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Purpose To clarify the predominant causative plaque constituent for periprocedural myocardial injury (PMI) following percutaneous coronary intervention: (a) erythrocyte-derived materials, indicated by a high plaque-to-myocardium signal intensity ratio (PMR) at coronary atherosclerosis T1-weighted characterization (CATCH) MRI, or (b) lipids, represented by a high maximum 4-mm lipid core burden index (maxLCBI4 mm) at near-infrared spectroscopy intravascular US (NIRS-IVUS). Materials and Methods This retrospective study included consecutive patients who underwent CATCH MRI before elective NIRS-IVUS-guided percutaneous coronary intervention at two facilities. PMI was defined as post-percutaneous coronary intervention troponin T values greater than five times the upper reference limit. Multivariable analysis was performed to identify predictors of PMI. Finally, the predictive capabilities of MRI, NIRS-IVUS, and their combination were compared. Results A total of 103 lesions from 103 patients (median age, 72 years [IQR, 64-78]; 78 male patients) were included. PMI occurred in 36 lesions. In multivariable analysis, PMR emerged as the strongest predictor (P = .001), whereas maxLCBI4 mm was not a significant predictor (P = .07). When PMR was excluded from the analysis, maxLCBI4 mm emerged as the sole independent predictor (P = .02). The combination of MRI and NIRS-IVUS yielded the largest area under the receiver operating curve (0.86 [95% CI: 0.64, 0.83]), surpassing that of NIRS-IVUS alone (0.75 [95% CI: 0.64, 0.83]; P = .02) or MRI alone (0.80 [95% CI: 0.68, 0.88]; P = .30). Conclusion Erythrocyte-derived materials in plaques, represented by a high PMR at CATCH MRI, were strongly associated with PMI independent of lipids. MRI may play a crucial role in predicting PMI by offering unique pathologic insights into plaques, distinct from those provided by NIRS. Keywords: Coronary Plaque, Periprocedural Myocardial Injury, MRI, Near-Infrared Spectroscopy Intravascular US Supplemental material is available for this article. © RSNA, 2024.

Background: The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual’s entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities. Objective: Our goal is to create a non-invasive preclinical imaging pipeline that can longitudinally probe murine placental health in vivo. We use advanced imaging processing schemes to establish functional biomarkers for non-invasive longitudinal evaluation of placental development. Methodology: We implement dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and analysis pipeline to quantify uterine contraction and placental perfusion dynamics. We use optic flow and time-frequency analysis to quantify and characterize contraction-related placental motion. Our novel imaging and analysis pipeline uses subcutaneous administration of gadolinium for steepest slope-based perfusion evaluation, enabling non-invasive longitudinal monitoring. Results: We demonstrate that the placenta exhibits spatially asymmetric contractile motion that develops from E14.5 to E17.5. Additionally, we see that placental perfusion, perfusion delivery rate, and substrate delivery all increase from E14.5 to E17.5, with the High Perfusion Chamber (HPC) leading the placental changes that occur from E14.5 to E17.5 Discussion: We advance the placental perfusion chamber paradigm with a novel, physiologically based threshold model for chamber localization and demonstrate spatially varying placental chambers using multiple functional metrics that assess mouse placental development and remodeling throughout gestation. Conclusion: Our pipeline enables the non-invasive, longitudinal assessment of multiple placenta functions from a single imaging session. Our pipeline serves as a key toolbox for advancing research in mouse models of placental disease and disorder.

Cardiovascular magnetic resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically "all-in-one" CMR, where several contrasts and/or motion states are acquired simultaneously, and "real-time" CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR. To this end, the vision of each is described, along with techniques which have been devised and tested along the pathway of clinical implementation. The pros and cons of the different methods are presented, and the remaining open needs of each are detailed. Part 1 will tackle the "all-in-one" approaches, and Part 2 the "real-time" approaches along with an overall summary of these emerging methods.

High-intensity plaque (HIP) on magnetic resonance imaging (MRI) has been documented as a powerful predictor of periprocedural myocardial injury (PMI) following percutaneous coronary intervention (PCI). Despite the recent proposal of three-dimensional HIP quantification to enhance the predictive capability, the conventional pulse sequence, which necessitates the separate acquisition of anatomical reference images, hinders accurate three-dimensional segmentation along the coronary vasculature. Coronary atherosclerosis T1-weighted characterization (CATCH) enables the simultaneous acquisition of inherently coregistered dark-blood plaque and bright-blood coronary artery images. We aimed to develop a novel HIP quantification approach using CATCH and to ascertain its superior predictive performance compared to the conventional two-dimensional assessment based on plaque-to-myocardium signal intensity ratio (PMR). In this prospective study, CATCH MRI was conducted before elective stent implantation in 137 lesions from 125 patients. On CATCH images, dedicated software automatically generated tubular three-dimensional volumes of interest on the dark-blood plaque images along the coronary vasculature, based on the precisely matched bright-blood coronary artery images, and subsequently computed PMR and HIP volume (HIPvol). Specifically, HIPvol was calculated as the volume of voxels with signal intensity exceeding that of the myocardium, weighted by their respective signal intensities. PMI was defined as post-PCI cardiac troponin-T >5× the upper reference limit. The entire analysis process was completed within 3minutes per lesion. PMI occurred in 44 lesions. Based on the receiver operating characteristic curve analysis, HIPvol outperformed PMR for predicting PMI (C-statistics, 0.870 [95% CI, 0.805-0.936] vs. 0.787 [95% CI, 0.706-0.868]; p = 0.001). This result was primarily driven by the higher sensitivity HIPvol offered: 0.886 (95% CI, 0.754-0.962) vs. 0.750 for PMR (95% CI, 0.597-0.868; p = 0.034). Multivariable analysis identified HIPvol as an independent predictor of PMI (odds ratio, 1.15 per 10-μL increase; 95% CI, 1.01-1.30, p = 0.035). Our semi-automated method of analyzing coronary plaque using CATCH MRI provided rapid HIP quantification. Three-dimensional assessment using this approach had a better ability to predict PMI than conventional two-dimensional assessment.

PurposeWidely used conventional 2D T2 * approaches that are based on breath-held, electrocardiogram (ECG)-gated, multi-gradient-echo sequences are prone to motion artifacts in the presence of incomplete breath holding or arrhythmias, which is common in cardiac patients. To address these limitations, a 3D, non-ECG-gated, free-breathing T2 * technique that enables rapid whole-heart coverage was developed and validated.MethodsA continuous random Gaussian 3D k-space sampling was implemented using a low-rank tensor framework for motion-resolved 3D T2 * imaging. This approach was tested in healthy human volunteers and in swine before and after intravenous administration of ferumoxytol.ResultsSpatial-resolution matched T2 * images were acquired with 2-3-fold reduction in scan time using the proposed T2 * mapping approach relative to conventional T2 * mapping. Compared with the conventional approach, T2 * images acquired with the proposed method demonstrated reduced off-resonance and flow artifacts, leading to higher image quality and lower coefficient of variation in T2 *-weighted images of the myocardium of swine and humans. Mean myocardial T2 * values determined using the proposed and conventional approaches were highly correlated and showed minimal bias.ConclusionThe proposed non-ECG-gated, free-breathing, 3D T2 * imaging approach can be performed within 5 min or less. It can overcome critical image artifacts from undesirable cardiac and respiratory motion and bulk off-resonance shifts at the heart-lung interface. The proposed approach is expected to facilitate faster and improved cardiac T2 * mapping in those with limited breath-holding capacity or arrhythmias.

