Association between placental oxygen transport and fetal brain cortical development: a study in monochorionic diamniotic twins.

Normal cortical growth and the resulting folding patterns are crucial for normal brain function. Although cortical development is largely influenced by genetic factors, environmental factors in fetal life can modify the gene expression associated with brain development. As the placenta plays a vital role in shaping the fetal environment, affecting fetal growth through the exchange of oxygen and nutrients, placental oxygen transport might be one of the environmental factors that also affect early human cortical growth. In this study, we aimed to assess the placental oxygen transport during maternal hyperoxia and its impact on fetal brain development using MRI in identical twins to control for genetic and maternal factors. We enrolled 9 pregnant subjects with monochorionic diamniotic twins (30.03 ± 2.39 gestational weeks [mean ± SD]). We observed that the fetuses with slower placental oxygen delivery had reduced volumetric and surface growth of the cerebral cortex. Moreover, when the difference between placenta oxygen delivery increased between the twin pairs, sulcal folding patterns were more divergent. Thus, there is a significant relationship between placental oxygen transport and fetal brain cortical growth and folding in monochorionic twins.

Local SAR management strategies to use two-channel RF shimming for fetal MRI at 3 T.

PURPOSE: This study evaluates the imaging performance of two-channel RF-shimming for fetal MRI at 3 T using four different local specific absorption rate (SAR) management strategies. METHODS: Due to the ambiguity of safe local SAR levels for fetal MRI, local SAR limits for RF shimming were determined based on either each individual's own SAR levels in standard imaging mode (CP mode) or the maximum SAR level observed across seven pregnant body models in CP mode. Local SAR was constrained either indirectly by further constraining the whole-body SAR (wbSAR) or directly by using subject-specific local SAR models. Each strategy was evaluated by the improvement of the transmit field efficiency (average |B1 + |) and nonuniformity (|B1 + | variation) inside the fetus compared with CP mode for the same wbSAR. RESULTS: Constraining wbSAR when using RF shimming decreases B1 + efficiency inside the fetus compared with CP mode (by 12%-30% on average), making it inefficient for SAR management. Using subject-specific models with SAR limits based on each individual's own CP mode SAR value, B1 + efficiency and nonuniformity are improved on average by 6% and 13% across seven pregnant models. In contrast, using SAR limits based on maximum CP mode SAR values across seven models, B1 + efficiency and nonuniformity are improved by 13% and 25%, compared with the best achievable improvement without SAR constraints: 15% and 26%. CONCLUSION: Two-channel RF-shimming can safely and significantly improve the transmit field inside the fetus when subject-specific models are used with local SAR limits based on maximum CP mode SAR levels in the pregnant population.

Cross-Sectional Observational Study of Typical in utero Fetal Movements Using Machine Learning.

Early variations of fetal movements are the hallmark of a healthy developing central nervous system. However, there are no automatic methods to quantify the complex 3D motion of the developing fetus in utero. The aim of this prospective study was to use machine learning (ML) on in utero MRI to perform quantitative kinematic analysis of fetal limb movement, assessing the impact of maternal, placental, and fetal factors. In this cross-sectional, observational study, we used 76 sets of fetal (24-40 gestational weeks [GW]) blood oxygenation level-dependent (BOLD) MRI scans of 52 women (18-45 years old) during typical pregnancies. Pregnant women were scanned for 5-10 min while breathing room air (21% O2) and for 5-10 min while breathing 100% FiO2 in supine and/or lateral position. BOLD acquisition time was 20 min in total with effective temporal resolution approximately 3 s. To quantify upper and lower limb kinematics, we used a 3D convolutional neural network previously trained to track fetal key points (wrists, elbows, shoulders, ankles, knees, hips) on similar BOLD time series. Tracking was visually assessed, errors were manually corrected, and the absolute movement time (AMT) for each joint was calculated. To identify variables that had a significant association with AMT, we constructed a mixed-model ANOVA with interaction terms. Fetuses showed significantly longer duration of limb movements during maternal hyperoxia. We also found a significant centrifugal increase of AMT across limbs and significantly longer AMT of upper extremities <31 GW and longer AMT of lower extremities >35 GW. In conclusion, using ML we successfully quantified complex 3D fetal limb motion in utero and across gestation, showing maternal factors (hyperoxia) and fetal factors (gestational age, joint) that impact movement. Quantification of fetal motion on MRI is a potential new biomarker of fetal health and neuromuscular development.

