Controlled aliasing in volumetric parallel imaging (2D CAIPIRINHA)

Simulation-based optimization and experimental comparison of intracranial T2-weighted DANTE-SPACE vessel wall imaging at 3T and 7T

PURPOSE

T2-weighted DANTE-SPACE (Delay Alternating with Nutation for Tailored Excitation - Sampling Perfection with Application optimized Contrasts using different flip angle Evolution) sequences facilitate non-invasive intracranial vessel wall imaging at 7T through simultaneous suppression of blood and CSF. However, the achieved vessel wall delineation depends closely on the selected sequence parameters, and little information is available about the performance of the sequence using more widely available 3T MRI. Therefore, in this paper a comprehensive DANTE-SPACE simulation framework is used for the optimization and quantitative comparison of T2-weighted DANTE-SPACE at both 7T and 3T.

METHODS

Simulations are used to propose optimized sequence parameters at both 3T and 7T. At 7T, an additional protocol which uses a parallel transmission (pTx) shim during the DANTE preparation for improved suppression of inflowing blood is also proposed. Data at both field strengths using optimized and literature protocols are acquired and quantitatively compared in six healthy volunteers.

RESULTS

At 7T, more vessel wall signal can be retained while still achieving sufficient CSF suppression by using fewer DANTE pulses than described in previous implementations. The use of a pTx shim during DANTE at 7T provides a modest further improvement to the inner vessel wall delineation. At 3T, aggressive DANTE preparation is required to achieve CSF suppression, resulting in reduced vessel wall signal. As a result, the achievable vessel wall definition at 3T is around half that of 7T.

CONCLUSION

Simulation-based optimization of DANTE parameters facilitates improved T2-weighted DANTE-SPACE contrasts at 7T. The improved vessel definition of T2-weighted DANTE-SPACE at 7T makes DANTE preparation more suitable for T2-weighted VWI at 7T than at 3T.

Design of calibration-free RF pulses for T 2 $$ {}_2 $$ -weighted single-slab 3D turbo-spin-echo sequences at 7T utilizing parallel transmission

PURPOSE

T  2 $$ {}_2 $$ -weighted turbo-spin-echo (TSE) sequences are a fundamental technique in brain imaging but suffer from field inhomogeneities at ultra-high fields. Several methods have been proposed to mitigate the problem, but were limited so far to nonselective three-dimensional (3D) measurements, making short acquisitions difficult to achieve when targeting very high resolution images, or needed additional calibration procedures, thus complicating their application.

METHODS

Slab-selective excitation pulses were designed for flexible placement utilizing the concept of k  T $$ {}_T $$ -spokes. Phase-coherent refocusing universal pulses were subsequently optimized with the Gradient Ascent Pulse Engineering algorithm and tested in vivo for improved signal homogeneity.

RESULTS

Implemented within a 3D variable flip angle TSE sequence, these pulses led to a signal-to-noise ratio (SNR) improvement ranging from 10% to 30% compared to a two-dimensional (2D) T2w TSE sequence employingB 1 + $$ {\mathrm{B}}_1^{+} $$ -shimmed pulses.B 1 + $$ {\mathrm{B}}_1^{+} $$ field inhomogeneities could be mitigated and artifacts fromB 0 $$ {\mathrm{B}}_0 $$ deviations reduced. The concept of universal pulses was successfully applied.

CONCLUSION

We present a pulse design method which provides a set of calibration-free universal pulses (UPs) for slab-selective excitation and phase-coherent refocusing in slab-selective TSE sequences.

Highly compressed SENSE accelerated relaxation-enhanced angiography without contrast and triggering (REACT) for fast non-contrast enhanced magnetic resonance angiography of the neck: Clinical evaluation in patients with acute ischemic stroke at 3 tesla

BACKGROUND AND PURPOSE

Long acquisition times limit the feasibility of established non-contrast-enhanced MRA (non-CE-MRA) techniques. The purpose of this study was to evaluate a highly accelerated flow-independent sequence (Relaxation-Enhanced Angiography without Contrast and Triggering [REACT]) for imaging of the extracranial arteries in acute ischemic stroke (AIS).

MATERIALS AND METHODS

Compressed SENSE (CS) accelerated (factor 7) 3D isotropic REACT (fixed scan time: 01:22 min, reconstructed voxel size 0.625 × 0.625 × 0.75 mm3) and CE-MRA (CS factor 6, scan time: 1:08 min, reconstructed voxel size 0.5 mm3) were acquired in 76 AIS patients (69.4 ± 14.3 years, 33 females) at 3 Tesla. Two radiologists assessed scans for the presence of internal carotid artery (ICA) stenosis and stated their diagnostic confidence using a 5-point scale (5 = excellent). Vessel quality of cervical arteries as well as the impact of artifacts and image noise were scored on 5-point scales (5 = excellent/none). Apparent signal- and contrast-to-noise ratios (aSNR/aCNR) were measured for the common carotid artery (CCA) and ICA (C1-segment).

RESULTS

REACT provided a sensitivity of 88.5% and specificity of 100% for clinically relevant (≥50%) ICA stenosis with substantial concordance to CE-MRA regarding stenosis grading (Cohen's kappa 0.778) and similar diagnostic confidence (REACT: mean 4.5 ± 0.4 vs. CE-MRA: 4.5 ± 0.6; P = 0.674). Presence of artifacts (3.6 ± 0.5 vs. 3.5 ± 0.7; P = 0.985) and vessel quality (all segments: 3.6 ± 0.7 vs. 3.8 ± 0.7; P = 0.004) were comparable between both techniques with REACT showing higher scores at the CCA (4.3 ± 0.6 vs. 3.8 ± 0.9; P < 0.001) and CE-MRA at V2- (3.3 ± 0.5 vs. 3.9 ± 0.8; P < 0.001) and V3-segments (3.3 ± 0.5 vs. 4.0 ± 0.8; P < 0.001). For all vessels, REACT showed a lower impact of image noise (3.8 ± 0.6 vs. 3.6 ± 0.7; P = 0.024) while yielding higher aSNR (52.5 ± 15.1 vs. 37.9 ± 12.5; P < 0.001) and aCNR (49.4 ± 15.0 vs. 34.7 ± 12.3; P < 0.001) for all vessels combined.

CONCLUSIONS

In patients with acute ischemic stroke, highly accelerated REACT provides an accurate detection of ICA stenosis with vessel quality and scan time comparable to CE-MRA.

Three-dimensional EPI with shot-selective CAIPIRIHANA for rapid high-resolution quantitative susceptibility mapping at 3 T

PURPOSE

QSM provides insight into healthy brain aging and neuropathologies such as multiple sclerosis (MS), traumatic brain injuries, brain tumors, and neurodegenerative diseases. Phase data for QSM are usually acquired from 3D gradient-echo (3D GRE) scans with long acquisition times that are detrimental to patient comfort and susceptible to patient motion. This is particularly true for scans requiring whole-brain coverage and submillimeter resolutions. In this work, we use a multishot 3D echo plannar imaging (3D EPI) sequence with shot-selective 2D CAIPIRIHANA to acquire high-resolution, whole-brain data for QSM with minimal distortion and blurring.

METHODS

To test clinical viability, the 3D EPI sequence was used to image a cohort of MS patients at 1-mm isotropic resolution at 3 T. Additionally, 3D EPI data of healthy subjects were acquired at 1-mm, 0.78-mm, and 0.65-mm isotropic resolution with varying echo train lengths (ETLs) and compared with a reference 3D GRE acquisition.

RESULTS

The appearance of the susceptibility maps and the susceptibility values for segmented regions of interest were comparable between 3D EPI and 3D GRE acquisitions for both healthy and MS participants. Additionally, all lesions visible in the MS patients on the 3D GRE susceptibility maps were also visible on the 3D EPI susceptibility maps. The interplay among acquisition time, resolution, echo train length, and the effect of distortion on the calculated susceptibility maps was investigated.

CONCLUSION

We demonstrate that the 3D EPI sequence is capable of rapidly acquiring submillimeter resolutions and providing high-quality, clinically relevant susceptibility maps.

Accelerated free-breathing liver fat and R 2 * quantification using multi-echo stack-of-radial MRI with motion-resolved multidimensional regularized reconstruction: Initial retrospective evaluation

PURPOSE

To improve image quality, mitigate quantification biases and variations for free-breathing liver proton density fat fraction (PDFF) andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ quantification accelerated by radial k-space undersampling.

METHODS

A free-breathing multi-echo stack-of-radial MRI method was developed with compressed sensing with multidimensional regularization. It was validated in motion phantoms with reference acquisitions without motion and in 11 subjects (6 patients with nonalcoholic fatty liver disease) with reference breath-hold Cartesian acquisitions. Images, PDFF, andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps were reconstructed using different radial view k-space sampling factors and reconstruction settings. Results were compared with reference-standard results using Bland-Altman analysis. Using linear mixed-effects model fitting (p < 0.05 considered significant), mean and SD were evaluated for biases and variations of PDFF andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ , respectively, and coefficient of variation on the first echo image was evaluated as a surrogate for image quality.

RESULTS

Using the empirically determined optimal sampling factor of 0.25 in the accelerated in vivo protocols, mean differences and limits of agreement for the proposed method were [-0.5; -33.6, 32.7] s-1 forR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and [-1.0%; -5.8%, 3.8%] for PDFF, close to those of a previous self-gating method using fully sampled radial views: [-0.1; -27.1, 27.0] s-1 forR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and [-0.4%; -4.5%, 3.7%] for PDFF. The proposed method had significantly lower coefficient of variation than other methods (p < 0.001). Effective acquisition time of 64 s or 59 s was achieved, compared with 171 s or 153 s for two baseline protocols with different radial views corresponding to sampling factor of 1.0.

CONCLUSION

This proposed method may allow accelerated free-breathing liver PDFF andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ mapping with reduced biases and variations.

