Keywords: Data Acquisition, Heart, Cardiac MRI planning

Motivation: Quantitative understanding of the differences in the heart’s habitus (position, orientation and size) between free-breathing (FB) and breath-hold (BH) mode of cardiac MR imaging (CMR) is lacking.

Goal(s): To quantitatively measure the differences in the heart’s position, orientation and size between free-breathing and breath-hold mode in cardiac patients

Approach: Used an accelerated 3D GRE survey, acquired in BH (cardiac gated) and FB modes (cardiac and respiratory gated) in a large cohort of cardiac patients and quantified the location, orientation and size differences.

Results: We find that quantitatively heart’s habitus differs significantly, in all three factors, between the two modes of imaging.

Impact: We have, for the first time, quantified the extent to which the heart’s habitus (position, orientation and size) changes between breath-hold and free-breathing modes of Cardiac MRI (CMR). CMRI planning, whether manual or AI based, needs to account for this.

Keywords: Artifacts, Data Processing, Visualization

Motivation: Radial k-space sampling is preferred over cartesian k-space sampling due to its many advantages. One major drawback of radial k-space is the streaking artifacts that arise from the non-linear gradients from the peripheral of FOV.

Goal(s): The goal of this study is to reduce streaky artifacts.

Approach: We developed an algorithm that aims to detect the streaky coils based on post-processing of the coils’ images and then remove these streaky coils for a cleaner image.

Results: Our results show that the proposed method precisely predicts streaky coils and improves the appearance of streaky artifacts in the CS reconstruction after removing the selected coils. 

Impact: Radial k-space sampling is improved using our new precise streaky coils detection algorithm that effectively removes them to produce a clean image with no streaky artifacts. An unmet need in the radial k-space sampling in the MRI field in general. 

Keywords: Quantitative Imaging, Quantitative Imaging, free‐breathing, ECG-free, multi-contrast

Motivation: A recently developed MACS technique provides exquisite delineation of the structure and motion of the whole heart and aorta. However, it lacks T1, T2 information and is limited in assessing complex vascular and myocardial pathologies.

Goal(s): To develop a quantitative MACS (qMACS) technique by incorporating T1 and T2 mapping into original MACS imaging pipeline.

Approach: The qMACS sequence builds on a multi-tasking imaging framework and stack-of-stars acquisition. Respiratory-resolved T1,T2 maps were generated using dictionary-matching approach.

Results: Free‐breathing and ECG-free 3D quantitative imaging of cardiovascular system in 10 minutes is feasible by proposed qMACS. qMACS measured slightly higher myocardial T1/T2 values than reference methods.

Impact: qMACS is a time-efficient and patient-friendly technique for both quantitative and qualitative imaging of the whole cardioaortic system and may be used as a gatekeeper approach to the diagnosis of a variety of cardiovascular diseases.

Keywords: Pulse Sequence Design, Data Acquisition

Motivation: Radial UTE can often be impacted by aliasing artifacts if undersampling is required to achieve a short scantime. More efficient trajectories may alleviate these limitations.

Goal(s): Our goal is to study how much aliasing reduction can be achieved in UTE MRI by applying a small amount of spiral twist to the readout trajectory.

Approach: In order to add some twist/spiral to the UTE trajectories, we simply added an orthogonal gradient while simultaneously ramping down the radial-out read gradient.

Results: Images using a longer, twisted readout trajectory results in less visible aliasing artifacts and increased SNR.

Impact: UTE MRI undersampling artifacts were found to be reduced using simple twisted k-space trajectories, hence allowing a reduction in scantime.

Keywords: Quantitative Imaging, Quantitative Imaging

Motivation: Simultaneous Multi-Slice (SMS) Multimapping can considerably improve the scan efficiency by acquiring myocardial T1 and T2 maps of 3 short-axis slices in 1 breath-hold.

Goal(s): To propose an accurate, precise, and reproducible SMS-Multimapping method.

Approach: A locally low-rank and sparsity-based reconstruction algorithm was developed to reduce noise and aliasing artifacts. Validation was performed in phantoms and 10 healthy subjects, where the method was compared with standard MOLLI/bSSFP T2 mapping and Multimapping.

Results: Despite the 6-fold reduction of scan time, the proposed method shows good accuracy, reasonable precision, and acceptable reproducibility in its regional myocardial T1 and T2 measurement.

Impact: The proposed method transforms a scan of 6 breath-holds down to a single breath-hold scan. Once employed, the method can greatly improve the patient comfort and efficiency of myocardial parametric mapping.

Keywords: Image Reconstruction, Liver, Deep Learning, Liver MR, LAVA sequence

Motivation: The potential of DLR to improve the quality of liver acquisition with volume acceleration (LAVA) sequence images and its impact on lesion diagnosis has not been extensively reported.

Goal(s): This study aims to investigate the utility of DLR in liver MR by comparing the image quality and diagnostic efficacy of the original LAVA sequence in the venous phase with the DL-LAVA sequence.

