. In vivo evaluations show improvements up to sixfold for dorsal subcutaneous fat in sagittal cervical spine acquisitions. The versatility of the tailored trajectory is confirmed through sagittal foot/ankle, coronal, and transversal cervical spine experiments. Additional measurements indicate that excitation field (B1) information can be disregarded at 1.5 T. Acceleration methods reduce computation time to a few seconds.DiscussionAn individual pulse design that primarily compensates for main field (B0) inhomogeneities in fat pre-saturation is successfully implemented within an online "push-button" workflow. Both fat saturation homogeneity and the level of suppression are improved.

Dynamic changes in lung water density and volume following supine body positioning.

Measure the changes in relative lung water density (rLWD), lung volume, and total lung water content as a function of time after supine body positioning. An efficient ultrashort-TE pulse sequence with a yarnball k-space trajectory was used to measure water density-weighted lung images for 25 min following supine body positioning (free breathing, 74-s acquisitions, 3D images at functional residual capacity, 18 time points) in 9 healthy volunteers. Global and regional (10 chest-to-back positions) rLWD, lung volume, and total lung water volume were measured in all subjects at all time points. Volume changes were validated with a nitrogen washout study in 3 participants. Global rLWD increased significantly (p = 0.001) from 31.8 ± 5.5% to 34.8 ± 6.8%, while lung volumes decreased significantly (p < 0.001) from 2390 ± 620 mL to 2130 ± 630 mL over the same 25-min interval. Total lung water volume decreased slightly from 730 ± 125 mL to 706 ± 126 mL (p = 0.028). There was a significant chest-to-back gradient in rLWD (20.7 ± 4.6% to 39.9 ± 6.1%) at all time points with absolute increases of 1.8 ± 1.2% at the chest and 5.4 ± 1.9% at the back. Nitrogen washout studies yielded a similar reduction in lung volume (12.5 ± 0.9%) and time course following supine positioning. Lung volumes during tidal breathing decrease significantly over tens of minutes following supine body positioning, with corresponding increases in lung water density (9.2 ± 4.4% relative increase). The total volume of lung water is slightly reduced over this interval (3.3 ± 4.0% relative change). Evaluation of rLWD should take time after supine positioning, and more generally, all sources of lung volume changes should be taken into consideration to avoid significant bias.

Trajectory correction enables free-running chemical shift encoded imaging for accurate cardiac proton-density fat fraction quantification at 3T

BackgroundMetabolic diseases can negatively alter epicardial fat accumulation and composition, which can be probed using quantitative cardiac chemical shift encoded(CSE) MRI by mapping proton-density fat fraction (PDFF). To obtain motion-resolved high-resolution PDFF maps, we proposed a free-running cardiac CSE-MRI framework at 3T. To employ faster bipolar readout gradients, a correction for gradients imperfections was added using the gradient impulse response function (GIRF) and evaluated on intermediate images and PDFF quantification. MethodsTen minutes free-running cardiac 3D radial CSE-MRI acquisitions were compared in vitro and in vivo at 3T. Monopolar and bipolar readout gradients schemes provided 8 echoes (TE1/ΔTE = 1.16/1.96ms) and 13 echoes (TE1/ΔTE = 1.12/1.07ms), respectively. Bipolar-gradients free-running cardiac fat and water images and PDFF maps were reconstructed with or without GIRF-correction. PDFF values were evaluated in silico, in vitro on a fat/water phantom, and in vivo in 10 healthy volunteers and three diabetic patients. ResultsIn monopolar mode, fat-water swaps were demonstrated in silico and confirmed in vitro. Using bipolar readout gradients, PDFF quantification was reliable and accurate with GIRF correction with a mean bias of 0.03% in silico and 0.36% in vitro while it suffered from artifacts without correction, leading to a PDFF bias of 4.9% in vitro and swaps in vivo. Using bipolar readout gradients, in vivo PDFF of epicardial adipose tissue was significantly lower than in subcutaneous fat (80.4±7.1% vs 92.5±4.3%, P<0.0001). ConclusionAiming for an accurate PDFF quantification, high-resolution free-running cardiac CSE-MRI imaging proved to benefit from bipolar echoes with k-space trajectory correction at 3T. This free-breathing acquisition framework enables to investigate epicardial adipose tissue PDFF in metabolic diseases.

