The detailed assessment of fetal brain maturation and development involves morphological evaluation, gyration analysis, and reliable biometric measurements. Manual measurements on conventional 2-D magnetic resonance imaging (MRI) are affected by fetal motion, and there is no clear consensus regarding definitions for brain biometric parameters and anatomical landmark placements, making consistent reference plane and slice selection challenging. Automated biometry with 3-D slice-to-volume reconstruction (SVR) has the potential to improve the reliability of derived measurements, allowing precise quantification of fetal brain development. Previous published works have primarily focused on the technical feasibility of automated fetal brain biometry methods for T2-weighted (T2W) MRI. However, none have proposed solutions for automating the reporting of biometry results, which could enhance clinical utility and support real-time integration into routine clinical workflows. Furthermore, there is no consensus on a universal fetal biometry protocol for 3-D fetal MRI. To implement and validate a fully automated biometry reporting pipeline for 3-D T2W fetal brain MRI, based on deep learning biometry measurements and computation of z-scores and centiles, by comparison to normative growth charts. Automated extraction of 13 routinely reported linear fetal biometry measurements using deep learning localization of anatomical landmarks in 3-D reconstructed T2W brain images based on 3-D UNet and presentation of the results in an .html report with centile calculation. The automated biometry method was quantitatively evaluated on 90 retrospective cases against expert manual measurements. Additionally, the fully automated, end-to-end biometry reporting pipeline was prospectively evaluated on 111 cases across a wide range of gestational ages, field strengths, and scanning parameters. We also generated normal centile ranges for 19-40 weeks GA range from 406 normal control datasets. The retrospective quantitative evaluation demonstrated good agreement with manual measurements, with the maximum absolute difference between automated vs. manual measurement within a 1-3-mm range. In the prospective evaluation, more than 98

Motion correction methods based on slice-to-volume registration (SVR) for fetal magnetic resonance imaging (MRI) allow reconstruction of three-dimensional (3-D) isotropic images of the fetal brain and body. However, all existing SVR methods are confined to research settings, which limits clinical integration. Furthermore, there have been no reported SVR solutions for low-field 0.55-T MRI. Integration of automated SVR motion correction methods directly into fetal MRI scanning process via the Gadgetron framework to enable automated T2-weighted (T2W) 3-D fetal brain and body reconstruction in the low-field 0.55-T MRI scanner within the duration of the scan. A deep learning fully automated pipeline was developed for T2W 3-D rigid and deformable (D/SVR) reconstruction of the fetal brain and body of 0.55-T T2W datasets. Next, it was integrated into 0.55-T low-field MRI scanner environment via a Gadgetron workflow that enables launching of the reconstruction process directly during scanning in real-time. During prospective testing on 12 cases (22–40 weeks gestational age), the fetal brain and body reconstructions were available on average 6:42 ± 3:13 min after the acquisition of the final stack and could be assessed and archived on the scanner console during the ongoing fetal MRI scan. The output image data quality was rated as good to acceptable for interpretation. The retrospective testing of the pipeline on 83 0.55-T datasets demonstrated stable reconstruction quality for low-field MRI. The proposed pipeline allows scanner-based prospective T2W 3-D motion correction for low-field 0.55-T fetal MRI via direct online integration into the scanner environment.

Background and Objectives: Epileptogenic lesions in focal epilepsy can be subtle or undetected on conventional brain MRI. Ultra-high field (7T) MRI offers higher spatial resolution, contrast and signal-to-noise ratio compared to conventional imaging systems and has shown promise in the pre-surgical evaluation of adult focal epilepsy. However, the utility of ultra-high field MRI in paediatric focal epilepsy, where malformations of cortical development are more common, is unclear. This study compared 7T to conventional 3T MRI in children with epilepsy by comparing: (i) scan tolerability; (ii) radiological image quality; (iii) lesion yield. Materials and Methods: Children with drug-resistant focal epilepsy and healthy controls were recruited prospectively and imaged at both 3T and 7T. Safety and tolerability during scanning was assessed via a questionnaire. Image quality was evaluated by an expert paediatric neuroradiologist and estimated quantitatively by comparing cortical thickness between field strengths. To assess lesion detection yield of 7T MRI, a multi-disciplinary team jointly reviewed patients' images. Results: 41 patients (8-17 years, mean=12.6 years, 22 male) and 22 healthy controls (8-17 years, mean=11.7 years, 15 male) were recruited. All children completed the scan, with no significant adverse events. Higher discomfort due to dizziness was reported at 7T (p=0.02), with side-effects more frequently noted in younger children (p=0.02). However, both field strengths were generally well-tolerated and side-effects were transient. 7T images had increased inhomogeneity and artefacts compared to those obtained at 3T. Cortical thickness measurements were significantly thinner at 7T (p<0.001). 8/26 (31%) patients had new lesions identified at 7T which were not identified at 3T, influencing the surgical management in 4/26 (15%). Discussion: 7T MRI in children with epilepsy is feasible, well-tolerated and is associated with a 31% improvement in lesion detection rates. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research was supported by GOSHCC Sparks Grant V4419, King's Health Partners, in part by the Medical Research Council (UK) (grants MR/ K006355/1 and MR/LO11530/1) and Medical Research Council Centre for Neurodevelopmental Disorders, King's College London (MR/N026063/1), and by core funding from the Wellcome EPSRC Centre for Medical Engineering at King's College London [WT203148/Z/16/Z]. J.O.M, K.V, and C.C were funded by a Sir Henry Dale Fellowship jointly by the Wellcome Trust and the Royal Society (206675/Z/17/Z). C.C was also funded by a grant from GOSHCC (VC1421). T.A. was also supported by an MRC Transition Support Award [MR/V036874/1] and Senior Clinical Fellowship [MR/Y009665/1]. M.E was funded by Action Medical Research (GN2835) and the British Paediatric Neurology Association. R.J.P was funded by a Surgeon-Scientist grant by GOSCHCC (VS0221). This research was funded in whole, or in part, by the Wellcome Trust [WT203148/Z/16/Z and 206675/Z/17/Z] and by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London and/or the NIHR Clinical Research Facility. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval was granted by the UK Health Research Authority and Health and Care Research Wales (ethics ref. 18/LO/1766). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The clinical and neuroimaging data used in the current work are available from the senior author (J.O.M.) on formal request indicating name and affiliation of the researcher as well as a brief description of the intended use for the data. All requests will undergo King's College London-regulated procedure, thus requiring submission of a Material Transfer Agreement. Full preprocessing steps and the code to run the HCP preprocessing pipeline can be found at https://github.com/Washington-University/HCPpipelines. Please also see https://github.com/Washington-University/workbench for the source code for Connectome Workbench. Other code excerpts, information regarding the analysis, or intermediary results can be made available upon request to chiara.casella@kcl.ac.uk.

