High-resolution whole-brain diffusion MRI at 3T using simultaneous multi-slab (SMSlab) acquisition

2D CAIPI accelerated 3D multi-slab diffusion weighted EPI combined with qModeL reconstruction for fast high resolution microstructure imaging

PURPOSE

To develop acceleration strategies for 3D multi-slab diffusion weighted imaging (3D ms-DWI) for enabling applications that require simultaneously high spatial (1 mm isotropic) and angular (> 30 directions) resolutions.

METHODS

3D ms-DWI offers high SNR-efficiency, with the ability to achieve high isotropic spatial resolution, yet suffers from long scan-times for studies requiring high angular resolutions. We develop 6D k-q space acceleration strategies to reduce the scan-time. Specifically, we develop non-uniform 3D ky-kz under-sampling employing a shot-selective 2D CAIPI sampling approach. To achieve inter-shot phase-compensation, 2D navigators were employed that utilize the same CAIPI trajectory. An iterative model-based 3D multi-shot reconstruction was designed by incorporating phase into the forward encoding process. Additionally, the shot-selective non-uniform ky-kz CAIPI acceleration was randomized along the q-dimension. The 3D model-based multi-shot reconstruction is then extended to a joint reconstruction that simultaneously reconstructs all the q-space points, with the help of a spatial total variation and deep-learned q-space regularization.

RESULTS

The proposed reconstruction is shown to achieve adequate phase-compensation in both 2D CAIPI accelerated and additional ky-kz under-sampled cases. Using retrospective under-sampling experiments, we show that k-q accelerations close a factor of 12 can be achieved with a reconstruction error < 3% for both single and multi-shell data. This translates to a scan-time reduction by 3-fold for experiments with simultaneously high spatial and angular resolutions.

CONCLUSION

The proposed method facilitates the utilization of 3D ms-DWI for simultaneously high k-q resolution applications with close to 3× reduced scan-time.

Romer-EPTI: rotating-view motion-robust super-resolution EPTI for SNR-efficient distortion-free in-vivo mesoscale dMRI and microstructure imaging

Purpose

To overcome the major challenges in dMRI acquisition, including low SNR, distortion/blurring, and motion vulnerability.

Methods

A novel Romer-EPTI technique is developed to provide distortion-free dMRI with significant SNR gain, high motion-robustness, sharp spatial resolution, and simultaneous multi-TE imaging. It introduces a ROtating-view Motion-robust supEr-Resolution technique (Romer) combined with a distortion/blurring-free EPTI encoding. Romer enhances SNR by a simultaneous multi-thick-slice acquisition with rotating-view encoding, while providing high motion-robustness through a motion-aware super-resolution reconstruction, which also incorporates slice-profile and real-value diffusion, to resolve high-isotropic-resolution volumes. The in-plane encoding is performed using distortion/blurring-free EPTI, which further improves effective spatial resolution and motion robustness by preventing not only T2/T2*-blurring but also additional blurring resulting from combining encoded volumes with inconsistent geometries caused by dynamic distortions. Self-navigation was incorporated to enable efficient phase correction. Additional developments include strategies to address slab-boundary artifacts, achieve minimal TE for SNR gain at 7T, and achieve high robustness to strong phase variations at high b-values.

Results

Using Romer-EPTI, we demonstrate distortion-free whole-brain mesoscale in-vivo dMRI at both 3T (500-μm-iso) and 7T (485-μm-iso) for the first time, with high SNR efficiency (e.g., 25 × ), and high image quality free from distortion and slab-boundary artifacts with minimal blurring. Motion experiments demonstrate Romer-EPTI's high motion-robustness and ability to recover sharp images in the presence of motion. Romer-EPTI also demonstrates significant SNR gain and robustness in high b-value (b=5000s/mm2) and time-dependent dMRI.

Conclusion

Romer-EPTI significantly improves SNR, motion-robustness, and image quality, providing a highly efficient acquisition for high-resolution dMRI and microstructure imaging.

Metal artifact reduction around cervical spine implant using diffusion tensor imaging at 3T: A phantom study

PURPOSE

Diffusion MRI continues to play a key role in non-invasively assessing spinal cord integrity and pre-operative injury evaluation. However, post-operative Diffusion Tensor Imaging (DTI) acquisition of patients with metal implants results in severe geometric distortion. We propose and demonstrate a method to alleviate the technical challenges facing the acquisition of DTI on post-operative cases and longitudinal evaluation of therapeutics.