Fast 19 F spectroscopic imaging with pseudo-spiral k-space sampling.

Fluorine MRI is finding wider acceptance in theranostics applications where imaging of 19 F hotspots of fluorinated contrast material is central. The essence of such applications is to capture ghosting-artifact-free images of the inherently low MR response under clinically viable conditions. To serve this purpose, this work introduces the balanced spiral spectroscopic imaging (BaSSI) sequence, which is implemented on a 3.0 T clinical scanner and is capable of generating 19 F hotspot images in an efficient manner. The sequence utilizes an all-phase-encoded pseudo-spiral k-space trajectory, enabling the acquisition of broadband (80 ppm) fluorine spectra free from chemical shift ghosting. BaSSI can acquire a 64 × 64 image with 1 mm × 1 mm voxels in just 14 s, significantly outperforming typical MRSI sequences used in 1 H or 31 P imaging. The study employed in silico characterization to verify essential design choices such as the excitation pulse, as well as to identify the boundaries of the parameter space explored for optimization. BaSSI's performance was further benchmarked against the 3D ultrashort-echo-time balanced steady-state free precession (3D UTE BSSFP) sequence, a well established method used in 19 F MRI, in vitro. Both sequences underwent extensive optimization through exploration of a wide parameter space on a small phantom containing 10 μL of non-diluted bulk perfluorooctylbromide (PFOB) prior to comparative experiments. Subsequent to optimization, BaSSI and 3D UTE BSSFP were employed to capture images of small non-diluted bulk PFOB samples (0.10 and 0.05 μL), with variations in the number of signal averages, and thus the total scan time, in order to assess the detection sensitivities of the sequences. In these experiments, the detection sensitivity was evaluated using the Rose criterion (Rc ), which provides a quantitative metric for assessing object visibility. The study further demonstrated BaSSI's utility as a (pre)clinical tool through postmortem imaging of polymer microspheres filled with PFOB in a BALB/c mouse. Anatomic localization of 19 F hotspots was achieved by denoising raw data obtained with BaSSI using a filter based on the Rose criterion. These data were then successfully registered to 1 H anatomical images. BaSSI demonstrated superior detection sensitivity in the benchmarking analysis, achieving Rc values approximately twice as high as those obtained with the 3D UTE BSSFP method. The technique successfully facilitated imaging and precise localization of 19 F hotspots in postmortem experiments. However, it is important to highlight that imaging 10 mM PFOB in small mice postmortem, utilizing a 48 × 48 × 48 3D scan, demanded a substantial scan time of 1 h and 45 min. Further studies will explore accelerated imaging techniques, such as compressed sensing, to enhance BaSSI's clinical utility.

Correcting gradient chain induced fat quantification errors in radial multi-echo Dixon imaging using a gradient modulation transfer function

Purpose: Multi-echo Stack-of-stars (SoS) radial k-space trajectories with golden angle ordering are becoming popular for free-breathing abdominal Dixon imaging and proton density fat fraction (PDFF) mapping. Gradient chain imperfections including eddy currents and system delays are known to affect the image quality of radial imaging and to confound the estimation of PDFF mapping. This work proposes a retrospective trajectory correction method based on a simple gradient modulation transfer function (GMTF) measurement to predict and correct gradient chain induced k-space trajectory errors.Methods: The GMTF was measured using the standard hardware of a 3 Tesla scanner on a phantom using the thin slice method and was applied to a 3D radial SoS Dixon imaging sequence. The impact of the GMTF-based correction on image reconstruction and PDFF quantification was investigated using numerical simulations and validated on experimental phantom data as well as on in vivo leg and liver data of healthy volunteers.Results: Correcting the k-space trajectories with the measured GMTF during image reconstruction reduced PDFF quantification errors for phantom and in vivo acquisitions. A Bland-Altman comparison of the measured PDFF phantom and reference data confirmed that the GMTF correction narrowed down the limits of agreement (LoA) from 1.3% ± 8.1% (uncorrected) to 1.9% ± 5.4% (GMTF-corrected) over the full PDFF range (0%–100%) and from −0.26% ± 2.8% (uncorrected) to 0.12% ± 1.5% (GMTF-corrected) within the 0%–50% PDFF range. Liver PDFF estimation was improved by reducing the standard deviation of the mean liver PDFF and the bias of the mean liver PDFF for all subjects.Conclusion: The proposed GMTF-based k-space trajectory correction is a fast alternative method for avoiding PDFF quantitation errors caused by gradient-system induced k-space trajectory errors in 3D radial multi-echo gradient-echo acquisitions.