Introduction: Dynamic contrast-enhanced (DCE) MRI has important clinical value for early detection, accurate staging, and therapeutic monitoring of cancers. However, conventional multi-phasic abdominal DCE-MRI has limited temporal resolution and provides qualitative or semi-quantitative assessments of tissue vascularity. In this study, the feasibility of retrospectively quantifying multi-phasic abdominal DCE-MRI by using pharmacokinetics-informed deep learning to improve temporal resolution was investigated. Method: Forty-five subjects consisting of healthy controls, pancreatic ductal adenocarcinoma (PDAC), and chronic pancreatitis (CP) were imaged with a 2-s temporal-resolution quantitative DCE sequence, from which 30-s temporal-resolution multi-phasic DCE-MRI was synthesized based on clinical protocol. A pharmacokinetics-informed neural network was trained to improve the temporal resolution of the multi-phasic DCE before the quantification of pharmacokinetic parameters. Through ten-fold cross-validation, the agreement between pharmacokinetic parameters estimated from synthesized multi-phasic DCE after deep learning inference was assessed against reference parameters from the corresponding quantitative DCE-MRI images. The ability of the deep learning estimated parameters to differentiate abnormal from normal tissues was assessed as well. Results: The pharmacokinetic parameters estimated after deep learning have a high level of agreement with the reference values. In the cross-validation, all three pharmacokinetic parameters (transfer constant Ktrans, fractional extravascular extracellular volume ve, and rate constant kep) achieved intraclass correlation coefficient and R2 between 0.84–0.94, and low coefficients of variation (10.1%, 12.3%, and 5.6%, respectively) relative to the reference values. Significant differences were found between healthy pancreas, PDAC tumor and non-tumor, and CP pancreas. Discussion: Retrospective quantification (RoQ) of clinical multi-phasic DCE-MRI is possible by deep learning. This technique has the potential to derive quantitative pharmacokinetic parameters from clinical multi-phasic DCE data for a more objective and precise assessment of cancer.

T1 mapping is becoming a staple magnetic resonance imaging method for diagnosing myocardial diseases such as ischemic cardiomyopathy, hypertrophic cardiomyopathy, myocarditis, and more. Clinically, most T1 mapping sequences acquire a single slice at a single cardiac phase across a 10 to 15-heartbeat breath-hold, with one to three slices acquired in total. This leaves opportunities for improving patient comfort and information density by acquiring data across multiple cardiac phases in free-running acquisitions and across multiple respiratory phases in free-breathing acquisitions. Scanning in the presence of cardiac and respiratory motion requires more complex motion characterization and compensation. Most clinical mapping sequences use 2D single-slice acquisitions; however newer techniques allow for motion-compensated reconstructions in three dimensions and beyond. To further address confounding factors and improve measurement accuracy, T1 maps can be acquired jointly with other quantitative parameters such as T2, T2∗, fat fraction, and more. These multiparametric acquisitions allow for constrained reconstruction approaches that isolate contributions to T1 from other motion and relaxation mechanisms. In this review, we examine the state of the literature in motion-corrected and motion-resolved T1 mapping, with potential future directions for further technical development and clinical translation.

Simple lanthanide cyclopentadienyl (Cp) complexes can photochemically cleave the sp3 carbon-chlorine bond of unactivated chlorinated hydrocarbons including polyvinyl chloride (PVC). The excited state lifetimes of these simple complexes are among the longest observed for cerium complexes (175 ns for [(CpMe4)2Ce(μ-Cl)]2) and the light absorption by the Cp ligand is efficient, so photocatalytic reactivity is enhanced for cerium and now also made possible for neighboring, normally photoinactive, lanthanide congeners.

Abstract: Purpose: Deep learning superresolution (SR) is a promising approach to reduce MRI scan time without requiring custom sequences or iterative reconstruction. Previous deep learning SR approaches have generated low‐resolution training images by simple k‐space truncation, but this does not properly model in‐plane turbo spin echo (TSE) MRI resolution degradation, which has variable T2 relaxation effects in different k‐space regions. To fill this gap, we developed a T2‐deblurred deep learning SR method for the SR of 3D‐TSE images. Methods: A SR generative adversarial network was trained using physically realistic resolution degradation (asymmetric T2 weighting of raw high‐resolution k‐space data). For comparison, we trained the same network structure on previous degradation models without TSE physics modeling. We tested all models for both retrospective and prospective SR with 3 × 3 acceleration factor (in the two phase‐encoding directions) of genetically engineered mouse embryo model TSE‐MR images. Results: The proposed method can produce high‐quality 3 × 3 SR images for a typical 500‐slice volume with 6–7 mouse embryos. Because 3 × 3 SR was performed, the image acquisition time can be reduced from 15 h to 1.7 h. Compared to previous SR methods without TSE modeling, the proposed method achieved the best quantitative imaging metrics for both retrospective and prospective evaluations and achieved the best imaging‐quality expert scores for prospective evaluation. Conclusion: The proposed T2‐deblurring method improved accuracy and image quality of deep learning–based SR of TSE MRI. This method has the potential to accelerate TSE image acquisition by a factor of up to 9.

PurposeTo extend the MR MultiTasking-based Multidimensional Assessment of Cardiovascular System (MT-MACS) technique with larger spatial coverage and water-fat separation for comprehensive aortocardiac assessment.MethodsMT-MACS adopts a low-rank tensor image model for 7D imaging, with three spatial dimensions for volumetric imaging, one cardiac motion dimension for cine imaging, one respiratory motion dimension for free-breathing imaging, one T2-prepared inversion recovery time dimension for multi-contrast assessment, and one T2*-decay time dimension for water-fat separation. Nine healthy subjects were recruited for the 3T study. Overall image quality was scored on bright-blood (BB), dark-blood (DB), and gray-blood (GB) contrasts using a 4-point scale (0-poor to 3-excellent) by two independent readers, and their interreader agreement was evaluated. Myocardial wall thickness and left ventricular ejection fraction (LVEF) were quantified on DB and BB contrasts, respectively. The agreement in these metrics between MT-MACS and conventional breath-held, electrocardiography-triggered 2D sequences were evaluated.ResultsMT-MACS provides both water-only and fat-only images with excellent image quality (average score = 3.725/3.780/3.835/3.890 for BB/DB/GB/fat-only images) and moderate to high interreader agreement (weighted Cohen's kappa value = 0.727/0.668/1.000/1.000 for BB/DB/GB/fat-only images). There were good to excellent agreements in myocardial wall thickness measurements (intraclass correlation coefficients [ICC] = 0.781/0.929/0.680/0.878 for left atria/left ventricle/right atria/right ventricle) and LVEF quantification (ICC = 0.716) between MT-MACS and 2D references. All measurements were within the literature range of healthy subjects.ConclusionThe refined MT-MACS technique provides multi-contrast, phase-resolved, and water-fat imaging of the aortocardiac systems and allows evaluation of anatomy and function. Clinical validation is warranted.

BackgroundTraumatizing events often result in long-term mental health symptoms. Identifying the features of the post-trauma experiences that can impact mental health symptoms is key to designing effective interventions.MethodsYouth living with HIV (YLH),1 predominantly sexual and gender minorities (SGM;2 84 % gay, bisexual, transgender, queer, pansexual identities), 78 % Black and Latino, (N = 170) were recruited in New Orleans, LA and Los Angeles, CA from 13 youth-serving agencies. They were assessed for trauma, rumination and depression, with 78 % reassessed for depression at 4 and 74 % at 8 months later. Relationships between these variables were examined using a Bayesian approach to structural equation modeling.ResultsAt recruitment, 78 % of YLH reported at least one traumatic event, and 21 % met the cut-off score indicating depression on the PHQ-9. Ruminations were reported by 41 % of YLH. While associations between trauma and depression were modest (rmean = 0.19), ruminations were moderately associated with depressive symptoms over time (rmean = 0.34). Ruminations were only modestly associated with trauma (rmean = 0.19) but had a robust negative association (λSTD = -0.29) with the slope of depressive symptoms such that the more ruminations YLH experienced, the smaller the decline in depression over time. The associations between trauma and depression were more modest (λSTD ≤ 0.12). Limitations The main limitations of this study are the lack of a scale to measure trauma and the use of a single item measure of rumination.ConclusionRuminations appear to be associated with traumatic events for a large subset of young people, suggesting that future interventions should consider including components addressing ruminations.Clinicaltrialsgov registration NCT03109431.

