Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques, eddy currents, image distortion, time-optimal

Motivation: Eddy current-induced image distortions in DWI require either tedious image-based corrections or time inefficient pulse sequence acquisitions that increase the minimum echo time (TE_min) and limit SNR.

Goal(s): Pre-excitation gradients for eddy current-nulled convex optimized diffusion encoding (Pre-ENCODE) was used to mitigate eddy current-induced image distortions without increasing TE_min.

Approach: Simulations, phantoms, and volunteer DWI with monopolar (MONO), eddy current-nulled convex optimized diffusion (ENCODE), and Pre-ENCODE were used to evaluate TE_min, eddy current-induced image distortions, and ADC.

Results: Pre-ENCODE offers shorter TE_min compared to MONO and ENCODE as well as reduced eddy current-induced image distortions and more accurate ADC values compared to MONO.

Impact: Pre-ENCODE reduces eddy current-induced image distortions by incorporating an additional pre-excitation gradient. Pre-ENCODE provides a shorter TE_min, increased SNR, improved image registration, and more accurate ADC quantification compared with conventional DWI encoding techniques.

Keywords: DWI/DTI/DKI, Diffusion/other diffusion imaging techniques, Reproducibility of results

Motivation: The quantitative brain diffusion metrics showed potential to provide functional information about diseases, but their robustness must be established before their implementation in clinical practice.

Goal(s): To evaluate the variability and reproducibility of quantitative brain diffusion metrics.

Approach: Fourteen volunteers prospectively underwent brain diffusion spectrum imagingusing a protocol designed to investigate the impact of scan-rescans, voxel size, coils on twenty-five quantitative diffusion metrics. Two observers drew thirteen regions of interests for metrics calculation.

Results: The voxel size has a greater influence on reproducibility of quantitative diffusion metrics than scan-rescans and coils. The reproducibility within an observer was higher than that between two observers.

Impact: Quantitative brain diffusion metrics, as promising tools for providing functional information of diseases, should be interpreted with caution because they are fragile to voxel size, which calls for standardization of scan protocols before prior to their implementation in clinical practice.

Keywords: Diffusion Reconstruction, Prostate

Motivation: Prostate DWI is an important contrast for the diagnosis of prostate cancer.

Goal(s): The aim is to achieve prostate DW images and ADC maps with less-geometric-distortion, high-resolution and high signal-to-noise ratio (SNR).

Approach: A novel multi-scale low-rank reconstruction approach is introduced to improve multi-shot EPI diffusion-weighted imaging of the prostate. It addresses the ability to jointly reconstruct images over all b-value/diffusion directions at multiple different spatial scales without loss of contrast/structure information. 

Results: Applied to healthy volunteers using different resolution protocols, the method demonstrates significant improvements in image resolution and SNR compared to a state-of-the-art reference method in a clinically acceptable scan time. 

Impact: This multi-scale, low-rank reconstruction approach for prostate DWI can significantly improve the quality of diagnostic images, benefiting clinicians and patients by enabling more accurate prostate cancer diagnoses within short scan times.

Keywords: DWI/DTI/DKI, High-Field MRI

Motivation: Diffusion weighted MRI (DWI) may blur structures due to limited resolution. Increasing to  submillimeter resolution reduces partial volume effects but sacrifices SNR.

Goal(s): We seek to demonstrate submillimeter isotropic DWI at 7T in 3 minutes, and enhanced high-resolution DTI maps.

Approach: Data acquisition is done via NAViEPI, enforcing consistent echo spacing between the imaging and the navigator echo, rendering minimal distortion mismatch. Image reconstruction is done using JETS, benefiting from complementary k-q-space sampling and regularization.

Results: We show a 3-scan trace acquisition with a scan time of 3:19 minutes, and offer high-resolution DTI measurement leading to Mean Diffusivity and colored Fractional Anisotropy maps.

