Interrogation of the dynamic properties of higher-order heterochromatin using CRISPR-dCas9.

Eukaryotic chromosomes feature large regions of compact, repressed heterochromatin hallmarked by Heterochromatin Protein 1 (HP1). HP1 proteins play multi-faceted roles in shaping heterochromatin, and in cells, HP1 tethering to individual gene promoters leads to epigenetic modifications and silencing. However, emergent properties of HP1 at supranucleosomal scales remain difficult to study in cells because of a lack of appropriate tools. Here, we develop CRISPR-engineered chromatin organization (EChO), combining live-cell CRISPR imaging with inducible large-scale recruitment of chromatin proteins to native genomic targets. We demonstrate that human HP1α tiled across kilobase-scale genomic DNA form novel contacts with natural heterochromatin, integrates two distantly targeted regions, and reversibly changes chromatin from a diffuse to compact state. The compact state exhibits delayed disassembly kinetics and represses transcription across over 600 kb. These findings support a polymer model of HP1α-mediated chromatin regulation and highlight the utility of CRISPR-EChO in studying supranucleosomal chromatin organization in living cells.

Multidimensional high-harmonic echo spectroscopy: Resolving coherent electron dynamics in the EUV regime.

We theoretically propose a multidimensional high-harmonic echo spectroscopy technique which utilizes strong optical fields to resolve coherent electron dynamics spanning an energy range of multiple electronvolts. Using our recently developed semi-perturbative approach, we can describe the coherent valence electron dynamics driven by a sequence of phase-matched and well-separated short few-cycle strong infrared laser pulses. The recombination of tunnel-ionized electrons by each pulse coherently populates the valence states of a molecule, which allows for a direct observation of its dynamics via the high harmonic echo signal. The broad bandwidth of the effective dipole between valence states originated from the strong-field excitation results in nontrivial ultra-delayed partial rephasing echo, which is not observed in standard two-dimensional optical spectroscopic techniques in a two-level molecular systems. We demonstrate the results of simulations for the anionic molecular system and show that the ultrafast valence electron dynamics can be well captured with femtosecond resolution.

Rapid basal melting of the Greenland Ice Sheet from surface meltwater drainage.

Subglacial hydrologic systems regulate ice sheet flow, causing acceleration or deceleration, depending on hydraulic efficiency and the rate at which surface meltwater is delivered to the bed. Because these systems are rarely observed, ice sheet basal drainage represents a poorly integrated and uncertain component of models used to predict sea level changes. Here, we report radar-derived basal melt rates and unexpectedly warm subglacial conditions beneath a large Greenlandic outlet glacier. The basal melt rates averaged 14 mm ⋅d-1 over 4 months, peaking at 57 mm ⋅d-1 when basal water temperature reached +0.88 ∘C in a nearby borehole. We attribute both observations to the conversion of potential energy of surface water to heat in the basal drainage system, which peaked during a period of rainfall and intense surface melting. Our findings reveal limitations in the theory of channel formation, and we show that viscous dissipation far surpasses other basal heat sources, even in a distributed, high-pressure system.

Decomposing predictability to identify dominant causal drivers in complex ecosystems.

Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of different levels of stochasticity and nonlinearity, handling these data is a challenge for existing methods of time series-based causal inferences. Here, we show that, by harnessing contemporary machine learning approaches, the concept of Granger causality can be effectively extended to the analysis of complex ecosystem time series and bridge the gap between dynamical and statistical approaches. The central idea is to use an ensemble of fast and highly predictive artificial neural networks to select a minimal set of variables that maximizes the prediction of a given variable. It enables decomposition of the relationship among variables through quantifying the contribution of an individual variable to the overall predictive performance. We show how our approach, EcohNet, can improve interaction network inference for a mesocosm experiment and simulated ecosystems. The application of the method to a long-term lake monitoring dataset yielded interpretable results on the drivers causing cyanobacteria blooms, which is a serious threat to ecological integrity and ecosystem services. Since performance of EcohNet is enhanced by its predictive capabilities, it also provides an optimized forecasting of overall components in ecosystems. EcohNet could be used to analyze complex and hybrid multivariate time series in many scientific areas not limited to ecosystems.