Practical utilization of nonlinear spatial encoding: Fast field mapping and FRONSAC-wave

PURPOSE

To study the additional value of FRONSAC encoding in 2D and 3D wave sequences, implementing a simple strategy to trajectory mapping for FRONSAC encoding gradients.

THEORY AND METHODS

The nonlinear gradient trajectory for each voxel was estimated by exploiting the sparsity of the point spread function in the frequency domain. Simulations and in-vivo experiments were used to analyze the performance of combinations of wave and FRONSAC encoding.

RESULTS

Field mapping using the simplified approach produced similar image quality with much shorter calibration time than the comprehensive mapping schemes utilized in previous work. In-vivo human brain images showed that the addition of FRONSAC encoding could improve wave image quality, particularly at very high undersampling factors and in the context of limited wave amplitudes. These results were further supported by g-factor maps.

CONCLUSION

Results show that FRONSAC can be used to improve image quality of wave at very high undersampling rates or in slew-limited acquisitions. Our study illustrates the potential of the proposed fast field mapping approach.

Modern acceleration in musculoskeletal MRI: applications, implications, and challenges

Magnetic resonance imaging (MRI) is crucial for accurately diagnosing a wide spectrum of musculoskeletal conditions due to its superior soft tissue contrast resolution. However, the long acquisition times of traditional two-dimensional (2D) and three-dimensional (3D) fast and turbo spin-echo (TSE) pulse sequences can limit patient access and comfort. Recent technical advancements have introduced acceleration techniques that significantly reduce MRI times for musculoskeletal examinations. Key acceleration methods include parallel imaging (PI), simultaneous multi-slice acquisition (SMS), and compressed sensing (CS), enabling up to eightfold faster scans while maintaining image quality, resolution, and safety standards. These innovations now allow for 3- to 6-fold accelerated clinical musculoskeletal MRI exams, reducing scan times to 4 to 6 min for joints and spine imaging. Evolving deep learning-based image reconstruction promises even faster scans without compromising quality. Current research indicates that combining acceleration techniques, deep learning image reconstruction, and superresolution algorithms will eventually facilitate tenfold accelerated musculoskeletal MRI in routine clinical practice. Such rapid MRI protocols can drastically reduce scan times by 80-90% compared to conventional methods. Implementing these rapid imaging protocols does impact workflow, indirect costs, and workload for MRI technologists and radiologists, which requires careful management. However, the shift from conventional to accelerated, deep learning-based MRI enhances the value of musculoskeletal MRI by improving patient access and comfort and promoting sustainable imaging practices. This article offers a comprehensive overview of the technical aspects, benefits, and challenges of modern accelerated musculoskeletal MRI, guiding radiologists and researchers in this evolving field.

Knowledge-driven deep learning for fast MR imaging: Undersampled MR image reconstruction from supervised to un-supervised learning

Deep learning (DL) has emerged as a leading approach in accelerating MRI. It employs deep neural networks to extract knowledge from available datasets and then applies the trained networks to reconstruct accurate images from limited measurements. Unlike natural image restoration problems, MRI involves physics-based imaging processes, unique data properties, and diverse imaging tasks. This domain knowledge needs to be integrated with data-driven approaches. Our review will introduce the significant challenges faced by such knowledge-driven DL approaches in the context of fast MRI along with several notable solutions, which include learning neural networks and addressing different imaging application scenarios. The traits and trends of these techniques have also been given which have shifted from supervised learning to semi-supervised learning, and finally, to unsupervised learning methods. In addition, MR vendors' choices of DL reconstruction have been provided along with some discussions on open questions and future directions, which are critical for the reliable imaging systems.

Rapid submillimeter QSM and R2* mapping using interleaved multishot 3D-EPI at 7 and 3 Tesla

PURPOSE

To explore the high signal-to-noise ratio (SNR) efficiency of interleaved multishot 3D-EPI with standard image reconstruction for fast and robust high-resolution whole-brain quantitative susceptibility (QSM) andR 2 ∗ $$ {R}_2^{\ast } $$ mapping at 7 and 3T.

METHODS

Single- and multi-TE segmented 3D-EPI is combined with conventional CAIPIRINHA undersampling for up to 72-fold effective gradient echo (GRE) imaging acceleration. Across multiple averages, scan parameters are varied (e.g., dual-polarity frequency-encoding) to additionally correct forB 0 $$ {\mathrm{B}}_0 $$ -induced artifacts, geometric distortions and motion retrospectively. A comparison to established GRE protocols is made. Resolutions range from 1.4 mm isotropic (1 multi-TE average in 36 s) up to 0.4 mm isotropic (2 single-TE averages in approximately 6 min) with whole-head coverage.

RESULTS

Only 1-4 averages are needed for sufficient SNR with 3D-EPI, depending on resolution and field strength. Fast scanning and small voxels together with retrospective corrections result in substantially reduced image artifacts, which improves susceptibility andR 2 ∗ $$ {R}_2^{\ast } $$ mapping. Additionally, much finer details are obtained in susceptibility-weighted image projections through significantly reduced partial voluming.

CONCLUSION

Using interleaved multishot 3D-EPI, single-TE and multi-TE data can readily be acquired 10 times faster than with conventional, accelerated GRE imaging. Even 0.4 mm isotropic whole-head QSM within 6 min becomes feasible at 7T. At 3T, motion-robust 0.8 mm isotropic whole-brain QSM andR 2 ∗ $$ {R}_2^{\ast } $$ mapping with no apparent distortion in less than 7 min becomes clinically feasible. Stronger gradient systems may allow for even higher effective acceleration rates through larger EPI factors while maintaining optimal contrast.

Integrating data distribution prior via Langevin dynamics for end-to-end MR reconstruction

PURPOSE

To develop a novel deep learning-based method inheriting the advantages of data distribution prior and end-to-end training for accelerating MRI.

METHODS

Langevin dynamics is used to formulate image reconstruction with data distribution before facilitate image reconstruction. The data distribution prior is learned implicitly through the end-to-end adversarial training to mitigate the hyper-parameter selection and shorten the testing time compared to traditional probabilistic reconstruction. By seamlessly integrating the deep equilibrium model, the iteration of Langevin dynamics culminates in convergence to a fix-point, ensuring the stability of the learned distribution.

RESULTS

The feasibility of the proposed method is evaluated on the brain and knee datasets. Retrospective results with uniform and random masks show that the proposed method demonstrates superior performance both quantitatively and qualitatively than the state-of-the-art.

CONCLUSION

The proposed method incorporating Langevin dynamics with end-to-end adversarial training facilitates efficient and robust reconstruction for MRI. Empirical evaluations conducted on brain and knee datasets compellingly demonstrate the superior performance of the proposed method in terms of artifact removing and detail preserving.

Improved test-retest reliability of R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and susceptibility quantification using multishot multi-echo 3D EPI

PURPOSE

This study aimed to evaluate the potential of 3D EPI for improving the reliability ofT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted data and quantification ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ decay rate and susceptibility (χ) compared with conventional gradient-echo (GRE)-based acquisition.

METHODS

Eight healthy subjects in a wide age range were recruited. Each subject received repeated scans for both GRE and EPI acquisitions with an isotropic 1 mm resolution at 3 T. Maps ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ were quantified, and their interscan differences were used to evaluate the test-retest reliability. Interprotocol differences ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ between GRE and EPI were also measured voxel by voxel and in selected regions of interest to test the consistency between the two acquisition methods.

RESULTS

The quantifications ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ using EPI protocols showed increased test-retest reliability with higher EPI factors up to 5 as performed in the experiment and were consistent with those based on GRE.

CONCLUSION

The result suggests that multishot multi-echo 3D EPI can be a useful alternative acquisition method forT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted MRI and quantification ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ with reduced scan time, improved test-retest reliability, and similar accuracy compared with commonly used 3D GRE.

Advanced MRI techniques in abdominal imaging

Magnetic resonance imaging (MRI) is a crucial modality for abdominal imaging evaluation of focal lesions and tissue properties. However, several obstacles, such as prolonged scan times, limitations in patients' breath-hold capacity, and contrast agent-associated artifacts, remain in abdominal MR images. Recent techniques, including parallel imaging, three-dimensional acquisition, compressed sensing, and deep learning, have been developed to reduce the scan time while ensuring acceptable image quality or to achieve higher resolution without extending the scan duration. Quantitative measurements using MRI techniques enable the noninvasive evaluation of specific materials. A comprehensive understanding of these advanced techniques is essential for accurate interpretation of MRI sequences. Herein, we therefore review advanced abdominal MRI techniques.

Non-Cartesian 3D-SPARKLING vs Cartesian 3D-EPI encoding schemes for functional Magnetic Resonance Imaging at 7 Tesla

The quest for higher spatial and/or temporal resolution in functional MRI (fMRI) while preserving a sufficient temporal signal-to-noise ratio (tSNR) has generated a tremendous amount of methodological contributions in the last decade ranging from Cartesian vs. non-Cartesian readouts, 2D vs. 3D acquisition strategies, parallel imaging and/or compressed sensing (CS) accelerations and simultaneous multi-slice acquisitions to cite a few. In this paper, we investigate the use of a finely tuned version of 3D-SPARKLING. This is a non-Cartesian CS-based acquisition technique for high spatial resolution whole-brain fMRI. We compare it to state-of-the-art Cartesian 3D-EPI during both a retinotopic mapping paradigm and resting-state acquisitions at 1mm3 (isotropic spatial resolution). This study involves six healthy volunteers and both acquisition sequences were run on each individual in a randomly-balanced order across subjects. The performances of both acquisition techniques are compared to each other in regards to tSNR, sensitivity to the BOLD effect and spatial specificity. Our findings reveal that 3D-SPARKLING has a higher tSNR than 3D-EPI, an improved sensitivity to detect the BOLD contrast in the gray matter, and an improved spatial specificity. Compared to 3D-EPI, 3D-SPARKLING yields, on average, 7% more activated voxels in the gray matter relative to the total number of activated voxels.

