Keywords: Quantitative Imaging, Quantitative Imaging

Motivation: Eliminate the need for B₀ gradients and improve the efficiency of quantitative imaging.

Goal(s): To develop an advanced approach for  gradient-free quantitative imaging called Quadratic RF Phase Selective Encoding through Nutation and Fingerprinting (qRF-SENF).

Approach: Design an improved sequence for qRF-SENF that increases sensitivities to off-resonance and relaxation parameters. Validate the advanced approach with a 1D experiment. Evaluate the SNR efficiency of the approach in simulation.

Results: Successfully validated an improved sequence for qRF-SENF with a 1D experiment that differentiates between two materials. Simulations of SNR efficiency show the advanced approach has sufficient SNR for current and future experiments.

Impact: Selective Encoding through Nutation and Fingerprinting (SENF) is a gradient-free quantitative imaging technique that simultaneously encodes spatial and quantitative information with the potential to be implemented on low-cost MRI scanners with flexible magnet design and acquisition strategies.

Keywords: Data Acquisition, Vessels

Motivation: The conventional velocity-selective ASL-based (VSASL) MRA's acquisition efficiency is low since a long waiting time is used for blood refreshing. A large turbo factor for acquisition window can be used, but will lead to image blurring and degraded depiction of small vessels.

Goal(s): To explore the potential of variable flip angle (VFA) strategy for improving conspicuity of distal small vessels in VSASL MRA.

Approach: Four VFA strategies were designed and compared with constant FA in vessel visualization. Vessel sharpness of ACA, MCA and PCA was calculated.

Results: Compared to constant FA, VFA has higher sharpness and can reduce the blurring of small vessels. 

Impact: The sharpness was higher for VFA than constant FA, suggesting the effectiveness of the VFA strategy in reducing blurring and improving the conspicuity of distal small vessels for VSASL MRA.

Keywords: Artifacts, Artifacts

Motivation: Echo-planar imaging (EPI) is prone to Nyquist ghosts, which are exacerbated on scanners with high-performance gradients. While dual-polarity GRAPPA (DPG) helps alleviate these artifacts, it does not permit regularized multi-shot reconstruction.

Goal(s): To introduce a SENSE-based method to address Nyquist ghosts on high-performance gradient systems and to lend itself to regularized multi-shot reconstruction.

Approach: We propose dual-polarity SENSE (DPS) for ghost correction where phase differences between even and odd lines are captured in ESPIRiT coil sensitivity estimates based on a tailored calibration scan.

Results: DPS effectively reduces Nyquist ghost artifacts in phantom and in vivo data on high-performance gradient systems.

Impact: We provide a robust SENSE-based Nyquist correction method that can be integrated with advanced multi-shot EPI reconstruction techniques and can address challenging Nyquist ghosts on high-performance gradient systems.

Keywords: Quantitative Imaging, Quantitative Imaging, B0 static magnetic field mapping, bSSFP, ellipse, elliptical signal model

Motivation: High fidelity B0 field mapping is often desirable for corrections and contrast, although most methods available require addition image acquisitions.

Goal(s): To generate a robust B0 mapping approach that is quantitatively accurate, time-efficient, and allows further understanding of coil information.

Approach: The bSSFP geometric solution is leveraged to compute a B0 map from a novel off-resonance parameter calculation. The maps are validated via comparisons to standards and coil element-by-element phase images.

Results: Simulation, phantom, and in vivo data confirmed that the method for B0 mapping not only computes quantitatively-accurate field maps, but also permits estimation of other phase contributions including coil-specific phase offsets. 

Impact: A robust B0 field mapping approach is proposed that facilitates research and clinical efforts seeking imaging techniques that minimize scan time and maximize practical data output.

Keywords: Image Reconstruction, Image Reconstruction

Motivation: In compressed sensing, it is impossible to separate folded-over images using equally spaced under-sampled signal when the subject is a real-valued image.

Goal(s): Our goal was to enable image reconstruction using equally spaced under-sampled signal, and to generalize it to phase-varied images.

Approach: Amplitude modulation in the phase-encoding direction makes the folded image complex-valued and thus facilitates separation of overlapping images in the image space.

Results: The image reconstruction was successful up to a speedup factor of 4 with U-Net. Phase images were successfully reconstructed by partial continuous signal acquisition and phase correction.

Impact: Reconstruction performance is improved by applying specific amplitude-modulated pulses prior to signal acquisition in equally spaced under-sampling CS, which is advantageous for sharp image reconstruction.

Keywords: Pulse Sequence Design, Diffusion/other diffusion imaging techniques

Motivation: High resolution distortion-free diffusion-prepared imaging (DiffPrep) is desirable for high-precision radiotherapy or surgical planning.

Goal(s): To demonstrate 3D high resolution distortion-free DiffPrep using a reduced field of view (RFOV) approach and gradient echo (GRE) readout.

