T cell antigen receptor recognition of antigen-presenting molecules.

The Major Histocompatibility Complex (MHC) locus encodes classical MHC class I and MHC class II molecules and nonclassical MHC-I molecules. The architecture of these molecules is ideally suited to capture and present an array of peptide antigens (Ags). In addition, the CD1 family members and MR1 are MHC class I-like molecules that bind lipid-based Ags and vitamin B precursors, respectively. These Ag-bound molecules are subsequently recognized by T cell antigen receptors (TCRs) expressed on the surface of T lymphocytes. Structural and associated functional studies have been highly informative in providing insight into these interactions, which are crucial to immunity, and how they can lead to aberrant T cell reactivity. Investigators have determined over thirty unique TCR-peptide-MHC-I complex structures and twenty unique TCR-peptide-MHC-II complex structures. These investigations have shown a broad consensus in docking geometry and provided insight into MHC restriction. Structural studies on TCR-mediated recognition of lipid and metabolite Ags have been mostly confined to TCRs from innate-like natural killer T cells and mucosal-associated invariant T cells, respectively. These studies revealed clear differences between TCR-lipid-CD1, TCR-metabolite-MR1, and TCR-peptide-MHC recognition. Accordingly, TCRs show remarkable structural and biological versatility in engaging different classes of Ag that are presented by polymorphic and monomorphic Ag-presenting molecules of the immune system.

Unconventional or Preset αß T Cells: Evolutionarily Conserved Tissue-Resident T Cells Recognizing Nonpeptidic Ligands.

A majority of T cells bearing the αß T cell receptor (TCR) are specific for peptides bound to polymorphic classical major histocompatibility complex (MHC) molecules. Smaller subsets of T cells are reactive toward various nonpeptidic ligands associated with nonpolymorphic MHC class-Ib (MHC-Ib) molecules. These cells have been termed unconventional for decades, even though only the composite antigen is different from the one seen by classical T cells. Herein, we discuss the identity of these particular T cells in light of the coevolution of their TCR and MHC-Ib restricting elements. We examine their original thymic development: selection on hematopoietic cells leading to the acquisition of an original differentiation program. Most of these cells acquire memory cell features during thymic maturation and exhibit unique patterns of migration into peripheral nonlymphoid tissues to become tissue resident. Thus, these cells are termed preset T cells, as they also display a variety of effector functions. They may act as microbial or danger sentinels, fight microbes, or regulate tissue homeostasis.

Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians.

Radiation therapy (RT) continues to play an important role in the treatment of cancer. Adaptive RT (ART) is a novel method through which RT treatments are evolving. With the ART approach, computed tomography or magnetic resonance (MR) images are obtained as part of the treatment delivery process. This enables the adaptation of the irradiated volume to account for changes in organ and/or tumor position, movement, size, or shape that may occur over the course of treatment. The advantages and challenges of ART maybe somewhat abstract to oncologists and clinicians outside of the specialty of radiation oncology. ART is positioned to affect many different types of cancer. There is a wide spectrum of hypothesized benefits, from small toxicity improvements to meaningful gains in overall survival. The use and application of this novel technology should be understood by the oncologic community at large, such that it can be appropriately contextualized within the landscape of cancer therapies. Likewise, the need to test these advances is pressing. MR-guided ART (MRgART) is an emerging, extended modality of ART that expands upon and further advances the capabilities of ART. MRgART presents unique opportunities to iteratively improve adaptive image guidance. However, although the MRgART adaptive process advances ART to previously unattained levels, it can be more expensive, time-consuming, and complex. In this review, the authors present an overview for clinicians describing the process of ART and specifically MRgART.

Engineering bionanoreactor in bacteria for efficient hydrogen production.