Enhancing gadoxetic acid-enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques

OBJECTIVE

To investigate whether a deep learning (DL) controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE) technique can improve image quality, lesion conspicuity, and lesion detection compared to a standard CAIPIRINHA-VIBE technique in gadoxetic acid-enhanced liver MRI.

METHODS

This retrospective single-center study included 168 patients who underwent gadoxetic acid-enhanced liver MRI at 3 T using both standard CAIPIRINHA-VIBE and DL CAIPIRINHA-VIBE techniques on pre-contrast and hepatobiliary phase (HBP) images. Additionally, high-resolution (HR) DL CAIPIRINHA-VIBE was obtained with 1-mm slice thickness on the HBP. Three abdominal radiologists independently assessed the image quality and lesion conspicuity of pre-contrast and HBP images. Statistical analyses involved the Wilcoxon signed-rank test for image quality assessment and the generalized estimation equation for lesion conspicuity and detection evaluation.

RESULTS

DL and HR-DL CAIPIRINHA-VIBE demonstrated significantly improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE (p < 0.001), with a shorter acquisition time (DL vs standard, 11 s vs 17 s). However, the former presented a more synthetic appearance (both p < 0.05). HR-DL CAIPIRINHA-VIBE showed superior lesion conspicuity to standard and DL CAIPIRINHA-VIBE on HBP images (p < 0.001). Moreover, HR-DL CAIPIRINHA-VIBE exhibited a significantly higher detection rate of small (< 2 cm) solid focal liver lesions (FLLs) on HBP images compared to standard CAIPIRINHA-VIBE (92.5% vs 87.4%; odds ratio = 1.83; p = 0.036).

CONCLUSION

DL and HR-DL CAIPIRINHA-VIBE achieved superior image quality compared to standard CAIPIRINHA-VIBE. Additionally, HR-DL CAIPIRINHA-VIBE improved the lesion conspicuity and detection of small solid FLLs. DL and HR-DL CAIPIRINHA-VIBE hold the potential clinical utility for gadoxetic acid-enhanced liver MRI.

CLINICAL RELEVANCE STATEMENT

DL and HR-DL CAIPIRINHA-VIBE hold promise as potential alternatives to standard CAIPIRINHA-VIBE in routine clinical liver MRI, improving the image quality and lesion conspicuity, enhancing the detection of small (< 2 cm) solid focal liver lesions, and reducing the acquisition time.

KEY POINTS

• DL and HR-DL CAIPIRINHA-VIBE demonstrated improved overall image quality and reduced artifacts on pre-contrast and HBP images compared to standard CAIPIRINHA-VIBE, in addition to a shorter acquisition time. • DL and HR-DL CAIPIRINHA-VIBE yielded a more synthetic appearance than standard CAIPIRINHA-VIBE. • HR-DL CAIPIRINHA-VIBE showed improved lesion conspicuity than standard CAIPIRINHA-VIBE on HBP images, with a higher detection of small (< 2 cm) solid focal liver lesions.

High Resolution Multi-delay Arterial Spin Labeling with Transformer based Denoising for Pediatric Perfusion MRI

Multi-delay arterial spin labeling (MDASL) can quantitatively measure cerebral blood flow (CBF) and arterial transit time (ATT), which is particularly suitable for pediatric perfusion imaging. Here we present a high resolution (iso-2mm) MDASL protocol and performed test-retest scans on 21 typically developing children aged 8 to 17 years. We further proposed a Transformer-based deep learning (DL) model with k-space weighted image average (KWIA) denoised images as reference for training the model. The performance of the model was evaluated by the SNR of perfusion images, as well as the SNR, bias and repeatability of the fitted CBF and ATT maps. The proposed method was compared to several benchmark methods including KWIA, joint denoising and reconstruction with total generalized variation (TGV) regularization, as well as directly applying a pretrained Transformer model on a larger dataset. The results show that the proposed Transformer model with KWIA reference can effectively denoise multi-delay ASL images, not only improving the SNR for perfusion images of each delay, but also improving the SNR for the fitted CBF and ATT maps. The proposed method also improved test-retest repeatability of whole-brain perfusion measurements. This may facilitate the use of MDASL in neurodevelopmental studies to characterize typical and aberrant brain development.

Advanced Abdominal MRI Techniques and Problem-Solving Strategies

MRI plays an important role in abdominal imaging because of its ability to detect and characterize focal lesions. However, MRI examinations have several challenges, such as comparatively long scan times and motion management through breath-holding maneuvers. Techniques for reducing scan time with acceptable image quality, such as parallel imaging, compressed sensing, and cutting-edge deep learning techniques, have been developed to enable problem-solving strategies. Additionally, free-breathing techniques for dynamic contrast-enhanced imaging, such as extra-dimensional-volumetric interpolated breath-hold examination, golden-angle radial sparse parallel, and liver acceleration volume acquisition Star, can help patients with severe dyspnea or those under sedation to undergo abdominal MRI. We aimed to present various advanced abdominal MRI techniques for reducing the scan time while maintaining image quality and free-breathing techniques for dynamic imaging and illustrate cases using the techniques mentioned above. A review of these advanced techniques can assist in the appropriate interpretation of sequences.

Comparative review of algorithms and methods for chemical-shift-encoded quantitative fat-water imaging

PURPOSE

To propose a standardized comparison between state-of-the-art open-source fat-water separation algorithms for proton density fat fraction (PDFF) andR 2 * $$ {R}_2^{\ast } $$ quantification using an open-source multi-language toolbox.

METHODS

Eight recent open-source fat-water separation algorithms were compared in silico, in vitro, and in vivo. Multi-echo data were synthesized with varying fat-fractions, B0 off-resonance, SNR and TEs. Experimental evaluation was conducted using calibrated fat-water phantoms acquired at 3T and multi-site open-source phantoms data. Algorithms' performances were observed on challenging in vivo datasets at 3T. Finally, reconstruction algorithms were investigated with different fat spectra to evaluate the importance of the fat model.

RESULTS

In silico and in vitro results proved most algorithms to be not sensitive to fat-water swaps andB 0 $$ {\mathrm{B}}_0 $$ offsets with five or more echoes. However, two methods remained inaccurate even with seven echoes and SNR = 50, and two other algorithms' precision depended on the echo spacing scheme (p < 0.05). The remaining four algorithms provided reliable performances with limits of agreement under 2% for PDFF and 6 s-1 forR 2 * $$ {R}_2^{\ast } $$ . The choice of fat spectrum model influenced quantification of PDFF mildly (<2% bias) and ofR 2 * $$ {R}_2^{\ast } $$ more severely, with errors up to 20 s-1 .

CONCLUSION

In promoting standardized comparisons of MRI-based fat and iron quantification using chemical-shift encoded multi-echo methods, this benchmark work has revealed some discrepancies between recent approaches for PDFF andR 2 * $$ {R}_2^{\ast } $$ mapping. Explicit choices and parameterization of the fat-water algorithm appear necessary for reproducibility. This open-source toolbox further enables the user to optimize acquisition parameters by predicting algorithms' margins of errors.

Accelerated 2D Cartesian MRI with an 8-channel local B0 coil array combined with parallel imaging

PURPOSE

In MRI, the magnetization of nuclear spins is spatially encoded with linear gradients and radiofrequency receivers sensitivity profiles to produce images, which inherently leads to a long scan time. Cartesian MRI, as widely adopted for clinical scans, can be accelerated with parallel imaging and rapid magnetic field modulation during signal readout. Here, by using an 8-channel localB 0 $$ {\mathrm{B}}_0 $$ coil array, the modulation scheme optimized for sampling efficiency is investigated to speed up 2D Cartesian scans.

THEORY AND METHODS

An 8-channel localB 0 $$ {\mathrm{B}}_0 $$ coil array is made to carry sinusoidal currents during signal readout to accelerate 2D Cartesian scans. An MRI sampling theory based on reproducing kernel Hilbert space is exploited to visualize the efficiency of nonlinear encoding in arbitrary sampling duration. A field calibration method using current monitors for localB 0 $$ {\mathrm{B}}_0 $$ coils and the ESPIRiT algorithm is proposed to facilitate image reconstruction. Image acceleration with various modulation field shapes, aliasing control, and distinct modulation frequencies are scrutinized to find an optimized modulation scheme. A safety evaluation is conducted. In vivo 2D Cartesian scans are accelerated by the localB 0 $$ {\mathrm{B}}_0 $$ coils.

RESULTS

For 2D Cartesian MRI, the optimal modulation field by this localB 0 $$ {\mathrm{B}}_0 $$ array converges to a nearly linear gradient field. With the field calibration technique, it accelerates the in vivo scans (i.e., proved safe) by threefold and eightfold free of visible artifacts, without and with SENSE, respectively.

CONCLUSION

The nonlinear encoding analysis tool, the field calibration method, the safety evaluation procedures, and the in vivo reconstructed scans make significant steps to push MRI speed further with the localB 0 $$ {\mathrm{B}}_0 $$ coil array.

A three-dimensional Magnetic Resonance Spin Tomography in Time-domain protocol for high-resolution multiparametric quantitative magnetic resonance imaging

Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) is a multiparametric quantitative MR framework, which allows for simultaneously acquiring quantitative tissue parameters such as T1, T2, and proton density from one single short scan. A typical two-dimensional (2D) MR-STAT acquisition uses a gradient-spoiled, gradient-echo sequence with a slowly varying RF flip-angle train and Cartesian readouts, and the quantitative tissue maps are reconstructed by an iterative, model-based optimization algorithm. In this work, we design a three-dimensional (3D) MR-STAT framework based on previous 2D work, in order to achieve better image signal-to-noise ratio, higher though-plane resolution, and better tissue characterization. Specifically, we design a 7-min, high-resolution 3D MR-STAT sequence, and the corresponding two-step reconstruction algorithm for the large-scale dataset. To reduce the long acquisition time, Cartesian undersampling strategies such as SENSE are adopted in our transient-state quantitative framework. To reduce the computational burden, a data-splitting scheme is designed for decoupling the 3D reconstruction problem into independent 2D reconstructions. The proposed 3D framework is validated by numerical simulations, phantom experiments, and in vivo experiments. High-quality knee quantitative maps with 0.8 × 0.8 × 1.5 mm3 resolution and bilateral lower leg maps with 1.6 mm isotropic resolution can be acquired using the proposed 7-min acquisition sequence and the 3-min-per-slice decoupled reconstruction algorithm. The proposed 3D MR-STAT framework could have wide clinical applications in the future.

