PURPOSE: To measure spatiotemporal B0 field changes in real time using FID navigators (FIDnavs) and to demonstrate the efficacy of retrospectively correcting high-resolution T 2 * -weighted images using a novel FIDnav framework. METHODS: A forward model of the complex FIDnav signals was generated by simulating the effect of changes in the underlying B0 inhomogeneity coefficients, with spatial encoding provided by a multi-channel reference image. Experiments were performed at 3T to assess the accuracy of B0 field estimates from FIDnavs acquired from a 64-channel head coil under different shim settings and in 5 volunteers performing deep-breathing and nose-touching tasks designed to modulate the B0 field. Second-order, in-plane spherical harmonic (SH) inhomogeneity coefficients estimated from FIDnavs were incorporated into an iterative reconstruction to retrospectively correct 2D gradient-echo images acquired in both axial and sagittal planes. RESULTS: Spatiotemporal B0 field changes measured from rapidly acquired FIDnavs were in good agreement with the results of second-order SH fitting to the measured field maps. FIDnav field estimates accounted for a significant proportion of the ΔB0 variance induced by deep breathing (64 ± 21%) and nose touching (67 ± 34%) across all volunteers. Ghosting, blurring, and intensity modulation artifacts in T 2 * -weighted images, induced by spatiotemporal field changes, were visibly reduced following retrospective correction with FIDnav inhomogeneity coefficients. CONCLUSIONS: Spatially resolved B0 inhomogeneity changes up to second order can be characterized in real time using the proposed approach. Retrospective FIDnav correction substantially improves T 2 * -weighted image quality in the presence of strong B0 field modulations, with potential for real-time shimming.

The desire to understand complex mental processes using functional MRI drives development of imaging techniques that scan the whole human brain at a high spatial and temporal resolution. In this work, an accelerated multishot three-dimensional echo-planar imaging sequence is proposed to increase the temporal resolution of these studies. A combination of two modern acceleration techniques, UNFOLD and GRAPPA is used in the secondary phase encoding direction to reduce the scan time effectively. The sequence (repetition time of 1.02 s) was compared with standard two-dimensional echo-planar imaging (3 s) and multishot three-dimensional echo-planar imaging (3 s) sequences with both block design and event-related functional MRI paradigms. With the same experimental setup and imaging time, the temporal resolution improvement with our sequence yields similar activation regions in the block design functional MRI paradigm with slightly increased t-scores. Moreover, additional information on the timing of rapid dynamic changes was extracted from accelerated images for the case of the event related complex mental paradigm.

BACKGROUND: Current methods to estimate glomerular filtration rate (GFR) have shortcomings. Estimates based on serum creatinine are known to be inaccurate in the chronically ill and during acute changes in renal function. Gold standard methods such as inulin and 99mTc diethylenetriamine pentaacetic acid (DTPA) require blood or urine sampling and thus can be difficult to perform in children. Motion-robust radial volumetric interpolated breath-hold examination (VIBE) dynamic contrast-enhanced MRI represents a novel tool for estimating GFR that has not been validated in children. OBJECTIVE: The purpose of our study was to determine the feasibility and accuracy of GFR measured by motion-robust radial VIBE dynamic contrast-enhanced MRI compared to estimates by serum creatinine (eGFR) and 99mTc DTPA in children. MATERIALS AND METHODS: We enrolled children, 0-18 years of age, who were undergoing both a contrast-enhanced MRI and nuclear medicine 99mTc DTPA glomerular filtration rate (NM-GFR) within 2 weeks of each other. Enrolled children consented to an additional 6-min dynamic contrast-enhanced MRI scan using the motion-robust high spatiotemporal resolution prototype dynamic radial VIBE sequence (Siemens, Erlangen, Germany) at 3 tesla (T). The images were reconstructed offline with high temporal resolution (~3 s/volume) using compressed sensing image reconstruction including regularization in temporal dimension to improve image quality and reduce streaking artifacts. Images were then automatically post-processed using in-house-developed software. Post-processing steps included automatic segmentation of kidney parenchyma and aorta using convolutional neural network techniques and tracer kinetic model fitting using the Sourbron two-compartment model to calculate the MR-based GFR (MR-GFR). The NM-GFR was compared to MR-GFR and estimated GFR based on serum creatinine (eGFR) using Pearson correlation coefficient and Bland-Altman analysis. RESULTS: Twenty-one children (7 female, 14 male) were enrolled between February 2017 and May 2018. Data from six of these children were not further analyzed because of deviations from the MRI protocol. Fifteen patients were analyzed (5 female, 10 male; average age 5.9 years); the method was technically feasible in all children. The results showed that the MR-GFR correlated with NM-GFR with a Pearson correlation coefficient (r-value) of 0.98. Bland-Altman analysis (i.e. difference of MR-GFR and NM-GFR versus mean of NM-GFR and MR-GFR) showed a mean difference of -0.32 and reproducibility coefficient of 18 with 95% confidence interval, and the coefficient of variation of 6.7% with values between -19 (-1.96 standard deviation) and 18 (+1.96 standard deviation). In contrast, serum creatinine compared with NM-GFR yielded an r-value of 0.73. Bland-Altman analysis (i.e. difference of eGFR and NM-GFR versus mean of NM-GFR and eGFR) showed a mean difference of 2.9 and reproducibility coefficient of 70 with 95% confidence interval, and the coefficient of variation of 25% with values between -67 (-1.96 standard deviation) and 73 (+1.96 standard deviation). CONCLUSION: MR-GFR is a technically feasible and reliable method of measuring GFR when compared to the reference standard, NM-GFR by serum 99mTc DTPA, and MR-GFR is more reliable than estimates based on serum creatinine.