Safety and imaging performance of two-channel RF shimming for fetal MRI at 3T.

PURPOSE: This study investigates whether two-channel radiofrequency (RF) shimming can improve imaging without increasing specific absorption rate (SAR) for fetal MRI at 3T. METHODS: Transmit field ( B1+ ) average and variation in the fetus was simulated in seven numerical pregnant body models. Safety was quantified by maternal and fetal peak local SAR and fetal average SAR. The shim parameter space was divided into improved B1+ (magnitude and homogeneity) and improved SAR regions, and an overlap where RF shimming improved both classes of metrics compared with birdcage mode was assessed. Additionally, the effect of fetal position, tissue detail, and dielectric properties on transmit field and SAR was studied. RESULTS: A region of subject-specific RF shim parameter space improving both B1+ and SAR metrics was found for five of the seven models. Optimizing only B1+ metrics improved B1+ efficiency across models by 15% on average and 28% for the best-case model. B1+ variation improved by 26% on average and 49% for the best case. However, for these shim settings, fetal SAR increased by up to 106%. The overlap region, where both B1+ and SAR metrics improve, showed an average B1+ efficiency improvement of 6% on average across models and 19% for the best-case model. B1+ variation improved by 13% on average and 40% for the best case. RFS could also decrease maternal/fetal SAR by up to 49%/58%. CONCLUSION: RF shimming can improve imaging compared with birdcage mode without increasing fetal and maternal SAR when a patient-specific SAR model is incorporated into the shimming procedure.

Individual variation in simulated fetal SAR assessed in multiple body models.

PURPOSE: We generate 12 models from 4 pregnant individuals to evaluate individual differences in local specific absorption rate (SAR) for differing body habitus and fetal and maternal positions. METHODS: Structural MR images from 4 pregnant subjects (including supine and left-lateral maternal positions) were manually segmented to create 12 body models by rotating the fetus, modifying the fat content, and altering the maternal arm position in 1 of the subjects. Electromagnetic simulations modeled at 3 Tesla determined the average and peak local SAR in the maternal trunk, fetus, fetal brain, and amniotic fluid. RESULTS: We observed a significant range of fetal and maternal peak local SAR across the models (maternal trunk: 19.14-44.03 watts/kg, fetus: 9.93-18.79 watts/kg, fetal brain 3.36-10.3 watts/kg). We found that maternal body habitus changes introduced a significant variation in the maternal peak local SAR but not the fetal local SAR. However, the maternal position (either rotating the mother to left-lateral position or altering the arm position) introduced changes in fetal peak local SAR (range: 11.9-17.9 watts/kg). Rotating the fetus also introduced variation in the fetal and fetal brain peak local SAR. CONCLUSION: The observed variation in SAR emphasizes the need for more anatomical models to enable better safety management of individuals during fetal MRI, including a wider range of gestational ages.

Exploring early human brain development with structural and physiological neuroimaging.

Early brain development, from the embryonic period to infancy, is characterized by rapid structural and functional changes. These changes can be studied using structural and physiological neuroimaging methods. In order to optimally acquire and accurately interpret this data, concepts from adult neuroimaging cannot be directly transferred. Instead, one must have a basic understanding of fetal and neonatal structural and physiological brain development, and the important modulators of this process. Here, we first review the major developmental milestones of transient cerebral structures and structural connectivity (axonal connectivity) followed by a summary of the contributions from ex vivo and in vivo MRI. Next, we discuss the basic biology of neuronal circuitry development (synaptic connectivity, i.e. ensemble of direct chemical and electrical connections between neurons), physiology of neurovascular coupling, baseline metabolic needs of the fetus and the infant, and functional connectivity (defined as statistical dependence of low-frequency spontaneous fluctuations seen with functional magnetic resonance imaging (fMRI)). The complementary roles of magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS) are discussed. We include a section on modulators of brain development where we focus on the placenta and emerging placental MRI approaches. In each section we discuss key technical limitations of the imaging modalities and some of the limitations arising due to the biology of the system. Although neuroimaging approaches have contributed significantly to our understanding of early brain development, there is much yet to be done and a dire need for technical innovations and scientific discoveries to realize the future potential of early fetal and infant interventions to avert long term disease.