Structured low-rank reconstruction for navigator-free water/fat separated multi-shot diffusion-weighted EPI

PURPOSE

Multi-shot diffusion-weighted EPI allows an increase in image resolution and reduced geometric distortions and can be combined with chemical-shift encoding (Dixon) to separate water/fat signals. However, such approaches suffer from physiological motion-induced shot-to-shot phase variations. In this work, a structured low-rank-based navigator-free algorithm is proposed to address the challenge of simultaneously separating water/fat signals and correcting for physiological motion-induced shot-to-shot phase variations in multi-shot EPI-based diffusion-weighted MRI.

THEORY AND METHODS

We propose an iterative, model-based reconstruction pipeline that applies structured low-rank regularization to estimate and eliminate the shot-to-shot phase variations in a data-driven way, while separating water/fat images. The algorithm is tested in different anatomies, including head-neck, knee, brain, and prostate. The performance is validated in simulations and in-vivo experiments in comparison to existing approaches.

RESULTS

In-vivo experiments and simulations demonstrated the effectiveness of the proposed algorithm compared to extra-navigated and an alternative self-navigation approach. The proposed algorithm demonstrates the capability to reconstruct in the multi-shot/Dixon hybrid space domain under-sampled datasets, using the same number of acquired EPI shots compared to conventional fat-suppression techniques but eliminating fat signals through chemical-shift encoding. In addition, partial Fourier reconstruction can also be achieved by using the concept of virtual conjugate coils in conjunction with the proposed algorithm.

CONCLUSION

The proposed algorithm effectively eliminates the shot-to-shot phase variations and separates water/fat images, making it a promising solution for future DWI on different anatomies.

Accelerated Musculoskeletal Magnetic Resonance Imaging

With a substantial growth in the use of musculoskeletal MRI, there has been a growing need to improve MRI workflow, and faster imaging has been suggested as one of the solutions for a more efficient examination process. Consequently, there have been considerable advances in accelerated MRI scanning methods. This article aims to review the basic principles and applications of accelerated musculoskeletal MRI techniques including widely used conventional acceleration methods, more advanced deep learning-based techniques, and new approaches to reduce scan time. Specifically, conventional accelerated MRI techniques, including parallel imaging, compressed sensing, and simultaneous multislice imaging, and deep learning-based accelerated MRI techniques, including undersampled MR image reconstruction, super-resolution imaging, artifact correction, and generation of unacquired contrast images, are discussed. Finally, new approaches to reduce scan time, including synthetic MRI, novel sequences, and new coil setups and designs, are also reviewed. We believe that a deep understanding of these fast MRI techniques and proper use of combined acceleration methods will synergistically improve scan time and MRI workflow in daily practice. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Three-dimensional echo-shifted EPI with simultaneous blip-up and blip-down acquisitions for correcting geometric distortion

PURPOSE

EPI with blip-up/down acquisition (BUDA) can provide high-quality images with minimal distortions by using two readout trains with opposing phase-encoding gradients. Because of the need for two separate acquisitions, BUDA doubles the scan time and degrades the temporal resolution when compared to single-shot EPI, presenting a major challenge for many applications, particularly fMRI. This study aims at overcoming this challenge by developing an echo-shifted EPI BUDA (esEPI-BUDA) technique to acquire both blip-up and blip-down datasets in a single shot.

METHODS

A 3D esEPI-BUDA pulse sequence was designed by using an echo-shifting strategy to produce two EPI readout trains. These readout trains produced a pair of k-space datasets whose k-space trajectories were interleaved with opposite phase-encoding gradient directions. The two k-space datasets were separately reconstructed using a 3D SENSE algorithm, from which time-resolved B0 -field maps were derived using TOPUP in FSL and then input into a forward model of joint parallel imaging reconstruction to correct for geometric distortion. In addition, Hankel structured low-rank constraint was incorporated into the reconstruction framework to improve image quality by mitigating the phase errors between the two interleaved k-space datasets.

RESULTS

The 3D esEPI-BUDA technique was demonstrated in a phantom and an fMRI study on healthy human subjects. Geometric distortions were effectively corrected in both phantom and human brain images. In the fMRI study, the visual activation volumes and their BOLD responses were comparable to those from conventional 3D echo-planar images.

CONCLUSION

The improved imaging efficiency and dynamic distortion correction capability afforded by 3D esEPI-BUDA are expected to benefit many EPI applications.

Ultrafast Brain MRI Protocol at 1.5 T Using Deep Learning and Multi-shot EPI

RATIONALE AND OBJECTIVES

To evaluate clinical feasibility and image quality of a comprehensive ultrafast brain MRI protocol with multi-shot echo planar imaging and deep learning-enhanced reconstruction at 1.5T.

MATERIALS AND METHODS

Thirty consecutive patients who underwent clinically indicated MRI at a 1.5 T scanner were prospectively included. A conventional MRI (c-MRI) protocol, including T1-, T2-, T2*-, T2-FLAIR, and diffusion-weighted images (DWI)-weighted sequences were acquired. In addition, ultrafast brain imaging with deep learning-enhanced reconstruction and multi-shot EPI (DLe-MRI) was performed. Subjective image quality was evaluated by three readers using a 4-point Likert scale. To assess interrater agreement, Fleiss' kappa (ϰ) was determined. For objective image analysis, relative signal intensity levels for grey matter, white matter, and cerebrospinal fluid were calculated.

RESULTS

Time of acquisition (TA) of c-MRI protocols added up to 13:55 minutes, whereas the TA of DLe-MRI-based protocol added up to 3:04 minutes, resulting in a time reduction of 78%. All DLe-MRI acquisitions yielded diagnostic image quality with good absolute values for subjective image quality. C-MRI demonstrated slight advantages for DWI in overall subjective image quality (c-MRI: 3.93 [+/- 0.25] vs DLe-MRI: 3.87 [+/- 0.37], P = .04) and diagnostic confidence (c-MRI: 3.93 [+/- 0.25] vs DLe-MRI: 3.83 [+/- 3.83], P = .01). For most evaluated quality scores, moderate interobserver agreement was found. Objective image evaluation revealed comparable results for both techniques.

CONCLUSION

DLe-MRI is feasible and allows for highly accelerated comprehensive brain MRI within 3minutes at 1.5 T with good image quality. This technique may potentially strengthen the role of MRI in neurological emergencies.

Super-resolution QSM in little or no additional time for imaging (NATIve) using 2D EPI imaging in 3 orthogonal planes

Quantitative Susceptibility Mapping has the potential to provide additional insights into neurological diseases but is typically based on a quite long (5-10 min) 3D gradient-echo scan which is highly sensitive to motion. We propose an ultra-fast acquisition based on three orthogonal (sagittal, coronal and axial) 2D simultaneous multi-slice EPI scans with 1 mm in-plane resolution and 3 mm thick slices. Images in each orientation are corrected for susceptibility-related distortions and co-registered with an iterative non-linear Minimum Deformation Averaging (Volgenmodel) approach to generate a high SNR, super-resolution data set with an isotropic resolution of close to 1 mm. The net acquisition time is 3 times the volume acquisition time of EPI or about 12 s, but the three volumes could also replace "dummy scans" in fMRI, making it feasible to acquire QSM in little or No Additional Time for Imaging (NATIve). NATIve QSM values agreed well with reference 3D GRE QSM in the basal ganglia in healthy subjects. In patients with multiple sclerosis, there was also a good agreement between the susceptibility values within lesions and control ROIs and all lesions which could be seen on 3D GRE QSMs could also be visualized on NATIve QSMs. The approach is faster than conventional 3D GRE by a factor of 25-50 and faster than 3D EPI by a factor of 3-5. As a 2D technique, NATIve QSM was shown to be much more robust to motion than the 3D GRE and 3D EPI, opening up the possibility of studying neurological diseases involving iron accumulation and demyelination in patients who find it difficult to lie still for long enough to acquire QSM data with conventional methods.

Prediction of Stroke Onset Time With Combined Fast High-Resolution Magnetic Resonance Spectroscopic and Quantitative T2 Mapping

OBJECTIVE

The purpose of this work is to develop a multispectral imaging approach that combines fast high-resolution 3D magnetic resonance spectroscopic imaging (MRSI) and fast quantitative T2 mapping to capture the multifactorial biochemical changes within stroke lesions and evaluate its potentials for stroke onset time prediction.

METHODS

Special imaging sequences combining fast trajectories and sparse sampling were used to obtain whole-brain maps of both neurometabolites (2.0 × 3.0 × 3.0 mm3) and quantitative T2 values (1.9 × 1.9 × 3.0 mm3) within a 9-minute scan. Participants with ischemic stroke at hyperacute (0-24 h, n = 23) or acute (24 h-7d, n = 33) phase were recruited in this study. Lesion N-acetylaspartate (NAA), lactate, choline, creatine, and T2 signals were compared between groups and correlated with patient symptomatic duration. Bayesian regression analyses were employed to compare the predictive models of symptomatic duration using multispectral signals.

RESULTS

In both groups, increased T2 and lactate levels, as well as decreased NAA and choline levels were detected within the lesion (all p < 0.001). Changes in T2, NAA, choline, and creatine signals were correlated with symptomatic duration for all patients (all p < 0.005). Predictive models of stroke onset time combining signals from MRSI and T2 mapping achieved the best performance (hyperacute: R2 = 0.438; all: R2 = 0.548).