Hydrogen production through water splitting is a vital strategy for renewable and sustainable clean energy. In this study, we developed an approach integrating nanomaterial engineering and synthetic biology to establish a bionanoreactor system for efficient hydrogen production. The periplasmic space (20 to 30 nm) of an electroactive bacterium, Shewanella oneidensis MR-1, was engineered to serve as a bionanoreactor to enhance the interaction between electrons and protons, catalyzed by hydrogenases for hydrogen generation. To optimize electron transfer, we used the microbially reduced graphene oxide (rGO) to coat the electrode, which improved the electron transfer from the electrode to the cells. Native MtrCAB protein complex on S. oneidensis and self-assembled iron sulfide (FeS) nanoparticles acted in tandem to facilitate electron transfer from an electrode to the periplasm. To enhance proton transport, S. oneidensis MR-1 was engineered to express Gloeobacter rhodopsin (GR) and the light-harvesting antenna canthaxanthin. This led to efficient proton pumping when exposed to light, resulting in a 35.6% increase in the rate of hydrogen production. The overexpression of native [FeFe]-hydrogenase further improved the hydrogen production rate by 56.8%. The bionanoreactor engineered in S. oneidensis MR-1 achieved a hydrogen yield of 80.4 µmol/mg protein/day with a Faraday efficiency of 80% at a potential of -0.75 V. This periplasmic bionanoreactor combines the strengths of both nanomaterial and biological components, providing an efficient approach for microbial electrosynthesis.

Mouse mucosal-associated invariant T cell receptor recognition of MR1 presenting the vitamin B metabolite, 5-(2-oxopropylideneamino)-6-d-ribitylaminouracil.

Mucosal-associated invariant T (MAIT) cells can elicit immune responses against riboflavin-based antigens presented by the evolutionary conserved MHC class I related protein, MR1. While we have an understanding of the structural basis of human MAIT cell receptor (TCR) recognition of human MR1 presenting a variety of ligands, how the semi-invariant mouse MAIT TCR binds mouse MR1-ligand remains unknown. Here, we determine the crystal structures of 2 mouse TRAV1-TRBV13-2+ MAIT TCR-MR1-5-OP-RU ternary complexes, whose TCRs differ only in the composition of their CDR3ß loops. These mouse MAIT TCRs mediate high affinity interactions with mouse MR1-5-OP-RU and cross-recognize human MR1-5-OP-RU. Similarly, a human MAIT TCR could bind mouse MR1-5-OP-RU with high affinity. This cross-species recognition indicates the evolutionary conserved nature of this MAIT TCR-MR1 axis. Comparing crystal structures of the mouse versus human MAIT TCR-MR1-5-OP-RU complexes provides structural insight into the conserved nature of this MAIT TCR-MR1 interaction and conserved specificity for the microbial antigens, whereby key germline-encoded interactions required for MAIT activation are maintained. This is an important consideration for the development of MAIT cell-based therapeutics that will rely on preclinical mouse models of disease.

MAIT cell-MR1 reactivity is highly conserved across multiple divergent species.

Mucosal-associated invariant T (MAIT) cells are a subset of unconventional T cells that recognize small molecule metabolites presented by major histocompatibility complex class I related protein 1 (MR1), via an αß T cell receptor (TCR). MAIT TCRs feature an essentially invariant TCR α-chain, which is highly conserved between mammals. Similarly, MR1 is the most highly conserved major histocompatibility complex-I-like molecule. This extreme conservation, including the mode of interaction between the MAIT TCR and MR1, has been shown to allow for species-mismatched reactivities unique in T cell biology, thereby allowing the use of selected species-mismatched MR1-antigen (MR1-Ag) tetramers in comparative immunology studies. However, the pattern of cross-reactivity of species-mismatched MR1-Ag tetramers in identifying MAIT cells in diverse species has not been formally assessed. We developed novel cattle and pig MR1-Ag tetramers and utilized these alongside previously developed human, mouse, and pig-tailed macaque MR1-Ag tetramers to characterize cross-species tetramer reactivities. MR1-Ag tetramers from each species identified T cell populations in distantly related species with specificity that was comparable to species-matched MR1-Ag tetramers. However, there were subtle differences in staining characteristics with practical implications for the accurate identification of MAIT cells. Pig MR1 is sufficiently conserved across species that pig MR1-Ag tetramers identified MAIT cells from the other species. However, MAIT cells in pigs were at the limits of phenotypic detection. In the absence of sheep MR1-Ag tetramers, a MAIT cell population in sheep blood was identified phenotypically, utilizing species-mismatched MR1-Ag tetramers. Collectively, our results validate the use and define the limitations of species-mismatched MR1-Ag tetramers in comparative immunology studies.