Whole brain multiparametric mapping in two minutes using a dual-flip-angle stack-of-stars blipped multi-gradient-echo acquisition.

A new MRI technique is presented for three-dimensional fast simultaneous whole brain mapping of myelin water fraction (MWF), T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+). Phantom and human (N = 9) datasets were acquired using a dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory. Images were reconstructed using a subspace-based algorithm with a locally low-rank constraint. A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation (JMSE) algorithm is proposed to correct for the T1 saturation effect and B1+/B1- inhomogeneities in the quantification of MWF. A tissue-prior-based B1+ estimation algorithm was adapted for B1 correction in the mapping of T1 and PD. In the phantom study, measurements obtained at an acceleration factor (R) of 12 using prospectively under-sampled SOS showed good consistency (R2 > 0.997) with Cartesian reference for R2*/T1app/M0app. In the in vivo study, results of retrospectively under-sampled SOS with R = 6, 12, 18, showed good quality (structure similarity index measure > 0.95) compared with those of fully-sampled SOS. Besides, results of prospectively under-sampled SOS with R = 12 showed good consistency (intraclass correlation coefficient > 0.91) with Cartesian reference for T1/PD/B1+/MWF/QSM/R2*, and good reproducibility (coefficient of variation < 7.0 %) in the test-retest analysis for T1/PD/B1+/MWF/R2*. This study has demonstrated the feasibility of simultaneous whole brain multiparametric mapping with a two-minute scan using the DFA-mGRE SOS sequence, which may overcome a major obstacle for neurological applications of multiparametric MRI.

Vessel density mapping of small cerebral vessels on 3D high resolution black blood MRI.

Small cerebral blood vessels are largely inaccessible to existing clinical in vivo imaging technologies. This study aims to present a novel analysis pipeline for vessel density mapping of small cerebral blood vessels from high-resolution 3D black-blood MRI at 3T. Twenty-eight subjects (10 under 35 years old, 18 over 60 years old) were imaged with the T1-weighted turbo spin-echo with variable flip angles (T1w TSE-VFA) sequence optimized for black-blood small vessel imaging with iso-0.5 mm spatial resolution (interpolated from 0.51×0.51×0.64 mm3) at 3T. Hessian-based vessel segmentation methods (Jerman, Frangi and Sato filter) were evaluated by vessel landmarks and manual annotation of lenticulostriate arteries (LSAs). Using optimized vessel segmentation, large vessel pruning and non-linear registration, a semiautomatic pipeline was proposed for quantification of small vessel density across brain regions and further for localized detection of small vessel changes across populations. Voxel-level statistics was performed to compare vessel density between two age groups. Additionally, local vessel density of aged subjects was correlated with their corresponding gross cognitive and executive function (EF) scores using Montreal Cognitive Assessment (MoCA) and EF composite scores compiled with Item Response Theory (IRT). Jerman filter showed better performance for vessel segmentation than Frangi and Sato filter which was employed in our pipeline. Small cerebral blood vessels including small artery, arterioles, small veins, and venules on the order of a few hundred microns can be delineated using the proposed analysis pipeline on 3D black-blood MRI at 3T. The mean vessel density across brain regions was significantly higher in young subjects compared to aged subjects. In the aged subjects, localized vessel density was positively correlated with MoCA and IRT EF scores. The proposed pipeline is able to segment, quantify, and detect localized differences in vessel density of small cerebral blood vessels based on 3D high-resolution black-blood MRI. This framework may serve as a tool for localized detection of small vessel density changes in normal aging and cerebral small vessel disease.

Precision mapping of the default network reveals common and distinct (inter) activity for autobiographical memory and theory of mind.