Eddy current-induced artifact correction in high b-value ex vivo human brain diffusion MRI with dynamic field monitoring.

To investigate whether spatiotemporal magnetic field monitoring can correct pronounced eddy current-induced artifacts incurred by strong diffusion-sensitizing gradients up to 300 mT/m used in high b-value diffusion-weighted (DW) EPI. A dynamic field camera equipped with 16 1 H NMR field probes was first used to characterize field perturbations caused by residual eddy currents from diffusion gradients waveforms in a 3D multi-shot EPI sequence on a 3T Connectom scanner for different gradient strengths (up to 300 mT/m), diffusion directions, and shots. The efficacy of dynamic field monitoring-based image reconstruction was demonstrated on high-gradient strength, submillimeter resolution whole-brain ex vivo diffusion MRI. A 3D multi-shot image reconstruction framework was developed that incorporated the nonlinear phase evolution measured with the dynamic field camera. Phase perturbations in the readout induced by residual eddy currents from strong diffusion gradients are highly nonlinear in space and time, vary among diffusion directions, and interfere significantly with the image encoding gradients, changing the k-space trajectory. During the readout, phase modulations between odd and even EPI echoes become non-static and diffusion encoding direction-dependent. Superior reduction of ghosting and geometric distortion was achieved with dynamic field monitoring compared to ghosting reduction approaches such as navigator- and structured low-rank-based methods or MUSE followed by image-based distortion correction with the FSL tool "eddy." Strong eddy current artifacts characteristic of high-gradient strength DW-EPI can be well corrected with dynamic field monitoring-based image reconstruction.

Very fast digital 2D rigid motion estimation directly on continuous k-space data using an RNN

Objective:Motion of the target during radiotherapy negatively impacts the effectiveness and can cause damage to nearby tissue. MRI offers great soft-tissue contrast to visualize the target but its long acquisition time requires high undersampling of k-space to monitor this motion in real time. This typically limits the achievable latency even though every saved millisecond can increase the effectiveness of the treatment. Methods:In this study, a recurrent neural network (RNN) is used to continuously estimate motion directly from incoming k-space data. A golden-angle radial k-space trajectory continuously scans the target region and feeds the acquired data spoke-by-spoke into the RNN. Skipping image reconstruction and focusing only on the motion in the data allows for very fast motion monitoring in the order of milliseconds. To improve network training and generalization, different amounts of peripheral values are removed from the k-space spokes during preprocessing. To train and evaluate the network, 2D MRI motion datasets with different motion characteristics were generated by synthetically transforming slices of 25 MRI head scans. Results:The RNN takes less than a millisecond to accurately estimate motion. By keeping only the inner 10% of each spoke, a mean rotational error of 0.37° and a mean translational error of 0.26 mm are achieved. No patient-specific preparation or retraining is necessary. Conclusion and significance:The network gives very fast motion estimations with sub-millimeter accuracy. The results demonstrate the feasibility of this approach and provide the groundwork to further reduce latency in real-time motion monitoring systems for radiotherapy without sacrificing accuracy.

Intra-frame motion deterioration effects and deep-learning-based compensation in MR-guided radiotherapy.