Radiofrequency heating studies on anesthetized swine using fractionated dipole antennas at 10.5 T.

PURPOSE: To validate electromagnetic and thermal simulations with in vivo temperature measurements, and to demonstrate a framework that can be used to predict temperature increase caused by radiofrequency (RF) excitation with dipole transmitter arrays. METHODS: Dipole arrays were used to deliver RF energy in the back/neck region of the swine using different RF excitation patterns (n = 2-4 per swine) for heating. The temperature in anesthetized swine (n = 3) was measured using fluoroscopic probes (n = 12) and compared against thermal modeling from animal-specific electromagnetic simulations. RESULTS: Simulated temperature curves were in agreement with the measured data. The root mean square error between simulated and measured temperature rise at all locations (at the end of each RF excitation) is calculated as 0.37°C. The mean experimental temperature rise at the maximum temperature rise locations (averaged over all experiments) is calculated as 2.89°C. The root mean square error between simulated and measured temperature at the maximum temperature rise location is calculated as 0.57°C. (Error values are averaged over all experiments.) CONCLUSIONS: Electromagnetic and thermal simulations were validated with experiments. Thermal effects of RF excitation at 10.5 Tesla with dipoles were investigated. Magn Reson Med 79:479-488, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Spatiotemporal alignment of in utero BOLD-MRI series.

PURPOSE: To present a method for spatiotemporal alignment of in-utero magnetic resonance imaging (MRI) time series acquired during maternal hyperoxia for enabling improved quantitative tracking of blood oxygen level-dependent (BOLD) signal changes that characterize oxygen transport through the placenta to fetal organs. MATERIALS AND METHODS: The proposed pipeline for spatiotemporal alignment of images acquired with a single-shot gradient echo echo-planar imaging includes 1) signal nonuniformity correction, 2) intravolume motion correction based on nonrigid registration, 3) correction of motion and nonrigid deformations across volumes, and 4) detection of the outlier volumes to be discarded from subsequent analysis. BOLD MRI time series collected from 10 pregnant women during 3T scans were analyzed using this pipeline. To assess pipeline performance, signal fluctuations between consecutive timepoints were examined. In addition, volume overlap and distance between manual region of interest (ROI) delineations in a subset of frames and the delineations obtained through propagation of the ROIs from the reference frame were used to quantify alignment accuracy. A previously demonstrated rigid registration approach was used for comparison. RESULTS: The proposed pipeline improved anatomical alignment of placenta and fetal organs over the state-of-the-art rigid motion correction methods. In particular, unexpected temporal signal fluctuations during the first normoxia period were significantly decreased (P < 0.01) and volume overlap and distance between region boundaries measures were significantly improved (P < 0.01). CONCLUSION: The proposed approach to align MRI time series enables more accurate quantitative studies of placental function by improving spatiotemporal alignment across placenta and fetal organs. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:403-412.

Approximate Fourier domain expression for Bloch-Siegert shift.

PURPOSE: In this study, a new simple Fourier domain-based analytical expression for the Bloch-Siegert (BS) shift-based B1 mapping method is proposed to obtain |B1+| more accurately while using short BS pulse durations and small off-resonance frequencies. THEORY AND METHODS: A new simple analytical expression for the BS shift is derived by simplifying the Bloch equations. In this expression, the phase is calculated in terms of the Fourier transform of the radiofrequency pulse envelope, and thus making the off- and on-resonance effects more easily understandable. To verify the accuracy of the proposed expression, Bloch simulations and MR experiments are performed for the hard, Fermi, and Shinner-Le Roux pulse shapes. RESULTS: Analyses of the BS phase shift-based B1 mapping method in terms of radiofrequency pulse shape, pulse duration, and off-resonance frequency show that |B1+| can be obtained more accurately with the aid of this new expression. CONCLUSIONS: In this study, a new simple frequency domain analytical expression is proposed for the BS shift. Using this expression, |B1+| values can be predicted from the phase data using the frequency spectrum of the radiofrequency pulse. This method works well even for short pulse durations and small offset frequencies.

SE(3)-Equivariant and Noise-Invariant 3D Rigid Motion Tracking in Brain MRI.

