High-resolution diffusion MRI studies of development in pregnant mice visualized by novel spatiotemporal encoding schemes

Unsupervised deep learning model for correcting Nyquist ghosts of single-shot spatiotemporal encoding

PURPOSE

To design an unsupervised deep learning (DL) model for correcting Nyquist ghosts of single-shot spatiotemporal encoding (SPEN) and evaluate the model for real MRI applications.

METHODS

The proposed method consists of three main components: (1) an unsupervised network that combines Residual Encoder and Restricted Subspace Mapping (RERSM-net) and is trained to generate a phase-difference map based on the even and odd SPEN images; (2) a spin physical forward model to obtain the corrected image with the learned phase difference map; and (3) cycle-consistency loss that is explored for training the RERSM-net.

RESULTS

The proposed RERSM-net could effectively generate smooth phase difference maps and correct Nyquist ghosts of single-shot SPEN. Both simulation and real in vivo MRI experiments demonstrated that our method outperforms the state-of-the-art SPEN Nyquist ghost correction method. Furthermore, the ablation experiments of generating phase-difference maps show the advantages of the proposed unsupervised model.

CONCLUSION

The proposed method can effectively correct Nyquist ghosts for the single-shot SPEN sequence.

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.

Spatiotemporal encoding MRI using subspace-constrained sampling and locally-low-rank regularization: Applications to diffusion weighted and diffusion kurtosis imaging of human brain and prostate

The benefits of performing locally low-rank (LLR) reconstructions on subsampled diffusion weighted and diffusion kurtosis imaging data employing spatiotemporal encoding (SPEN) methods, is investigated. SPEN allows for self-referenced correction of motion-induced phase errors in case of interleaved diffusion-oriented acquisitions, and allows one to overcome distortions otherwise observed along EPI's phase-encoded dimension. In combination with LLR-based reconstructions of the pooled imaging data and with a joint subsampling of b-weighted and interleaved images, additional improvements in terms of sensitivity as well as shortened acquisition times are demonstrated, without noticeable penalties. Details on how the LLR-regularized, subspace-constrained image reconstructions were adapted to SPEN are given; the improvements introduced by adopting these reconstruction frameworks for the accelerated acquisition of diffusivity and of kurtosis imaging data in both relatively homogeneous regions like the human brain and in more challenging regions like the human prostate, are presented and discussed within the context of similar efforts in the field.

Deuterium Magnetic Resonance Imaging and the Discrimination of Fetoplacental Metabolism in Normal and L-NAME-Induced Preeclamptic Mice

Recent magnetic resonance studies in healthy and cancerous organs have concluded that deuterated metabolites possess highly desirable properties for mapping non-invasively and, as they happen, characterizing glycolysis and other biochemical processes in animals and humans. A promising avenue of this deuterium metabolic imaging (DMI) approach involves looking at the fate of externally administered ²H_6,6′-glucose, as it is taken up and metabolized into different products as a function of time. This study employs deuterium magnetic resonance to follow the metabolism of wildtype and preeclamptic pregnant mice models, focusing on maternal and fetoplacental organs over ≈2 h post-injection. ²H_6,6′-glucose uptake was observed in the placenta and in specific downstream organs such as the fetal heart and liver. Main metabolic products included ²H_3,3′-lactate and ²H-water, which were produced in individual fetoplacental organs with distinct time traces. Glucose uptake in the organs of most preeclamptic animals appeared more elevated than in the control mice (p = 0.02); also higher was the production of ²H-water arising from this glucose. However, the most notable differences arose in the ²H_3,3′-lactate concentration, which was ca. two-fold more abundant in the placenta (p = 0.005) and in the fetal (p = 0.01) organs of preeclamptic-like animals, than in control mice. This is consistent with literature reports about hypoxic conditions arising in preeclamptic and growth-restricted pregnancies, which could lead to an enhancement in anaerobic glycolysis. Overall, the present measurements suggest that DMI, a minimally invasive approach, may offer new ways of studying and characterizing health and disease in mammalian pregnancies, including humans.

Simultaneous multi-banding and multi-echo phase encoding for the accelerated acquisition of high-resolution volumetric diffusivity maps by spatiotemporally encoded MRI

PURPOSE

Spatiotemporal Encoding (SPEN) is an ultrafast imaging technique where the low-bandwidth axis is rasterized in a joint spatial/k-domain. SPEN benefits from increased robustness to field inhomogeneities, folding-free reconstruction of subsampled data, and an ability to combine multiple interleaved or signal averaged scans -yet its relatively high SAR complicates volumetric uses. Here we show how this can be alleviated by merging simultaneous multi-band excitation, with intra-slab multi-echo (ME) phase encoding, for the acquisition of high definition volumetric DWI/DTI data.