CONCLUSION

The proposed multispectral imaging approach provides a combination of biomarkers that index early pathological changes after stroke in a clinical-feasible time and improves the assessment of the duration of cerebral infarction.

SIGNIFICANCE

Developing accurate and efficient neuroimaging techniques to provide sensitive biomarkers for prediction of stroke onset time is of great importance for maximizing the proportion of patients eligible for therapeutic intervention. The proposed method provides a clinically feasible tool for the assessment of symptom onset time post ischemic stroke, which will help guide time-sensitive clinical management.

Fetal-placental MR angiography at 1.5 T and 3 T

OBJECTIVES

The objective of this work was to investigate the application of 2D Time-of-Flight (TOF) magnetic resonance angiography (MRA) to observe the placental vasculature at both 1.5 T and 3 T.

METHODS

Fifteen appropriate for gestational age (AGA) (GA: 29.7 ± 3.4 weeks; GA range: 23 and 6/7 weeks to 36 and 2/7 weeks) and eleven patients with an abnormal singleton pregnancy (GA: 31.4 ± 4.4 weeks; GA range: 24 weeks to 35 and 2/7 weeks) were recruited in the study. Three AGA patients were scanned twice at different gestational ages. Patients were scanned either at 3 T or 1.5 T using both T2-HASTE and 2D TOF to image the entire placental vasculature.

RESULTS

The umbilical, chorionic vessels, stem vessels, arcuate arteries, radial arteries, and spiral arteries were shown in most of the subjects. Hyrtl's anastomosis was found in two subjects in the 1.5 T data. The uterine arteries were observed in more than half of the subjects. For those patients scanned twice, the same spiral arteries were identified in both scans.

CONCLUSIONS

2D TOF is a technique that can be applied in studying the fetal-placental vasculature at both 1.5 T and 3 T.

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.

Improved detection of juxtacortical lesions using highly accelerated double inversion-recovery MRI in patients with multiple sclerosis

PURPOSE

The purpose of this study was to compare a highly-accelerated double inversion recovery (fast-DIR) sequence using a recent parallel imaging technique (CAIPIRINHA) with a conventional DIR (conv-DIR) sequence for image quality and the detection of juxtacortical and infratentorial multiple sclerosis (MS) lesions.

MATERIALS AND METHODS

A total of 38 patients with MS who underwent brain MRI at 3 T between 2020 and 2021 were included. There were 27 women and 12 men with a mean age of 40 ± 12.8 (standard deviation) years (range: 20-59 years). All patients underwent conv-DIR sequence and fast-DIR sequence. Fast-DIR was obtained with a T2-preparation module to improve contrast and an iterative denoising algorithm to compensate noise enhancement. Two blinded readers reported the number of juxtacortical and infratentorial MS lesions for fast-DIR and conv-DIR, confirmed by further consensus reading that was used as the standard of reference. Image quality and contrast were evaluated for fast-DIR and conv-DIR sequences. Comparisons between fast-DIR and conv-DIR sequences were performed using Wilcoxon test and Lin concordance correlation coefficient.

RESULTS

Thirty-eight patients were analyzed. Fast-DIR imaging allowed detection of 289 juxtacortical lesions vs. 238 with conv-DIR, corresponding to a significant improved detection rate with fast-DIR (P < 0.001). Conversely, 117 infratentorial lesions were detected with conv-DIR sequence vs. 80 with fast-DIR sequence (P < 0.001). Inter-observer agreement for lesion detection with fast-DIR and conv-DIR was very high (Lin concordance correlation coefficient ranging between 0.86 and 0.96).

CONCLUSION

Fast-DIR improves the detection of juxtacortical MS lesions, but is limited for the detection of infratentorial MS lesions.

Whole-Cerebrum distortion-free three-dimensional pseudo-continuous arterial spin labeling at 7T

Fulfilling potentials of ultrahigh field for pseudo-Continuous Arterial Spin Labeling (pCASL) has been hampered by B1/B0 inhomogeneities that affect pCASL labeling, background suppression (BS), and the readout sequence. This study aimed to present a whole-cerebrum distortion-free three-dimensional (3D) pCASL sequence at 7T by optimizing pCASL labeling parameters, BS pulses, and an accelerated Turbo-FLASH (TFL) readout. A new set of pCASL labeling parameters (Gave = 0.4 mT/m, Gratio = 14.67) was proposed to avoid interferences in bottom slices while achieving robust labeling efficiency (LE). An OPTIM BS pulse was designed based on the range of B1/B0 inhomogeneities at 7T. A 3D TFL readout with 2D-CAIPIRINHA undersampling (R = 2 × 2) and centric ordering was developed, and the number of segments (Nseg) and flip angle (FA) were varied in simulation to achieve the optimal trade-off between SNR and spatial blurring. In-vivo experiments were performed on 19 subjects. The results showed that the new set of labeling parameters effectively achieved whole-cerebrum coverage by eliminating interferences in bottom slices while maintaining a high LE. The OPTIM BS pulse achieved 33.3% higher perfusion signal in gray matter (GM) than the original BS pulse with a cost of 4.8-fold SAR. Incorporating a moderate FA (8°) and Nseg (2), whole-cerebrum 3D TFL-pCASL imaging was achieved with a 2 × 2 × 4 mm3 resolution without distortion and susceptibility artifacts compared to 3D GRASE-pCASL. In addition, 3D TFL-pCASL showed a good to excellent test-retest repeatability and potential of higher resolution (2 mm isotropic). The proposed technique also significantly improved SNR when compared to the same sequence at 3T and simultaneous multislice TFL-pCASL at 7T. By combining a new set of labeling parameters, OPTIM BS pulse, and accelerated 3D TFL readout, we achieved high resolution pCASL at 7T with whole-cerebrum coverage, detailed perfusion and anatomical information without distortion, and sufficient SNR.

Stochastic optimization of three-dimensional non-Cartesian sampling trajectory

PURPOSE

Optimizing three-dimensional (3D) k-space sampling trajectories is important for efficient MRI yet presents a challenging computational problem. This work proposes a generalized framework for optimizing 3D non-Cartesian sampling patterns via data-driven optimization.

METHODS

We built a differentiable simulation model to enable gradient-based methods for sampling trajectory optimization. The algorithm can simultaneously optimize multiple properties of sampling patterns, including image quality, hardware constraints (maximum slew rate and gradient strength), reduced peripheral nerve stimulation (PNS), and parameter-weighted contrast. The proposed method can either optimize the gradient waveform (spline-based freeform optimization) or optimize properties of given sampling trajectories (such as the rotation angle of radial trajectories). Notably, the method can optimize sampling trajectories synergistically with either model-based or learning-based reconstruction methods. We proposed several strategies to alleviate the severe nonconvexity and huge computation demand posed by the large scale. The corresponding code is available as an open-source toolbox.

RESULTS

We applied the optimized trajectory to multiple applications including structural and functional imaging. In the simulation studies, the image quality of a 3D kooshball trajectory was improved from 0.29 to 0.22 (NRMSE) with Stochastic optimization framework for 3D NOn-Cartesian samPling trajectorY (SNOPY) optimization. In the prospective studies, by optimizing the rotation angles of a stack-of-stars (SOS) trajectory, SNOPY reduced the NRMSE of reconstructed images from 1.19 to 0.97 compared to the best empirical method (RSOS-GR). Optimizing the gradient waveform of a rotational EPI trajectory improved participants' rating of the PNS from "strong" to "mild."

CONCLUSION

SNOPY provides an efficient data-driven and optimization-based method to tailor non-Cartesian sampling trajectories.

Highly accelerated intracranial time-of-flight magnetic resonance angiography using wave-encoding

PURPOSE

To develop an accelerated 3D intracranial time-of-flight (TOF) magnetic resonance angiography (MRA) sequence with wave-encoding (referred to as 3D wave-TOF) and to evaluate two variants: wave-controlled aliasing in parallel imaging (CAIPI) and compressed-sensing wave (CS-wave).

METHODS

A wave-TOF sequence was implemented on a 3 T clinical scanner. Wave-encoded and Cartesian k-space datasets from six healthy volunteers were retrospectively and prospectively undersampled with 2D-CAIPI sampling and variable-density Poisson disk sampling. 2D-CAIPI, wave-CAIPI, standard CS, and CS-wave schemes were compared at various acceleration factors. Flow-related artifacts in wave-TOF were investigated, and a set of practicable wave parameters was developed. Quantitative analysis of wave-TOF and traditional Cartesian TOF MRA was performed by comparing the contrast-to-background ratio between the vessel and background tissue in source images, and the structural similarity index measure (SSIM) between the maximum intensity projection images from accelerated acquisitions and their respective fully sampled references.

RESULTS

Flow-related artifacts caused by the wave-encoding gradients in wave-TOF were eliminated by properly chosen parameters. Images from wave-CAIPI and CS-wave acquisitions had a higher SNR and better-preserved contrast than traditional parallel imaging (PI) and CS methods. Maximum intensity projection images from wave-CAIPI and CS-wave acquisitions had a cleaner background, with vessels that were better depicted. Quantitative analyses indicated that wave-CAIPI had the highest contrast-to-background ratio, SSIM, and vessel-masked SSIM among the sampling schemes studied, followed by the CS-wave acquisition.

CONCLUSION

3D wave-TOF improves the capability of accelerated MRA and provides better image quality at higher acceleration factors compared to traditional PI- or CS-accelerated TOF, suggesting the potential use of wave-TOF in cerebrovascular disease.

A review of machine learning applications for the proton MR spectroscopy workflow

This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured overview of the state-of-the-art methods. Specifically, we examine and summarize studies published between 2017 and 2023 from major journals in the MR field. We categorize these studies based on a typical MRS workflow, including data acquisition, processing, analysis, and artificial data generation. Our review reveals that ML in MRS is still in its early stages, with a primary focus on processing and analysis techniques, and less attention given to data acquisition. We also found that many studies use similar model architectures, with little comparison to alternative architectures. Additionally, the generation of artificial data is a crucial topic, with no consistent method for its generation. Furthermore, many studies demonstrate that artificial data suffers from generalization issues when tested on in vivo data. We also conclude that risks related to ML models should be addressed, particularly for clinical applications. Therefore, output uncertainty measures and model biases are critical to investigate. Nonetheless, the rapid development of ML in MRS and the promising results from the reviewed studies justify further research in this field.