The T2K experiment presents new measurements of neutrino oscillation parameters using 19.7(16.3)×1020 protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional 4.7×1020 POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on sin2θ13 and the impact of priors on the δCP measurement. Both analyses prefer the normal mass ordering and upper octant of sin2θ23 with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on sin2θ13 from reactors, sin2θ23=0.561-0.032+0.021 using Feldman-Cousins corrected intervals, and Δm322=2.494-0.058+0.041×10-3eV2 using constant Δχ2 intervals. The CP-violating phase is constrained to δCP=-1.97-0.70+0.97 using Feldman-Cousins corrected intervals, and δCP=0,π is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than 2σ credible level using a flat prior in δCP, and just below 2σ using a flat prior in sinδCP. When the external constraint on sin2θ13 is removed, sin2θ13=28.0-6.5+2.8×10-3, in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.

PurposeTo develop a deep learning-based method to retrospectively quantify T2 from conventional T1- and T2-weighted images.MethodsTwenty-five subjects were imaged using a multi-echo spin-echo sequence to estimate reference prostate T2 maps. Conventional T1- and T2-weighted images were acquired as the input images. A U-Net based neural network was developed to directly estimate T2 maps from the weighted images using a four-fold cross-validation training strategy. The structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), mean percentage error (MPE), and Pearson correlation coefficient were calculated to evaluate the quality of network-estimated T2 maps. To explore the potential of this approach in clinical practice, a retrospective T2 quantification was performed on a high-risk prostate cancer cohort (Group 1) and a low-risk active surveillance cohort (Group 2). Tumor and non-tumor T2 values were evaluated by an experienced radiologist based on region of interest (ROI) analysis.ResultsThe T2 maps generated by the trained network were consistent with the corresponding reference. Prostate tissue structures and contrast were well preserved, with a PSNR of 26.41 ± 1.17 dB, an SSIM of 0.85 ± 0.02, and a Pearson correlation coefficient of 0.86. Quantitative ROI analyses performed on 38 prostate cancer patients revealed estimated T2 values of 80.4 ± 14.4 ms and 106.8 ± 16.3 ms for tumor and non-tumor regions, respectively. ROI measurements showed a significant difference between tumor and non-tumor regions of the estimated T2 maps (P

PurposeTo develop an MR multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE) technique for simultaneous quantification of permeability and leakage-insensitive perfusion with a single-dose contrast injection.MethodsMT-DICE builds on a saturation-recovery prepared multi-echo fast low-angle shot sequence. The k-space is randomly sampled for 7.6 min, with single-dose contrast agent injected 1.5 min into the scan. MR multitasking is used to model the data into six dimensions, including three spatial dimensions for whole-brain coverage, a saturation-recovery time dimension, and a TE dimension for dynamic T1$$ {\mathrm{T}}_1 $$ and T2*$$ {\mathrm{T}}_2^{\ast } $$ quantification, respectively, and a contrast dynamics dimension for capturing contrast kinetics. The derived pixel-wise T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ time series are converted into contrast concentration-time curves for calculation of kinetic metrics. The technique was assessed for its agreement with reference methods in T1$$ {\mathrm{T}}_1 $$ and T2*$$ {\mathrm{T}}_2^{\ast } $$ measurements in eight healthy subjects and, in three of them, inter-session repeatability of permeability and leakage-insensitive perfusion parameters. Its feasibility was also demonstrated in four patients with brain tumors.ResultsMT-DICE T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ values of normal gray matter and white matter were in excellent agreement with reference values (intraclass correlation coefficients = 0.860/0.962 for gray matter and 0.925/0.975 for white matter ). Both permeability and perfusion parameters demonstrated good to excellent intersession agreement with the lowest intraclass correlation coefficients at 0.694. Contrast kinetic parameters in all healthy subjects and patients were within the literature range.ConclusionBased on dynamic T1/T2*$$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ mapping, MT-DICE allows for simultaneous quantification of permeability and leakage-insensitive perfusion metrics with a single-dose contrast injection.

Primary mitochondrial diseases are a group of genetically and clinically heterogeneous disorders resulting from oxidative phosphorylation (OXPHOS) defects. COX11 encodes a copper chaperone that participates in the assembly of complex IV and has not been previously linked to human disease. In a previous study, we identified that COX11 knockdown decreased cellular adenosine triphosphate (ATP) derived from respiration, and that ATP levels could be restored with coenzyme Q10 (CoQ10 ) supplementation. This finding is surprising since COX11 has no known role in CoQ10 biosynthesis. Here, we report a novel gene-disease association by identifying biallelic pathogenic variants in COX11 associated with infantile-onset mitochondrial encephalopathies in two unrelated families using trio genome and exome sequencing. Functional studies showed that mutant COX11 fibroblasts had decreased ATP levels which could be rescued by CoQ10 . These results not only suggest that COX11 variants cause defects in energy production but reveal a potential metabolic therapeutic strategy for patients with COX11 variants.

PURPOSE: MR elastography (MRE) is a technique to characterize brain mechanical properties in vivo. Due to the need to capture tissue deformation in multiple directions over time, MRE is an inherently long acquisition, which limits achievable resolution and use in challenging populations. The purpose of this work is to develop a method for accelerating MRE acquisition by using low-rank image reconstruction to exploit inherent spatiotemporal correlations in MRE data. THEORY AND METHODS: The proposed MRE sampling and reconstruction method, OSCILLATE (Observing Spatiotemporal Correlations for Imaging with Low-rank Leveraged Acceleration in Turbo Elastography), involves alternating which k-space points are sampled between each repetition by a reduction factor, ROSC. Using a predetermined temporal basis from a low-resolution navigator in a joint low-rank image reconstruction, all images can be accurately reconstructed from a reduced amount of k-space data. RESULTS: Decomposition of MRE displacement data demonstrated that, on average, 96.1% of all energy from an MRE dataset is captured at rank L = 12 (reduced from a full rank of 24). Retrospectively undersampling data with ROSC  = 2 and reconstructing at low-rank (L = 12) yields highly accurate stiffness maps with voxel-wise error of 5.8% ± 0.7%. Prospectively undersampled data at ROSC  = 2 were successfully reconstructed without loss of material property map fidelity, with average global stiffness error of 1.0% ± 0.7% compared to fully sampled data. CONCLUSIONS: OSCILLATE produces whole-brain MRE data at 2 mm isotropic resolution in 1 min 48 s.

PURPOSE: To develop a free-breathing, non-electrocardiogram technique for simultaneous myocardial T1 , T2 , T2 *, and fat-fraction (FF) mapping in a single scan. METHODS: The MR Multitasking framework is adapted to quantify T1 , T2 , T2 *, and FF simultaneously. A variable TR scheme is developed to preserve temporal resolution and imaging efficiency. The underlying high-dimensional image is modeled as a low-rank tensor, which allows accelerated acquisition and efficient reconstruction. The accuracy and/or repeatability of the technique were evaluated on static and motion phantoms, 12 healthy volunteers, and 3 patients by comparing to the reference techniques. RESULTS: In static and motion phantoms, T1 /T2 /T2 */FF measurements showed substantial consistency (R > 0.98) and excellent agreement (intraclass correlation coefficient > 0.93) with reference measurements. In human subjects, the proposed technique yielded repeatable T1 , T2 , T2 *, and FF measurements that agreed with those from references. CONCLUSIONS: The proposed free-breathing, non-electrocardiogram, motion-resolved Multitasking technique allows simultaneous quantification of myocardial T1 , T2 , T2 *, and FF in a single 2.5-min scan.

