Fast and reliable quantitative measures of white matter development with magnetic resonance fingerprinting.

Developmental cognitive neuroscience aims to shed light on evolving relationships between brain structure and cognitive development. To this end, quantitative methods that reliably measure individual differences in brain tissue properties are fundamental. Standard qualitative MRI sequences are influenced by scan parameters and hardware-related biases, and also lack physical units, making the analysis of individual differences problematic. In contrast, quantitative MRI can measure physical properties of the tissue but with the cost of long scan durations and sensitivity to motion. This poses a critical limitation for studying young children. Here, we examine the reliability and validity of an efficient quantitative multiparameter mapping method - Magnetic Resonance Fingerprinting (MRF) - in children scanned longitudinally. We focus on T1 values in white matter, since quantitative T1 values are known to primarily reflect myelin content, a key factor in brain development. Forty-nine children aged 8-13y (mean 10.3y ±1.4) completed two scanning sessions 2-4 months apart. In each session, two 2-minute 3D-MRF scans at 1mm isotropic resolution were collected to evaluate the effect of scan duration on image quality and scan-rescan reliability. A separate calibration scan was used to measure B0 inhomogeneity and correct for bias. We examined the impact of scan time and B0 inhomogeneity correction on scan-rescan reliability of values in white matter, by comparing single 2-min and combined two 2-min scans, with and without B0-correction. Whole-brain voxel-based reliability analysis showed that combining two 2-min MRF scans improved reliability (pearson's r=0.87) compared with a single 2-min scan (r=0.84), while B0-correction had no effect on reliability in white matter (r=0.86 and 0.83 4-min vs 2-min). Using diffusion tractography, we delineated MRF-derived T1 profiles along major white matter fiber tracts and found similar or higher reliability for T1 from MRF compared to diffusion parameters (based on a 10-minute dMRI scan). Lastly, we found that T1 values in multiple white matter tracts were significantly correlated with age. In sum, MRF-derived T1 values were highly reliable in a longitudinal sample of children and replicated known age effects. Reliability in white matter was improved by longer scan duration but was not affected by B0-correction, making it a quick and straightforward scan to collect. We propose that MRF provides a promising avenue for acquiring quantitative brain metrics in children and patient populations where scan time and motion are of particular concern.

Phase stabilization with motion compensated diffusion weighted imaging.

PURPOSE: Diffusion encoding gradient waveforms can impart intra-voxel and inter-voxel dephasing owing to bulk motion, limiting achievable signal-to-noise and complicating multishot acquisitions. In this study, we characterize improvements in phase consistency via gradient moment nulling of diffusion encoding waveforms. METHODS: Healthy volunteers received neuro ( N = 10 $$ N=10 $$ ) and cardiac ( N = 10 $$ N=10 $$ ) MRI. Three gradient moment nulling levels were evaluated: compensation for position ( M 0 $$ {M}_0 $$ ), position + velocity ( M 1 $$ {M}_1 $$ ), and position + velocity + acceleration ( M 1 + M 2 $$ {M}_1+{M}_2 $$ ). Three experiments were completed: (Exp-1) Fixed Trigger Delay Neuro DWI; (Exp-2) Mixed Trigger Delay Neuro DWI; and (Exp-3) Fixed Trigger Delay Cardiac DWI. Significant differences ( p < 0 . 05 $$ p<0.05 $$ ) of the temporal phase SD between repeated acquisitions and the spatial phase gradient across a given image were assessed. RESULTS: M 0 $$ {M}_0 $$ moment nulling was a reference for all measures. In Exp-1, temporal phase SD for G z $$ {G}_z $$ diffusion encoding was significantly reduced with M 1 $$ {M}_1 $$ (35% of t-tests) and M 1 + M 2 $$ {M}_1+{M}_2 $$ (68% of t-tests). The spatial phase gradient was reduced in 23% of t-tests for M 1 $$ {M}_1 $$ and 2% of cases for M 1 + M 2 $$ {M}_1+{M}_2 $$ . In Exp-2, temporal phase SD significantly decreased with M 1 + M 2 $$ {M}_1+{M}_2 $$ gradient moment nulling only for G z $$ {G}_z $$ (83% of t-tests), but spatial phase gradient significantly decreased with only M 1 $$ {M}_1 $$ (50% of t-tests). In Exp-3, M 1 + M 2 $$ {M}_1+{M}_2 $$ gradient moment nulling significantly reduced temporal phase SD and spatial phase gradients (100% of t-tests), resulting in less signal attenuation and more accurate ADCs. CONCLUSION: We characterized gradient moment nulling phase consistency for DWI. Using M1 for neuroimaging and M1 + M2 for cardiac imaging minimized temporal phase SDs and spatial phase gradients.