PURPOSE: Abdominal MRI scans may require breath-holding to prevent image quality degradation, which can be challenging for patients, especially children. In this study, we evaluate whether FID navigators can be used to measure and correct for motion prospectively, in real-time. METHODS: FID navigators were inserted into a 3D radial sequence with stack-of-stars sampling. MRI experiments were conducted on 6 healthy volunteers. A calibration scan was first acquired to create a linear motion model that estimates the kidney displacement due to respiration from the FID navigator signal. This model was then applied to predict and prospectively correct for motion in real time during deep and continuous deep breathing scans. Resultant images acquired with the proposed technique were compared with those acquired without motion correction. Dice scores were calculated between inhale/exhale motion states. Furthermore, images acquired using the proposed technique were compared with images from extra-dimensional golden-angle radial sparse parallel, a retrospective motion state binning technique. RESULTS: Images reconstructed for each motion state show that the kidneys' position could be accurately tracked and corrected with the proposed method. The mean of Dice scores computed between the motion states were improved from 0.93 to 0.96 using the proposed technique. Depiction of the kidneys was improved in the combined images of all motion states. Comparing results of the proposed technique and extra-dimensional golden-angle radial sparse parallel, high-quality images can be reconstructed from a fraction of spokes using the proposed method. CONCLUSION: The proposed technique reduces blurriness and motion artifacts in kidney imaging by prospectively correcting their position both in-plane and through-slice.

This study used a swine model of mildly hypothermic prolonged circulatory arrest and found that the addition of 2.4% inhaled hydrogen gas to inspiratory gases during and after the ischemic insult significantly decreased neurologic and renal injury compared with controls. With proper precautions, inhalational hydrogen may be administered safely through conventional ventilators and may represent a complementary therapy that can be easily incorporated into current workflows. In the future, inhaled hydrogen may diminish the sequelae of ischemia that occurs in congenital heart surgery, cardiac arrest, extracorporeal life-support events, acute myocardial infarction, stroke, and organ transplantation.

OBJECTIVE: To determine normative ranges for fetal ocular biometrics between 19 and 38 weeks gestational age (GA) using volumetric MRI reconstruction. METHOD: The 3D images of 114 healthy fetuses between 19 and 38 weeks GA were created using super-resolution volume reconstructions from MRI slice acquisitions. These 3D images were semi-automatically segmented to measure fetal orbit volume, binocular distance (BOD), interocular distance (IOD), and ocular diameter (OD). RESULTS: All biometry correlated with GA (Volume, Pearson's correlation coefficient (CC) = 0.9680; BOD, CC = 0.9552; OD, CC = 0.9445; and IOD, CC = 0.8429), and growth curves were plotted against linear and quadratic growth models. Regression analysis showed quadratic models to best fit BOD, IOD, and OD and a linear model to best fit volume. CONCLUSION: Orbital volume had the greatest correlation with GA, although BOD and OD also showed strong correlation. The normative data found in this study may be helpful for the detection of congenital fetal anomalies with more consistent measurements than are currently available. © 2015 John Wiley & Sons, Ltd.

Background Tools in image reconstruction, motion correction, and segmentation have enabled the accurate volumetric characterization of fetal brain growth at MRI. Purpose To evaluate the volumetric growth of intracranial structures in healthy fetuses, accounting for gestational age (GA), sex, and laterality with use of a spatiotemporal MRI atlas of fetal brain development. Materials and Methods T2-weighted 3.0-T half-Fourier acquired single-shot turbo spin-echo sequence MRI was performed in healthy fetuses from prospectively recruited pregnant volunteers from March 2013 to May 2019. A previously validated section-to-volume reconstruction algorithm was used to generate intensity-normalized superresolution three-dimensional volumes that were registered to a fetal brain MRI atlas with 28 anatomic regions of interest. Atlas-based segmentation was performed and manually refined. Labels included the bilateral hippocampus, amygdala, caudate nucleus, lentiform nucleus, thalamus, lateral ventricle, cerebellum, cortical plate, hemispheric white matter, internal capsule, ganglionic eminence, ventricular zone, corpus callosum, brainstem, hippocampal commissure, and extra-axial cerebrospinal fluid. For fetuses younger than 31 weeks of GA, the subplate and intermediate zones were delineated. A linear regression analysis was used to determine weekly age-related change adjusted for sex and laterality. Results The final analytic sample consisted of 122 MRI scans in 98 fetuses (mean GA, 29 weeks ± 5 [range, 20-38 weeks]). All structures had significant volume growth with increasing GA (P < .001). Weekly age-related change for individual structures in the brain parenchyma ranged from 2.0% (95% CI: 0.9, 3.1; P < .001) in the hippocampal commissure to 19.4% (95% CI: 18.7, 20.1; P < .001) in the cerebellum. The largest sex-related differences were 22.1% higher volume in male fetuses for the lateral ventricles (95% CI: 10.9, 34.4; P < .001). There was rightward volumetric asymmetry of 15.6% for the hippocampus (95% CI: 14.2, 17.2; P < .001) and leftward volumetric asymmetry of 8.1% for the lateral ventricles (95% CI: 3.7, 12.2; P < .001). Conclusion With use of a spatiotemporal MRI atlas, volumetric growth of the fetal brain showed complex trajectories dependent on structure, gestational age, sex, and laterality. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Rollins in this issue.