Current commercially available hybrid magnetic resonance linear accelerators (MR-Linac) use 2D+t cine MR imaging to provide intra-fractional motion monitoring. However, given the limited temporal resolution of cine MR imaging, target intra-frame motion deterioration effects, resulting in effective time latency and motion artifacts in the image domain, can be appreciable, especially in the case of fast breathing. The aim of this work is to investigate intra-frame motion deterioration effects in MR-guided radiotherapy (MRgRT) by simulating the motion-corrupted image acquisition, and to explore the feasibility of deep-learning-based compensation approaches, relying on the intra-frame motion information which is spatially and temporally encoded in the raw data (k-space). An intra-frame motion model was defined to simulate motion-corrupted MR images, with 4D anthropomorphic digital phantoms being exploited to provide ground truth 2D+t cine MR sequences. A total number of 10 digital phantoms were generated for lung cancer patients, with randomly selected eight patients for training or validation and the remaining two for testing. The simulation code served as the data generator, and a dedicated motion pattern perturbation scheme was proposed to build the intra-frame motion database, where three degrees of freedom were designed to guarantee the diversity of intra-frame motion trajectories, enabling a thorough exploration in the domain of the potential anatomical structure positions. U-Nets with three types of loss functions: L1 or L2 loss defined in image or Fourier domain, referred to as NNImgLoss-L1 , NNFloss-L1 and NNL2-Loss were trained to extract information from the motion-corrupted image and used to estimate the ground truth final-position image, corresponding to the end of the acquisition. Images before and after compensation were evaluated in terms of (i) image mean-squared error (MSE) and mean absolute error (MAE), and (ii) accuracy of gross tumor volume (GTV) contouring, based on optical-flow image registration. Image degradation caused by intra-frame motion was observed: for a linearly and fully acquired Cartesian readout k-space trajectory, intra-frame motion resulted in an imaging latency of approximately 50% of the acquisition time; in comparison, the motion artifacts exhibited only a negligible contribution to the overall geometric errors. All three compensation models led to a decrease in image MSE/MAE and GTV position offset compared to the motion-corrupted image. In the investigated testing dataset for GTV contouring, the average dice similarity coefficients (DSC) improved from 88% to 96%, and the 95th percentile Hausdorff distance (HD95 ) dropped from 4.8mm to 2.1mm. Different models showed slight performance variations across different intra-frame motion amplitude categories: NNImgLoss-L1 excelled for small/medium amplitudes, whereas NNFloss-L1 demonstrated higher DSC median values at larger amplitudes. The saliency maps of the motion-corrupted image highlighted the major contribution of the later acquired k-space data, as well as the edges of the moving anatomical structures at their final positions, during the model inference stage. Our results demonstrate the deep-learning-based approaches have the potential to compensate for intra-frame motion by utilizing the later acquired data to drive the convergence of the earlier acquired k-space components.

Improving spreading projection algorithm for rapid k-space sampling trajectories through minimized off-resonance effects and gridding of low frequencies.

Non-Cartesian MRI with long arbitrary readout directions are susceptible to off-resonance artifacts due to patient induced inhomogeneities. This results in degraded image quality with strong signal losses and blurring. Current solutions to address this issue involve correcting the off-resonance artifacts during image reconstruction or reducing inhomogeneities through improved shimming. The recently developed SPARKLING algorithm is extended to drastically diminish off-resonance artifacts by generating temporally smooth k-space sampling patterns. For doing so, the cost function which is optimized in SPARKLING is modified using a temporal weighting factor. Additionally, oversampling of the center of k-space beyond the Nyquist criteria is prevented through the use of gridded sampling in the region, enforced with affine constraints. Prospective k-space data was acquired at 3 T on new trajectories, and we show robustness to inhomogeneities through in silico experiments by adding through artificial degradation of system shimming. Later on, in vivo experiments were carried out to optimize parameters of the new improvements and benchmark the gain in performance. The improved trajectories allowed for the recovery of signal dropouts observed on original SPARKLING acquisitions at larger field inhomogeneities. Furthermore, imposing gridded sampling at the center of k-space provided improved reconstructed image quality with limited artifacts. These advancements allowed us for nearly shorter scan time compared to GRAPPA-p4x1, allowing us to reach 600 µm isotropic resolution in 3D -w imaging in just 3.3 min at 3 T with negligible degradation in image quality.