Micron-resolution fiber mapping in histology independent of sample preparation.

Detailed knowledge of the brain's nerve fiber network is crucial for understanding its function in health and disease. However, mapping fibers with high resolution remains prohibitive in most histological sections because state-of-the-art techniques are incompatible with their preparation. Here, we present a micron-resolution light-scattering-based technique that reveals intricate fiber networks independent of sample preparation for extended fields of view. We uncover fiber structures in both label-free and stained, paraffin-embedded and deparaffinized, newly-prepared and archived, animal and human brain tissues - including whole-brain sections from the BigBrain atlas. We identify altered microstructures in demyelination and hippocampal neurodegeneration, and show key advantages over diffusion magnetic resonance imaging, polarization microscopy, and structure tensor analysis. We also reveal structures in non-brain tissues - including muscle, bone, and blood vessels. Our cost-effective, versatile technique enables studies of intricate fiber networks in any type of histological tissue section, offering a new dimension to neuroscientific and biomedical research.

Pre-excitation gradients for eddy current nulled convex optimized diffusion encoding (Pre-ENCODE).

PURPOSE: To evaluate the use of pre-excitation gradients for eddy current-nulled convex optimized diffusion encoding (Pre-ENCODE) to mitigate eddy current-induced image distortions in diffusion-weighted MRI (DWI). METHODS: DWI sequences using monopolar (MONO), ENCODE, and Pre-ENCODE were evaluated in terms of the minimum achievable echo time (TE min $$ {}_{\mathrm{min}} $$ ) and eddy current-induced image distortions using simulations, phantom experiments, and in vivo DWI in volunteers ( N = 6 $$ N=6 $$ ). RESULTS: Pre-ENCODE provided a shorter TE min $$ {}_{\mathrm{min}} $$ than MONO (71.0 ± $$ \pm $$ 17.7ms vs. 77.6 ± $$ \pm $$ 22.9ms) and ENCODE (71.0 ± $$ \pm $$ 17.7ms vs. 86.2 ± $$ \pm $$ 14.2ms) in 100 % $$ \% $$ of the simulated cases for a commercial 3T MRI system with b-values ranging from 500 to 3000 s/mm 2 $$ {}^2 $$ and in-plane spatial resolutions ranging from 1.0 to 3.0mm 2 $$ {}^2 $$ . Image distortion was estimated by intravoxel signal variance between diffusion encoding directions near the phantom edges and was significantly lower with Pre-ENCODE than with MONO (10.1 % $$ \% $$ vs. 22.7 % $$ \% $$ , p = 6 - 5 $$ p={6}^{-5} $$ ) and comparable to ENCODE (10.1 % $$ \% $$ vs. 10.4 % $$ \% $$ , p = 0 . 12 $$ p=0.12 $$ ). In vivo measurements of apparent diffusion coefficients were similar in global brain pixels (0.37 [0.28,1.45] × 1 0 - 3 $$ \times 1{0}^{-3} $$ mm 2 $$ {}^2 $$ /s vs. 0.38 [0.28,1.45] × 1 0 - 3 $$ \times 1{0}^{-3} $$ mm 2 $$ {}^2 $$ /s, p = 0 . 25 $$ p=0.25 $$ ) and increased in edge brain pixels (0.80 [0.17,1.49] × 1 0 - 3 $$ \times 1{0}^{-3} $$ mm 2 $$ {}^2 $$ /s vs. 0.70 [0.18,1.48] × 1 0 - 3 $$ \times 1{0}^{-3} $$ mm 2 $$ {}^2 $$ /s, p = 0 . 02 $$ p=0.02 $$ ) for MONO compared to Pre-ENCODE. CONCLUSION: Pre-ENCODE mitigated eddy current-induced image distortions for diffusion imaging with a shorter TE min $$ {}_{\mathrm{min}} $$ than MONO and ENCODE.