Approach: The image quality and diagnostic performance of the DL-LAVA sequence were compared with the original LAVA sequence.

Results: The results revealed that the DL-LAVA sequence significantly improved the image quality of the LAVA sequence, and its diagnostic performance was superior.

Impact: The results show that DLR can significantly improve the image quality of LAVA sequence, which may improve the detection and diagnosis of liver-related lesions, providing a powerful imaging basis for prevention and treatment.

Keywords: Data Acquisition, Diffusion Tensor Imaging, Cardiac Diffusion Tensor Imaging

Motivation: High gradient hardware has the potential to reduce TE and improve SNR for Cardiac diffusion tensor imaging (cDTI) for both single-shot (SS-EPI) and multi-shot EPI (MS-EPI) approaches. However, gradient amplitude and slew rate can be limited due to Peripheral and Cardiac Nerve stimulation (PNS/CNS).

Goal(s): To compare G_max=200mT/m and G_max=80mT/m systems for cDTI.

Approach: Healthy volunteers (n=3) were imaged on both systems using SS-EPI and MS-EPI. PNS/CNS and diffusion parametric mapping were compared.   

Results: Equivalent diffusion parameters were found for all acquisitions and systems. At Gmax=200mT/m, MS-EPI used the hardware system efficiently due to reduced PNS but remained limited by CNS.

Impact: In this work, we studied hardware limitations due to PNS/CNS for two high-gradient systems for SS-EPI and MS-EPI. MS-EPI reduces image distortions due to B₀ inhomogeneities, improves SNR compared to SS-EPI, and used the most efficiently the hardware system.

Keywords: Quantitative Imaging, Body

Motivation: Three-dimensional magnetic transfer ratio (MTR) measurement of the abdomen could be challenging due to the impact of motion.

Goal(s): To validate if the 3D abdominal MTR could be measured under a single breath-hold using a 3D segmented EPI sequence. 

Approach: This study applied a 3D segmented EPI sequence with in- and through- plane accelerations to achieve 3D MTR measurement under a single breath-hold.

Results: Three-dimensional MTR could be measured in a breath-hold of 17~18s, where 8s for a MT-on acquisition and 8s for a MT-off acquisition and a second or two for the system adjustment. 

Impact: Three-dimensional abdominal MTR measurement could be feasible in a single breath-hold using 3D EPI sequence. The gastrointestinal motility was noticed even at a time interval of 8s, which could impact the stability of the MTR measurement.  

Keywords: Data Acquisition, MSK, Dixon

Motivation: Common to existing TSE Dixon sequences is that the chemical shift between water and fat is encoded by shifting the readout window away from the spin-echo time point. The shifting prolongs the echo spacing by twice the shift. A short echo spacing is an important component of modern 3D-TSE sequences to enable high resolution 3D imaging in clinically acceptable times.

Goal(s): Develop a 3D-TSE Dixon sequence with unchanged echo spacing.

Approach: Encode the chemical shift via the excitation. Acquire in-phase and opposed-phase data for 2pt-Dixon symmetric around the spin-echo time point.

Results: Homogeneous fat-water separation in knee, hand and ankle.

Impact: 3D-TSE 2pt-Dixon sequence with unchanged echo spacing between second and subsequent echoes compared to a conventional 3D-TSE sequence with same acquisition parameters.

Keywords: Pulse Sequence Design, Quantitative Imaging

Motivation: T1 mapping is a promising biomarker of various chronic diseases, yet existing methods of T1 mapping suffer from high variability.

Goal(s): Improve the overall performance of water-specific T1 (T1_W) estimation with a rapid sequence for feasible implementation in body applications.

Approach: Design and implement a multi-echo chemical shift-encoded MRI sequence with an optimized preparation pulse, optimized flip angle-modulation readout scheme, centric encoding, and joint parameter estimation to improve the performance of T1_W estimation.

Results: We successfully implemented the proposed sequence on an MRI system and demonstrated its feasibility for T1_W mapping in the body.

Impact: The proposed approach to chemical shift-encoded T1 mapping improves the overall performance of T1W estimation in the presence of confounding factors. By showing robustness to confounding factors, this helps improve T1 mapping as a clinically viable diagnostic tool.

Keywords: Image Reconstruction, Hyperpolarized MR (Non-Gas), Cardiac phase detection

Motivation: The predetermined trigger delay may fail to acquire ¹³C images at an unstable heart rate and cause a misalignment between the cardiac phases depicted in structural and metabolic images.

Goal(s): Aim to exploit the volumetric PBSR algorithm to establish an automated alignment workflow to identify the actual cardiac phase for HP ¹³C images.

Approach: Image pairs of multiple ¹H cardiac phases and single-phase ¹³C images will be reconstructed by 3D PBSR, and the pair with the best similarity/in-focus index will be elected.

Results: The digital phantom and an in-vivo HP ¹³C cardiac image demonstrated the feasibility of cardiac phase detection.