Impact: This work demonstrates submillimeter isotropic diffusion MRI at ultra-high field 7T with improved image quality and reduced scan duration. The JETS-NAViEPI method has the potential to advance high-resolution diffusion MRI, enhancing both spatial and temporal resolution.

Keywords: Diffusion Reconstruction, Diffusion/other diffusion imaging techniques, Postmortem

Motivation: In diffusion MRI, large post-mortem samples reach steady-state temperature and diffusivity only after a very long scan time.

Goal(s): Our goal was to use data during steady-state temperature adaptation to model changing diffusivity and still obtain reliable tissue orientations.

Approach: We estimated the diffusivities at steady-state temperature with a subset of the data and computed the temperature correction coefficients from the difference between predicted and measured data.

Results: The corrected data has greatly increased test-retest agreement and angular accuracy of fiber orientation estimates.

Impact: Accelerate post-mortem diffusion MRI by replacing dummy scans with our new data-driven temperature modeling.

Keywords: Diffusion Acquisition, Diffusion Tensor Imaging, Spiral Acquisition, Multi-Interleave, SMS, Field Inhomogeneity Correction

Motivation: Diffusion-weighted imaging (DWI) using spiral readout has higher signal-to-noise efficiency comparing to EPI approaches. Spiral DWI with a high spatial-resolution with improved image qualities is desirable for studies in fine-scale brain structures.

Goal(s): The goal is to develop a short echo-time distortion-free diffusion imaging method with about 1 mm in-plane resolution with spiral readouts and simultaneous multi-slice (SMS) to accelerate acquisition.

Approach: We developed a SMS multi-interleave spiral acquisition of DWI with gradient and B₀ inhomogeneity corrections. The between-interleave phase error was corrected using a CG-SENSE method.

Results: We demonsrated that a distortion-free short-TE high-resolution DWI using SMS multi-interleave spiral readout is feasible.

Impact: A short echo-time multi-interleave spiral diffusion-weighted imaging (DWI) method with gradient and B₀ inhomogeneity corrections without additional hardware is developed, leading to a high spatial-resolution DWI with an improved image quality for studies in fine-scale brain structures.

Keywords: Simulation/Validation, Pulse Sequence Design, Cardiac Diffusion MRI

Motivation: In cardiac diffusion MRI, spatial resolution is often limited by the available SNR and scan time. However, reducing voxel size enables precise microstructure characterisation.

Goal(s): To develop and evaluate the feasibility of a new sampling/reconstruction scheme that takes advantage of similarities between diffusion-weighted images in (k,q) space in order to provide high spatial resolution with significantly reduced scan times.

Approach: A new spiral-based sampling scheme is proposed and its benefits when combined with an efficient reconstruction is demonstrated through simulations.

Results: Evaluations showed that the proposed technique provides high-quality diffusion parameter maps comparable to fully sampled reference data with RMSEs less than 4%.

Impact: We introduce a novel sampling technique for accelerating high-resolution cardiac diffusion tensor imaging (cDTI). Harnessing the improved spatial resolution and scan time reduction has the potential to make significant contributions to practicability of more complex diffusion models in the heart.

Keywords: Diffusion Reconstruction, Diffusion/other diffusion imaging techniques, Breast cancer, Deep learning

Motivation: The challenges such as image quality and long scan time limitations have degraded the diffusion-weighted imaging (DWI) of breast cancer in clinical practice. 

Goal(s): This study aims to investigate the application of deep learning constrained compressed sensing (CS) reconstruction in DWI to overcome existing limitations.

Approach: Quantitative and qualitative image quality of DWI and value apparent diffusion coefficient (ADC) of using CS (DWI-CS) and deep learning constrained CS (DWI-DLCS) were compared.

Results: The results of DWI-DLCS exhibited better contrast, contrast-to-noise ratio (CNR), lesion detectability and diagnostic confidence. There were no differences regarding the signal intensity values of the apparent diffusion coefficient (ADC).

Impact: Our study showcases the potential of deep learning constrained reconstruction in enhancing the quality and efficiency of DWI. This approach offers a promising clinical implementation to obtain high-quality DWI images while reducing scan time.