Clinical Evaluation of a 2-Minute Ultrafast Brain MR Protocol for Evaluation of Acute Pathology in the Emergency and Inpatient Settings.

BACKGROUND AND PURPOSE: The use of MR imaging in emergency settings has been limited by availability, long scan times, and sensitivity to motion. This study assessed the diagnostic performance of an ultrafast brain MR imaging protocol for evaluation of acute intracranial pathology in the emergency department and inpatient settings. MATERIALS AND METHODS: Sixty-six adult patients who underwent brain MR imaging in the emergency department and inpatient settings were included in the study. All patients underwent both the reference and the ultrafast brain MR protocols. Both brain MR imaging protocols consisted of T1-weighted, T2/T2*-weighted, FLAIR, and DWI sequences. The ultrafast MR images were reconstructed by using a machine-learning assisted framework. All images were reviewed by 2 blinded neuroradiologists. RESULTS: The average acquisition time was 2.1 minutes for the ultrafast brain MR protocol and 10 minutes for the reference brain MR protocol. There was 98.5% agreement on the main clinical diagnosis between the 2 protocols. In head-to-head comparison, the reference protocol was preferred in terms of image noise and geometric distortion (P < .05 for both). The ultrafast ms-EPI protocol was preferred over the reference protocol in terms of reduced motion artifacts (P < .01). Overall diagnostic quality was not significantly different between the 2 protocols (P > .05). CONCLUSIONS: The ultrafast brain MR imaging protocol provides high accuracy for evaluating acute pathology while only requiring a fraction of the scan time. Although there was greater image noise and geometric distortion on the ultrafast brain MR protocol images, there was significant reduction in motion artifacts with similar overall diagnostic quality between the 2 protocols.

Improved reconstruction for highly accelerated propeller diffusion 1.5 T clinical MRI.

PURPOSE: Propeller fast-spin-echo diffusion magnetic resonance imaging (FSE-dMRI) is essential for the diagnosis of Cholesteatoma. However, at clinical 1.5 T MRI, its signal-to-noise ratio (SNR) remains relatively low. To gain sufficient SNR, signal averaging (number of excitations, NEX) is usually used with the cost of prolonged scan time. In this work, we leveraged the benefits of Locally Low Rank (LLR) constrained reconstruction to enhance the SNR. Furthermore, we enhanced both the speed and SNR by employing Convolutional Neural Networks (CNNs) for the accelerated PROPELLER FSE-dMRI on a 1.5 T clinical scanner. METHODS: Residual U-Net (RU-Net) was found to be efficient for propeller FSE-dMRI data. It was trained to predict 2-NEX images obtained by Locally Low Rank (LLR) constrained reconstruction and used 1-NEX images obtained via simplified reconstruction as the inputs. The brain scans from healthy volunteers and patients with cholesteatoma were performed for model training and testing. The performance of trained networks was evaluated with normalized root-mean-square-error (NRMSE), structural similarity index measure (SSIM), and peak SNR (PSNR). RESULTS: For 4 × under-sampled with 7 blades data, online reconstruction appears to provide suboptimal images-some small details are missing due to high noise interferences. Offline LLR enables suppression of noises and discovering some small structures. RU-Net demonstrated further improvement compared to LLR by increasing 18.87% of PSNR, 2.11% of SSIM, and reducing 53.84% of NRMSE. Moreover, RU-Net is about 1500 × faster than LLR (0.03 vs. 47.59 s/slice). CONCLUSION: The LLR remarkably enhances the SNR compared to online reconstruction. Moreover, RU-Net improves propeller FSE-dMRI as reflected in PSNR, SSIM, and NRMSE. It requires only 1-NEX data, which allows a 2 × scan time reduction. In addition, its speed is approximately 1500 times faster than that of LLR-constrained reconstruction.