MATERIAL AND METHODS

The described technique is based on the combination of the reduced Field-Of-View (rFOV) strategy and the phase segmented EPI, termed rFOV-PS-EPI. A custom-built phantom based on a cervical spine model with metal implants was used to collect DTI data at 3 Tesla scanner using: rFOV-PS-EPI, reduced Field-Of-View single-shot EPI (rFOV-SS-EPI), and conventional full FOV techniques including SS-EPI, PS-EPI, and readout-segmented EPI (RS-EPI). Geometric distortion, SNR, and signal void were assessed to evaluate images and compare the sequences. A two-sample t-test was performed with p-value of 0.05 or less to indicate statistical significance.

RESULTS

The reduced FOV techniques showed better capability to reduce distortions compared to the Full FOV techniques. The rFOV-PS-EPI method provided DTI images of the phantom at the level of the hardware whereas the conventional rFOV-SS-EPI is useful only when the metal is approximately 20 mm away. In addition, compared to the rFOV-SS-EPI technique, the suggested approach produced smaller signal voids area as well as significantly reduced geometric distortion in Circularity (p < 0.005) and Eccentricity (p < 0.005) measurements. No statistically significant differences were found for these geometric distortion measurements between the rFOV-PS-EPI DTI sequence and conventional structural T2 images (p > 0.05).

CONCLUSION

The combination of rFOV and a phase-segmented acquisition approach is effective for reducing metal-induced distortions in DTI scan on spinal cord with metal hardware at 3 T.

3D diffusion MRI with twin navigator-based GRASE and comparison with 2D EPI for tractography in the human brain

PURPOSE

3D pulse sequences enable high-resolution acquisition with a high SNR and ideal slice profiles, which, however, is particularly difficult for diffusion MRI (dMRI) due to the additional phase errors from diffusion encoding.

METHODS

We proposed a twin navigator-based 3D diffusion-weighted gradient spin-echo (GRASE) sequence to correct the phase errors between shots and between odd and even spin echoes for human whole-brain acquisition. We then compared the SNR of 3D GRASE and 2D simultaneous multi-slice EPI within the same acquisition time. We further tested the performance of 2D versus 3D acquisition at equivalent SNR on fiber tracking and microstructural mapping, using the diffusion tensor and high-order fiber orientation density-based metrics.

RESULTS

The proposed twin navigator approach removed multi-shot phase errors to some extent in the whole brain dMRI, and the 2D navigator performed better than the 1D navigator. Comparisons of SNR between the 2D simultaneous multi-slice EPI and 3D GRASE sequences demonstrated that the SNR of the GRASE sequence was 1.4-1.5-fold higher than the EPI sequence at an equivalent scan time. More importantly, we found a significantly higher fiber cross-section in the cerebrospinal tract, as well as richer subcortical fibers (U-fibers) using the 3D GRASE sequence compared to 2D EPI.

CONCLUSION

The twin navigator-based 3D diffusion-weighted-GRASE sequence minimized the multishot phase error and effectively improved the SNR for whole-brain dMRI acquisition. We found differences in fiber tracking and microstructural mapping between 2D and 3D acquisitions, possibly due to the different slice profiles.

Sampling strategies and integrated reconstruction for reducing distortion and boundary slice aliasing in high-resolution 3D diffusion MRI

PURPOSE

To develop a new method for high-fidelity, high-resolution 3D multi-slab diffusion MRI with minimal distortion and boundary slice aliasing.

METHODS

Our method modifies 3D multi-slab imaging to integrate blip-reversed acquisitions for distortion correction and oversampling in the slice direction (kz ) for reducing boundary slice aliasing. Our aim is to achieve robust acceleration to keep the scan time the same as conventional 3D multi-slab acquisitions, in which data are acquired with a single direction of blip traversal and without kz -oversampling. We employ a two-stage reconstruction. In the first stage, the blip-up/down images are respectively reconstructed and analyzed to produce a field map for each diffusion direction. In the second stage, the blip-reversed data and the field map are incorporated into a joint reconstruction to produce images that are corrected for distortion and boundary slice aliasing.