Objective.To develop and test the feasibility of a novel Single ProjectIon DrivEn Real-time Multi-contrast (SPIDERM) MR imaging technique that can generate real-time 3D images on-the-fly with flexible contrast weightings and a low latency.Approach.In SPIDERM, a 'prep' scan is first performed, with sparse k-space sampling periodically interleaved with the central k-space line (navigator data), to learn a subject-specific model, incorporating a spatial subspace and a linear transformation between navigator data and subspace coordinates. A 'live' scan is then performed by repeatedly acquiring the central k-space line only to dynamically determine subspace coordinates. With the 'prep'-learned subspace and 'live' coordinates, real-time 3D images are generated on-the-fly with computationally efficient matrix multiplication. When implemented based on a multi-contrast pulse sequence, SPIDERM further allows for data-driven image contrast regeneration to convert real-time contrast-varying images into contrast-frozen images at user's discretion while maintaining motion states. Both digital phantom andin-vivoexperiments were performed to evaluate the technical feasibility of SPIDERM.Main results.The elapsed time from the input of the central k-space line to the generation of real-time contrast-frozen 3D images was approximately 45 ms, permitting a latency of 55 ms or less. Motion displacement measured from SPIDERM and reference images showed excellent correlation (R2≥0.983). Geometric variation from the ground truth in the digital phantom was acceptable as demonstrated by pancreas contour analysis (Dice ≥ 0.84, mean surface distance ≤ 0.95 mm). Quantitative image quality metrics showed good consistency between reference images and contrast-varying SPIDREM images inin-vivostudies (meanNMRSE=0.141,PSNR=30.12,SSIM=0.88).Significance.SPIDERM is capable of generating real-time multi-contrast 3D images with a low latency. An imaging framework based on SPIDERM has the potential to serve as a standalone package for MR-guided radiation therapy by offering adaptive simulation through a 'prep' scan and real-time image guidance through a 'live' scan.

PurposeTo perform fast 3D steady-state CEST (ss-CEST) imaging using MR Multitasking.MethodsA continuous acquisition sequence with repetitive ss-CEST modules was developed. Each ss-CEST module contains a single-lobe Gaussian saturation pulse, followed by a spoiler gradient and eight FLASH readouts (one "training line" + seven "imaging lines"). Three-dimensional Cartesian encoding was used for k-space acquisition. Reconstructed CEST images were quantified with four-pool Lorentzian fitting.ResultsSteady-state CEST with whole-brain coverage was performed in 5.6 s per saturation frequency offset at the spatial resolution of 1.7 × 1.7 × 3.0 mm3 . The total scan time was 5.5 min for 55 different frequency offsets. Quantitative CEST maps from multipool fitting showed consistent image quality across the volume.ConclusionThree-dimensional ss-CEST with whole-brain coverage can be done at 3 T within 5.5 min using MR Multitasking.

Non-Cartesian sampling with subspace-constrained image reconstruction is a popular approach to dynamic MRI, but slow iterative reconstruction limits its clinical application. Data-consistent (DC) deep learning can accelerate reconstruction with good image quality, but has not been formulated for non-Cartesian subspace imaging. In this study, we propose a DC non-Cartesian deep subspace learning framework for fast, accurate dynamic MR image reconstruction. Four novel DC formulations are developed and evaluated: two gradient decent approaches, a directly solved approach, and a conjugate gradient approach. We applied a U-Net model with and without DC layers to reconstruct T1-weighted images for cardiac MR Multitasking (an advanced multidimensional imaging method), comparing our results to the iteratively reconstructed reference. Experimental results show that the proposed framework significantly improves reconstruction accuracy over the U-Net model without DC, while significantly accelerating the reconstruction over conventional iterative reconstruction.

PurposeTo develop a new technique that enables simultaneous quantification of whole-brain T1 , T2 , T2∗ , as well as susceptibility and synthesis of six contrast-weighted images in a single 9.1-minute scan.MethodsThe technique uses hybrid T2 -prepared inversion-recovery pulse modules and multi-echo gradient-echo readouts to collect k-space data with various T1, T2, and T2∗ weightings. The underlying image is represented as a six-dimensional low-rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi-echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast-weighted images was also examined.ResultsHigh quality, co-registered T1 , T2 , and T2∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and T2∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast-weighted images.ConclusionThe MR Multitasking-based 3D brain mapping of T1 , T2 , T2∗ , and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.

Background and aimsAccurate differentiation of chronic pancreatitis (CP) and pancreatic ductal adenocarcinoma (PDAC) is an area of unmet clinical need. In this study, a novel Multitasking dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) technique was used to quantitatively evaluate the microcirculation properties of pancreas in CP and PDAC and differentiate between them.MethodsThe Multitasking DCE technique was able to acquire one 3D image per second during the passage of MRI contrast agent, allowing the quantitative estimation of microcirculation properties of tissue, including blood flow Fp, plasma volume fraction vp, transfer constant Ktrans, and extravascular extracellular volume fraction ve. Receiver operating characteristic (ROC) analysis was performed to differentiate the CP pancreas, PDAC pancreas, normal control pancreas, PDAC tumor, PDAC upstream, and PDAC downstream. ROCs from quantitative analysis and conventional analysis were compared.ResultsFourteen PDAC patients, 8 CP patients and 20 healthy subjects were prospectively recruited. The combination of Fp, vp, Ktrans, and ve can differentiate CP versus PDAC pancreas with good AUC (AUC [95% CI] = 0.821 [0.654 - 0.988]), CP versus normal pancreas with excellent AUC (1.000 [1.000 - 1.000]), PDAC pancreas versus normal pancreas with excellent AUC (1.000 [1.000 - 1.000]), CP versus PDAC tumor with excellent AUC (1.000 [1.000 - 1.000]), CP versus PDAC downstream with excellent AUC (0.917 [0.795 - 1.000]), and CP versus PDAC upstream with fair AUC (0.722 [0.465 - 0.980]). This quantitative analysis outperformed conventional analysis in differentiation of each pair.ConclusionMultitasking DCE MRI is a promising clinical tool that is capable of unbiased quantitative differentiation between CP from PDAC.

PurposeTo address head motion in brain MRI with a novel motion-resolved imaging framework, with application to motion-robust quantitative multiparametric mapping.MethodsMR multitasking conceptualizes the underlying multiparametric image in the presence of motion as a multidimensional low-rank tensor. By incorporating a motion-state dimension into the parameter dimensions and introducing unsupervised motion-state binning and outlier motion reweighting mechanisms, the brain motion can be readily resolved for motion-robust quantitative imaging. A numerical motion phantom was used to simulate different discrete and periodic motion patterns under various translational and rotational scenarios, as well as investigate the sensitivity to exceptionally small and large displacements. In vivo brain MRI was performed to also evaluate different real discrete and periodic motion patterns. The effectiveness of motion-resolved imaging for simultaneous T1 /T2 /T1ρ mapping in the brain was investigated.ResultsFor all 14 simulation scenarios of small, intermediate, and large motion displacements, the motion-resolved approach produced T1 /T2 /T1ρ maps with less absolute difference errors against the ground truth, lower RMSE, and higher structural similarity index measure of T1 /T2 /T1ρ measurements compared to motion removal, and no motion handling. For in vivo experiments, the motion-resolved approach produced T1 /T2 /T1ρ maps with the best image quality free from motion artifacts under random discrete motion, tremor, periodic shaking, and nodding patterns compared to motion removal and no motion handling. The proposed method also yielded T1 /T2 /T1ρ measurement distributions closest to the motion-free reference, with minimal measurement bias and variance.ConclusionMotion-resolved quantitative brain imaging is achieved with multitasking, which is generalizable to various head motion patterns without explicit need for registration-based motion correction.