Acquisition sequences and reconstruction methods for fast chemical exchange saturation transfer imaging

Chemical exchange saturation transfer (CEST) imaging is an emerging molecular magnetic resonance imaging (MRI) technique that has been developed and employed in numerous diseases. Based on the unique saturation transfer principle, a family of CEST-detectable biomolecules in vivo have been found capable of providing valuable diagnostic information. However, CEST MRI needs a relatively long scan time due to the common long saturation labeling module and typical acquisition of multiple frequency offsets and signal averages, limiting its widespread clinical applications. So far, a plethora of imaging schemes and techniques has been developed to accelerate CEST MRI. In this review, the key acquisition and reconstruction methods for fast CEST imaging are summarized from a practical and systematic point of view. The first acquisition sequence section describes the major development of saturation schemes, readout patterns, ultrafast z-spectroscopy, and saturation-editing techniques for rapid CEST imaging. The second reconstruction method section lists the important advances of parallel imaging, compressed sensing, sparsity in the z-spectrum, and algorithms beyond the Fourier transform for speeding up CEST MRI.

3D-EPI blip-up/down acquisition (BUDA) with CAIPI and joint Hankel structured low-rank reconstruction for rapid distortion-free high-resolution T 2 * mapping

PURPOSE

This work aims to develop a novel distortion-free 3D-EPI acquisition and image reconstruction technique for fast and robust, high-resolution, whole-brain imaging as well as quantitativeT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping.

METHODS

3D Blip-up and -down acquisition (3D-BUDA) sequence is designed for both single- and multi-echo 3D gradient recalled echo (GRE)-EPI imaging using multiple shots with blip-up and -down readouts to encode B0 field map information. Complementary k-space coverage is achieved using controlled aliasing in parallel imaging (CAIPI) sampling across the shots. For image reconstruction, an iterative hard-thresholding algorithm is employed to minimize the cost function that combines field map information informed parallel imaging with the structured low-rank constraint for multi-shot 3D-BUDA data. Extending 3D-BUDA to multi-echo imaging permitsT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping. For this, we propose constructing a joint Hankel matrix along both echo and shot dimensions to improve the reconstruction.

RESULTS

Experimental results on in vivo multi-echo data demonstrate that, by performing joint reconstruction along with both echo and shot dimensions, reconstruction accuracy is improved compared to standard 3D-BUDA reconstruction. CAIPI sampling is further shown to enhance image quality. ForT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping, parameter values from 3D-Joint-CAIPI-BUDA and reference multi-echo GRE are within limits of agreement as quantified by Bland-Altman analysis.

CONCLUSIONS

The proposed technique enables rapid 3D distortion-free high-resolution imaging andT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping. Specifically, 3D-BUDA enables 1-mm isotropic whole-brain imaging in 22 s at 3T and 9 s on a 7T scanner. The combination of multi-echo 3D-BUDA with CAIPI acquisition and joint reconstruction enables distortion-free whole-brainT 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping in 47 s at 1.1 × 1.1 × 1.0 mm3 resolution.

Whole-Cerebrum distortion-free three-dimensional pseudo-Continuous Arterial Spin Labeling at 7T

Fulfilling potentials of ultrahigh field for pseudo-Continuous Arterial Spin Labeling (pCASL) has been hampered by B1/B0 inhomogeneities that affect pCASL labeling, background suppression (BS), and the readout sequence. This study aimed to present a whole-cerebrum distortion-free three-dimensional (3D) pCASL sequence at 7T by optimizing pCASL labeling parameters, BS pulses, and an accelerated Turbo-FLASH (TFL) readout. A new set of pCASL labeling parameters (Gave=0.4mT/m, Gratio=14.67) was proposed to avoid interferences in bottom slices while achieving robust labeling efficiency (LE). An OPTIM BS pulse was designed based on the range of B1/B0 inhomogeneities at 7T. A 3D TFL readout with 2D-CAIPIRINHA undersampling (R=2×2) and centric ordering was developed, and the number of segments (Nseg) and flip angle (FA) were varied in simulation to achieve the optimal trade-off between SNR and spatial blurring. In-vivo experiments were performed on 19 subjects. The results showed that the new set of labeling parameters effectively achieved whole-cerebrum coverage by eliminating interferences in bottom slices while maintaining a high LE. The OPTIM BS pulse achieved 33.3% higher perfusion signal in gray matter (GM) than the original BS pulse with a cost of 4.8-fold SAR. Incorporating a moderate FA (8 ° ) and Nseg (2), whole-cerebrum 3D TFL-pCASL imaging was achieved with a 2×2×4 mm 3 resolution without distortion and susceptibility artifacts compared to 3D GRASE-pCASL. In addition, 3D TFL-pCASL showed a good to excellent test-retest repeatability and potential of higher resolution (2 mm isotropic). The proposed technique also significantly improved SNR when compared to the same sequence at 3T and simultaneous multislice TFL-pCASL at 7T. By combining a new set of labeling parameters, OPTIM BS pulse, and accelerated 3D TFL readout, we achieved high resolution pCASL at 7T with whole-cerebrum coverage, detailed perfusion and anatomical information without distortion, and sufficient SNR.

Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T

MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.

Volume-Controlled 19 F MR Ventilation Imaging of Fluorinated Gas

BACKGROUND

¹⁹ F MRI of inhaled gas tracers has developed into a promising tool for pulmonary diagnostics. Prior to clinical use, the intersession repeatability of acquired ventilation parameters must be quantified and maximized.

PURPOSE

To evaluate repeatability of static and dynamic ¹⁹ F ventilation parameters and correlation with predicted forced expiratory volume in 1 second (FEV₁ %pred) with and without inspiratory volume control.

STUDY TYPE

Prospective.

POPULATION

A total of 30 healthy subjects and 26 patients with chronic obstructive pulmonary disease (COPD).

FIELD STRENGTH/SEQUENCE

Three-dimensional (3D) gradient echo pulse sequence with golden-angle stack-of-stars k-space encoding at 1.5 T.

ASSESSMENT

All study participants underwent ¹⁹ F ventilation MRI over eight breaths with inspiratory volume control (w VC) and without inspiratory volume control (w/o VC), which was repeated within 1 week. Ventilated volume percentage (VVP), fractional ventilation (FV), and wash-in time (WI) were computed. Lung function testing was conducted on the first visit.

STATISTICAL TESTS

Correlation between imaging and FEV₁ %pred was measured using Pearson correlation coefficient (r). Differences in imaging parameters between first and second visit were analyzed using paired t-test. Repeatability was quantified using intraclass correlation coefficient (ICC) and coefficient of variation (CoV). Minimum detectable effect size (MDES) was calculated with a power analysis for study size n = 30 and a power of 0.8. All hypotheses were tested with a significance level of 5% two sided.

RESULTS

Strong and moderate linear correlations with FEV₁ %pred for COPD patients were found in almost all imaging parameters. The ICC w VC exceeds the ICC w/o VC for all imaging parameters. CoV was significantly lower w VC for initial VVP in COPD patients, FV, CoV FV, WI and standard deviation (SD) of WI. MDES of all imaging parameters were smaller w VC.

DATA CONCLUSION

¹⁹ F gas wash-in MRI with inspiratory volume control increases the correlation and repeatability of imaging parameters with lung function testing.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Volumetric Evaluation of 3D Multi-Gradient-Echo MRI Data to Assess Whole Liver Iron Distribution by Segmental R2* Analysis: First Experience

PURPOSE

MR transverse relaxation rate R₂* has been shown to be useful for monitoring liver iron overload. A sequence enabling acquisition of the whole liver in a single breath hold is now available, thus allowing volumetric hepatic R₂* distribution studies. We evaluated the feasibility of computer-assisted whole liver segmentation of 3 D multi-gradient-echo MRI data, and compared whole liver R₂* determination to analyzing only a single slice. Also, segmental R₂* differences were studied.

MATERIALS AND METHODS

The liver of 44 patients, investigated by multi-gradient echo MRI at 1.5 T, was segmented and divided into nine segments. Segmental R₂* values were examined for all patients together and with respect to two criteria: average R₂* values, and reason for iron overload. Correlation of single-slice and volumetric data was tested with Spearman's rank test, segmental and group differences were evaluated by analysis of variance.

RESULTS

Whole-liver R₂* values correlated excellent to single slice data (p < 0.001). The lowest R₂* occurred in segment 1 (S1), differences of S1 with regard to other segments were significant in five cases and highly significant in two cases. Patients with high average R₂* showed significant differences between S1 and segments 2, 6, and 7. Disease-related differences with respect to S1 were significant in segments 3 to 5 and 7.

CONCLUSION

Our results suggest inhomogeneous hepatic iron distribution. Low R₂* in S1 may be explained by its special vascularization.

KEY POINTS

· Hepatic R2* distribution is not as homogeneous as previously thought.. · Liver segments might have a functional relevance.. · Segmental and total liver R2* values coincide best in segment 8..

CITATION FORMAT

· Wunderlich AP, Cario H, Kannengießer S et al. Volumetric Evaluation of 3D Multi-Gradient-Echo MRI Data to Assess Whole Liver Iron Distribution by Segmental R2* Analysis: First Experience. Fortschr Röntgenstr 2023; 195: 224 - 233.