Elucidating the role of liver enzymes as markers and regulators in ovarian cancer: a synergistic approach using Mendelian randomization, single-cell analysis, and clinical evidence.

OBJECTIVE: To investigate the association between liver enzymes and ovarian cancer (OC), and to validate their potential as biomarkers and their mechanisms in OC. Methods Genome-wide association studies for OC and levels of enzymes such as Alkaline phosphatase (ALP), Aspartate aminotransferase (AST), Alanine aminotransferase, and gamma-glutamyltransferase were analyzed. Univariate and multivariate Mendelian randomization (MR), complemented by the Steiger test, identified enzymes with a potential causal relationship to OC. Single-cell transcriptomics from the GSE130000 dataset pinpointed pivotal cellular clusters, enabling further examination of enzyme-encoding gene expression. Transcription factors (TFs) governing these genes were predicted to construct TF-mRNA networks. Additionally, liver enzyme levels were retrospectively analyzed in healthy individuals and OC patients, alongside the evaluation of correlations with cancer antigen 125 (CA125) and Human Epididymis Protein 4 (HE4). RESULTS: A total of 283 single nucleotide polymorphisms (SNPs) and 209 SNPs related to ALP and AST, respectively. Using the inverse-variance weighted method, univariate MR (UVMR) analysis revealed that ALP (P = 0.050, OR = 0.938) and AST (P = 0.017, OR = 0.906) were inversely associated with OC risk, suggesting their roles as protective factors. Multivariate MR (MVMR) confirmed the causal effect of ALP (P = 0.005, OR = 0.938) on OC without reverse causality. Key cellular clusters including T cells, ovarian cells, endothelial cells, macrophages, cancer-associated fibroblasts (CAFs), and epithelial cells were identified, with epithelial cells showing high expression of genes encoding AST and ALP. Notably, TFs such as TCE4 were implicated in the regulation of GOT2 and ALPL genes. OC patient samples exhibited decreased ALP levels in both blood and tumor tissues, with a negative correlation between ALP and CA125 levels observed. CONCLUSION: This study has established a causal link between AST and ALP with OC, identifying them as protective factors. The increased expression of the genes encoding these enzymes in epithelial cells provides a theoretical basis for developing novel disease markers and targeted therapies for OC.

A diffusion MRI-based spatiotemporal continuum of the embryonic mouse brain for probing gene-neuroanatomy connections.

The embryonic mouse brain undergoes drastic changes in establishing basic anatomical compartments and laying out major axonal connections of the developing brain. Correlating anatomical changes with gene-expression patterns is an essential step toward understanding the mechanisms regulating brain development. Traditionally, this is done in a cross-sectional manner, but the dynamic nature of development calls for probing gene-neuroanatomy interactions in a combined spatiotemporal domain. Here, we present a four-dimensional (4D) spatiotemporal continuum of the embryonic mouse brain from E10.5 to E15.5 reconstructed from diffusion magnetic resonance microscopy (dMRM) data. This study achieved unprecedented high-definition dMRM at 30- to 35-µm isotropic resolution, and together with computational neuroanatomy techniques, we revealed both morphological and microscopic changes in the developing brain. We transformed selected gene-expression data to this continuum and correlated them with the dMRM-based neuroanatomical changes in embryonic brains. Within the continuum, we identified distinct developmental modes comprising regional clusters that shared developmental trajectories and similar gene-expression profiles. Our results demonstrate how this 4D continuum can be used to examine spatiotemporal gene-neuroanatomical interactions by connecting upstream genetic events with anatomical changes that emerge later in development. This approach would be useful for large-scale analysis of the cooperative roles of key genes in shaping the developing brain.

The immune system in neurological diseases: What innate-like T cells have to say.