High-resolution diffusion-weighted imaging at 7 Tesla: Single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy

Diffusion MRI (dMRI) is a valuable imaging technique to study the connectivity and microstructure of the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various multi-shot acquisition strategies have been developed to achieve sub-millimeter resolution, but they require long scan times which can be restricting for patient scans. Alternatively, the SNR of single-shot acquisitions can be increased by using a spiral readout trajectory to minimize the sequence echo time. Imaging at ultra-high fields (UHF) could further increase the SNR of single-shot dMRI; however, the shorter T2* of brain tissue and the greater field non-uniformities at UHFs will degrade image quality, causing image blurring, distortions, and signal loss.In this study, we investigated the trade-off between the SNR and resolution of different k-space trajectories, including echo planar imaging (EPI), partial Fourier EPI, and spiral trajectories, over a range of dMRI resolutions at 7T. The effective resolution, spatial specificity and sharpening effect were measured from the point spread function (PSF) of the simulated diffusion sequences for a nominal resolution range of 0.6–1.8 mm. In-vivo partial brain scans at a nominal resolution of 1.5 mm isotropic were acquired using the three readout trajectories to validate the simulation results. Field probes were used to measure dynamic magnetic fields offline up to the 3rd order of spherical harmonics. Image reconstruction was performed using static ΔB0 field maps and the measured trajectories to correct image distortions and artifacts, leaving T2* effects as the primary source of blurring. The effective resolution was examined in fractional anisotropy (FA) maps calculated from a multi-shell dataset with b-values of 300, 1000, and 2000 s/mm2 in 5, 16, and 48 directions, respectively. In-vivo scans at nominal resolutions of 1, 1.2, and 1.5 mm were acquired and the SNR of the different trajectories calculated using the multiple replica method to investigate the SNR. Finally, in-vivo whole brain scans with an effective resolution of 1.5 mm isotropic were acquired to explore the SNR and efficiency of different trajectories at a matching effective resolution. FA and intra-cellular volume fraction (ICVF) maps calculated using neurite orientation dispersion and density imaging (NODDI) were used for the comparison. The simulations and in vivo imaging results showed that for matching nominal resolutions, EPI trajectories had the highest specificity and effective resolution with maximum image sharpening effect. However, spirals have a significantly higher SNR, in particular at higher resolutions and even when the effective image resolutions are matched. Overall, this work shows that the higher SNR of single-shot spiral trajectories at 7T allows us to achieve higher effective resolutions compared to EPI and PF-EPI to map the microstructure and connectivity of small brain structures.

Quantitative Magnetic Resonance Imaging of the epicardial adipose tissue with free-running cardiac Dixon

There is a growing interest to better understand the pathophysiological role of cardiac fat towards cardiovascular degradation in metabolic diseases. As epicardial adipose tissue (EAT) can become an inflammatory substrate under pathological conditions, emerging therapies are aiming at modulating its metabolic functions. However, there is a lack of non-invasive tools that can probe EAT, which is thin and moves with cardiac and respiratory motion. This study aims at developing quantitative MRI biomarkers that can characterize EAT. As detailed in the Fig. 1, a custom-built free-running Dixon-MRI technique enabled high resolution mapping of proton density fat-fraction (PDFF) and R2*, free-breathing, in the heart. Cardiac Dixon MRI was implemented on a 3 T MRI with a self-navigated gradient echo radial sequence (Fig. 1.1) acquiring N = 13-echo bipolar 3D (TE1/ΔTE = 1.12/1.07ms). The “free-running’ self-navigation (Fig. 1.2) reconstructed 4 respiratory and 8-12 cardiac phases of 100 ms. Measurements were performed on end-expiratory peak-systole volume. K-space trajectories were corrected (Fig. 1.3) with the gradient impulse function (GIRF). The 5D reconstruction (Fig. 1.4) of volumes was performed by Compressed Sensing followed by iterative least-square IDEAL water-fat separation (Fig. 1.5). Eventually, R2*&PDFF 3D maps (overlayed in Fig. 1 over echo TE1 image) are resolved in cardiac and respiratory time. The sequence proved highly accurate and precise with mean biases of PDFF and R2* estimated by simulation under 0.05% and 0.05 s-1 and an accuracy of ±1.2% and 5.0 s-1. As expected, in the healthy population, epicardial fat had a significantly lower fat fraction than subcutaneous fat (PDFF EAT = 81.6 ± 9.6% vs. PDFF ScAT = 92.7 ± 4.2%, P < 0.001) and paracardiac fat (PDFF PAT = 90.6 ± 3.7%). Preliminary results in type-2 diabetic patients also showed a lower PDFF in EAT compared to neighbor paracardiac fat, which remains to be confirmed in a larger cohort. This study demonstrated precise and highly-resolved PDFF and R2* 3D maps to probe cardiac fat, in particular epicardial adipose tissue, thanks to free-running cardiac Dixon-MRI at 3 T. Due to the proximity of the lungs, the B0 inhomogeneities field map had large spatial variations, hampering unbiased R2* quantification. Nevertheless, 3D maps of PDFF in the heart allow characterization of the EAT, whose brown-beige fat composition was confirmed in controls and few type 2 diabetic patients.