Keywords: IVIM, Diffusion/other diffusion imaging techniques, Intravoxel incoherent motion, IVIM

Motivation: Can flow-compensated intravoxel incoherent motion be performed on a wide-bore scanner with a 33 mT/m gradient system?

Goal(s): To find the shortest feasible diffusion encoding time for double diffusion encoding waveforms.

Approach: Phantom measurements with various diffusion encoding times, with application of the optimal encoding times on in-vivo brain and prostate scans.

Results: The shortest achievable encoding time was found to be 80 ms, with artefacts being the limiting factor. This encoding time was found to not be sufficiently short for brain imaging. For prostate imaging, it was found to be sufficient for imaging the transitional zone, but not the peripheral zone.

Impact: Due to ghosting artefacts associated with higher gradient amplitudes, we found a diffusion encoding time of 80 ms to be the shortest practically feasible. This encoding time was shown to be insufficient for brain IVIM, and partially so for prostate.

Keywords: Diffusion Acquisition, Spectroscopy, Spectroscopic imaging

Motivation: We show the first demonstration of single-shot diffusion trace-weighted radial echo planar spectroscopic imaging with tetrahedral diffusion encoding in both phantom and in vivo at 7T.

Goal(s): The advantage of the single-shot DW-REPS is the reduction of the measurement time. This proof-of-concept study applies radial EPSI at 7T for diffusion trace-weighted MRSI.

Approach: Trace ADCs from 3 phantom and 2 in vivo datasets were determined from single-shot DW-REPSI acquisitions. 

Results: Preliminary results show good agreement in the estimated phantom ADC values, while in vivo trace ADCs are generally within the expected range although the values tend to be slightly higher than previously reported.  

Impact: Our preliminary results indicate a promising approach for determining the orientation-independent trace ADC value with DW-REPSI at 7T. This technique can reduce the total acquisition time for DW-MRSI studies relevant for probing the intracellular properties underlying pathological conditions.

Keywords: Diffusion Analysis & Visualization, Susceptibility, Distortion correction, Nonrigid registration, Susceptibility distortion, Deep learning

Motivation: Diffusion MR images suffer from susceptibility distortion artifacts due to field inhomogenities and susceptibility changes at tissue interfaces. This results in a spatial mismatch of the MR signal. Current methods either use blip-up, blip-down acquisitions and/or are compute-intensive.

Goal(s): Our goal is to develop a fast registration-based susceptibility distortion correction method without the need to acquire an opposite phase-encode scan.

Approach: We use synthesized b0 volumes generated using synb0 as a registration target for SyN registration to correct susceptibility distortion.

Results: Our distortion correction method produces results that are qualitatively and quantitatively similar to state-of-the-art methods in a fraction of the time.

Impact: Our approach serves as a good starting point to explore registration based distortion correction methods. Faster correction methods will enable widespread use of dMRI in the clinical setting where accurate shape is needed for critical decisions like treatment planning.

Keywords: Diffusion Acquisition, Brain

Motivation: Several multi-shot 2D acquisition techniques have been developed to improve the resolution of diffusion MRI (dMRI) of the brain, but require long scan times.

Goal(s): To develop a 3D dMRI sequence with improved SNR efficiency to achieve high-resolution scans in a reasonable time.

Approach: We implemented a 3D spin echo sequence with an inversion pulse before the excitation to improve SNR at short repetition times and a TURBINE readout trajectory. Projection-based image reconstruction is employed to avoid artifacts caused by shot-to-shot phase errors.

Results: Phantom and human scans at 3T show an improvement in SNR efficiency over 2D dMRI.

Impact: We designed a multi-shot 3D dMRI sequence that is SNR efficient and robust to motion artifacts between shots. This sequence will enable high-resolution diffusion-weighted imaging of the whole brain in short scan times.

Keywords: Diffusion Acquisition, Data Acquisition, Diffusion Acquisition

Motivation: The progress in in-vivo high-resolution and high-b-value dMRI has advanced the investigation of structural connectivity and tissue microstructure. 