The immune system classically consists of 2 lines of defense, innate and adaptive, both of which interact with one another effectively to protect us against any pathogenic threats. Importantly, there is a diverse subset of cells known as innate-like T cells that act as a bridge between the innate and adaptive immune systems and are pivotal players in eliciting inflammatory immune responses. A growing body of evidence has demonstrated the regulatory impact of these innate-like T cells in central nervous system (CNS) diseases and that such immune cells can traffic into the brain in multiple pathological conditions, which can be typically attributed to the breakdown of the blood-brain barrier. However, until now, it has been poorly understood whether innate-like T cells have direct protective or causative properties, particularly in CNS diseases. Therefore, in this review, our attention is focused on discussing the critical roles of 3 unique subsets of unconventional T cells, namely, natural killer T cells, γδ T cells, and mucosal-associated invariant T cells, in the context of CNS diseases, disorders, and injuries and how the interplay of these immune cells modulates CNS pathology, in an attempt to gain a better understanding of their complex functions.

Weak and pleiotropy robust sex-stratified Mendelian randomization in the one sample and two sample settings.

BACKGROUND: Mendelian randomization (MR) leverages genetic data as an instrumental variable to provide estimates for the causal effect of an exposure X on a health outcome Y that is robust to confounding. Unfortunately, horizontal pleiotropy-the direct association of a genetic variant with multiple phenotypes-is highly prevalent and can easily render a genetic variant an invalid instrument. METHODS: Building on existing work, we propose a simple method for leveraging sex-specific genetic associations to perform weak and pleiotropy-robust MR analysis. This is achieved by constructing an MR estimator in which pleiotropy is perfectly removed by cancellation, while placing it within the powerful machinery of the robust adjusted profile score (MR-RAPS) method. Pleiotropy cancellation has the attractive property that it removes heterogeneity and therefore justifies a statistically efficient fixed effects model. We extend the method from the typical two-sample summary-data MR setting to the one-sample setting by adapting the technique of Collider-Correction. Simulation studies and applied examples are used to assess how the sex-stratified MR-RAPS estimator performs against other common approaches. RESULTS: The sex-stratified MR-RAPS method is shown to be robust to pleiotropy even in cases where all genetic variants violated the standard Instrument Strength Independent of Direct Effect assumption. In some cases where the strength of the pleiotropic effect additionally varied by sex (and so perfect cancellation was not achieved), over-dispersed MR-RAPS implementations can still consistently estimate the true causal effect. In applied analyses, we investigate the causal effect of waist-hip ratio (WHR), an important marker of central obesity, on a range of downstream traits. While the conventional approaches suggested paradoxical links between WHR and height and body mass index, the sex-stratified approach obtained a more realistic null effect. Nonzero effects were also detected for systolic and diastolic blood pressure as well as high-density and low-density lipoprotein cholesterol. DISCUSSION: We provide a simple but attractive method for weak and pleiotropy robust causal estimation of sexually dimorphic traits on downstream outcomes, by combining several existing approaches in a novel fashion.

Field study of the fire-blight-resistant cisgenic apple line C44.4.146.

Cisgenesis, the genetic modification of a plant with genes from a sexually compatible plant, was used to confer fire blight resistance to the cultivar 'Gala Galaxy' by amendment of the resistance gene FB_MR5, resulting in the line C44.4.146. To verify whether cisgenesis changed other tree-, flower- or fruit-related traits, a 5-year field trial was conducted with trees of C44.4.146 and multiple control genotypes, including members of the 'Gala' sports group. None of the 44 investigated tree-, flower- or fruit-related traits significantly differed between C44.4.146 and at least one of the control genotypes in all observation years. However, fruits of C44.4.146 and its wild-type 'Gala Galaxy' from tissue culture were paler in color than fruits of 'Gala Galaxy' that had not undergone tissue culture. There was no significant and consistently detected difference in the fruit flesh and peel metabolome of C44.4.146 compared with the control genotypes. Finally, the disease resistance of C44.4.146 was confirmed also when the fire blight pathogen was inoculated through the flowers. We conclude that the use of cisgenesis to confer fire blight resistance to 'Gala Galaxy' in C44.4.146 did not have unintended effects, and that the in vitro establishment of 'Gala Galaxy' had a greater effect on C44.4.146 properties than its generation applying cisgenesis.

The multidimensional value of natriuretic peptides in heart failure, integrating laboratory and clinical aspects.