RESULTS

We conducted experiments at 7T in six healthy subjects. Stage 1 reconstruction produces images from highly under-sampled data (R = 7.2) with sufficient quality to provide accurate field map estimation. Stage 2 joint reconstruction substantially reduces distortion artifacts with comparable quality to fully-sampled blip-reversed results (2.4× scan time). Whole-brain in-vivo results acquired at 1.22 mm and 1.05 mm isotropic resolutions demonstrate improved anatomical fidelity compared to conventional 3D multi-slab imaging. Data demonstrate good reliability and reproducibility of the proposed method over multiple subjects.

CONCLUSION

The proposed acquisition and reconstruction framework provide major reductions in distortion and boundary slice aliasing for 3D multi-slab diffusion MRI without increasing the scan time, which can potentially produce high-quality, high-resolution diffusion MRI.

Three-dimensional diffusion MRI using simultaneous multislab with blipped-CAIPI in a 4D k-space framework

PURPOSE

To develop an efficient simultaneous multislab imaging method with blipped-controlled aliasing in parallel imaging (blipped-SMSlab) in a 4D k-space framework, and to demonstrate its efficacy in high-resolution diffusion MRI (dMRI).

THEORY AND METHODS

First, the SMSlab 4D k-space signal expression is formulated, and the phase interferences from intraslab and interslab encodings on the same physical z-axis are analyzed. Then, the blipped-SMSlab dMRI sequence is designed, with blipped-controlled aliasing in parallel imaging (blipped-CAIPI) gradients for interslab encoding, and a 2D multiband accelerated navigator for inter-kz-shot phase correction. Third, strategies are developed to remove the phase interferences, by RF phase modulation and/or phase correction during reconstruction, thus decoupling intraslab and interslab encodings that are otherwise entangled. In vivo experiments are performed to validate the blipped-SMSlab method and preliminarily evaluate its performance in high-resolution dMRI compared with traditional 2D imaging.

RESULTS

In the 4D k-space framework, interslab and intraslab phase interferences of blipped-SMSlab are successfully removed using the proposed strategies. Compared with non-CAIPI sampling, the blipped-SMSlab acquisition reduces the g-factor and g-factor-related SNR penalty by about 12%. In addition, in vivo experiments show the SNR advantage of blipped-SMSlab dMRI over traditional 2D dMRI for 1.3-mm and 1.0-mm isotropic resolution imaging with matched acquisition time.

CONCLUSION

Removing interslab and intraslab phase interferences enables SMSlab dMRI with blipped-CAIPI in a 4D k-space framework. The proposed blipped-SMSlab dMRI is demonstrated to be more SNR-efficient than 2D dMRI and thus capable of high-quality, high-resolution fiber orientation detection.

High-fidelity mesoscale in-vivo diffusion MRI through gSlider-BUDA and circular EPI with S-LORAKS reconstruction

PURPOSE

To develop a high-fidelity diffusion MRI acquisition and reconstruction framework with reduced echo-train-length for less T2* image blurring compared to typical highly accelerated echo-planar imaging (EPI) acquisitions at sub-millimeter isotropic resolution.

METHODS

We first proposed a circular-EPI trajectory with partial Fourier sampling on both the readout and phase-encoding directions to minimize the echo-train-length and echo time. We then utilized this trajectory in an interleaved two-shot EPI acquisition with reversed phase-encoding polarity, to aid in the correction of off-resonance-induced image distortions and provide complementary k-space coverage in the missing partial Fourier regions. Using model-based reconstruction with structured low-rank constraint and smooth phase prior, we corrected the shot-to-shot phase variations across the two shots and recover the missing k-space data. Finally, we combined the proposed acquisition/reconstruction framework with an SNR-efficient RF-encoded simultaneous multi-slab technique, termed gSlider, to achieve high-fidelity 720 µm and 500 µm isotropic resolution in-vivo diffusion MRI.

RESULTS

Both simulation and in-vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide distortion-corrected diffusion imaging at the mesoscale with markedly reduced T2*-blurring. The in-vivo results of 720 µm and 500 µm datasets show high-fidelity diffusion images with reduced image blurring and echo time using the proposed approaches.

CONCLUSIONS

The proposed method provides high-quality distortion-corrected diffusion-weighted images with ∼40% reduction in the echo-train-length and T2* blurring at 500µm-isotropic-resolution compared to standard multi-shot EPI.