Rapid and accurate navigators for motion and B0 tracking using QUEEN: Quantitatively enhanced parameter estimation from navigators.

PURPOSE: To develop a framework that jointly estimates rigid motion and polarizing magnetic field (B0 ) perturbations ( δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ ) for brain MRI using a single navigator of a few milliseconds in duration, and to additionally allow for navigator acquisition at arbitrary timings within any type of sequence to obtain high-temporal resolution estimates. THEORY AND METHODS: Methods exist that match navigator data to a low-resolution single-contrast image (scout) to estimate either motion or δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ . In this work, called QUEEN (QUantitatively Enhanced parameter Estimation from Navigators), we propose combined motion and δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ estimation from a fast, tailored trajectory with arbitrary-contrast navigator data. To this end, the concept of a quantitative scout (Q-Scout) acquisition is proposed from which contrast-matched scout data is predicted for each navigator. Finally, navigator trajectories, contrast-matched scout, and δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ are integrated into a motion-informed parallel-imaging framework. RESULTS: Simulations and in vivo experiments show the need to model δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ to obtain accurate motion parameters estimated in the presence of strong δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ . Simulations confirm that tailored navigator trajectories are needed to robustly estimate both motion and δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ . Furthermore, experiments show that a contrast-matched scout is needed for parameter estimation from multicontrast navigator data. A retrospective, in vivo reconstruction experiment shows improved image quality when using the proposed Q-Scout and QUEEN estimation. CONCLUSIONS: We developed a framework to jointly estimate rigid motion parameters and δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ from navigators. Combing a contrast-matched scout with the proposed trajectory allows for navigator deployment in almost any sequence and/or timing, which allows for higher temporal-resolution motion and δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ estimates.

DTI-MR fingerprinting for rapid high-resolution whole-brain T1 , T2 , proton density, ADC, and fractional anisotropy mapping.

PURPOSE: This study aims to develop a high-efficiency and high-resolution 3D imaging approach for simultaneous mapping of multiple key tissue parameters for routine brain imaging, including T1 , T2 , proton density (PD), ADC, and fractional anisotropy (FA). The proposed method is intended for pushing routine clinical brain imaging from weighted imaging to quantitative imaging and can also be particularly useful for diffusion-relaxometry studies, which typically suffer from lengthy acquisition time. METHODS: To address challenges associated with diffusion weighting, such as shot-to-shot phase variation and low SNR, we integrated several innovative data acquisition and reconstruction techniques. Specifically, we used M1-compensated diffusion gradients, cardiac gating, and navigators to mitigate phase variations caused by cardiac motion. We also introduced a data-driven pre-pulse gradient to cancel out eddy currents induced by diffusion gradients. Additionally, to enhance image quality within a limited acquisition time, we proposed a data-sharing joint reconstruction approach coupled with a corresponding sequence design. RESULTS: The phantom and in vivo studies indicated that the T1 and T2 values measured by the proposed method are consistent with a conventional MR fingerprinting sequence and the diffusion results (including diffusivity, ADC, and FA) are consistent with the spin-echo EPI DWI sequence. CONCLUSION: The proposed method can achieve whole-brain T1 , T2 , diffusivity, ADC, and FA maps at 1-mm isotropic resolution within 10 min, providing a powerful tool for investigating the microstructural properties of brain tissue, with potential applications in clinical and research settings.

High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting.

PURPOSE: This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time. METHODS: We developed 3D visualization of short transverse relaxation time component (ViSTa)-MRF, which combined ViSTa technique with MR fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multicompartment fitting that could introduce bias and/or noise from additional assumptions or priors. RESULTS: The in vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in vivo results of 1 mm- and 0.66 mm-isotropic resolution datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30× slower with lower SNR. Furthermore, we applied the proposed method to enable 5-min whole-brain 1 mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples. CONCLUSIONS: In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1 and 0.66 mm isotropic resolution in 5 and 15 min, respectively. This advancement allows for quantitative investigations of myelination changes in the brain.

Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla.

To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

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.

Deep Learning Initialized Compressed Sensing (Deli-CS) in Volumetric Spatio-Temporal Subspace Reconstruction.