The default network is widely implicated as a common neural substrate for self-generated thought, such as remembering one's past (autobiographical memory) and imagining the thoughts and feelings of others (theory of mind). Findings that the default network comprises subnetworks of regions, some commonly and some distinctly involved across processes, suggest that one's own experiences inform their understanding of others. With the advent of precision functional MRI (fMRI) methods, however, it is unclear if this shared substrate is observed instead due to traditional group analysis methods. We investigated this possibility using a novel combination of methodological strategies. Twenty-three participants underwent multi-echo resting-state and task fMRI. We used their resting-state scans to conduct cortical parcellation sensitive to individual variation while preserving our ability to conduct group analysis. Using multivariate analyses, we assessed the functional activation and connectivity profiles of default network regions while participants engaged in autobiographical memory, theory of mind, or a sensorimotor control condition. Across the default network, we observed stronger activity associated with both autobiographical memory and theory of mind compared to the control condition. Nonetheless, we also observed that some regions showed preferential activity to either experimental condition, in line with past work. The connectivity results similarly indicated shared and distinct functional profiles. Our results support that autobiographical memory and theory of mind, two theoretically important and widely studied domains of social cognition, evoke common and distinct aspects of the default network even when ensuring high fidelity to individual-specific characteristics.NEW & NOTEWORTHY We used cutting-edge precision functional MRI (fMRI) methods such as multi-echo fMRI acquisition and denoising, a robust experimental paradigm, and individualized cortical parcellation across 23 participants to provide evidence that remembering one's past experiences and imagining the thoughts and feelings of others share a common neural substrate. Evidence from activation and connectivity analyses indicate overlapping and distinct functional profiles of these widely studied episodic and social processes.

DeepEMC-T2 mapping: Deep learning-enabled T2 mapping based on echo modulation curve modeling.

PURPOSE: Echo modulation curve (EMC) modeling enables accurate quantification of T2 relaxation times in multi-echo spin-echo (MESE) imaging. The standard EMC-T2 mapping framework, however, requires sufficient echoes and cumbersome pixel-wise dictionary-matching steps. This work proposes a deep learning version of EMC-T2 mapping, called DeepEMC-T2 mapping, to efficiently estimate accurate T2 maps from fewer echoes. METHODS: DeepEMC-T2 mapping was developed using a modified U-Net to estimate both T2 and proton density (PD) maps directly from MESE images. The network implements several new features to improve the accuracy of T2/PD estimation. A total of 67 MESE datasets acquired in axial orientation were used for network training and evaluation. An additional 57 datasets acquired in coronal orientation with different scan parameters were used to evaluate the generalizability of the framework. The performance of DeepEMC-T2 mapping was evaluated in seven experiments. RESULTS: Compared to the reference, DeepEMC-T2 mapping achieved T2 estimation errors from 1% to 11% and PD estimation errors from 0.4% to 1.5% with ten/seven/five/three echoes, which are more accurate than standard EMC-T2 mapping. By incorporating datasets acquired with different scan parameters and orientations for joint training, DeepEMC-T2 exhibits robust generalizability across varying imaging protocols. Increasing the echo spacing and including longer echoes improve the accuracy of parameter estimation. The new features proposed in DeepEMC-T2 mapping all enabled more accurate T2 estimation. CONCLUSIONS: DeepEMC-T2 mapping enables simplified, efficient, and accurate T2 quantification directly from MESE images without dictionary matching. Accurate T2 estimation from fewer echoes allows for increased volumetric coverage and/or higher slice resolution without prolonging total scan times.

Multiband accelerated 2D EPI for multi-echo brain QSM at 3 T.