Goal(s): We aim to further push the spatial resolution and b-value of in-vivo diffusion MRI. 

Approach: A high-SNR(√25x), distortion-free, motion-robust Romer-EPTI technique that addresses the challenges in dMRI acquisition with further enhanced capabilities by taking advantage of the cutting-edge Connectome 2.0 scanner.

Results: We demonstrate motion-robust distortion-free in-vivo mesoscale dMRI (~485um-istropic) on clinical 3T&7T scanners, and further improvements in SNR on Connectome2.0 scanner enabling high-SNR, high b-value dMRI and a spatial resolution up to 400um-iso.   

Impact: Romer-EPTI achieves high-SNR motion-robust distortion-free in-vivo mesoscale dMRI (~485 um) with exceptional quality on clinical 3T&7T scanners. Its capabilities were further enhanced on the Connectome 2.0 scanner, enabling high-SNR high b-value dMRI and a spatial resolution up to 400um-iso.

Keywords: Diffusion Acquisition, Cardiovascular

Motivation: Spin-echo (SE) diffusion tensor cardiovascular magnetic resonance (DT-CMR) imaging with monopolar diffusion encoding scheme is limited by bulk motion induced signal loss.

Goal(s): Utilization of ultrahigh gradient-strengths to substantially reduce the echo-time (TE) in monopolar SE DT-CMR.

Approach: A monopolar SE DT-CMR pulse-sequence was developed. An in-vivo study at ultra-high gradient-strength (180mT/m, Connectom scanner) for diastolic cardiac phases was conducted.

Results: With ultra-high gradient strength, it was possible to obtain reasonable DT-CMR data with monopolar SE in 60% of subjects. To our knowledge this is the first report of SE DT-CMR with monopolar diffusion encoding utilizing the ultra-high gradient-strength of the Connectom scanner.

Impact: The ability to acquire monopolar SE using ultra-high diffusion gradient strengths and the associated drastic reductions in TE may provide substantial increase in imaging efficiency for DT-CMR acquired in diastolic cardiac phases, a key step towards clinical translation.

Keywords: Diffusion Analysis & Visualization, Diffusion/other diffusion imaging techniques

Motivation: Joint denoising diffusion-weighted images in high b-values

Goal(s): to achieve a better joint denoising of diffusion-weighted image at high b-values.

Approach: A low-rank tensor dictionary learning model was introduced to joint denoising diffusion-weighted images at b-values of 1000/2000 s/mm² for both simulations and in vivo datasets. Three state-of-the-art methods, MPPCA, WNNM, and a pre-trained complex-valued DnCNN were compared.

Results: In the simulation, the proposed method achieved the smallest RMSE. In vivo, the proposed method demonstrated a promising denoising ability while better preserving the image structures. 

Impact: We proposed a low-rank tensor dictionary learning method to better exploit non-local spatial redundancies and image correlations across different b-values with learned dictionaries and low-rank tensor approximation, providing a promising performance in denoising and preserving the image structures. 

Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques, fat suppresstion

Motivation: TSE-DWI provides distortion-free images, but it has a disadvantage in terms of its low signal-to-noise ratio (SNR). TSE-DWI basically requires several signal averages to obtain sufficient SNR, resulting in long scan time.

Goal(s): We modified and optimized the LIPO selective gradients (enhanced LIPO) to maximize the fat suppression effect for TSE-DWI in the neck, and compared with conventional methods (SPAIR TSE-DWI and LION TSE-DWI) to investigate its clinical usefulness.

Approach: SNR and CR were calculated with ROIs placed in parotid gland and fat around neck.

Results: Combining TSE-DWI with enhanced LION improves the robustness of fat suppression while maintaining better SNR.

Impact: The present findings suggest that both conventional and enhanced LION TSE-DWI showed improved SNR because it does not require fat suppression pre-pulse. Furthermore, enhanced LION further improved the robustness of fat suppression.