Rigid motion tracking is paramount in many medical imaging applications where movements need to be detected, corrected, or accounted for. Modern strategies rely on convolutional neural networks (CNN) and pose this problem as rigid registration. Yet, CNNs do not exploit natural symmetries in this task, as they are equivariant to translations (their outputs shift with their inputs) but not to rotations. Here we propose EquiTrack, the first method that uses recent steerable SE(3)-equivariant CNNs (E-CNN) for motion tracking. While steerable E-CNNs can extract corresponding features across different poses, testing them on noisy medical images reveals that they do not have enough learning capacity to learn noise invariance. Thus, we introduce a hybrid architecture that pairs a denoiser with an E-CNN to decouple the processing of anatomically irrelevant intensity features from the extraction of equivariant spatial features. Rigid transforms are then estimated in closed-form. EquiTrack outperforms state-of-the-art learning and optimisation methods for motion tracking in adult brain MRI and fetal MRI time series. Our code is available at https://github.com/BBillot/EquiTrack.

Reduction of the radiofrequency heating of metallic devices using a dual-drive birdcage coil.

In this work, it is demonstrated that a dual-drive birdcage coil can be used to reduce the radiofrequency heating of metallic devices during magnetic resonance imaging. By controlling the excitation currents of the two channels of a birdcage coil, the radiofrequency current that is induced near the lead tip could be set to zero. To monitor the current, the image artifacts near the lead tips were measured. The electric field distribution was controlled using a dual-drive birdcage coil. With this method, the lead currents and the lead tip temperatures were reduced substantially [<0.3 °C for an applied 4.4 W/kg SAR compared to >4.9 °C using quadrature excitation], as demonstrated by phantom and animal experiments. The homogeneity of the flip angle distribution was preserved, as shown by volunteer experiments. The normalized root-mean-square error of the flip angle distribution was less than 10% for all excitations. The average specific absorption rate increased as a trade-off for using different excitation patterns.

Volumetric Parameterization of the Placenta to a Flattened Template.

We present a volumetric mesh-based algorithm for parameterizing the placenta to a flattened template to enable effective visualization of local anatomy and function. MRI shows potential as a research tool as it provides signals directly related to placental function. However, due to the curved and highly variable in vivo shape of the placenta, interpreting and visualizing these images is difficult. We address interpretation challenges by mapping the placenta so that it resembles the familiar ex vivo shape. We formulate the parameterization as an optimization problem for mapping the placental shape represented by a volumetric mesh to a flattened template. We employ the symmetric Dirichlet energy to control local distortion throughout the volume. Local injectivity in the mapping is enforced by a constrained line search during the gradient descent optimization. We validate our method using a research study of 111 placental shapes extracted from BOLD MRI images. Our mapping achieves sub-voxel accuracy in matching the template while maintaining low distortion throughout the volume. We demonstrate how the resulting flattening of the placenta improves visualization of anatomy and function. Our code is freely available at https://github.com/mabulnaga/placenta-flattening.

Change in T2* measurements of placenta and fetal organs during Braxton Hicks contractions.

Maternal-placental perfusion can be temporarily compromised by Braxton Hicks (BH) uterine contractions. Although prior studies have employed T2* changes to investigate the effect of BH contractions on placental oxygen, the effect of these contractions on the fetus has not been fully characterized. We investigated the effect of BH contractions on quantitative fetal organ T2* across gestation together with the birth information. We observed a slight but significant decrease in fetal brain and liver T2* during contractions.

An assessment of spatial distribution and atmospheric concentrations of ozone, nitrogen dioxide, sulfur dioxide, benzene, toluene, ethylbenzene, and xylenes: ozone formation potential and health risk estimation in Bolu city of Turkey.