PurposeTo develop a deep-learning-based method to quantify multiple parameters in the brain from conventional contrast-weighted images.MethodsEighteen subjects were imaged using an MR Multitasking sequence to generate reference T1 and T2 maps in the brain. Conventional contrast-weighted images consisting of T1 MPRAGE, T1 GRE, and T2 FLAIR were acquired as input images. A U-Net-based neural network was trained to estimate T1 and T2 maps simultaneously from the contrast-weighted images. Six-fold cross-validation was performed to compare the network outputs with the MR Multitasking references.ResultsThe deep-learning T1 /T2 maps were comparable with the references, and brain tissue structures and image contrasts were well preserved. A peak signal-to-noise ratio >32 dB and a structural similarity index >0.97 were achieved for both parameter maps. Calculated on brain parenchyma (excluding CSF), the mean absolute errors (and mean percentage errors) for T1 and T2 maps were 52.7 ms (5.1%) and 5.4 ms (7.1%), respectively. ROI measurements on four tissue compartments (cortical gray matter, white matter, putamen, and thalamus) showed that T1 and T2 values provided by the network outputs were in agreement with the MR Multitasking reference maps. The mean differences were smaller than ± 1%, and limits of agreement were within ± 5% for T1 and within ± 10% for T2 after taking the mean differences into account.ConclusionA deep-learning-based technique was developed to estimate T1 and T2 maps from conventional contrast-weighted images in the brain, enabling simultaneous qualitative and quantitative MRI without modifying clinical protocols.

PurposeTo develop a 3D multitasking multi-echo (MT-ME) technique for the comprehensive characterization of liver tissues with 5-min free-breathing acquisition; whole-liver coverage; a spatial resolution of 1.5 × 1.5 × 6 mm3 ; and simultaneous quantification of T1 , water-specific T1 (T1w ), proton density fat fraction (PDFF), and R2∗ .MethodsSix-echo bipolar spoiled gradient echo readouts following inversion recovery preparation was performed to generate T1 , water/fat, and R2∗ contrast. MR multitasking was used to reconstruct the MT-ME images with 3 spatial dimensions: 1 T1 recovery dimension, 1 multi-echo dimension, and 1 respiratory dimension. A basis function-based approach was developed for T1w quantification, followed by the estimation of R2∗ and T1 -corrected PDFF. The intrasession repeatability and agreement against references of MT-ME measurements were tested on a phantom and 15 clinically healthy subjects. In addition, 4 patients with confirmed liver diseases were recruited, and the agreement between MT-ME measurements and references was assessed.ResultsMT-ME produced high-quality, coregistered T1 , T1w , PDFF, and R2∗ maps with good intrasession repeatability and substantial agreement with references on phantom and human studies. The intra-class coefficients of T1 , T1w , PDFF, and R2∗ from the repeat MT-ME measurements on clinically healthy subjects were 0.989, 0.990, 0.999, and 0.988, respectively. The intra-class coefficients of T1 , PDFF, and R2∗ between the MT-ME and reference measurements were 0.924, 0.987, and 0.975 in healthy subjects and 0.980, 0.999, and 0.998 in patients. The T1w was independent to PDFF (R = -0.029, P = .904).ConclusionThe proposed MT-ME technique quantifies T1 , T1w , PDFF, and R2∗ simultaneously and is clinically promising for the comprehensive characterization of liver tissue properties.

The aim of this study is to simultaneously quantify T1/T2 across three slices of the left-ventricular myocardium without breath-holds or ECG monitoring, all within a 3 min scan. Radial simultaneous multi-slice (SMS) encoding, self-gating, and image reconstruction was incorporated into the cardiovascular magnetic resonance (CMR) Multitasking framework to simultaneously image three short-axis slices. A T2prep-IR FLASH sequence with two flip angles was designed and implemented to allow B1+-robust T1 and T2 mapping. The proposed Multitasking-SMS method was validated in a standardized phantom and 10 healthy volunteers, comparing T1 and T2 measurements and scan-rescan repeatability against corresponding reference methods in one layer of phantom vials and in 16 American Heart Association (AHA) myocardial segments. In phantom, Multitasking-SMS T1/T2 measurements showed substantial correlation (R 2 > 0.996) and excellent agreement [intraclass correlation coefficients (ICC) ≥ 0.999)] with reference measurements. In healthy volunteers, Multitasking-SMS T1/T2 maps reported similar myocardial T1/T2 values (1,215 ± 91.0/41.5 ± 6.3 ms) to the reference myocardial T1/T2 values (1,239 ± 67.5/42.7 ± 4.1 ms), with P = 0.347 and P = 0.296, respectively. Bland-Altman analyses also demonstrated good in vivo repeatability in both the multitasking and references, with segment-wise coefficients of variation of 4.7% (multitasking T1), 8.9% (multitasking T2), 2.4% [modified look-locker inversion recovery (MOLLI)], and 4.6% (T2-prep FLASH), respectively. In summary, multitasking-SMS is feasible for free-breathing, non-ECG, myocardial T1/T2 quantification in 16 AHA segments over 3 short-axis slices in 3 min. The method shows the great potential for reducing exam time for quantitative CMR without ECG or breath-holds.

PurposeTo develop a single-scan method for B1+ -corrected T1 mapping and apply it for free-breathing (FB) cardiac MR multitasking without electrocardiogram (ECG) triggering.MethodsOne dual flip-angle (2FA) inversion recovery (IR)-FLASH scan provides two observations of T1∗ (apparent T1 ) corresponding to two distinct combinations of the nominal FA α and B1+ . Spatiotemporally coregistered T1 and B1+ spin history maps are obtained by fitting the 2FA signal model. T1 estimate accuracy and repeatability for single flip-angle (1FA) and 2FA IR-FLASH sequence MR multitasking were evaluated at 3T. A T1 phantom was first imaged on the scanner table, then on two human subjects' thoraxes in both breath-hold (BH) and FB conditions. IR-turbo spin echo (IR-TSE) static phantom T1 measurements served as reference. In 10 healthy subjects, myocardial T1 was evaluated with ECG-free, FB multitasking sequences alongside ECG-triggered BH MOLLI.ResultsFor phantom-on-table T1 estimates, 2FA agreed better with IR-TSE (intraclass correlation coefficient [ICC] = 0.996, mean error ± SD = -1.6% ± 1.9%) than did 1FA (ICC = 0.922; mean error ± SD = -4.3% ± 12%). For phantom-on-thorax, 2FA was more repeatable and robust to respiration than 1FA (coefficient of variation [CoV] = 1.2% 2FA, = 11.3% 1FA). In vivo, in intrasession T1 repeatability, 2FA (septal CoV = 2.4%, six-segment CoV = 4.4%) outperformed 1FA (septal CoV = 3.1%, six-segment CoV = 5.5%). In six-segment T1 homogeneity, 2FA (CoV = 7.9%) also outperformed 1FA (CoV = 11.1%).ConclusionThe 2FA IR-FLASH improves T1 estimate accuracy and repeatability over 1FA IR-FLASH, and enables single-scan B1+ -corrected T1 mapping without BHs or ECG when used with MR multitasking.

Adherence to antiretroviral therapy (ART) among youth remains low. We piloted an adapted active visualization device that demonstrates how ART works in the body. Youth living with HIV were randomized to: (1) standard care (n = 14) or the (2) adapted active visualization intervention (n = 14) and 71% of the sample (n = 19) were re-assessed on viral load, adherence behaviors, and illness perceptions 2.5 months later. Intervention youth had lower viral loads, reported less difficulty in adhering to ART, and more motivation and control over their HIV than standard care at follow-up. Active visualization may be an acceptable tool to address ART adherence among youth.