METHODS

A protocol involving phase-cycling of simultaneous multi-banded z-slab excitations in independently k_y-interleaved scans, together with ME trains that k_z-encoded positions within these slabs, was implemented. A reconstruction incorporating a CAIPIRINHA-like encoding of the multiple bands and exploiting SPEN's ability to deliver self-referenced, per-shot phase maps, then led to high-definition diffusivity acquisitions, with reduced SAR and acquisition times vis-à-vis non-optimized 3D counterparts.

RESULTS

The new protocol was used to collect full brain 3 T DTI experiments at a variety of nominal voxel sizes, ranging from 1.95 to 2.54 mm³. In general, the new protocol yielded superior sensitivity and fewer distortions than what could be observed in comparably timed phase-encoded 3D SPEN, multi-slice 2D SPEN, or optimized EPI counterparts.

CONCLUSIONS

A robust procedure for acquiring volumetric DWI/DTI data was developed and demonstrated.

Respiratory Motion Mitigation and Repeatability of Two Diffusion-Weighted MRI Methods Applied to a Murine Model of Spontaneous Pancreatic Cancer

Respiratory motion and increased susceptibility effects at high magnetic fields pose challenges for quantitative diffusion-weighted MRI (DWI) of a mouse abdomen on preclinical MRI systems. We demonstrate the first application of radial k-space-sampled (RAD) DWI of a mouse abdomen using a genetically engineered mouse model of pancreatic ductal adenocarcinoma (PDAC) on a 4.7 T preclinical scanner equipped with moderate gradient capability. RAD DWI was compared with the echo-planar imaging (EPI)-based DWI method with similar voxel volumes and acquisition times over a wide range of b-values (0.64, 535, 1071, 1478, and 2141 mm²/s). The repeatability metrics are assessed in a rigorous test-retest study (n = 10 for each DWI protocol). The four-shot EPI DWI protocol leads to higher signal-to-noise ratio (SNR) in diffusion-weighted images with persisting ghosting artifacts, whereas the RAD DWI protocol produces relatively artifact-free images over all b-values examined. Despite different degrees of motion mitigation, both RAD DWI and EPI DWI allow parametric maps of apparent diffusion coefficients (ADC) to be produced, and the ADC of the PDAC tumor estimated by the two methods are 1.3 ± 0.24 and 1.5 ± 0.28 × 10^-3 mm²/s, respectively (p = 0.075, n = 10), and those of a water phantom are 3.2 ± 0.29 and 2.8 ± 0.15 × 10^-3 mm²/s, respectively (p = 0.001, n = 10). Bland-Altman plots and probability density function reveal good repeatability for both protocols, whose repeatability metrics do not differ significantly. In conclusion, RAD DWI enables a more effective respiratory motion mitigation but lower SNR, while the performance of EPI DWI is expected to improve with more advanced gradient hardware.

Identification of variable stages in murine pancreatic tumors by a multiparametric approach employing hyperpolarized 13 C MRSI, 1 H diffusivity and 1 H T1 MRI

This study explored the usefulness of multiple quantitative MRI approaches to detect pancreatic ductal adenocarcinomas in two murine models, PAN-02 and KPC. Methods assayed included 1 H T1 and T2 measurements, quantitative diffusivity mapping, magnetization transfer (MT) 1 H MRI throughout the abdomen and hyperpolarized 13 C spectroscopic imaging. The progress of the disease was followed as a function of its development; studies were also conducted for wildtype control mice and for mice with induced mild acute pancreatitis. Customized methods developed for scanning the motion- and artifact-prone mice abdomens allowed us to obtain quality 1 H images for these targeted regions. Contrasts between tumors and surrounding tissues, however, were significantly different. Anatomical images, T2 maps and MT did not yield significant contrast unless tumors were large. By contrast, tumors showed statistically lower diffusivities than their surroundings (≈8.3 ± 0.4 x 10-4 for PAN-02 and ≈10.2 ± 0.6 x 10-4 for KPC vs 13 ± 1 x 10-3 mm2 s-1 for surroundings), longer T1 relaxation times (≈1.44 ± 0.05 for PAN-02 and ≈1.45 ± 0.05 for KPC vs 0.95 ± 0.10 seconds for surroundings) and significantly higher lactate/pyruvate ratios by hyperpolarized 13 C MR (0.53 ± 0.2 for PAN-02 and 0.78 ± 0.2 for KPC vs 0.11 ± 0.04 for control and 0.31 ± 0.04 for pancreatitis-bearing mice). Although the latter could also distinguish early-stage tumors from healthy animal controls, their response was similar to that in our pancreatitis model. Still, this ambiguity could be lifted using the 1 H-based reporters. If confirmed for other kinds of pancreatic tumors this means that these approaches, combined, can provide a route to an early detection of pancreatic cancer.