PURPOSE: Data for QSM are typically acquired using multi-echo 3D gradient echo (GRE), but EPI can be used to accelerate QSM and provide shorter acquisition times. So far, EPI-QSM has been limited to single-echo acquisitions, which, for 3D GRE, are known to be less accurate than multi-echo sequences. Therefore, we compared single-echo and multi-echo EPI-QSM reconstructions across a range of parallel imaging and multiband acceleration factors. METHODS: Using 2D single-shot EPI in the brain, we compared QSM from single-echo and multi-echo acquisitions across combined parallel-imaging and multiband acceleration factors ranging from 2 to 16, with volume pulse TRs from 21.7 to 3.2 s, respectively. For single-echo versus multi-echo reconstructions, we investigated the effect of acceleration factors on regional susceptibility values, temporal noise, and image quality. We introduce a novel masking method based on thresholding the magnitude of the local field gradients to improve brain masking in challenging regions. RESULTS: At 1.6-mm isotropic resolution, high-quality QSM was achieved using multi-echo 2D EPI with a combined acceleration factor of 16 and a TR of 3.2 s, which enables functional applications. With these high acceleration factors, single-echo reconstructions are inaccurate and artefacted, rendering them unusable. Multi-echo acquisitions greatly improve QSM quality, particularly at higher acceleration factors, provide more consistent regional susceptibility values across acceleration factors, and decrease temporal noise compared with single-echo QSM reconstructions. CONCLUSION: Multi-echo acquisition is more robust for EPI-QSM across parallel imaging and multiband acceleration factors than single-echo acquisition. Multi-echo EPI can be used for highly accelerated acquisition while preserving QSM accuracy and quality relative to gold-standard 3D-GRE QSM.

Signatures of microstructure in gradient-echo and spin-echo signals.

PURPOSE: To determine whether the spatial scale and magnetic susceptibility of microstructure can be evaluated robustly from the decay of gradient-echo and spin-echo signals. THEORY AND METHODS: Gradient-echo and spin-echo images were acquired from suspensions of spherical polystyrene microbeads of 10, 20, and 40 µm nominal diameter. The sizes of the beads and their magnetic susceptibility relative to the medium were estimated from the signal decay curves, using a lookup table generated from Monte Carlo simulations and an analytic model based on the Gaussian phase approximation. RESULTS: Fitting Monte Carlo predictions to spin-echo data yielded acceptable estimates of microstructural parameters for the 20 and 40 µm microbeads. Using gradient-echo data, the Monte Carlo lookup table provided satisfactory parameter estimates for the 20 µm beads but unstable results for the diameter of the largest beads. Neither spin-echo nor gradient-echo data allowed accurate parameter estimation for the smallest beads. The analytic model performed poorly over all bead sizes. CONCLUSIONS: Microstructural sources of magnetic susceptibility produce distinctive non-exponential signatures in the decay of gradient-echo and spin-echo signals. However, inverting the problem to extract microstructural parameters from the signals is nontrivial and, in certain regimes, ill-conditioned. For microstructure with small characteristic length scales, parameter estimation is hampered by the difficulty of acquiring accurate data at very short echo times. For microstructure with large characteristic lengths, the gradient-echo signal approaches the static-dephasing regime, where it becomes insensitive to size. Applicability of the analytic model was further limited by failure of the Gaussian phase approximation for all but the smallest beads.

Fast and High-Resolution T2 Mapping Based on Echo Merging Plus k-t Undersampling with Reduced Refocusing Flip Angles (TEMPURA) as Methods for Human Renal MRI.

PURPOSE: To develop a highly accelerated multi-echo spin-echo method, TEMPURA, for reducing the acquisition time and/or increasing spatial resolution for kidney T2 mapping. METHODS: TEMPURA merges several adjacent echoes into one k-space by either combining independent echoes or sharing one echo between k-spaces. The combined k-space is reconstructed based on compressed sensing theory. Reduced flip angles are used for the refocusing pulses, and the extended phase graph algorithm is used to correct the effects of indirect echoes. Two sequences were developed: a fast breath-hold sequence; and a high-resolution sequence. The performance was evaluated prospectively on a phantom, 16 healthy subjects, and two patients with different types of renal tumors. RESULTS: The fast TEMPURA method reduced the acquisition time from 3-5 min to one breath-hold (18 s). Phantom measurements showed that fast TEMPURA had a mean absolute percentage error (MAPE) of 8.2%, which was comparable to a standardized respiratory-triggered sequence (7.4%), but much lower than a sequence accelerated by purely k-t undersampling (21.8%). High-resolution TEMPURA reduced the in-plane voxel size from 3 × 3 to 1 × 1 mm2, resulting in improved visualization of the detailed anatomical structure. In vivo T2 measurements demonstrated good agreement (fast: MAPE = 1.3%-2.5%; high-resolution: MAPE = 2.8%-3.3%) and high correlation coefficients (fast: R = 0.85-0.98; high-resolution: 0.82-0.96) with the standardized method, outperforming k-t undersampling alone (MAPE = 3.3-4.5%, R = 0.57-0.59). CONCLUSION: TEMPURA provides fast and high-resolution renal T2 measurements. It has the potential to improve clinical throughput and delineate intratumoral heterogeneity and tissue habitats at unprecedented spatial resolution.