Adherence to antiretroviral therapy (ART) among youth remains low. We piloted an adapted active visualization device that demonstrates how ART works in the body. Youth living with HIV were randomized to: (1) standard care (n = 14) or the (2) adapted active visualization intervention (n = 14) and 71% of the sample (n = 19) were re-assessed on viral load, adherence behaviors, and illness perceptions 2.5 months later. Intervention youth had lower viral loads, reported less difficulty in adhering to ART, and more motivation and control over their HIV than standard care at follow-up. Active visualization may be an acceptable tool to address ART adherence among youth.

Adherence to antiretroviral therapy (ART) among youth remains low. We piloted an adapted active visualization device that demonstrates how ART works in the body. Youth living with HIV were randomized to: (1) standard care (n = 14) or the (2) adapted active visualization intervention (n = 14) and 71% of the sample (n = 19) were re-assessed on viral load, adherence behaviors, and illness perceptions 2.5 months later. Intervention youth had lower viral loads, reported less difficulty in adhering to ART, and more motivation and control over their HIV than standard care at follow-up. Active visualization may be an acceptable tool to address ART adherence among youth.

Teebi hypertelorism syndrome (THS; OMIM 145420) is a rare craniofacial disorder characterized by hypertelorism, prominent forehead, short nose with broad or depressed nasal root. Some cases of THS have been attributed to SPECC1L variants. Homozygous variants in CDH11 truncating the transmembrane and intracellular domains have been implicated in Elsahy-Waters syndrome (EWS; OMIM 211380) with hypertelorism. We report THS due to CDH11 heterozygous missense variants on 19 subjects from 9 families. All affected residues in the extracellular region of Cadherin-11 (CHD11) are highly conserved across vertebrate species and classical cadherins. Six of the variants that cluster around the EC2-EC3 and EC3-EC4 linker regions are predicted to affect Ca2+ binding that is required for cadherin stability. Two of the additional variants [c.164G > C, p.(Trp55Ser) and c.418G > A, p.(Glu140Lys)] are also notable as they are predicted to directly affect trans-homodimer formation. Immunohistochemical study demonstrates that CDH11 is strongly expressed in human facial mesenchyme. Using multiple functional assays, we show that five variants from the EC1, EC2-EC3 linker, and EC3 regions significantly reduced the cell-substrate trans adhesion activity and one variant from EC3-EC4 linker results in changes in cell morphology, focal adhesion, and migration, suggesting dominant negative effect. Characteristic features in this cohort included depressed nasal root, cardiac and umbilical defects. These features distinguished this phenotype from that seen in SPECC1L-related hypertelorism syndrome and CDH11-related EWS. Our results demonstrate heterozygous variants in CDH11, which decrease cell-cell adhesion and increase cell migratory behavior, cause a form of THS, as termed CDH11-related THS.

Households experiencing intimate partner violence (IPV) and food insecurity are at high risk of lifelong physical and behavioral difficulties. Longitudinal data from a perinatal home-visiting cluster-randomized controlled intervention trial in South Africa townships were used to examine the relationships between household settings and mothers' histories of risk and children's behavior problems at 3 and 5 years of age. IPV, food insecurity, maternal depressed mood, and geriatric pregnancy (at age of 35 or older) were consistently associated with children's internalizing and externalizing behavior problems. Aggressive behavior was more prevalent among 3- and 5-year olds boys, and was associated with maternal alcohol use. The effects of these factors on child behavior were more prominent than maternal HIV status. There is a continuing need to reduce IPV and household food insecurity, as well as supporting older, depressed, alcohol using mothers in order to address children's behavioral needs.

The T2K experiment reports updated measurements of neutrino and antineutrino oscillations using both appearance and disappearance channels. This result comes from an exposure of 14.9(16.4)×1020 protons on target in neutrino (antineutrino) mode. Significant improvements have been made to the neutrino interaction model and far detector reconstruction. An extensive set of simulated data studies have also been performed to quantify the effect interaction model uncertainties have on the T2K oscillation parameter sensitivity. T2K performs multiple oscillation analyses that present both frequentist and Bayesian intervals for the Pontecorvo-Maki-Nakagawa-Sakata parameters. For fits including a constraint on sin2θ13 from reactor data and assuming normal mass ordering T2K measures sin2θ23=0.53-0.04+0.03 and Δm322=(2.45±0.07)×10-3 eV2 c-4. The Bayesian analyses show a weak preference for normal mass ordering (89% posterior probability) and the upper sin2θ23 octant (80% posterior probability), with a uniform prior probability assumed in both cases. The T2K data exclude CP conservation in neutrino oscillations at the 2σ level.

This paper reports the first T2K measurement of the transverse kinematic imbalance in the single-π+ production channel of neutrino interactions. We measure the differential cross sections in the muon-neutrino charged-current interaction on hydrocarbon with a single π+ and at least one proton in the final state, at the ND280 off axis near detector of the T2K experiment. The extracted cross sections are compared to the predictions from different neutrino-nucleus interaction event generators. Overall, the results show a preference for models that have a more realistic treatment of nuclear medium effects including the initial nuclear state and final-state interactions.

This paper reports the first T2K measurement of the transverse kinematic imbalance in the single-π+ production channel of neutrino interactions. We measure the differential cross sections in the muon-neutrino charged-current interaction on hydrocarbon with a single π+ and at least one proton in the final state, at the ND280 off axis near detector of the T2K experiment. The extracted cross sections are compared to the predictions from different neutrino-nucleus interaction event generators. Overall, the results show a preference for models that have a more realistic treatment of nuclear medium effects including the initial nuclear state and final-state interactions.

The T2K experiment reports updated measurements of neutrino and antineutrino oscillations using both appearance and disappearance channels. This result comes from an exposure of 14.9(16.4)×1020 protons on target in neutrino (antineutrino) mode. Significant improvements have been made to the neutrino interaction model and far detector reconstruction. An extensive set of simulated data studies have also been performed to quantify the effect interaction model uncertainties have on the T2K oscillation parameter sensitivity. T2K performs multiple oscillation analyses that present both frequentist and Bayesian intervals for the Pontecorvo-Maki-Nakagawa-Sakata parameters. For fits including a constraint on sin2θ13 from reactor data and assuming normal mass ordering T2K measures sin2θ23=0.53-0.04+0.03 and Δm322=(2.45±0.07)×10-3 eV2 c-4. The Bayesian analyses show a weak preference for normal mass ordering (89% posterior probability) and the upper sin2θ23 octant (80% posterior probability), with a uniform prior probability assumed in both cases. The T2K data exclude CP conservation in neutrino oscillations at the 2σ level.

Households experiencing intimate partner violence (IPV) and food insecurity are at high risk of lifelong physical and behavioral difficulties. Longitudinal data from a perinatal home-visiting cluster-randomized controlled intervention trial in South Africa townships were used to examine the relationships between household settings and mothers' histories of risk and children's behavior problems at 3 and 5 years of age. IPV, food insecurity, maternal depressed mood, and geriatric pregnancy (at age of 35 or older) were consistently associated with children's internalizing and externalizing behavior problems. Aggressive behavior was more prevalent among 3- and 5-year olds boys, and was associated with maternal alcohol use. The effects of these factors on child behavior were more prominent than maternal HIV status. There is a continuing need to reduce IPV and household food insecurity, as well as supporting older, depressed, alcohol using mothers in order to address children's behavioral needs.