Longitudinal characterization of early brain growth in-utero has been limited by a number of challenges in fetal imaging, the rapid change in size, shape and volume of the developing brain, and the consequent lack of suitable algorithms for fetal brain image analysis. There is a need for an improved digital brain atlas of the spatiotemporal maturation of the fetal brain extending over the key developmental periods. We have developed an algorithm for construction of an unbiased four-dimensional atlas of the developing fetal brain by integrating symmetric diffeomorphic deformable registration in space with kernel regression in age. We applied this new algorithm to construct a spatiotemporal atlas from MRI of 81 normal fetuses scanned between 19 and 39 weeks of gestation and labeled the structures of the developing brain. We evaluated the use of this atlas and additional individual fetal brain MRI atlases for completely automatic multi-atlas segmentation of fetal brain MRI. The atlas is available online as a reference for anatomy and for registration and segmentation, to aid in connectivity analysis, and for groupwise and longitudinal analysis of early brain growth.

BACKGROUND: The right ventricle (RV) often fails when functioning as the systemic ventricle, but the cause is not understood. We tested the hypothesis that myofiber organization is abnormal in the failing systemic right ventricle. METHODS: We used diffusion-weighted cardiovascular magnetic resonance imaging to examine 3 failing hearts explanted from young patients with a systemic RV and one structurally normal heart with postnatally acquired RV hypertrophy for comparison. Diffusion compartment imaging was computed to separate the free diffusive component representing free water from an anisotropic component characterizing the orientation and diffusion characteristics of myofibers. The orientation of each anisotropic compartment was displayed in glyph format and used for qualitative description of myofibers and for construction of tractograms. The helix angle was calculated across the ventricular walls in 5 locations and displayed graphically. Scalar parameters (fractional anisotropy and mean diffusivity) were compared among specimens. RESULTS: The hypertrophied systemic RV has an inner layer, comprising about 2/3 of the wall, composed of hypertrophied trabeculae and an epicardial layer of circumferential myofibers. Myofibers within smaller trabeculae are aligned and organized with parallel fibers while larger, composite bundles show marked disarray, largely between component trabeculae. We observed a narrow range of helix angles in the outer, compact part of the wall consistent with aligned, approximately circumferential fibers. However, there was marked variation of helix angle in the inner, trabecular part of the wall consistent with marked variation in fiber orientation. The apical whorl was disrupted or incomplete and we observed myocardial whorls or vortices at other locations. Fractional anisotropy was lower in abnormal hearts while mean diffusivity was more variable, being higher in 2 but lower in 1 heart, compared to the structurally normal heart. CONCLUSIONS: Myofiber organization is abnormal in the failing systemic RV and might be an important substrate for heart failure and arrhythmia. It is unclear if myofiber disorganization is due to hemodynamic factors, developmental problems, or both.

Spatial resolution plays a critically important role in MRI for the precise delineation of the imaged tissues. Unfortunately, acquisitions with high spatial resolution require increased imaging time, which increases the potential of subject motion, and suffers from reduced signal-to-noise ratio (SNR). Super-resolution reconstruction (SRR) has recently emerged as a technique that allows for a trade-off between high spatial resolution, high SNR, and short scan duration. Deconvolution-based SRR has recently received significant interest due to the convenience of using the image space. The most critical factor to succeed in deconvolution is the accuracy of the estimated blur kernels that characterize how the image was degraded in the acquisition process. Current methods use handcrafted filters, such as Gaussian filters, to approximate the blur kernels, and have achieved promising SRR results. As the image degradation is complex and varies with different sequences and scanners, handcrafted filters, unfortunately, do not necessarily ensure the success of the deconvolution. We sought to develop a technique that enables accurately estimating blur kernels from the image data itself. We designed a deep architecture that utilizes an adversarial scheme with a generative neural network against its degradation counterparts. This design allows for the SRR tailored to an individual subject, as the training requires the scan-specific data only, i.e., it does not require auxiliary datasets of high-quality images, which are practically challenging to obtain. With this technique, we achieved high-quality brain MRI at an isotropic resolution of 0.125 cubic mm with six minutes of imaging time. Extensive experiments on both simulated low-resolution data and clinical data acquired from ten pediatric patients demonstrated that our approach achieved superior SRR results as compared to state-of-the-art deconvolution-based methods, while in parallel, at substantially reduced imaging time in comparison to direct high-resolution acquisitions.