A 3D dual-echo spiral sequence for simultaneous dynamic susceptibility contrast and dynamic contrast-enhanced MRI with single bolus injection.

PURPOSE: Perfusion MRI reveals important tumor physiological and pathophysiologic information, making it a critical component in managing brain tumor patients. This study aimed to develop a dual-echo 3D spiral technique with a single-bolus scheme to simultaneously acquire both dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) data and overcome the limitations of current EPI-based techniques. METHODS: A 3D spiral-based technique with dual-echo acquisition was implemented and optimized on a 3T MRI scanner with a spiral staircase trajectory and through-plane SENSE acceleration for improved speed and image quality, in-plane variable-density undersampling combined with a sliding-window acquisition and reconstruction approach for increased speed, and an advanced iterative deblurring algorithm. Four volunteers were scanned and compared with the standard of care (SOC) single-echo EPI and a dual-echo EPI technique. Two patients were scanned with the spiral technique during a preload bolus and compared with the SOC single-echo EPI collected during the second bolus injection. RESULTS: Volunteer data demonstrated that the spiral technique achieved high image quality, reduced geometric artifacts, and high temporal SNR compared with both single-echo and dual-echo EPI. Patient perfusion data showed that the spiral acquisition achieved accurate DSC quantification comparable to SOC single-echo dual-dose EPI, with the additional DCE information. CONCLUSION: A 3D dual-echo spiral technique was developed to simultaneously acquire both DSC and DCE data in a single-bolus injection with reduced contrast use. Preliminary volunteer and patient data demonstrated increased temporal SNR, reduced geometric artifacts, and accurate perfusion quantification, suggesting a competitive alternative to SOC-EPI techniques for brain perfusion MRI.

Dynamic T 2 * relaxometry of hyperpolarized [1-13 C]pyruvate MRI in the human brain and kidneys.

PURPOSE: This study aimed to quantify T 2 * $$ {T}_2^{\ast } $$ for hyperpolarized [1-13 C]pyruvate and metabolites in the healthy human brain and renal cell carcinoma (RCC) patients at 3 T. METHODS: Dynamic T 2 * $$ {T}_2^{\ast } $$ values were measured with a metabolite-specific multi-echo spiral sequence. The dynamic T 2 * $$ {T}_2^{\ast } $$ of [1-13 C]pyruvate, [1-13 C]lactate, and 13 C-bicarbonate was estimated in regions of interest in the whole brain, sinus vein, gray matter, and white matter in healthy volunteers, as well as in kidney tumors and the contralateral healthy kidneys in a separate group of RCC patients. T 2 * $$ {T}_2^{\ast } $$ was fit using a mono-exponential function; and metabolism was quantified using pyruvate-to-lactate conversion rate maps and lactate-to-pyruvate ratio maps, which were compared with and without an estimated T 2 * $$ {T}_2^{\ast } $$ correction. RESULTS: The T 2 * $$ {T}_2^{\ast } $$ of pyruvate was shown to vary during the acquisition, whereas the T 2 * $$ {T}_2^{\ast } $$ of lactate and bicarbonate were relatively constant through time and across the organs studied. The T 2 * $$ {T}_2^{\ast } $$ of lactate was similar in gray matter (29.75 ± 1.04 ms), white matter (32.89 ± 0.9 ms), healthy kidney (34.61 ± 4.07 ms), and kidney tumor (33.01 ± 2.31 ms); and the T 2 * $$ {T}_2^{\ast } $$ of bicarbonate was different between whole-brain (108.17 ± 14.05 ms) and healthy kidney (58.45 ± 6.63 ms). The T 2 * $$ {T}_2^{\ast } $$ of pyruvate had similar trends in both brain and RCC studies, reducing from 75.56 ± 2.23 ms to 22.24 ± 1.24 ms in the brain and reducing from 122.72 ± 9.86 ms to 57.38 ± 7.65 ms in the kidneys. CONCLUSION: Multi-echo dynamic imaging can quantify T 2 * $$ {T}_2^{\ast } $$ and metabolism in a single integrated acquisition. Clear differences were observed in the T 2 * $$ {T}_2^{\ast } $$ of metabolites and in their behavior throughout the timecourse.

