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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. [ABSTRACT FROM AUTHOR]

Deuterium metabolic imaging (DMI) is a promising molecular MRI approach, which follows the administration of deuterated substrates and their metabolization. [6,6'‐2H2]‐glucose for instance is preferentially converted in tumors to [3,3'‐2H2]‐lactate as a result of the Warburg effect, providing a distinct resonance whose mapping using time‐resolved spectroscopic imaging can diagnose cancer. The MR detection of low‐concentration metabolites such as lactate, however, is challenging. It has been recently shown that multi‐echo balanced steady‐state free precession (ME‐bSSFP) increases the signal‐to‐noise ratio (SNR) of these experiments approximately threefold over regular chemical shift imaging; the present study examines how DMI's sensitivity can be increased further by advanced processing methods. Some of these, such as compressed sensing multiplicative denoising and block‐matching/3D filtering, can be applied to any spectroscopic/imaging methods. Sensitivity‐enhancing approaches were also specifically tailored to ME‐bSSFP DMI, by relying on priors related to the resonances' positions and to features of the metabolic kinetics. Two new methods are thus proposed that use these constraints for enhancing the sensitivity of both the spectral images and the metabolic kinetics. The ability of these methods to improve DMI is evidenced in pancreatic cancer studies carried at 15.2 T, where suitable implementations of the proposals imparted eightfold or more SNR improvement over the original ME‐bSSFP data, at no informational cost. Comparisons with other propositions in the literature are briefly discussed. [ABSTRACT FROM AUTHOR]

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 1H T1 and T2 measurements, quantitative diffusivity mapping, magnetization transfer (MT) 1H MRI throughout the abdomen and hyperpolarized 13C 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 1H 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 13C 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 1H‐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. [ABSTRACT FROM AUTHOR]

Purpose: To develop a pulse sequence for acquiring robust, quantitative T2 relaxation maps in real time. Methods: The pulse scheme relies on fully refocused spatiotemporally encoded multi‐spin‐echo trains, which provide images that are significantly less distorted than spin‐echo echo planar imaging‐based counterparts. This enables single‐shot T2 mapping in inhomogeneity‐prone regions. Another advantage of these schemes stems from their ability to interleave multiple scans in a reference‐free manner, providing an option to increase sensitivity and spatial resolution with minimal motional artifacts. Results: The method was implemented in preclinical and clinical scanners, where single‐shot acquisitions delivered reliable T2 maps in ≤200 ms with ≈250 µm and ≈3 mm resolutions, respectively. Ca. 4 times higher spatial resolutions were achieved for the motion‐compensated interleaved versions of these acquisitions, delivering T2 maps in ca. 10 s per slice. These maps were nearly indistinguishable from multi‐scan relaxometric maps requiring orders‐of‐magnitude longer acquisitions; this was confirmed by mice head and real‐time mice abdomen 7T scans performed following contrast‐agent injections, as well as by 3T human brain and breast scans. Conclusion: This study introduced and demonstrated a new approach for acquiring rapid and quantitative T2 data, which is particularly reliable when operating at high fields and/or targeting heterogeneous organs or regions. [ABSTRACT FROM AUTHOR]

This study introduces an MRI approach to map diffusion of water in vivo with high resolution under challenging conditions; the approach's potential is then used in diffusivity characterizations of embryos and fetoplacental units in pregnant mice, as well as of newborn mice in their initial postnatal period. The method relies on performing self‐referenced spatiotemporal encoded MRI acquisitions, which can achieve the motional and susceptibility immunities needed to target challenging regions such as a mouse's abdominal cavity in a single shot. When suitably combined with zooming‐in and novel interleaving procedures, these scans can overcome the inhomogeneity and sensitivity challenges arising upon targeting ≈100 μm in‐plane resolutions, and thereby enable longitudinal development studies of abdominal organs that have hitherto eluded in vivo diffusion‐weighted imaging. This is employed here to follow processes related to embryonic implantation and placentation, including the final stages of mouse gastrulation, the development of white matter in fetal brains, the maturation of fetal spines, and the evolution of the different layers making up mouse hemochorial placentas. The protocol's ability to extract diffusivity information in challenging regions as a function of embryonic mouse development is thus demonstrated, and its usefulness as a tool for visualizing pregnancy‐related developmental changes in rodents is discussed. [ABSTRACT FROM AUTHOR]