PurposeWe aimed to develop a novel free-breathing cardiac diffusion tensor MRI (DT-MRI) approach, M2-MT-MOCO, capable of whole left ventricular coverage that leverages second-order motion compensation (M2) diffusion encoding and multitasking (MT) framework to efficiently correct for respiratory motion (MOCO).MethodsImaging was performed in 16 healthy volunteers and 3 heart failure patients with symptomatic dyspnea. The healthy volunteers were scanned to compare the accuracy of interleaved multislice coverage of the entire left ventricle with a single-slice acquisition and the accuracy of the free-breathing conventional MOCO and MT-MOCO approaches with reference breath-hold DT-MRI. Mean diffusivity (MD), fractional anisotropy (FA), helix angle transmurality (HAT), and intrascan repeatability were quantified and compared.ResultsIn all subjects, free-breathing M2-MT-MOCO DT-MRI yielded DWI of the entire left ventricle without bulk motion-induced signal loss. No significant differences were seen in the global values of MD, FA, and HAT in the multislice and single-slice acquisitions. Furthermore, global quantification of MD, FA, and HAT were also not significantly different between the MT-MOCO and breath-hold, whereas conventional MOCO yielded significant differences in MD, FA, and HAT with MT-MOCO and FA with breath-hold. In heart failure patients, M2-MT-MOCO DT-MRI was feasible yielding higher MD, lower FA, and lower HAT compared with healthy volunteers. Substantial agreement was found between repeated scans across all subjects for MT-MOCO.ConclusionM2-MT-MOCO enables free-breathing DT-MRI of the entire left ventricle in 10 min, while preserving quantification of myocardial microstructure compared to breath-held and single-slice acquisitions and is feasible in heart failure patients.

We report measurements of the flux-integrated and + charged-current cross-sections on water and hydrocarbon targets using the T2K anti-neutrino beam with a mean beam energy of 0.86 GeV. The signal is defined as the (anti-)neutrino charged-current interaction with one induced and no detected charged pion or proton. These measurements are performed using a new WAGASCI module recently added to the T2K setup in combination with the INGRID Proton Module. The phase space of muons is restricted to the high-detection efficiency region, 400 and 30 , in the laboratory frame. An absence of pions and protons in the detectable phase spaces of 200, 70 and 600, 70 is required. In this paper, both the; cross-sections and +; cross-sections on water and hydrocarbon targets and their ratios are provided by using the D'Agostini unfolding method. The results of the integrated ; cross-section measurements over this phase space are ;\sigma{\rm H{2}O}=(1.082\pm0.068(\rm stat.) {+0.145}{-0.128}(\rm syst.)) \times 10 {-39}\,{\rm cm {2} / nucleon};, ;\sigma{\rm CH}=(1.096\pm0.054(\rm stat.) {+0.132}{-0.117}(\rm syst.)) \times 10 {-39}\,{\rm cm {2} / nucleon};, and ;\sigma{\rm H{2}O}/\sigma{\rm CH} = 0.987\pm0.078(\rm stat.) {+0.093}{-0.090}(\rm syst.);. The +; cross-section is ;\sigma{\rm H{2}O} = (1.155\pm0.064(\rm stat.) {+0.148}{-0.129}(\rm syst.)) \times 10 {-39}\,{\rm cm {2} / nucleon};, ;\sigma{\rm CH}=(1.159\pm0.049(\rm stat.) {+0.129}{-0.115}(\rm syst.)) \times 10 {-39}\,{\rm cm {2} / nucleon};, and ;\sigma{\rm H{2}O}/\sigma{\rm CH}=0.996\pm0.069(\rm stat.) {+0.083}{-0.078}(\rm syst.);.

PurposeTo develop a 3D whole-brain simultaneous T1/T2/T1ρ quantification method with MR Multitasking that provides high quality, co-registered multiparametric maps in 9 min.MethodsMR Multitasking conceptualizes T1/T2/T1ρ relaxations as different time dimensions, simultaneously resolving all three dimensions with a low-rank tensor image model. The proposed method was validated on a phantom and in healthy volunteers, comparing quantitative measurements against corresponding reference methods and evaluating the scan-rescan repeatability. Initial clinical validation was performed in age-matched relapsing-remitting multiple sclerosis (RRMS) patients to examine the feasibility of quantitative tissue characterization and to compare with the healthy control cohort. The feasibility of synthesizing six contrast-weighted images was also examined.ResultsOur framework produced high quality, co-registered T1/T2/T1ρ maps that closely resemble the reference maps. Multitasking T1/T2/T1ρ measurements showed substantial agreement with reference measurements on the phantom and in healthy controls. Bland-Altman analysis indicated good in vivo repeatability of all three parameters. In RRMS patients, lesions were conspicuously delineated on all three maps and on four synthetic weighted images (T2-weighted, T2-FLAIR, double inversion recovery, and a novel "T1ρ-FLAIR" contrast). T1 and T2 showed significant differences for normal appearing white matter between patients and controls, while T1ρ showed significant differences for normal appearing white matter, cortical gray matter, and deep gray matter. The combination of three parameters significantly improved the differentiation between RRMS patients and healthy controls, compared to using any single parameter alone.ConclusionMR Multitasking simultaneously quantifies whole-brain T1/T2/T1ρ and is clinically promising for quantitative tissue characterization of neurological diseases, such as MS.

BackgroundExtracellular volume fraction (ECV) quantification with cardiovascular magnetic resonance (CMR) T1 mapping is a powerful tool for the characterization of focal or diffuse myocardial fibrosis. However, it is technically challenging to acquire high-quality T1 and ECV maps in small animals for preclinical research because of high heart rates and high respiration rates. In this work, we developed an electrocardiogram (ECG)-less, free-breathing ECV mapping method using motion-resolved CMR Multitasking on a 9.4 T small animal CMR system. The feasibility of characterizing diffuse myocardial fibrosis was tested in a rat heart failure model with preserved ejection fraction (HFpEF).MethodsHigh-salt fed rats diagnosed with HFpEF (n = 9) and control rats (n = 9) were imaged with the proposed ECV Multitasking technique. A 25-min exam, including two 4-min T1 Multitasking scans before and after gadolinium injection, were performed on each rat. It allows a cardiac temporal resolution of 20 ms for a heart rate of ~ 300 bpm. Myocardial ECV was calculated from the hematocrit (HCT) and fitted T1 values of the myocardium and the blood pool. Masson's trichrome stain was used to measure the extent of fibrosis. Welch's t-test was performed between control and HFpEF groups.ResultsECV was significantly higher in the HFpEF group (22.4% ± 2.5% vs. 18.0% ± 2.1%, P = 0.0010). A moderate correlation between the ECV and the extent of fibrosis was found (R = 0.59, P = 0.0098).ConclusionsMotion-resolved ECV Multitasking CMR can quantify ECV in the rat myocardium at high heart rates without ECG triggering or respiratory gating. Elevated ECV found in the HFpEF group is consistent with previous human studies and well correlated with histological data. This technique has the potential to be a viable imaging tool for myocardial tissue characterization in small animal models.

BackgroundExtracellular volume fraction (ECV) quantification with cardiovascular magnetic resonance (CMR) T1 mapping is a powerful tool for the characterization of focal or diffuse myocardial fibrosis. However, it is technically challenging to acquire high-quality T1 and ECV maps in small animals for preclinical research because of high heart rates and high respiration rates. In this work, we developed an electrocardiogram (ECG)-less, free-breathing ECV mapping method using motion-resolved CMR Multitasking on a 9.4 T small animal CMR system. The feasibility of characterizing diffuse myocardial fibrosis was tested in a rat heart failure model with preserved ejection fraction (HFpEF).MethodsHigh-salt fed rats diagnosed with HFpEF (n = 9) and control rats (n = 9) were imaged with the proposed ECV Multitasking technique. A 25-min exam, including two 4-min T1 Multitasking scans before and after gadolinium injection, were performed on each rat. It allows a cardiac temporal resolution of 20 ms for a heart rate of ~ 300 bpm. Myocardial ECV was calculated from the hematocrit (HCT) and fitted T1 values of the myocardium and the blood pool. Masson's trichrome stain was used to measure the extent of fibrosis. Welch's t-test was performed between control and HFpEF groups.ResultsECV was significantly higher in the HFpEF group (22.4% ± 2.5% vs. 18.0% ± 2.1%, P = 0.0010). A moderate correlation between the ECV and the extent of fibrosis was found (R = 0.59, P = 0.0098).ConclusionsMotion-resolved ECV Multitasking CMR can quantify ECV in the rat myocardium at high heart rates without ECG triggering or respiratory gating. Elevated ECV found in the HFpEF group is consistent with previous human studies and well correlated with histological data. This technique has the potential to be a viable imaging tool for myocardial tissue characterization in small animal models.