Atmospheric pollutants including ozone, nitrogen dioxide, sulfur dioxide, and BTEX (benzene, toluene, ethylbenzene, and xylenes) compounds were evaluated concerning their spatial distribution, temporal variation, and health risk factor. Bolu plateau where sampling was performed has a densely populated city center, semi-rural areas, and forested areas. Additionally, the ozone formation potentials of BTEXs were calculated, and toluene was found to be the most important compound in ground level ozone formation. The spatial distribution of BTEXs and nitrogen dioxide pollution maps showed that their concentrations were higher around the major roads and city center, while rural-forested areas were found to be rich in ozone. BTEXs and nitrogen dioxide were found to have higher atmospheric concentrations in winter. That was mostly related to the source strength and low mixing height during that season. The average toluene to benzene ratios demonstrated that there was a significant influence of traffic emissions in the region. Although there was no significant change in sulfur dioxide concentrations in the summer and winter seasons of 2017, the differences in the spatial distribution showed that seasonal sources such as domestic heating and intensive outdoor barbecue cooking were effective in the atmospheric presence of this pollutant. The lifetime cancer risk through inhalation of benzene was found to be comparable with the limit value (1 × 10-6) recommended by USEPA. On the other hand, hazard ratios for BTEXs were found at an acceptable level for different outdoor environments (villages, roadside, and city center) for both seasons.

STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning.

Fetal motion is unpredictable and rapid on the scale of conventional MR scan times. Therefore, dynamic fetal MRI, which aims at capturing fetal motion and dynamics of fetal function, is limited to fast imaging techniques with compromises in image quality and resolution. Super-resolution for dynamic fetal MRI is still a challenge, especially when multi-oriented stacks of image slices for oversampling are not available and high temporal resolution for recording the dynamics of the fetus or placenta is desired. Further, fetal motion makes it difficult to acquire high-resolution images for supervised learning methods. To address this problem, in this work, we propose STRESS (Spatio-Temporal Resolution Enhancement with Simulated Scans), a self-supervised super-resolution framework for dynamic fetal MRI with interleaved slice acquisitions. Our proposed method simulates an interleaved slice acquisition along the high-resolution axis on the originally acquired data to generate pairs of low- and high-resolution images. Then, it trains a super-resolution network by exploiting both spatial and temporal correlations in the MR time series, which is used to enhance the resolution of the original data. Evaluations on both simulated and in utero data show that our proposed method outperforms other self-supervised super-resolution methods and improves image quality, which is beneficial to other downstream tasks and evaluations.

Rapid head-pose detection for automated slice prescription of fetal-brain MRI.

In fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views essential to clinical assessment. As motion limits acquisitions to thick slices that preclude retrospective resampling, technologists repeat ~55-second stack-of-slices scans (HASTE) with incrementally reoriented field of view numerous times, deducing the head pose from previous stacks. To address this inefficient workflow, we propose a robust head-pose detection algorithm using full-uterus scout scans (EPI) which take ~5 seconds to acquire. Our ~2-second procedure automatically locates the fetal brain and eyes, which we derive from maximally stable extremal regions (MSERs). The success rate of the method exceeds 94% in the third trimester, outperforming a trained technologist by up to 20%. The pipeline may be used to automatically orient the anatomical sequence, removing the need to estimate the head pose from 2D views and reducing delays during which motion can occur.

Quantitative T1 and T2 mapping by magnetic resonance fingerprinting (MRF) of the placenta before and after maternal hyperoxia.

INTRODUCTION: MR relaxometry has been used to assess placental exchange function, but methods to date are not sufficiently fast to be robust to placental motion. Magnetic resonance fingerprinting (MRF) permits rapid, voxel-wise, intrinsically co-registered T1 and T2 mapping. After characterizing measurement error, we scanned pregnant women during air and oxygen breathing to demonstrate MRF's ability to detect placental oxygenation changes. METHODS: The accuracy of FISP-based, sliding-window reconstructed MRF was tested on phantoms. MRF scans in 9-s breath holds were acquired at 3T in 31 pregnant women during air and oxygen breathing. A mixed effects model was used to test for changes in placenta relaxation times between physiological states, to assess the dependency on gestational age (GA), and the impact of placental motion. RESULTS: MRF estimates of known phantom relaxation times resulted in mean absolute errors for T1 of 92 ms (4.8%), but T2 was less accurate at 16 ms (13.6%). During normoxia, placental T1 = 1825 ± 141 ms (avg ± standard deviation) and T2 = 60 ± 16 ms (gestational age range 24.3-36.7, median 32.6 weeks). In the statistical model, placental T2 rose and T1 remained contant after hyperoxia, and no GA dependency was observed for T1 or T2. DISCUSSION: Well-characterized, motion-robust MRF was used to acquire T1 and T2 maps of the placenta. Changes with hyperoxia are consistent with a net increase in oxygen saturation. Toward the goal of whole-placenta quantitative oxygenation imaging over time, we aim to implement 3D MRF with integrated motion correction to improve T2 accuracy.