Simultaneous multi-segment (SMSeg) EPI over multiple focal regions

Objective. This study aimed at developing a simultaneous multi-segment (SMSeg) imaging technique using a two-dimensional (2D) RF pulse in conjunction with echo planar imaging (EPI) to image multiple focal regions. Approach. The SMSeg technique leveraged periodic replicates of the excitation profile of a 2D RF pulse to simultaneously excite multiple focal regions at different locations. These locations were controlled by rotating and scaling transmit k-space trajectories. The resulting multiple isolated focal regions were projected into a composite ‘slice’ for display. GRAPPA-based parallel imaging was incorporated into SMSeg by taking advantage of coil sensitivity variations in both the phase-encoded and slice-selection directions. The SMSeg technique was implemented at 3 T in a single-shot gradient-echo EPI sequence and demonstrated in a phantom and human brains for both anatomic imaging and functional imaging. Main results. In both the phantom and the human brain, SMSeg images from three focal regions were simultaneously acquired. SMSeg imaging enabled up to a six-fold acceleration in parallel imaging without causing appreciable residual aliasing artifacts when compared with a conventional gradient-echo EPI sequence with the same acceleration factor. In the functional imaging experiment, BOLD activations associated with a visuomotor task were simultaneously detected in two non-coplanar segments (each with a size of 240 × 30 mm2), corresponding to visual and motor cortices, respectively. Significance. Our study has demonstrated that SMSeg imaging can be a viable method for studying multiple focal regions simultaneously.

Jointly Learning Non-Cartesian k-Space Trajectories and Reconstruction Networks for 2D and 3D MR Imaging through Projection.

Compressed sensing in magnetic resonance imaging essentially involves the optimization of (1) the sampling pattern in k-space under MR hardware constraints and (2) image reconstruction from undersampled k-space data. Recently, deep learning methods have allowed the community to address both problems simultaneously, especially in the non-Cartesian acquisition setting. This work aims to contribute to this field by tackling some major concerns in existing approaches. Particularly, current state-of-the-art learning methods seek hardware compliant k-space sampling trajectories by enforcing the hardware constraints through additional penalty terms in the training loss. Through ablation studies, we rather show the benefit of using a projection step to enforce these constraints and demonstrate that the resulting k-space trajectories are more flexible under a projection-based scheme, which results in superior performance in reconstructed image quality. In 2D studies, our novel method trajectories present an improved image reconstruction quality at a 20-fold acceleration factor on the fastMRI data set with SSIM scores of nearly 0.92-0.95 in our retrospective studies as compared to the corresponding Cartesian reference and also see a 3-4 dB gain in PSNR as compared to earlier state-of-the-art methods. Finally, we extend the algorithm to 3D and by comparing optimization as learning-based projection schemes, we show that data-driven joint learning-based method trajectories outperform model-based methods such as SPARKLING through a 2 dB gain in PSNR and 0.02 gain in SSIM.