Natriuretic peptides (NP) play an essential role in heart failure (HF) regulation, and their measurement has improved diagnostic and prognostic accuracy. Clinical symptoms and objective measurements, such as NP levels, should be included in the HF definition to render it more reliable and consistent among observers, hospitals, and healthcare systems. BNP and NT-proBNP are reasonable surrogates for cardiac disease, and their measurement is critical to early diagnosis and risk stratification of HF patients. NPs should be measured in all patients presenting with dyspnea or other symptoms suggestive of HF to facilitate early diagnosis and risk stratification. Both BNP and NT-proBNP are currently used for guided HF management and display comparable diagnostic and prognostic accuracy. Standardized cutoffs for each NP assay are essential for data comparison. The value of NP testing is recognized at various levels, including patient empowerment and education, analytical and operational issues, clinical HF management, and cost-effectiveness.

Peripheral blood MR1 tetramer-positive mucosal-associated invariant T-cell function is modulated by mammalian target of rapamycin complex 1 in patients with active tuberculosis.

Tuberculosis (TB) is still an urgent global public health problem. Notably, mucosal-associated invariant T (MAIT) cells play an important role in early anti-TB immune response. Targeted control of them may be an effective method to improve vaccine efficacy and TB treatment. However, the biology and signal regulation mechanisms of MAIT cells in TB patients are still poorly understood. Previous studies have been limited by the lack of reagents to specifically identify MAIT cells. In addition, the use of alternative markers may subsume non-MAIT cell into MAIT cell populations. In this study, the human MR1 tetramer which can specifically identify MAIT cells was used to further explore the effect and mechanism of MAIT cells in anti-TB immune response. Our results showed that the tetramer+ MAIT cells in peripheral blood of TB patients were mainly CD8+ or CD4-CD8- cells, and very few were CD4+ cells. After BCG infecting autologous antigen-presenting cells, MAIT cells in patients produced significantly higher levels of cytokines, lysis and proliferation compared with healthy controls. After suppression of mTORC1 by the mTORC1-specific inhibitor rapamycin, the immune response of MAIT cells in patients was significantly reduced. This study demonstrates that peripheral blood tetramer+ MAIT cells from TB patients have significant anti-TB immune effect, which is regulated by mTORC1. This could provide ideas and potential therapeutic targets for the development of novel anti-TB immunotherapy.

Gastroesophageal reflux disease and the risk of respiratory diseases: a Mendelian randomization study.

BACKGROUND: Observational studies have suggested a suspected association between gastroesophageal reflux disease (GERD) and respiratory diseases, but the causality remains equivocal. The goal of this study was to evaluate the causal role of GERD in respiratory diseases by employing Mendelian randomization (MR) studies. METHODS: We conducted Mendelian randomization analysis based on summary data of genome-wide association studies (GWASs) and three MR statistical techniques (inverse variance weighted, weighted median and MR-Egger) were employed to assess the probable causal relationship between GERD and the risk of respiratory diseases. Sensitivity analysis was also carried out to ensure more trustworthy results, which involves examining the heterogeneity, pleiotropy and leave-one-SNP-out method. We also identified 33 relevant genes and explored their distribution in 26 normal tissues. RESULTS: In the analysis, for every unit increase in developing GERD, the odds ratio for developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism rose by 72% (ORIVW = 1.72, 95% CI 1.50; 1.99), 19% (ORIVW = 1.19, 95% CI 1.11; 1.28), 16% (ORIVW = 1.16, 95% CI 1.07; 1.26), 0. 3% (ORIVW = 1.003, 95% CI 1.0012; 1.0043) and 33% (ORIVW = 1.33, 95% CI 1.12; 1.58), respectively, in comparison with non-GERD cases. In addition, neither heterogeneity nor pleiotropy was found in the study. This study also found that gene expression was higher in the central nervous system and brain tissue than in other normal tissues. CONCLUSIONS: This study provided evidence that people who developed GERD had a higher risk of developing COPD, bronchitis, pneumonia, lung cancer and pulmonary embolism. Our research suggests physicians to give effective treatments for GERD on respiratory diseases. By exploring the gene expression, our study may also help to reveal the role played by the central nervous system and brain tissue in developing respiratory diseases caused by GERD.