Introduction: Spatio-temporal MRI methods enable whole-brain multi-parametric mapping at ultra-fast acquisition times through efficient k-space encoding, but can have very long reconstruction times, which limit their integration into clinical practice. Deep learning (DL) is a promising approach to accelerate reconstruction, but can be computationally intensive to train and deploy due to the large dimensionality of spatio-temporal MRI. DL methods also need large training data sets and can produce results that don't match the acquired data if data consistency is not enforced. The aim of this project is to reduce reconstruction time using DL whilst simultaneously limiting the risk of deep learning induced hallucinations, all with modest hardware requirements. Methods: Deep Learning Initialized Compressed Sensing (Deli-CS) is proposed to reduce the reconstruction time of iterative reconstructions by "kick-starting" the iterative reconstruction with a DL generated starting point. The proposed framework is applied to volumetric multi-axis spiral projection MRF that achieves whole-brain T1 and T2 mapping at 1-mm isotropic resolution for a 2-minute acquisition. First, the traditional reconstruction is optimized from over two hours to less than 40 minutes while using more than 90% less RAM and only 4.7 GB GPU memory, by using a memory-efficient GPU implementation. The Deli-CS framework is then implemented and evaluated against the above reconstruction. Results: Deli-CS achieves comparable reconstruction quality with 50% fewer iterations bringing the full reconstruction time to 20 minutes. Conclusion: Deli-CS reduces the reconstruction time of subspace reconstruction of volumetric spatio-temporal acquisitions by providing a warm start to the iterative reconstruction algorithm.

High-resolution motion- and phase-corrected functional MRI at 7 T using shuttered multishot echo-planar imaging.

PURPOSE: To achieve high-resolution multishot echo-planar imaging (EPI) for functional MRI (fMRI) with reduced sensitivity to in-plane motion and between-shot phase variations. METHODS: Two-dimensional radiofrequency pulses were incorporated in a multishot EPI sequence at 7T which selectively excited a set of in-plane bands (shutters) in the phase encoding direction, which moved between shots to cover the entire slice. A phase- and motion-corrected reconstruction was implemented for the acquisition. Brain imaging experiments were performed with instructed motion to evaluate image quality for conventional multishot and shuttered EPI. Temporal stability was assessed in three subjects by quantifying temporal SNR (tSNR) and artifact levels, and fMRI activation experiments using visual stimulation were performed to assess the strength and distribution of activation, using both conventional multishot and shuttered EPI. RESULTS: In the instructed motion experiment, ghosting was lower in shuttered EPI images without or with corrections and image quality metrics were improved with motion correction. tSNR was improved by phase correction in both conventional multishot and shuttered EPI and the acquisitions had similar tSNR without and with phase correction. However, while phase correction was necessary to maximize tSNR in conventional multishot EPI, it also increased intermittent ghosting, but did not increase intermittent ghosting in shuttered EPI. Phase correction increased activation strength in both conventional multishot and shuttered EPI, but caused increased spurious activation outside the brain and in frontal brain regions in conventional multishot EPI. CONCLUSION: Shuttered EPI supports multishot segmented EPI acquisitions with lower sensitivity to artifacts from motion for high-resolution fMRI.

Validation of a highly accelerated post-contrast wave-controlled aliasing in parallel imaging (CAIPI) 3D-T1 MPRAGE compared to standard 3D-T1 MPRAGE for detection of intracranial enhancing lesions on 3-T MRI.