Improving robustness of 3D multi-shot EPI by structured low-rank reconstruction of segmented CAIPI sampling for fMRI at 7T

Three-dimensional (3D) encoding methods are increasingly being explored as alternatives to two-dimensional (2D) multi-slice acquisitions in fMRI, particularly in cases where high isotropic resolution is needed. 3D multi-shot EPI acquisition, as the workhorse of 3D fMRI imaging, is susceptible to physiological fluctuations which can induce inter-shot phase variations, and thus reducing the achievable tSNR, negating some of the benefit of 3D encoding. This issue can be particularly problematic at ultra-high fields like 7T, which have more severe off-resonance effects. In this work, we aim to improve the temporal stability of 3D multi-shot EPI at 7T by improving its robustness to inter-shot phase variations. We presented a 3D segmented CAIPI sampling trajectory ("seg-CAIPI") and an improved reconstruction method based on Hankel structured low-rank matrix recovery. Simulation and in-vivo results demonstrate that the combination of the seg-CAIPI sampling scheme and the proposed structured low-rank reconstruction is a promising way to effectively reduce the unwanted temporal variance induced by inter-shot physiological fluctuations, and thus improve the robustness of 3D multi-shot EPI for fMRI.

Clinical Evaluation of Scout Accelerated Motion Estimation and Reduction Technique for 3D MR Imaging in the Inpatient and Emergency Department Settings

BACKGROUND AND PURPOSE

A scout accelerated motion estimation and reduction (SAMER) framework has been developed for efficient retrospective motion correction. The goal of this study was to perform an initial evaluation of SAMER in a series of clinical brain MR imaging examinations.

MATERIALS AND METHODS

Ninety-seven patients who underwent MR imaging in the inpatient and emergency department settings were included in the study. SAMER motion correction was retrospectively applied to an accelerated T1-weighted MPRAGE sequence that was included in brain MR imaging examinations performed with and without contrast. Two blinded neuroradiologists graded images with and without SAMER motion correction on a 5-tier motion severity scale (none = 1, minimal = 2, mild = 3, moderate = 4, severe = 5).

RESULTS

The median SAMER reconstruction time was 1 minute 47 seconds. SAMER motion correction significantly improved overall motion grades across all examinations (P < .005). Motion artifacts were reduced in 28% of cases, unchanged in 64% of cases, and increased in 8% of cases. SAMER improved motion grades in 100% of moderate motion cases and 75% of severe motion cases. Sixty-nine percent of nondiagnostic motion cases (grades 4 and 5) were considered diagnostic after SAMER motion correction. For cases with minimal or no motion, SAMER had negligible impact on the overall motion grade. For cases with mild, moderate, and severe motion, SAMER improved the motion grade by an average of 0.3 (SD, 0.5), 1.1 (SD, 0.3), and 1.1 (SD, 0.8) grades, respectively.

CONCLUSIONS

SAMER improved the diagnostic image quality of clinical brain MR imaging examinations with motion artifacts. The improvement was most pronounced for cases with moderate or severe motion.

Iterative training of robust k-space interpolation networks for improved image reconstruction with limited scan specific training samples

PURPOSE

To evaluate an iterative learning approach for enhanced performance of robust artificial-neural-networks for k-space interpolation (RAKI), when only a limited amount of training data (auto-calibration signals [ACS]) are available for accelerated standard 2D imaging.

METHODS

In a first step, the RAKI model was tailored for the case of limited training data amount. In the iterative learning approach (termed iterative RAKI [iRAKI]), the tailored RAKI model is initially trained using original and augmented ACS obtained from a linear parallel imaging reconstruction. Subsequently, the RAKI convolution filters are refined iteratively using original and augmented ACS extracted from the previous RAKI reconstruction. Evaluation was carried out on 200 retrospectively undersampled in vivo datasets from the fastMRI neuro database with different contrast settings.

RESULTS

For limited training data (18 and 22 ACS lines for R = 4 and R = 5, respectively), iRAKI outperforms standard RAKI by reducing residual artifacts and yields better noise suppression when compared to standard parallel imaging, underlined by quantitative reconstruction quality metrics. Additionally, iRAKI shows better performance than both GRAPPA and standard RAKI in case of pre-scan calibration with varying contrast between training- and undersampled data.

CONCLUSION

RAKI benefits from the iterative learning approach, which preserves the noise suppression feature, but requires less original training data for the accurate reconstruction of standard 2D images thereby improving net acceleration.

Water-Fat Separated T1 Mapping in the Liver and Correlation to Hepatic Fat Fraction

(1) Background: T1 mapping in magnetic resonance imaging (MRI) of the liver has been proposed to estimate liver function or to detect the stage of liver disease, among others. Thus far, the impact of intrahepatic fat on T1 quantification has only been sparsely discussed. Therefore, the aim of this study was to evaluate the potential of water-fat separated T1 mapping of the liver. (2) Methods: A total of 386 patients underwent MRI of the liver at 3 T. In addition to routine imaging techniques, a 3D variable flip angle (VFA) gradient echo technique combined with a two-point Dixon method was acquired to calculate T1 maps from an in-phase (T1_in) and water-only (T1_W) signal. The results were correlated with proton density fat fraction using multi-echo 3D gradient echo imaging (PDFF) and multi-echo single voxel spectroscopy (PDFF_MRS). Using T1_in and T1_W, a novel parameter FF_T1 was defined and compared with PDFF and PDFF_MRS. Furthermore, the value of retrospectively calculated T1_W (T1_W_calc) based on T1_in and PDFF was assessed. Wilcoxon test, Pearson correlation coefficient and Bland-Altman analysis were applied as statistical tools. (3) Results: T1_in was significantly shorter than T1_W and the difference of both T1 values was correlated with PDFF (R = 0.890). FF_T1 was significantly correlated with PDFF (R = 0.930) and PDFF_MRS (R = 0.922) and yielded only minor bias compared to both established PDFF methods (0.78 and 0.21). T1_W and T1_W_calc were also significantly correlated (R = 0.986). (4) Conclusion: T1_W acquired with a water-fat separated VFA technique allows to minimize the influence of fat on liver T1. Alternatively, T1_W can be estimated retrospectively from T1_in and PDFF, if a Dixon technique is not available for T1 mapping.

Simultaneous multi-slice T1 mapping using MOLLI with blipped CAIPIRINHA bSSFP

BACKGROUND

This study evaluates the possibility for replacing conventional 3 slices, 3 breath-holds MOLLI cardiac T1 mapping with single breath-hold 3 simultaneous multi-slice (SMS3) T1 mapping using blipped-CAIPIRINHA SMS-bSSFP MOLLI sequence. As a major drawback, SMS-bSSFP presents unique artefacts arising from side-lobe slice excitations that are explained by imperfect RF modulation rendering and bSSFP low flip angle enhancement. Amplitude-only RF modulation (AM) is proposed to reduce these artefacts in SMS-MOLLI compared to conventional Wong multi-band RF modulation (WM).

MATERIALS AND METHODS

Phantoms and ten healthy volunteers were imaged at 1.5 T using a modified blipped-CAIPIRINHA SMS-bSSFP MOLLI sequence with 3 simultaneous slices. WM-SMS3 and AM-SMS3 were compared to conventional single-slice (SMS1) MOLLI. First, SNR degradation and T1 accuracy were measured in phantoms. Second, artefacts from side-lobe excitations were evaluated in a phantom designed to reproduce fat presence near the heart. Third, the occurrence of these artefacts was observed in volunteers, and their impact on T1 quantification was compared between WM-SMS3 and AM-SMS3 with conventional MOLLI as a reference.

RESULTS

In the phantom, larger slice gaps and slice thicknesses yielded higher SNR. There was no significant difference of T1 values between conventional MOLLI and SMS3-MOLLI (both WM and AM). Positive banding artefacts were identified from fat neighbouring the targeted FOV due to side-lobe excitations from WM and the unique bSSFP signal profile. AM RF pulses reduced these artefacts by 38%. In healthy volunteers, AM-SMS3-MOLLI showed similar artefact reduction compared to WM-SMS3-MOLLI (3 ± 2 vs 5 ± 3 corrupted LV segments out of 16). In-vivo native T1 values obtained from conventional MOLLI and AM-SMS3-MOLLI were equivalent in LV myocardium (SMS1-T1 = 935.5 ± 36.1 ms; AM-SMS3-T1 = 933.8 ± 50.2 ms; P = 0.436) and LV blood pool (SMS1-T1 = 1475.4 ± 35.9 ms; AM-SMS3-T1 = 1452.5 ± 70.3 ms; P = 0.515). Identically, no differences were found between SMS1 and SMS3 postcontrast T1 values in the myocardium (SMS1-T1 = 556.0 ± 19.7 ms; SMS3-T1 = 521.3 ± 28.1 ms; P = 0.626) and the blood (SMS1-T1 = 478 ± 65.1 ms; AM-SMS3-T1 = 447.8 ± 81.5; P = 0.085).

CONCLUSIONS

Compared to WM RF modulation, AM SMS-bSSFP MOLLI was able to reduce side-lobe artefacts considerably, providing promising results to image the three levels of the heart in a single breath hold. However, few artefacts remained even using AM-SMS-bSSFP due to residual RF imperfections. The proposed blipped-CAIPIRINHA MOLLI T1 mapping sequence provides accurate in vivo T1 quantification in line with those obtained with a single slice acquisition.