High-Resolution 3D in vivo Brain Diffusion Tensor Imaging at Ultrahigh Fields: Following Maturation on Juvenile and Adult Mice

Diffusion tensor imaging (DTI) is a well-established technique for mapping brain microstructure and white matter tracts in vivo. High resolution DTI, however, is usually associated with low intrinsic sensitivity and therefore long acquisition times. By increasing sensitivity, high magnetic fields can alleviate these demands, yet high fields are also typically associated with significant susceptibility-induced image distortions. This study explores the potential arising from employing new pulse sequences and emerging hardware at ultrahigh fields, to overcome these limitations. To this end, a 15.2 T MRI instrument equipped with a cryocooled surface transceiver coil was employed, and DTI experiments were compared between SPatiotemporal ENcoding (SPEN), a technique that tolerates well susceptibility-induced image distortions, and double-sampled Spin-Echo Echo-Planar Imaging (SE-EPI) methods. Following optimization, SE-EPI afforded whole brain DTI maps at 135 μm isotropic resolution that possessed higher signal-to-noise ratios (SNRs) than SPEN counterparts. SPEN, however, was a better alternative to SE-EPI when focusing on challenging regions of the mouse brain -including the olfactory bulb and the cerebellum. In these instances, the higher robustness of fully refocused SPEN acquisitions coupled to its built-in zooming abilities, provided in vivo DTI maps with 75 μm nominal isotropic spatial resolution. These DTI maps, and in particular the mean diffusion direction (MDD) details, exhibited variations that matched very well the anatomical features known from histological brain Atlases. Using these capabilities, the development of the olfactory bulb (OB) in live mice was followed from week 1 post-partum, until adulthood. The diffusivity of this organ showed a systematic decrease in its overall isotropic value and increase in its fractional anisotropy with age; this maturation was observed for all regions used in the OB's segmentation but was most evident for the lobules' centers, in particular for the granular cell layer. The complexity of the OB neuronal connections also increased during maturation, as evidenced by the growth in directionalities arising in the mean diffusivity direction maps.

Diffusion tensor distribution imaging of an in vivo mouse brain at ultrahigh magnetic field by spatiotemporal encoding

Diffusion tensor distribution (DTD) imaging builds on principles from diffusion, solid-state and low-field NMR spectroscopies, to quantify the contents of heterogeneous voxels as nonparametric distributions, with tensor "size", "shape" and orientation having direct relations to corresponding microstructural properties of biological tissues. The approach requires the acquisition of multiple images as a function of the magnitude, shape and direction of the diffusion-encoding gradients, leading to long acquisition times unless fast image read-out techniques like EPI are employed. While in previous in vivo human brain studies performed at 3 T this proved a viable option, porting these measurements to very high magnetic fields and/or to heterogeneous organs induces B0 - and B1 -inhomogeneity artifacts that challenge the limits of EPI. To overcome such challenges, we demonstrate here that high spatial resolution DTD of mouse brain can be carried out at 15.2 T with a surface-cryoprobe, by relying on SPatiotemporal ENcoding (SPEN) imaging sequences. These new acquisition and data-processing protocols are demonstrated with measurements on in vivo mouse brain, and validated with synthetic phantoms designed to mimic the diffusion properties of white matter, gray matter and cerebrospinal fluid. While still in need of full extensions to 3D mappings and of scanning additional animals to extract more general physiological conclusions, this work represents another step towards the model-free, noninvasive in vivo characterization of tissue microstructure and heterogeneity in animal models, at ≈0.1 mm resolutions.

Diffusion and perfusion MRI of normal, preeclamptic and growth-restricted mice models reveal clear fetoplacental differences

Diffusion-weighted MRI on rodents could be valuable to evaluate pregnancy-related dysfunctions, particularly in knockout models whose biological nature is well understood. Echo Planar Imaging’s sensitivity to motions and to air/water/fat heterogeneities, complicates these studies in the challenging environs of mice abdomens. Recently developed MRI methodologies based on SPatiotemporal ENcoding (SPEN) can overcome these obstacles, and deliver diffusivity maps at ≈150 µm in-plane resolutions. The present study exploits these capabilities to compare the development in wildtype vs vascularly-altered mice. Attention focused on the various placental layers—deciduae, labyrinth, trophoblast, fetal vessels—that the diffusivity maps could resolve. Notable differences were then observed between the placental developments of wildtype vs diseased mice; these differences remained throughout the pregnancies, and were echoed by perfusion studies relying on gadolinium-based dynamic contrast-enhanced MRI. Longitudinal monitoring of diffusivity in the animals throughout the pregnancies also showed differences between the development of the fetal brains in the wildtype and vascularly-altered mice, even if these disparities became progressively smaller as the pregnancies progressed. These results are analyzed on the basis of the known physiology of normal and preeclamptic pregnancies, as well as in terms of the potential that they might open for the early detection of disorders in human pregnancies.