Approach: A DiffPrep sequence was developed with magnitude stabilisers, RFOV excitation, fat suppression, 3D-GRE readout and 2D phase-correction navigator. The proposed approach using selective excitation of the tip-down pulse was compared against non-selective excitation at 3T in a phantom and in the spinal cord of a healthy volunteer.

Results: Preliminary results presented in a phantom and in-vivo demonstrate successful outer volume signal suppression using the reduced FOV approach.  

Impact: The sequence introduced in this work enables 3D RFOV distortion-free DiffPrep  with a GRE readout. This sequence could be advantageous for applications requiring accurate target delineation, such as radiotherapy planning or surgical planning. 

Keywords: Artifacts, Artifacts, Chemical-Shift, Off-resonance, Deep-Learning, radial, ZTE

Motivation: Chemical Shift artifacts in non-Cartesian MRI scans can lead to blurring and other artifacts at tissue interfaces. ZTE scans are particularly sensitive to this issue.

Goal(s): Addressing this artifact can enable the generation of more accurate ZTE images. Additionally, subsequent post-processing tasks like bone volume rendering, pseudo CT etc., can benefit from mitigating this artifact.

Approach: We introduce a deep learning based method to address this artifact and demonstrate its performance on phantom and in-vivo cases.

Results: The results demonstrate that gross chemical shift artifact can be corrected using the proposed method.

Impact: ZTE suffers from poor intrinsic SNR and chemical shift related blurring. Scanning at high field helps SNR but makes blurring more serious. Our proposed method helps mitigate chemical shift artifacts and opens up new possibilities for ZTE imaging.

Keywords: Quantitative Imaging, High-Field MRI, B1+ mapping, Actual Flip Angle Imaging (AFI)

Motivation: Polyvinylpyrrolidone (PVP) solutions have dielectric properties similar to human tissue and therefore are widely used for validating electromagnetic simulations in phantoms. For validating the flip angle in such applications, actual flip angle imaging (AFI) is highly suitable.

Goal(s): This work investigates measurement errors of AFI with PVP solutions.

Approach: Different PVP/H2O ratios are investigated at 3T, with different RF-spoiling phase increments, and with NMR spectroscopy.

Results:  NMR spectra show the existence of off-resonant PVP signals. Integrating two isochromat ensembles with different frequencies into an EPG-simulation qualitatively explain the measured signals and resulting flip angle errors in AFI.

Impact: Understanding the cause of unexpected measurement errors of actual flip angle imaging with polyvinylpyrrolidone solutions will improve their use for the validation of new B₁⁺ mapping techniques or new transmit arrays.

Keywords: Data Acquisition, Gradients, Gradient delay estimate

Motivation: The study was motivated by substantially reducing the calibration scan time for gradient delay estimation in spiral imaging. 

Goal(s): we only acquire a single spiral readout along each channel for delay estimation, which enables a substantial reduction in the calibration scan time. 

Approach: Our proposed method of SODA estimates the delay by calculating the relative shift between the MR spectrums required  in a single scan as the k-space trajectory progresses from the negative kx direction to the positive kx direction and vice versa, i.e., from +kx to -kx.

Results: The delay values demonstrated robust agreement and consistency between SODA and the reference.

Impact: The SODA method delivers accurate delay estimates within extremely short scan time (about 50 ms). This technique can seamlessly integrate with any host sequence to correct k-space location errors stemming from gradient delays.

Keywords: Quantitative Imaging, Quantitative Imaging

Motivation: Fat DESPOT, a fat and water R₁ mapping technique, has been proposed to image tumor hypoxia through the oxygen-induced change in fat R₁. 

Goal(s): Using the complex signal for Fat DESPOT doubles the usable data for each acquisition, reducing the total number of acquisitions required and scan time.

Approach: The published magnitude approach to fat DESPOT was compared to the complex approach in simulations and phantom experiments.

Results: Compared to the magnitude approach, the complex approach to Fat DESPOT increased the precision and accuracy of fat R­₁ estimates in simulations and phantom experiments and increased the accuracy of PDFF in phantom experiments.

Impact: This study suggests that the complex approach to fat DESPOT R1 measurements could reduce imaging time without compromising PDFF or R­1f estimates. It could therefore offer sensitive and versatile R1-based tumor hypoxia mapping in potentially clinically feasible scan times. 

Keywords: Artifacts, Neuro

Motivation: Previous studies have demonstrated field correction with 3D-EPI for fMRI and SWI, but ideal correction would account for both field inhomogeneities and motion.

Goal(s): We aimed to investigate the limits of simultaneous motion and field correction with 3D-EPI.

Approach: Our approach was to acquire in vivo data with controlled head motion. Volunteers were directed to rotate their heads 4-8 degrees and move left/right during scanning. We performed correction for field inhomogeneities using FID navigators after rigid motion registration.