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 3^rd 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.

Column-based cortical depth analysis of the diffusion anisotropy and radiality in submillimeter whole-brain diffusion tensor imaging of the human cortical gray matter in vivo

High-resolution diffusion tensor imaging (DTI) can noninvasively probe the microstructure of cortical gray matter in vivo. In this study, 0.9-mm isotropic whole-brain DTI data were acquired in healthy subjects with an efficient multi-band multi-shot echo-planar imaging sequence. A column-based analysis that samples the fractional anisotropy (FA) and radiality index (RI) along radially oriented cortical columns was then performed to quantitatively analyze the FA and RI dependence on the cortical depth, cortical region, cortical curvature, and cortical thickness across the whole brain, which has not been simultaneously and systematically investigated in previous studies. The results showed characteristic FA and RI vs. cortical depth profiles, with an FA local maximum and minimum (or two inflection points) and a single RI maximum at intermediate cortical depths in most cortical regions, except for the postcentral gyrus where no FA peaks and a lower RI were observed. These results were consistent between repeated scans from the same subjects and across different subjects. They were also dependent on the cortical curvature and cortical thickness in that the characteristic FA and RI peaks were more pronounced i) at the banks than at the crown of gyri or at the fundus of sulci and ii) as the cortical thickness increases. This methodology can help characterize variations in microstructure along the cortical depth and across the whole brain in vivo, potentially providing quantitative biomarkers for neurological disorders.

Metal Artifact Reduction Around Cervical Spine Implant Using Diffusion Tensor Imaging at 3T: A Phantom Study

Diffusion MRI continues to play a key role in non-invasively assessing spinal cord integrity and pre-operative injury evaluation. However, post-operative Diffusion Tensor Imaging (DTI) acquisition of a patient with a metal implant results in severe geometric image distortion. A method has been proposed here to alleviate the technical challenges facing the acquisition of DTI in post-operative cases and to evaluate longitudinal therapeutics. The described technique is based on the combination of the reduced Field-Of-View (rFOV) strategy and the phase segmented acquisition scheme (rFOV-PS-EPI) for significantly mitigating metal-induced distortions. A custom-built phantom based on spine model with metal implant was used to collect high-resolution DTI data at 3 Tesla scanner using a home-grown diffusion MRI pulse sequence, rFOV-PS-EPI, single-shot (rFOV-SS-EPI), and the conventional full FOV techniques including SS-EPI, PS-EPI, and the readout-segmented (RS-EPI). This newly developed method provides high-resolution images with significant reduced metal-induced artifacts. In contrast to the other techniques, the rFOV-PS-EPI allows DTI measurement at the level of the metal hardware whereas the current rFOV-SS-EPI is useful when the metal is approximately 20 mm away. The developed approach enables high-resolution DTI in patients with metal implant.

Multi-band multi-shot diffusion MRI reconstruction with joint usage of structured low-rank constraints and explicit phase mapping

PURPOSE

To develop a joint reconstruction method for multi-band multi-shot diffusion MRI.

THEORY AND METHODS

Multi-band multi-shot EPI acquisition is an effective approach for high-resolution diffusion MRI, but requires specific algorithms to correct the inter-shot phase variations. The phase correction can be done by first estimating the explicit phase map and then feeding it into the k-space signal formulation model. Alternatively, the phase information can be used indirectly as structured low-rank constraints in k-space. The 2 methods differ in reconstruction accuracy and efficiency. We aim to combine the 2 different approaches for improved image quality and reconstruction efficiency simultaneously, termed "joint usage of structured low-rank constraints and explicit phase mapping" (JULEP). The proposed JULEP reconstruction is tested on both single-band and multi-band, multi-shot diffusion data, with different resolutions and b values. The results of JULEP are compared with conventional methods with explicit phase mapping (i.e., multiplexed sensitivity-encoding [MUSE]) and structured low-rank constraints (i.e., MUSSELS), and another joint reconstruction method (i.e., network estimated artifacts for tempered reconstruction [NEATR]).