Enhanced detection of fetal pose in 3D MRI by Deep Reinforcement Learning with physical structure priors on anatomy.

Fetal MRI is heavily constrained by unpredictable and substantial fetal motion that causes image artifacts and limits the set of viable diagnostic image contrasts. Current mitigation of motion artifacts is predominantly performed by fast, single-shot MRI and retrospective motion correction. Estimation of fetal pose in real time during MRI stands to benefit prospective methods to detect and mitigate fetal motion artifacts where inferred fetal motion is combined with online slice prescription with low-latency decision making. Current developments of deep reinforcement learning (DRL), offer a novel approach for fetal landmarks detection. In this task 15 agents are deployed to detect 15 landmarks simultaneously by DRL. The optimization is challenging, and here we propose an improved DRL that incorporates priors on physical structure of the fetal body. First, we use graph communication layers to improve the communication among agents based on a graph where each node represents a fetal-body landmark. Further, additional reward based on the distance between agents and physical structures such as the fetal limbs is used to fully exploit physical structure. Evaluation of this method on a repository of 3-mm resolution in vivo data demonstrates a mean accuracy of landmark estimation within 10 mm of ground truth as 87.3%, and a mean error of 6.9 mm. The proposed DRL for fetal pose landmark search demonstrates a potential clinical utility for online detection of fetal motion that guides real-time mitigation of motion artifacts as well as health diagnosis during MRI of the pregnant mother.

Semi-Supervised Learning for Fetal Brain MRI Quality Assessment with ROI consistency.

Fetal brain MRI is useful for diagnosing brain abnormalities but is challenged by fetal motion. The current protocol for T2-weighted fetal brain MRI is not robust to motion so image volumes are degraded by inter- and intra-slice motion artifacts. Besides, manual annotation for fetal MR image quality assessment are usually time-consuming. Therefore, in this work, a semi-supervised deep learning method that detects slices with artifacts during the brain volume scan is proposed. Our method is based on the mean teacher model, where we not only enforce consistency between student and teacher models on the whole image, but also adopt an ROI consistency loss to guide the network to focus on the brain region. The proposed method is evaluated on a fetal brain MR dataset with 11,223 labeled images and more than 200,000 unlabeled images. Results show that compared with supervised learning, the proposed method can improve model accuracy by about 6% and outperform other state-of-the-art semi-supervised learning methods. The proposed method is also implemented and evaluated on an MR scanner, which demonstrates the feasibility of online image quality assessment and image reacquisition during fetal MR scans.

Placental MRI: Development of an MRI compatible ex vivo system for whole placenta dual perfusion.

PURPOSE: Placental dysfunction plays a key role in diseases that affect the fetus in utero and after birth. Aiming to develop a platform for validating in vivo placental MRI and investigations into placental physiology, we designed and built a prototype MRI-compatible perfusion chamber with an integrated MRI receive coil for high SNR ex vivo placental imaging. PRINCIPAL RESULTS: After optimizing placenta vascular clearing and perfusion protocols, we performed contrast enhanced MR angiography and MR relaxometry on eight carefully selected placentas while they were perfused via the umbilical arteries (UAs). Additionally, two of these placentas underwent maternal perfusion via the intervillous space (IVS). Despite striving for homogenous perfusion across the whole placenta, imaging results were highly heterogeneous for both UA and IVS perfused placentas. By histology, we observed blood congestion in the villi in regions that showed low UA perfusion during MRI. In two placentas prominent chorionic arteries followed by adjacent veins underwent contrast enhancement in the absence of villous capillary blush. The single placenta from a pregnancy affected by IUGR had the most homogeneous villous capillary perfusion. MAJOR CONCLUSIONS: A dual perfusion system for ex vivo placentas compatible with MRI permitted assessment of UA and IVS placental perfusion. We observed spatial UA perfusion heterogeneity and evidence for arteriovenous shunting in placentas from normal pregnancies and deliveries, but relative villous capillary perfusion homogeneity in a single IUGR placenta. Future work will focus on system optimization, followed by physiological manipulation and validation of in vivo placental MRI.