Impact: The currently proposed automated alignment workflow identifies the actual cardiac phase when the HP ¹³C images are acquired, and this technique will potentially benefit patients with arrhythmia or pediatric populations.

Keywords: Quantitative Imaging, Diffusion/other diffusion imaging techniques

Motivation: High-resolution diffusion imaging is often perceived as less beneficial at ultra-high magnetic fields due to shorter T2 relaxation times. However, it is critical for detecting small lesions and assessing cartilage integrity.

Goal(s): Our goal was to achieve high-resolution diffusion imaging that leverages the advantages of ultra-high magnetic fields.

Approach: We employed diffusion-weighted DESS imaging to estimate diffusion tensor and fractional anisotropy in hand imaging.

Results: DW DESS yielded superior image quality compared to conventional spin-echo EPI. It shows promise as a high-resolution diffusion imaging method, harnessing the potential benefits of ultra-high magnetic fields for musculoskeletal applications.

Impact: Our study shows that DW DESS imaging offers high-resolution diffusion imaging benefits at ultra-high magnetic fields, particularly in musculoskeletal applications, with superior image quality and clinical relevance.

Keywords: Data Acquisition, Data Acquisition, Data Processing

Motivation: Abdominal MRI plays a crucial role in non-invasively visualizing abdominal structures. 

Goal(s): But abdominal MRI data often faces artifacts such as the strong noise.

Approach: In this work, a low-field abdominal MRI dataset is presented, comprising multi-contrast multi-repetition abdominal images of 58 healthy subjects. The dataset includes images with different contrasts, i.e., BH (Breath Hold)-T1, FB (Free breath)-T2, RT (Respiratory Triggered)-T2, RT-FST2 (Respiratory Triggered Fat-Suppressed T2). Additionally, various denoising methods, including traditional, supervised and self-supervised approaches, were explored with different structures and various loss functions. 

Results: These methods show promising results and provide some initial comparative conclusions for abdominal MRI denoising task. 

Impact: A low-field abdominal MRI dataset is presented, and various denoising methods were explored. During denoising, the main challenge is the trade-off between detail preservation and denoising. This dataset can inspire further exploration and research in this field.  

Keywords: Image Reconstruction, Data Processing, dynamic imaging, closed-form solution, non-iterative methods

Motivation: In cine MRI, the measurements within each time-frame alone are too noisy for image reconstruction. Some information must be ‘borrowed’ from other time frames and the reconstruction algorithm is a slow iterative procedure.

Goal(s): We set up a constrained objective function, which uses the measurements at other time frames to regularize the image reconstruction. We derive a non-iterative algorithm to minimize this objective function.

Approach: The derivation of the algorithm is based on the calculus of variations. The resultant algorithm is in the form of filtered backprojection.

Results: The feasibility of the proposed algorithm is demonstrated with a clinical patient brain study.

Impact: Non-iterative reconstruction that minimizes a constrained objective function increases the throughput in healthcare institutions. This translates to reduced healthcare costs. The new reconstruction formula has a closed-form explicit expression of how to incorporate the reference image in dynamic reconstruction.

Keywords: Data Acquisition, Translational Studies, Lung water, Heart Failure

Motivation: Our recently developed 0.55T MRI sequence to measure lung water dynamics has clinical utility in the evaluation of heart failure, but cardiac MRI is more widely performed at 1.5T.

Goal(s): To translate a 3D stack-of-spirals lung water MRI sequence from 0.55T to 1.5T.

Approach: We optimized sequence parameters through Bloch equation simulation, phantom experiments, and in vivo imaging in 10 healthy volunteers, acquired at two different centers.

Results: The sequence parameters TE/TR/FA/readout duration=0.70ms/9.0ms/1°/1.5ms at 1.5T yielded proton density weighted images with apparent SNR 13.5±2.2, limited image blur, and quantified a lung water density 20±3.2%. 

Impact: Lung water quantification has emerged as a promising method to monitor and predict outcomes in heart failure. Translation of a lung water MRI sequence from 0.55T to 1.5T enables a more widespread adoption of this tool.

Keywords: Artifacts, Spinal Cord, Respiration, multi-echo, GRE

Motivation: Respiration induces artifacts and signal loss in axial multi-echo gradient echo imaging of the lumbar spinal cord.

Goal(s): To investigate respiration-induced field shifts in the lumbar cord and to mitigate respiration induced artifacts using a 1D phase navigator.

Approach: A 1D phase navigator, added prior to the multi-echo gradient echo readout, was used to measure and provide compensation for respiration-induced and shot-dependent phase shifts. 

Results: The proposed navigator was effective in measuring field shifts and providing a substantial reduction in artifacts in the lumbar spinal cord. Navigator post-processing was simplified compared to that required for a 1D navigator post-readout.

Impact: This work demonstrates, via phantom and in-vivo experiments, self-consistent measurements of respiration-induced field shifts and proposes an approach for their compensation that could be integrated into future spinal cord studies using multi-echo gradient echo acquisitions.