Artificial Intelligence-Driven Ultra-Fast Superresolution MRI: 10-Fold Accelerated Musculoskeletal Turbo Spin Echo MRI Within Reach

ABSTRACT

Magnetic resonance imaging (MRI) is the keystone of modern musculoskeletal imaging; however, long pulse sequence acquisition times may restrict patient tolerability and access. Advances in MRI scanners, coil technology, and innovative pulse sequence acceleration methods enable 4-fold turbo spin echo pulse sequence acceleration in clinical practice; however, at this speed, conventional image reconstruction approaches the signal-to-noise limits of temporal, spatial, and contrast resolution. Novel deep learning image reconstruction methods can minimize signal-to-noise interdependencies to better advantage than conventional image reconstruction, leading to unparalleled gains in image speed and quality when combined with parallel imaging and simultaneous multislice acquisition. The enormous potential of deep learning-based image reconstruction promises to facilitate the 10-fold acceleration of the turbo spin echo pulse sequence, equating to a total acquisition time of 2-3 minutes for entire MRI examinations of joints without sacrificing spatial resolution or image quality. Current investigations aim for a better understanding of stability and failure modes of image reconstruction networks, validation of network reconstruction performance with external data sets, determination of diagnostic performances with independent reference standards, establishing generalizability to other centers, scanners, field strengths, coils, and anatomy, and building publicly available benchmark data sets to compare methods and foster innovation and collaboration between the clinical and image processing community. In this article, we review basic concepts of deep learning-based acquisition and image reconstruction techniques for accelerating and improving the quality of musculoskeletal MRI, commercially available and developing deep learning-based MRI solutions, superresolution, denoising, generative adversarial networks, and combined strategies for deep learning-driven ultra-fast superresolution musculoskeletal MRI. This article aims to equip radiologists and imaging scientists with the necessary practical knowledge and enthusiasm to meet this exciting new era of musculoskeletal MRI.

A 2D-GRAPPA Algorithm with a Boomerang Kernel for 3D MRI Data Accelerated along Two Phase-Encoding Directions

For the reconstruction of 3D MRI data that are accelerated along the two phase-encoding directions, the 2D-generalized autocalibrating partially parallel acquisitions (GRAPPA) algorithm can be used to estimate the missing data in the k-space. We propose a new boomerang-shaped kernel based on theoretic and systemic analyses of the shape and dimensions of the kernel. The reconstruction efficiency of the 2D-GRAPPA algorithm with the proposed boomerang-shaped kernel (i.e., boomerang kernel (BK)-2D-GRAPPA) was compared with other 2D-GRAPPA algorithms that utilize different types of kernels (i.e., EX-2D-GRAPPA and SK-2D-GRAPPA) based on computer simulation, phantom and in vivo experiments. The proposed method was validated for different sets of ACS lines with acceleration factors from four to eight and various sizes of the kernels. A quantitative analysis was also performed by comparing the normalized root mean squared error (nRMSE) in the images and the undersampled edges. Computer simulation, in vivo and phantom experiments, and the quantitative analysis, showed that the proposed method could reduce aliasing artifacts without reducing the SNRs of the reconstructed images.

Multi-mask self-supervised learning for physics-guided neural networks in highly accelerated magnetic resonance imaging

Self-supervised learning has shown great promise because of its ability to train deep learning (DL) magnetic resonance imaging (MRI) reconstruction methods without fully sampled data. Current self-supervised learning methods for physics-guided reconstruction networks split acquired undersampled data into two disjoint sets, where one is used for data consistency (DC) in the unrolled network, while the other is used to define the training loss. In this study, we propose an improved self-supervised learning strategy that more efficiently uses the acquired data to train a physics-guided reconstruction network without a database of fully sampled data. The proposed multi-mask self-supervised learning via data undersampling (SSDU) applies a holdout masking operation on the acquired measurements to split them into multiple pairs of disjoint sets for each training sample, while using one of these pairs for DC units and the other for defining loss, thereby more efficiently using the undersampled data. Multi-mask SSDU is applied on fully sampled 3D knee and prospectively undersampled 3D brain MRI datasets, for various acceleration rates and patterns, and compared with the parallel imaging method, CG-SENSE, and single-mask SSDU DL-MRI, as well as supervised DL-MRI when fully sampled data are available. The results on knee MRI show that the proposed multi-mask SSDU outperforms SSDU and performs as well as supervised DL-MRI. A clinical reader study further ranks the multi-mask SSDU higher than supervised DL-MRI in terms of signal-to-noise ratio and aliasing artifacts. Results on brain MRI show that multi-mask SSDU achieves better reconstruction quality compared with SSDU. The reader study demonstrates that multi-mask SSDU at R = 8 significantly improves reconstruction compared with single-mask SSDU at R = 8, as well as CG-SENSE at R = 2.

Open-source MR imaging and reconstruction workflow

PURPOSE

This work presents an end-to-end open-source MR imaging workflow. It is highly flexible in rapid prototyping across the whole imaging process and integrates vendor-independent openly available tools. The whole workflow can be shared and executed on different MR platforms. It is also integrated in the JEMRIS simulation framework, which makes it possible to generate simulated data from the same sequence that runs on the MRI scanner using the same pipeline for image reconstruction.

METHODS

MRI sequences can be designed in Python or JEMRIS using the Pulseq framework, allowing simplified integration of new sequence design tools. During the sequence design process, acquisition metadata required for reconstruction is stored in the MR raw data format. Data acquisition is possible on MRI scanners supported by Pulseq and in simulations through JEMRIS. An image reconstruction and postprocessing pipeline was implemented into a Python server that allows real-time processing of data as it is being acquired. The Berkeley Advanced Reconstruction Toolbox is integrated into this framework for image reconstruction. The reconstruction pipeline supports online integration through a vendor-dependent interface.

RESULTS

The flexibility of the workflow is demonstrated with different examples, containing 3D parallel imaging with controlled aliasing in volumetric parallel imaging (CAIPIRINHA) acceleration, spiral imaging, and B₀ mapping. All sequences, data, and the corresponding processing pipelines are publicly available.

CONCLUSION

The proposed workflow is highly flexible and allows integration of advanced tools at all stages of the imaging process. All parts of this workflow are open-source, simplifying collaboration across different MR platforms or sites and improving reproducibility of results.

Wave-Encoded Model-Based Deep Learning for Highly Accelerated Imaging with Joint Reconstruction

A recently introduced model-based deep learning (MoDL) technique successfully incorporates convolutional neural network (CNN)-based regularizers into physics-based parallel imaging reconstruction using a small number of network parameters. Wave-controlled aliasing in parallel imaging (CAIPI) is an emerging parallel imaging method that accelerates imaging acquisition by employing sinusoidal gradients in the phase- and slice/partition-encoding directions during the readout to take better advantage of 3D coil sensitivity profiles. We propose wave-encoded MoDL (wave-MoDL) combining the wave-encoding strategy with unrolled network constraints for highly accelerated 3D imaging while enforcing data consistency. We extend wave-MoDL to reconstruct multicontrast data with CAIPI sampling patterns to leverage similarity between multiple images to improve the reconstruction quality. We further exploit this to enable rapid quantitative imaging using an interleaved look-locker acquisition sequence with T₂ preparation pulse (3D-QALAS). Wave-MoDL enables a 40 s MPRAGE acquisition at 1 mm resolution at 16-fold acceleration. For quantitative imaging, wave-MoDL permits a 1:50 min acquisition for T₁, T₂, and proton density mapping at 1 mm resolution at 12-fold acceleration, from which contrast-weighted images can be synthesized as well. In conclusion, wave-MoDL allows rapid MR acquisition and high-fidelity image reconstruction and may facilitate clinical and neuroscientific applications by incorporating unrolled neural networks into wave-CAIPI reconstruction.

A comparison of multiband and multiband multiecho gradient-echo EPI for task fMRI at 3 T

A multiband (MB) echo-planar imaging (EPI) sequence is compared to a multiband multiecho (MBME) EPI protocol to investigate differences in sensitivity for task functional magnetic resonance imaging (fMRI) at 3 T. Multiecho sampling improves sensitivity in areas where single-echo-EPI suffers from dropouts. However, It requires in-plane acceleration to reduce the echo train length, limiting the slice acceleration factor and the temporal and spatial resolution Data were acquired for both protocols in two sessions 24 h apart using an adapted color-word interference Stroop task. Besides protocol comparison statistically, we performed test-retest reliability across sessions for different protocols and denoising methods. We evaluated the sensitivity of two different echo-combination strategies for MBME-EPI. We examined the performance of three different data denoising approaches: "Standard," "AROMA," and "FIX" for MB and MBME, and assessed whether a specific method is preferable. We consider using an appropriate autoregressive model order within the general linear model framework to correct TR differences between the protocols. The comparison between protocols and denoising methods showed at group level significantly higher mean z-scores and the number of active voxels for MBME in the motor, subcortical and medial frontal cortices. When comparing different echo combinations, our results suggest that a contrast-to-noise ratio weighted echo combination improves sensitivity in MBME compared to simple echo-summation. This study indicates that MBME can be a preferred protocol in task fMRI at spatial resolution (≥2 mm), primarily in medial prefrontal and subcortical areas.

Customized whole brain-covering 3D GRASE in multi-delay pseudo-continuous arterial spin labeling for duplex distinct hemodynamic mapping contrasts of brain tissues and circulation pathways

Gradient and spin echo (GRASE) is widely employed in arterial spin labeling (ASL) as an efficient readout sequence. Hemodynamic parameter mappings of perfusion, such as cerebral blood flow (CBF) and arterial transit time (ATT), can be derived via multi-delay ASL acquisitions. Multi-delay ASL perfusion imaging inevitably suffers limited signal-to-noise ratio (SNR) since a motion-sensitized vessel suppressing module has to be employed to highlight perfusion signals. The present work reveals that in multi-delay ASL, manipulation of GRASE sequence on either planar imaging echo echo train for adjusted spatial resolutions or FSE echo train for modulated extent of T 2-blurring can significantly alter the mapping contrasts among tissues and among cerebral lobes under different pathways of blood circulation, and meanwhile regulates SNR. Four separate multi-delay ASL scans with different echo train designs in 3D whole brain covering GRASE were carried out for healthy subjects to evaluate the variations in regard to the parameter quantifications and SNR. Based on the quantification mappings, the GRASE acquisition with moderate spatial resolution (3.5 × 3.5 × 4 mm3) and segmented k z scheme was recognized for the first time to be recommended for more unambiguous CBF and ATT contrasts between GM and WM in conjunction with more enhanced ATT contrast between anterior and posterior cerebral circulations, with reasonably good SNR. The technical proposal is of great value for the cutting-edge research of a variety of neurological diseases of global concerns.