Three contrasts in 3 min: Rapid, high-resolution, and bone-selective UTE MRI for craniofacial imaging with automated deep-learning skull segmentation.

PURPOSE: Ultrashort echo time (UTE) MRI can be a radiation-free alternative to CT for craniofacial imaging of pediatric patients. However, unlike CT, bone-specific MR imaging is limited by long scan times, relatively low spatial resolution, and a time-consuming bone segmentation workflow. METHODS: A rapid, high-resolution UTE technique for brain and skull imaging in conjunction with an automatic segmentation pipeline was developed. A dual-RF, dual-echo UTE sequence was optimized for rapid scan time (3 min) and smaller voxel size (0.65 mm3). A weighted least-squares conjugate gradient method for computing the bone-selective image improves bone specificity while retaining bone sensitivity. Additionally, a deep-learning U-Net model was trained to automatically segment the skull from the bone-selective images. Ten healthy adult volunteers (six male, age 31.5 ± 10 years) and three pediatric patients (two male, ages 12 to 15 years) were scanned at 3 T. Clinical CT for the three patients were obtained for validation. Similarities in 3D skull reconstructions relative to clinical standard CT were evaluated based on the Dice similarity coefficient and Hausdorff distance. Craniometric measurements were used to assess geometric accuracy of the 3D skull renderings. RESULTS: The weighted least-squares method produces images with enhanced bone specificity, suppression of soft tissue, and separation from air at the sinuses when validated against CT in pediatric patients. Dice similarity coefficient overlap was 0.86 ± 0.05, and the 95th percentile Hausdorff distance was 1.77 ± 0.49 mm between the full-skull binary masks of the optimized UTE and CT in the testing dataset. CONCLUSION: An optimized MRI acquisition, reconstruction, and segmentation workflow for craniofacial imaging was developed.

QRAGE-Simultaneous multiparametric quantitative MRI of water content, T1, T2*, and magnetic susceptibility at ultrahigh field strength.

PURPOSE: To introduce quantitative rapid gradient-echo (QRAGE), a novel approach for the simultaneous mapping of multiple quantitative MRI parameters, including water content, T1, T2*, and magnetic susceptibility at ultrahigh field strength. METHODS: QRAGE leverages a newly developed multi-echo MPnRAGE sequence, facilitating the acquisition of 171 distinct contrast images across a range of inversion and TE points. To maintain a short acquisition time, we introduce MIRAGE2, a novel model-based reconstruction method that exploits prior knowledge of temporal signal evolution, represented as damped complex exponentials. MIRAGE2 minimizes local Block-Hankel and Casorati matrices. Parameter maps are derived from the reconstructed contrast images through postprocessing steps. We validate QRAGE through extensive simulations, phantom studies, and in vivo experiments, demonstrating its capability for high-precision imaging. RESULTS: In vivo brain measurements show the promising performance of QRAGE, with test-retest SDs and deviations from reference methods of < 0.8% for water content, < 17 ms for T1, and < 0.7 ms for T2*. QRAGE achieves whole-brain coverage at a 1-mm isotropic resolution in just 7 min and 15 s, comparable to the acquisition time of an MP2RAGE scan. In addition, QRAGE generates a contrast image akin to the UNI image produced by MP2RAGE. CONCLUSION: QRAGE is a new, successful approach for simultaneously mapping multiple MR parameters at ultrahigh field.