OBJECTIVES: High-resolution post-contrast T1-weighted imaging is a workhorse sequence in the evaluation of neurological disorders. The T1-MPRAGE sequence has been widely adopted for the visualization of enhancing pathology in the brain. However, this three-dimensional (3D) acquisition is lengthy and prone to motion artifact, which often compromises diagnostic quality. The goal of this study was to compare a highly accelerated wave-controlled aliasing in parallel imaging (CAIPI) post-contrast 3D T1-MPRAGE sequence (Wave-T1-MPRAGE) with the standard 3D T1-MPRAGE sequence for visualizing enhancing lesions in brain imaging at 3 T. METHODS: This study included 80 patients undergoing contrast-enhanced brain MRI. The participants were scanned with a standard post-contrast T1-MPRAGE sequence (acceleration factor [R] = 2 using GRAPPA parallel imaging technique, acquisition time [TA] = 5 min 18 s) and a prototype post-contrast Wave-T1-MPRAGE sequence (R = 4, TA = 2 min 32 s). Two neuroradiologists performed a head-to-head evaluation of both sequences and rated the visualization of enhancement, sharpness, noise, motion artifacts, and overall diagnostic quality. A 15% noninferiority margin was used to test whether post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE. Inter-rater and intra-rater agreement were calculated. Quantitative assessment of CNR/SNR was performed. RESULTS: Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE for delineating enhancing lesions with unanimous agreement in all cases between raters. Wave-T1-MPRAGE was noninferior in the perception of noise (p < 0.001), motion artifact (p < 0.001), and overall diagnostic quality (p < 0.001). CONCLUSION: High-accelerated post-contrast Wave-T1-MPRAGE enabled a two-fold reduction in acquisition time compared to the standard sequence with comparable performance for visualization of enhancing pathology and equivalent perception of noise, motion artifacts and overall diagnostic quality without loss of clinically important information. KEY POINTS: • Post-contrast wave-controlled aliasing in parallel imaging (CAIPI) T1-MPRAGE accelerated the acquisition of three-dimensional (3D) high-resolution post-contrast images by more than two-fold. • Post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE with unanimous agreement between reviewers (100% in 80 cases) for the visualization of intracranial enhancing lesions. • Wave-T1-MPRAGE was equivalent to the standard sequence in the perception of noise in 94% (75 of 80) of cases and was preferred in 16% (13 of 80) of cases for decreased motion artifact.

High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting.

Purpose: This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time. Methods: We developed 3D ViSTa-MRF, which combined Visualization of Short Transverse relaxation time component (ViSTa) technique with MR Fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multi-compartment fitting that could introduce bias and/or noise from additional assumptions or priors. Results: The in-vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in-vivo results of 1mm- and 0.66mm-iso datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30x slower with lower SNR. Furthermore, we applied the proposed method to enable 5-minute whole-brain 1mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples. Conclusions: In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1mm and 0.66mm isotropic resolution in 5 and 15 minutes, respectively. This advancement allows for quantitative investigations of myelination changes in the brain.

Sequence adaptive field-imperfection estimation (SAFE): retrospective estimation and correction of $B_1

$B_1^+$ and $B_0$ field-inhomogeneities can significantly reduce accuracy and robustness of MRF's quantitative parameter estimates. Additional $B_1^+$ and $B_0$ calibration scans can mitigate this but add scan time and cannot be applied retrospectively to previously collected data. Here, we proposed a calibration-free sequence-adaptive deep-learning framework, to estimate and correct for $B_1^+$ and $B_0$ effects of any MRF sequence. We demonstrate its capability on arbitrary MRF sequences at 3T, where no training data were previously obtained. Such approach can be applied to any previously-acquired and future MRF-scans. The flexibility in directly applying this framework to other quantitative sequences is also highlighted.

Optimal deep brain stimulation sites and networks for stimulation of the fornix in Alzheimer's disease.

Deep brain stimulation (DBS) to the fornix is an investigational treatment for patients with mild Alzheimer's Disease. Outcomes from randomized clinical trials have shown that cognitive function improved in some patients but deteriorated in others. This could be explained by variance in electrode placement leading to differential engagement of neural circuits. To investigate this, we performed a post-hoc analysis on a multi-center cohort of 46 patients with DBS to the fornix (NCT00658125, NCT01608061). Using normative structural and functional connectivity data, we found that stimulation of the circuit of Papez and stria terminalis robustly associated with cognitive improvement (R = 0.53, p < 0.001). On a local level, the optimal stimulation site resided at the direct interface between these structures (R = 0.48, p < 0.001). Finally, modulating specific distributed brain networks related to memory accounted for optimal outcomes (R = 0.48, p < 0.001). Findings were robust to multiple cross-validation designs and may define an optimal network target that could refine DBS surgery and programming.