BackgroundMore than 50% of Africa's population lives in rural areas, which have few professional health workers. South Africa has adopted task shifting health care to Community Health Workers (CHWs) to achieve the Sustainable Development Goals, but little is known about CHWs' efficacy in rural areas.MethodsIn this longitudinal prospective cohort study, almost all mothers giving birth (N = 470) in the Zithulele Hospital catchment area of the OR Tambo District were recruited and repeatedly assessed for 2 years after birth with 84.7-96% follow-up rates. During the cohort assessment we found that some mothers had received standard antenatal and HIV care (SC) (n = 313 mothers), while others had received SC, supplemented with home-visiting by CHWs before and after birth (HV) (n = 157 mothers, 37 CHWs). These visits were unrelated to the cohort study. Multiple linear and logistic regressions evaluated maternal comorbidities, maternal caretaking, and child development outcomes over time.ResultsCompared to mothers receiving SC, mothers who also received home visits by CHWs were more likely to attend the recommended four antenatal care visits, to exclusively breastfeed at 3 months, and were less likely to consult traditional healers at 3 months. Mothers in both groups were equally likely to secure the child grant, and infant growth and achievement of developmental milestones were similar over the first 2 years of life.ConclusionCHW home visits resulted in better maternal caretaking, but did not have direct benefits for infants in the domains assessed. The South African Government is planning broad implementation of CHW programmes, and this study examines a comprehensive, home-visiting model in a rural region.

PurposeTo develop an MR multitasking-based multidimensional assessment of cardiovascular system (MT-MACS) with electrocardiography-free and navigator-free data acquisition for a comprehensive evaluation of thoracic aortic diseases.MethodsThe MT-MACS technique adopts a low-rank tensor image model with a cardiac time dimension for phase-resolved cine imaging and a T2 -prepared inversion-recovery dimension for multicontrast assessment. Twelve healthy subjects and 2 patients with thoracic aortic diseases were recruited for the study at 3 T, and both qualitative (image quality score) and quantitative (contrast-to-noise ratio between lumen and wall, lumen and wall area, and aortic strain index) analyses were performed in all healthy subjects. The overall image quality was scored based on a 4-point scale: 3, excellent; 2, good; 1, fair; and 0, poor. Statistical analysis was used to test the measurement agreement between MT-MACS and its corresponding 2D references.ResultsThe MT-MACS images reconstructed from acquisitions as short as 6 minutes demonstrated good or excellent image quality for bright-blood (2.58 ± 0.46), dark-blood (2.58 ± 0.50), and gray-blood (2.17 ± 0.53) contrast weightings, respectively. The contrast-to-noise ratios for the three weightings were 49.2 ± 12.8, 20.0 ± 5.8 and 2.8 ± 1.8, respectively. There were good agreements in the lumen and wall area (intraclass correlation coefficient = 0.993, P < .001 for lumen; intraclass correlation coefficient = 0.969, P < .001 for wall area) and strain (intraclass correlation coefficient = 0.947, P < .001) between MT-MACS and conventional 2D sequences.ConclusionThe MT-MACS technique provides high-quality, multidimensional images for a comprehensive assessment of the thoracic aorta. Technical feasibility was demonstrated in healthy subjects and patients with thoracic aortic diseases. Further clinical validation is warranted.

Asparagine-linked glycosylation 13 homolog (ALG13) encodes a nonredundant, highly conserved, X-linked uridine diphosphate (UDP)-N-acetylglucosaminyltransferase required for the synthesis of lipid linked oligosaccharide precursor and proper N-linked glycosylation. De novo variants in ALG13 underlie a form of early infantile epileptic encephalopathy known as EIEE36, but given its essential role in glycosylation, it is also considered a congenital disorder of glycosylation (CDG), ALG13-CDG. Twenty-four previously reported ALG13-CDG cases had de novo variants, but surprisingly, unlike most forms of CDG, ALG13-CDG did not show the anticipated glycosylation defects, typically detected by altered transferrin glycosylation. Structural homology modeling of two recurrent de novo variants, p.A81T and p.N107S, suggests both are likely to impact the function of ALG13. Using a corresponding ALG13-deficient yeast strain, we show that expressing yeast ALG13 with either of the highly conserved hotspot variants rescues the observed growth defect, but not its glycosylation abnormality. We present molecular and clinical data on 29 previously unreported individuals with de novo variants in ALG13. This more than doubles the number of known cases. A key finding is that a vast majority of the individuals presents with West syndrome, a feature shared with other CDG types. Among these, the initial epileptic spasms best responded to adrenocorticotropic hormone or prednisolone, while clobazam and felbamate showed promise for continued epilepsy treatment. A ketogenic diet seems to play an important role in the treatment of these individuals.

The rate of cell growth is crucial for bacterial fitness and drives the allocation of bacterial resources, affecting, for example, the expression levels of proteins dedicated to metabolism and biosynthesis1,2. It is unclear, however, what ultimately determines growth rates in different environmental conditions. Moreover, increasing evidence suggests that other objectives are also important3-7, such as the rate of physiological adaptation to changing environments8,9. A common challenge for cells is that these objectives cannot be independently optimized, and maximizing one often reduces another. Many such trade-offs have indeed been hypothesized on the basis of qualitative correlative studies8-11. Here we report a trade-off between steady-state growth rate and physiological adaptability in Escherichia coli, observed when a growing culture is abruptly shifted from a preferred carbon source such as glucose to fermentation products such as acetate. These metabolic transitions, common for enteric bacteria, are often accompanied by multi-hour lags before growth resumes. Metabolomic analysis reveals that long lags result from the depletion of key metabolites that follows the sudden reversal in the central carbon flux owing to the imposed nutrient shifts. A model of sequential flux limitation not only explains the observed trade-off between growth and adaptability, but also allows quantitative predictions regarding the universal occurrence of such tradeoffs, based on the opposing enzyme requirements of glycolysis versus gluconeogenesis. We validate these predictions experimentally for many different nutrient shifts in E. coli, as well as for other respiro-fermentative microorganisms, including Bacillus subtilis and Saccharomyces cerevisiae.

PurposeTo develop a quantitative DCE MRI technique enabling entire-abdomen coverage, free-breathing acquisition, 1-second temporal resolution, and T1 -based quantification of contrast agent concentration and kinetic modeling for the characterization of pancreatic ductal adenocarcinoma (PDAC).MethodsSegmented FLASH readouts following saturation-recovery preparation with randomized 3D Cartesian undersampling was used for incoherent data acquisition. MR Multitasking was used to reconstruct 6-dimensional images with 3 spatial dimensions, 1 T1 recovery dimension for dynamic T1 quantification, 1 respiratory dimension to resolve respiratory motion, and 1 DCE time dimension to capture the contrast kinetics. Sixteen healthy subjects and 14 patients with pathologically confirmed PDAC were recruited for the in vivo studies, and kinetic parameters vp , Ktrans , ve , and Kep were evaluated for each subject. Intersession repeatability of Multitasking DCE was assessed in 8 repeat healthy subjects. One-way unbalanced analysis of variance was performed between control and patient groups.ResultsIn vivo studies demonstrated that vp , Ktrans , and Kep of PDAC were significantly lower compared with nontumoral regions in the patient group (P = .002, .003, .004, respectively) and normal pancreas in the control group (P = .011,