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

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

Diffusion-weighted MR spectroscopy of the prostate.

PURPOSE: Prostate tissue has a complex microstructure, mainly composed of epithelial and stromal cells, and of extracellular (acinar-luminal) spaces. Diffusion-weighted MR spectroscopy (DW-MRS) is ideally suited to explore complex microstructure in vivo with metabolites selectively distributed in different subspaces. To date, this technique has been applied to brain and muscle. This study presents the development and pioneering utilization of 1H-DW-MRS in the prostate, accompanied by in vitro studies to support interpretations of in vivo findings. METHODS: Nine healthy volunteers underwent a prostate MR examination (mean age, 56 years; range, 31-66). Metabolic complexation was studied in vitro using solutions with major compounds found in prostatic fluid of the lumen. DW-MRS was performed at 3 T with a non-water-suppressed single-voxel sequence with metabolite-cycling to concurrently measure metabolite and water signals. The water signal was used in postprocessing as a reference in a motion-compensation scheme. The spectra were fitted simultaneously in the spectral and diffusion-weighting dimensions. Apparent diffusion coefficients (ADCs) were derived by fitting signal decays that were assumed to be mono-exponential for metabolites and biexponential for water. RESULTS: DW-MRS of the prostate revealed relatively low ADCs for Cho and Cr compounds, aligning with their intracellular location and higher ADCs for citrate and spermine supporting their luminal origin. In vitro assessments of the ADCs of citrate and spermine demonstrated their complex formation and protein binding. Tissue concentrations of MRS-detectable metabolites were as expected for the voxel location. CONCLUSIONS: This work successfully demonstrates the feasibility of 1H-DW-MRS of the prostate and its potential for providing valuable microstructural information.

An augmented hybrid multibaseline and referenceless MR thermometry motion compensation algorithm for MRgHIFU hyperthermia.

PURPOSE: A hybrid principal component analysis and projection onto dipole fields (PCA-PDF) MR thermometry motion compensation algorithm was optimized with atlas image augmentation and validated. METHODS: Experiments were conducted on a 3T Philips MRI and Profound V1 Sonalleve high intensity focused ultrasound (high intensity focused ultrasound system. An MR-compatible robot was configured to induce motion on custom gelatin phantoms. Trials with periodic and sporadic motion were introduced on phantoms while hyperthermia was administered. The PCA-PDF algorithm was augmented with a predictive atlas to better compensate for larger sporadic motion. RESULTS: During periodic motion, the temperature SD in the thermometry was improved from 1 . 1 ± 0 . 1 $$ 1.1\pm 0.1 $$ to 0 . 5 ± 0 . 1 ∘ $$ 0.5\pm 0.{1}^{\circ } $$ C with both the original and augmented PCA-PDF application. For large sporadic motion, the augmented atlas improved the motion compensation from the original PCA-PDF correction from 8 . 8 ± 0 . 5 $$ 8.8\pm 0.5 $$ to 0 . 7 ± 0 . 1 ∘ $$ 0.7\pm 0.{1}^{\circ } $$ C. CONCLUSION: The PCA-PDF algorithm improved temperature accuracy to <1°C during periodic motion, but was not able to adequately address sporadic motion. By augmenting the PCA-PDF algorithm, temperature SD during large sporadic motion was also reduced to <1°C, greatly improving the original PCA-PDF algorithm.

Deep learning-assisted preclinical MR fingerprinting for sub-millimeter T1 and T2 mapping of entire macaque brain.