Clinical validation of Wave-CAIPI susceptibility-weighted imaging for routine brain MRI at 1.5 T.

OBJECTIVES: Wave-CAIPI (Controlled Aliasing in Parallel Imaging) enables dramatic reduction in acquisition time of 3D MRI sequences such as 3D susceptibility-weighted imaging (SWI) but has not been clinically evaluated at 1.5 T. We sought to compare highly accelerated Wave-CAIPI SWI (Wave-SWI) with two alternative standard sequences, conventional three-dimensional SWI and two-dimensional T2*-weighted Gradient-Echo (T2*w-GRE), in patients undergoing routine brain MRI at 1.5 T. METHODS: In this study, 172 patients undergoing 1.5 T brain MRI were scanned with a more commonly used susceptibility sequence (standard SWI or T2*w-GRE) and a highly accelerated Wave-SWI sequence. Two radiologists blinded to the acquisition technique scored each sequence for visualization of pathology, motion and signal dropout artifacts, image noise, visualization of normal anatomy (vessels and basal ganglia mineralization), and overall diagnostic quality. Superiority testing was performed to compare Wave-SWI to T2*w-GRE, and non-inferiority testing with 15% margin was performed to compare Wave-SWI to standard SWI. RESULTS: Wave-SWI performed superior in terms of visualization of pathology, signal dropout artifacts, visualization of normal anatomy, and overall image quality when compared to T2*w-GRE (all p < 0.001). Wave-SWI was non-inferior to standard SWI for visualization of normal anatomy and pathology, signal dropout artifacts, and overall image quality (all p < 0.001). Wave-SWI was superior to standard SWI for motion artifact (p < 0.001), while both conventional susceptibility sequences were superior to Wave-SWI for image noise (p < 0.001). CONCLUSIONS: Wave-SWI can be performed in a 1.5 T clinical setting with robust performance and preservation of diagnostic quality. KEY POINTS: • Wave-SWI accelerated the acquisition of 3D high-resolution susceptibility images in 70% of the acquisition time of the conventional T2*GRE. • Wave-SWI performed superior to T2*w-GRE for visualization of pathology, signal dropout artifacts, and overall diagnostic image quality. • Wave-SWI was noninferior to standard SWI for visualization of normal anatomy and pathology, signal dropout artifacts, and overall diagnostic image quality.

Highly accelerated EPI with wave encoding and multi-shot simultaneous multislice imaging.

PURPOSE: To introduce wave-encoded acquisition and reconstruction techniques for highly accelerated EPI with reduced g-factor penalty and image artifacts. THEORY AND METHODS: Wave-EPI involves application of sinusoidal gradients during the EPI readout, which spreads the aliasing in all spatial directions, thereby taking better advantage of 3D coil sensitivity profiles. The amount of voxel spreading that can be achieved by the wave gradients during the short EPI readout period is constrained by the slew rate of the gradient coils and peripheral nerve stimulation monitor. We propose to use a "half-cycle" sinusoidal gradient to increase the amount of voxel spreading that can be achieved while respecting the slew and stimulation constraints. Extending wave-EPI to multi-shot acquisition minimizes geometric distortion and voxel blurring at high in-plane resolutions, while structured low-rank regularization mitigates shot-to-shot phase variations. To address gradient imperfections, we propose to use different point spread functions for the k-space lines with positive and negative polarities, which are calibrated with a FLEET-based reference scan. RESULTS: Wave-EPI enabled whole-brain single-shot gradient-echo (GE) and multi-shot spin-echo (SE) EPI acquisitions at high acceleration factors at 3T and was combined with g-Slider encoding to boost the SNR level in 1 mm isotropic diffusion imaging. Relative to blipped-CAIPI, wave-EPI reduced average and maximum g-factors by up to 1.21- and 1.37-fold at Rin × Rsms  = 3 × 3, respectively. CONCLUSION: Wave-EPI allows highly accelerated single- and multi-shot EPI with reduced g-factor and artifacts and may facilitate clinical and neuroscientific applications of EPI by improving the spatial and temporal resolution in functional and diffusion imaging.