JUST-Net: Jointly unrolled cross-domain optimization based spatio-temporal reconstruction network for accelerated 3D myelin water imaging.

PURPOSE: We introduced a novel reconstruction network, jointly unrolled cross-domain optimization-based spatio-temporal reconstruction network (JUST-Net), aimed at accelerating 3D multi-echo gradient-echo (mGRE) data acquisition and improving the quality of resulting myelin water imaging (MWI) maps. METHOD: An unrolled cross-domain spatio-temporal reconstruction network was designed. The main idea is to combine frequency and spatio-temporal image feature representations and to sequentially implement convolution layers in both domains. The k-space subnetwork utilizes shared information from adjacent frames, whereas the image subnetwork applies separate convolutions in both spatial and temporal dimensions. The proposed reconstruction network was evaluated for both retrospectively and prospectively accelerated acquisition. Furthermore, it was assessed in simulation studies and real-world cases with k-space corruptions to evaluate its potential for motion artifact reduction. RESULTS: The proposed JUST-Net enabled highly reproducible and accelerated 3D mGRE acquisition for whole-brain MWI, reducing the acquisition time from fully sampled 15:23 to 2:22 min within a 3-min reconstruction time. The normalized root mean squared error of the reconstructed mGRE images increased by less than 4.0%, and the correlation coefficients for MWI showed a value of over 0.68 when compared to the fully sampled reference. Additionally, the proposed method demonstrated a mitigating effect on both simulated and clinical motion-corrupted cases. CONCLUSION: The proposed JUST-Net has demonstrated the capability to achieve high acceleration factors for 3D mGRE-based MWI, which is expected to facilitate widespread clinical applications of MWI.

Three-dimensional radial echo-planar spectroscopic imaging for hyperpolarized 13C MRSI in vivo.

PURPOSE: To demonstrate the feasibility of 3D echo-planar spectroscopic imaging (EPSI) technique with rapid volumetric radial k-space sampling for hyperpolarized (HP) 13C magnetic resonance spectroscopic imaging (MRSI) in vivo. METHODS: A radial EPSI (rEPSI) was implemented on a 3 T clinical PET/MR system. To enable volumetric coverage, the sinusoidal shaped readout gradients per k-t-spoke were rotated along the three spatial dimensions in a golden-angle like manner. A distance-weighted, density-compensated gridding reconstruction was used, also in cases with undersampling of spokes in k-space. Measurements without and with HP 13C-labeled substances were performed in phantoms and rats using a double-resonant 13C/1H volume resonator with 72 mm inner diameter. RESULTS: Phantom measurements demonstrated the feasibility of the implemented rEPSI sequence, as well as the robustness to undersampling in k-space up to a factor of 5 without advanced reconstruction techniques. Applied to measurements with HP [1-13C]pyruvate in a tumor-bearing rat, we obtained well-resolved MRSI datasets with a large matrix size of 123 voxels covering the whole imaging FOV of (180 mm)3 within 6.3 s, enabling to observe metabolism in dynamic acquisitions. CONCLUSION: After further optimization, the proposed rEPSI method may be useful in applications of HP 13C-tracers where unknown or varying metabolite resonances are expected, and the acquisition of dynamic, volumetric MRSI datasets with an adequate temporal resolution is a challenge.

Human prostate MRI at ultrahigh-performance gradient: A feasibility study.