RESULTS

JULEP improves the quality of the navigator and subsequently facilitates the reconstruction of final diffusion images. Compared with all 3 other methods (MUSE, MUSSELS, and NEATR), JULEP mitigates residual structural bias and improves temporal SNRs in the final diffusion image, particularly at high multi-band factors. Compared with MUSSELS, JULEP also improves computational efficiency.

CONCLUSION

The proposed JULEP method significantly improves the image quality and reconstruction efficiency of multi-band multi-shot diffusion MRI, which can promote a broader application of high-resolution diffusion MRI.

Deep Learning-Enhanced Parallel Imaging and Simultaneous Multislice Acceleration Reconstruction in Knee MRI

OBJECTIVES

This study aimed to examine various combinations of parallel imaging (PI) and simultaneous multislice (SMS) acceleration imaging using deep learning (DL)-enhanced and conventional reconstruction. The study also aimed at comparing the diagnostic performance of the various combinations in internal knee derangement and provided a quantitative evaluation of image sharpness and noise using edge rise distance (ERD) and noise power (NP), respectively.

MATERIALS AND METHODS

The data from adult patients who underwent knee magnetic resonance imaging using various DL-enhanced acquisitions between June 2021 and January 2022 were retrospectively analyzed. The participants underwent conventional 2-fold PI and DL protocols with 4- to 8-fold acceleration imaging (P2S2 [2-fold PI with 2-fold SMS], P3S2, and P4S2). Three readers evaluated the internal knee derangement and the overall image quality. The diagnostic performance was calculated using consensus reading as a standard reference, and we conducted comparative evaluations. We calculated the ERD and NP for quantitative evaluations of image sharpness and noise, respectively. Interreader and intermethod agreements were calculated using Fleiss κ.

RESULTS

A total of 33 patients (mean age, 49 ± 19 years; 20 women) were included in this study. The diagnostic performance for internal knee derangement and the overall image quality were similar among the evaluated protocols. The NP values were significantly lower using the DL protocols than with conventional imaging ( P < 0.001), whereas the ERD values were similar among these methods ( P > 0.12). Interreader and intermethod agreements were moderate-to-excellent (κ = 0.574-0.838) and good-to-excellent (κ = 0.755-1.000), respectively. In addition, the mean acquisition time was reduced by 47% when using DL with P2S2, by 62% with P3S2, and by 71% with P4S2, compared with conventional P2 imaging (2 minutes and 55 seconds).

CONCLUSIONS

The combined use of DL-enhanced 8-fold acceleration imaging (4-fold PI with 2-fold SMS) showed comparable performance with conventional 2-fold PI for the evaluation of internal knee derangement, with a 71% reduction in acquisition time.

Slab boundary artifact correction in multislab imaging using convolutional-neural-network-enabled inversion for slab profile encoding

PURPOSE

This study aims to propose a novel algorithm for slab boundary artifact correction in both single-band multislab imaging and simultaneous multislab (SMSlab) imaging.

THEORY AND METHODS

In image domain, the formation of slab boundary artifacts can be regarded as modulating the artifact-free images using the slab profiles and introducing aliasing along the slice direction. Slab boundary artifact correction is the inverse problem of this process. An iterative algorithm based on convolutional neural networks (CNNs) is proposed to solve the problem, termed CNN-enabled inversion for slab profile encoding (CPEN). Diffusion-weighted SMSlab images and reference images without slab boundary artifacts were acquired in 7 healthy subjects for training. Images of 5 healthy subjects were acquired for testing, including single-band multislab and SMSlab images with 1.3-mm or 1-mm isotropic resolution. CNN-enabled inversion for slab profile encoding was compared with a previously reported method (i.e., nonlinear inversion for slab profile encoding [NPEN]).

RESULTS

CNN-enabled inversion for slab profile encoding reduces the slab boundary artifacts in both single-band multislab and SMSlab images. It also suppresses the slab boundary artifacts in the diffusion metric maps. Compared with NPEN, CPEN shows fewer residual artifacts in different acquisition protocols and more significant improvements in quantitative assessment, and it also accelerates the computation by more than 35 times.

CONCLUSION

CNN-enabled inversion for slab profile encoding can reduce the slab boundary artifacts in multislab acquisitions. It shows better slab boundary artifact correction capacity, higher robustness, and computation efficiency when compared with NPEN. It has the potential to improve the accuracy of multislab acquisitions in high-resolution DWI and functional MRI.