Results: Analysis across varying rotation degrees showed the ability to successfully correct both motion and field distortions in 3D-EPI using FID navigators.

Impact: This simultaneous motion and field correction technique could enable high-resolution artifact-free 3D-EPI for fMRI studies. By correcting head motion and field inhomogeneities concurrently, the approach opens possibilities for investigating new research questions dependent on artifact-free imaging with substantial subject motion.

Keywords: Artifacts, RF Arrays & Systems, electromagnetic interference suppression, EMI

Motivation: To reduce siting costs, improve accessibility and relax electromagnetic compatibility (EMC) requirements on in-room equipment in 3T MRI.

Goal(s): To assess a deep-learning based active electromagnetic interference (EMI) elimination algorithm Deep-DSP at 3T.

Approach: Deep-DSP approach previously implemented for 0.055T MRI was applied to 3D imaging at 3 Tesla, performed within the standard shielded room and with deliberately added EMI sources using a 64-channel head coil and four coil arrays located outside the magnet bore for EMI sensing.

Results: Deep-DSP demonstrates excellent performance in phantoms and outperforms a comparison technique in vivo.

Impact: The proposed approach does not require additional dedicated hardware and has potential of substantially reducing siting costs of modern high-performance MR imagers. Furthermore, EMC and RF shielding requirements on the additional equipment in the scanner room may be largely relaxed.

Keywords: Image Reconstruction, Atherosclerosis, Plaque, Black-blood MRI, Trajectory

Motivation: The two-shot SNAP MRI is effective for carotid plaque diagnosis with extended scan time. To accelerate the scan, under-sampling reconstruction and optimization of sampling locations are considered.

Goal(s): To optimize the sampling masks for IR-TFE and REF-TFE of SNAP MRI respectively and to reconstruct the under-sampled images with higher quality.

Approach: After the parameterization of ky-kz sampling locations for the two shots, a model-based deep learning framework was utilized to achieve the goals.

Results: The framework demonstrated superior performance compared with other under-sampling reconstruction methods. Distinct sampling masks were generated for the two shots after the training process.

Impact: The optimized sampling masks facilitate the acquisition of SNAP MRI with more crucial information. Combined with high-quality under-sampling reconstruction, the utilization of the framework could enhance the clinical applicability, flexibility, and versatility of SNAP MRI.

Keywords: Data Acquisition, Diffusion/other diffusion imaging techniques

Motivation: High-performance gradients of the Connectome 2.0 system drastically improve diffusion and imaging encoding to enable submillimeter diffusion imaging with high geometric fidelity.

Goal(s): To enable high-resolution, distortion-free diffusion imaging with adequate SNR.

Approach: Distortion-free BUDA-gSlider acquisition was deployed on the Connectome 2.0 system, and was compared against acquisitions using gradients derated to the level of clinical systems.

Results: The Connectome 2.0 system provides improved diffusion-weighted images with higher SNR and geometric fidelity, particularly at submillimeter resolutions.

Impact: High-performance Connectome 2.0 gradients enable high-resolution, distortion-free diffusion-weighted imaging with improved SNR at submillimeter resolutions.

Keywords: Image Reconstruction, Image Reconstruction

Motivation: Diffusion model has been applied to MRI reconstruction, including single and multi-coil acquisition of MRI data. Simultaneous multi-slice imaging (SMS), as a method for accelerating MR acquisition, significantly reduces scanning time, but further optimization of reconstruction results is still possible.

Goal(s): In order to optimize the reconstruction of SMS, we proposed a method to use diffusion model based on slice-GRAPPA and SPIRiT method.

Approach: Specifically, our method characterizes the prior distribution of SMS data by score matching and characterizes the k-space redundant prior between coils and slices based on self-consistency.

Results: With the utilization of diffusion model, we achieved better reconstruction results.

Impact: The application of diffusion model can further reduce the scanning time of MRI without compromising image quality, making it more advantageous for clinical application.

Keywords: Quantitative Imaging, Elastography

Motivation: MR Elastography (MRE) is a quantitative, noninvasive method to map viscoelastic properties in tissue. We propose a method of advanced image reconstruction to increase resolution and accuracy for fast MRE.

Goal(s): We aim to reduce scan time and, eventually, enable real-time MRE.

Approach: To overcome artifacts resulting from the accelerated data acquisition, we employ a data-driven regularization method. Our approach utilizes a physics-informed convolutional neural network (CNN) that exploits spatio-temporal correlation among the images.

Results: We show that the employed spatio-temporal approach can improve the image reconstruction performance and further outperforms iterative SENSE reconstructions and standard 2D U-Net approaches.

Impact: Our approach allows for the accurate estimation of elastograms from strongly undersampled data, thus allowing a highly reduced scan time. These improvements will eventually benefit clinical practice, making MRE an even more powerful imaging tool.