PURPOSE: To demonstrate the technical feasibility and the value of ultrahigh-performance gradient in imaging the prostate in a 3T MRI system. METHODS: In this local institutional review board-approved study, prostate MRI was performed on 4 healthy men. Each subject was scanned in a prototype 3T MRI system with a 42-cm inner-diameter gradient coil that achieves a maximum gradient amplitude of 200 mT/m and slew rate of 500 T/m/s. PI-RADS V2.1-compliant axial T2 -weighted anatomical imaging and single-shot echo planar DWI at standard gradient of 70 mT/m and 150 T/m/s were obtained, followed by DWI at maximum performance (i.e., 200 mT/m and 500 T/m/s). In comparison to state-of-the-art clinical whole-body MRI systems, the high slew rate improved echo spacing from 1020 to 596 µs and, together with a high gradient amplitude for diffusion encoding, TE was reduced from 55 to 36 ms. RESULTS: In all 4 subjects (waist circumference = 81-91 cm, age = 45-65 years), no peripheral nerve stimulation sensation was reported during DWI. Reduced image distortion in the posterior peripheral zone prostate gland and higher signal intensity, such as in the surrounding muscle of high-gradient DWI, were noted. CONCLUSION: Human prostate MRI at simultaneously high gradient amplitude of 200 mT/m and slew rate of 500 T/m/s is feasible, demonstrating that improved gradient performance can address image distortion and T2 decay-induced SNR issues for in vivo prostate imaging.

Unsupervised motion artifact correction of turbo spin-echo MRI using deep image prior.

PURPOSE: In MRI, motion artifacts can significantly degrade image quality. Motion artifact correction methods using deep neural networks usually required extensive training on large datasets, making them time-consuming and resource-intensive. In this paper, an unsupervised deep learning-based motion artifact correction method for turbo-spin echo MRI is proposed using the deep image prior framework. THEORY AND METHODS: The proposed approach takes advantage of the high impedance to motion artifacts offered by the neural network parameterization to remove motion artifacts in MR images. The framework consists of parameterization of MR image, automatic spatial transformation, and motion simulation model. The proposed method synthesizes motion-corrupted images from the motion-corrected images generated by the convolutional neural network, where an optimization process minimizes the objective function between the synthesized images and the acquired images. RESULTS: In the simulation study of 280 slices from 14 subjects, the proposed method showed a significant increase in the averaged structural similarity index measure by 0.2737 in individual coil images and by 0.4550 in the root-sum-of-square images. In addition, the ablation study demonstrated the effectiveness of each proposed component in correcting motion artifacts compared to the corrected images produced by the baseline method. The experiments on real motion dataset has shown its clinical potential. CONCLUSION: The proposed method exhibited significant quantitative and qualitative improvements in correcting rigid and in-plane motion artifacts in MR images acquired using turbo spin-echo sequence.

A vendor-neutral EPI sequence for hyperpolarized 13C MRI.

PURPOSE: To develop a flexible, vendor-neutral EPI sequence for hyperpolarized 13C metabolic imaging. METHODS: An open-source EPI sequence consisting of a metabolite-specific spectral-spatial RF excitation pulse and a customizable EPI readout was created using the Pulseq framework. To explore the flexibility of our sequence, we tested several versions of the sequence including a symmetric 3D readout with different spatial resolutions for each metabolite (1.0 cm3 and 1.5 cm3). A multichamber phantom constructed with a Shepp-Logan geometry, containing two chambers filled with either natural abundance 13C compounds or hyperpolarized (HP) [1-13C]pyruvate, was used to test each sequence. For experiments involving HP [1-13C]pyruvate, a single chamber was prefilled with nicotinamide adenine dinucleotide hydride and lactate dehydrogenase to facilitate the conversion of [1-13C]pyruvate to [1-13C]lactate. All experiments were performed on a Siemens Prisma 3T scanner. RESULTS: All the sequence variations localized natural-abundance 13C ethylene glycol and methanol to the appropriate compartment of the multichamber phantom. [1-13C]pyruvate was detectable in both chambers following the injection of HP [1-13C]pyruvate, whereas [1-13C]lactate was only found in the chamber containing nicotinamide adenine dinucleotide hydride and lactate dehydrogenase. The conversion rate from [1-13C]pyruvate to [1-13C]lactate (kPL) was 0.01 s-1 (95% confidence interval [0.00, 0.02]). CONCLUSION: We have developed and tested a vendor-neutral EPI sequence for imaging HP 13C agents. We have made all of our sequence creation and image reconstruction code freely available online for other investigators to use.