PURPOSE: Preclinical MR fingerprinting (MRF) suffers from long acquisition time for organ-level coverage due to demanding image resolution and limited undersampling capacity. This study aims to develop a deep learning-assisted fast MRF framework for sub-millimeter T1 and T2 mapping of entire macaque brain on a preclinical 9.4 T MR system. METHODS: Three dimensional MRF images were reconstructed by singular value decomposition (SVD) compressed reconstruction. T1 and T2 mapping for each axial slice exploited a self-attention assisted residual U-Net to suppress aliasing-induced quantification errors, and the transmit-field (B1 + ) measurements for robustness against B1 + inhomogeneity. Supervised network training used MRF images simulated via virtual parametric maps and a desired undersampling scheme. This strategy bypassed the difficulties of acquiring fully sampled preclinical MRF data to guide network training. The proposed fast MRF framework was tested on experimental data acquired from ex vivo and in vivo macaque brains. RESULTS: The trained network showed reasonable adaptability to experimental MRF images, enabling robust delineation of various T1 and T2 distributions in the brain tissues. Further, the proposed MRF framework outperformed several existing fast MRF methods in handling the aliasing artifacts and capturing detailed cerebral structures in the mapping results. Parametric mapping of entire macaque brain at nominal resolution of 0.35 × $$ \times $$ 0.35 × $$ \times $$ 1 mm3 can be realized via a 20-min 3D MRF scan, which was sixfold faster than the baseline protocol. CONCLUSION: Introducing deep learning to MRF framework paves the way for efficient organ-level high-resolution quantitative MRI in preclinical applications.

A reusable 3D printed brain-like phantom for benchmarking electrical properties tomography reconstructions.

PURPOSE: In MR electrical properties tomography (MR-EPT), electrical properties (EPs, conductivity and permittivity) are reconstructed from MR measurements. Phantom measurements are important to characterize the performance of MR-EPT reconstruction methods, since they allow knowledge of reference EPs values. To assess reconstruction methods in a more realistic scenario, it is important to test the methods using phantoms with realistic shapes, internal structures, and dielectric properties. In this work, we present a 3D printing procedure for the creation of realistic brain-like phantoms to benchmark MR-EPT reconstructions. METHODS: We created two brain-like geometries with three different compartments using 3D printing. The first geometry was filled once, while the second geometry was filled three times with different saline-gelatin solutions, resulting in a total of four phantoms with different EPs. The saline solutions were characterized using a probe. 3D MR-EPT reconstructions were performed from MR measurements at 3T. The reconstructed conductivity values were compared to reference values of the saline-gelatin solutions. The measured fields were also compared to simulated fields using the same phantom geometry and electrical properties. RESULTS: The measured fields were consistent with simulated fields. Reconstructed conductivity values were consistent with the reference (probe) conductivity values. This indicated the suitability of such phantoms for benchmarking MR-EPT reconstructions. CONCLUSION: We presented a new workflow to 3D print realistic brain-like phantoms in an easy and affordable way. These phantoms are suitable to benchmark MR-EPT reconstructions, but can also be used for benchmarking other quantitative MR methods.

Resolution enhancement, noise suppression, and joint T2* decay estimation in dual-echo sodium-23 MR imaging using anatomically guided reconstruction.

PURPOSE: Sodium MRI is challenging because of the low tissue concentration of the 23 Na nucleus and its extremely fast biexponential transverse relaxation rate. In this article, we present an iterative reconstruction framework using dual-echo 23 Na data and exploiting anatomical prior information (AGR) from high-resolution, low-noise, 1 H MR images. This framework enables the estimation and modeling of the spatially varying signal decay due to transverse relaxation during readout (AGRdm), which leads to images of better resolution and reduced noise resulting in improved quantification of the reconstructed 23 Na images. METHODS: The proposed framework was evaluated using reconstructions of 30 noise realizations of realistic simulations of dual echo twisted projection imaging (TPI) 23 Na data. Moreover, three dual echo 23 Na TPI brain datasets of healthy controls acquired on a 3T Siemens Prisma system were reconstructed using conventional reconstruction, AGR and AGRdm. RESULTS: Our simulations show that compared to conventional reconstructions, AGR and AGRdm show improved bias-noise characteristics in several regions of the brain. Moreover, AGR and AGRdm images show more anatomical detail and less noise in the reconstructions of the experimental data sets. Compared to AGR and the conventional reconstruction, AGRdm shows higher contrast in the sodium concentration ratio between gray and white matter and between gray matter and the brain stem. CONCLUSION: AGR and AGRdm generate 23 Na images with high resolution, high levels of anatomical detail, and low levels of noise, potentially enabling high-quality 23 Na MR imaging at 3T.