BACKGROUND: Preeclampsia is a multiorgan disease of pregnancy that has short- and long-term implications for the woman and fetus, whose immediate impact is poorly understood. We present a novel multiorgan approach to magnetic resonance imaging (MRI) investigation of preeclampsia, with the acquisition of maternal cardiac, placental, and fetal brain anatomic and functional imaging. METHODS: An observational study was performed recruiting 3 groups of pregnant women: those with preeclampsia, chronic hypertension, or no medical complications. All women underwent a cardiac MRI, and pregnant women underwent a placental-fetal MRI. Cardiac analysis for structural, morphological, and flow data were undertaken; placenta and fetal brain volumetric and T2* (which describes relative tissue oxygenation) data were obtained. All results were corrected for gestational age. A nonpregnant cohort was identified for inclusion in the statistical shape analysis. RESULTS: Seventy-eight MRIs were obtained during pregnancy. Cardiac MRI analysis demonstrated higher left ventricular mass in preeclampsia with 3-dimensional modeling revealing additional specific characteristics of eccentricity and outflow track remodeling. Pregnancies affected by preeclampsia demonstrated lower placental and fetal brain T2*. Within the preeclampsia group, 23% placental T2* results were consistent with controls, these were the only cases with normal placental histopathology. Fetal brain T2* results were consistent with normal controls in 31% of cases. CONCLUSIONS: We present the first holistic assessment of the immediate implications of preeclampsia on maternal heart, placenta, and fetal brain. As well as having potential clinical implications for the risk stratification and management of women with preeclampsia, this gives an insight into the disease mechanism.

PurposeWe propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements.MethodsStacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system.ResultsThe simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies.ConclusionThe motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus.

Purpose Integrating the SVRTK methods within the Gadgetron framework enables automated 3D fetal brain and body reconstruction in the low-field 0.55T MRI scanner within the duration of the scan. Methods A deep-learning based, integrated, robust, and deployable workflow from several motion-corrupted individual T2-weighted single-shot Turbo Spin Echo stacks to produce super-resolved 3D reconstructed fetal brain and body is enabled by combining automated deformable and rigid Slice-to-Volume (D/SVR) reconstruction adapted for low field MRI with a real-time scanner-based Gadgetron workflow. Qualitative evaluation of the pipeline in terms of image quality and efficiency is performed in 12 prospectively acquired fetal datasets from the 22-40 weeks gestational age range. Results The reconstructions were available on average 6:42±3:13 minutes after the acquisition of the final stack and could be assessed and archived on the scanner console during the ongoing fetal MRI scan. The output image data quality was rated as good to acceptable for interpretation. The additional retrospective testing of the pipeline on 83 0.55T datasets demonstrated stable reconstruction quality for low-field MRI. Conclusion The proposed pipeline allows scanner-based prospective motion correction for low-field fetal MRI. The main novel components of this work are the compilation of automated fetal and body D/SVR methods into one combined pipeline, the first application of 3D reconstruction methods to 0.55T T2-weighted data, and the online integration into the scanner environment. ### Competing Interest Statement Sarah McElroy - Siemens Healthineers ### Funding Statement This work was supported by the Wellcome Trust, Sir Henry Wellcome Fellowship to JH [201374/Z/16/Z], the UKRI FLF to JH [MR/T018119/1], DFG Heisenberg [502024488] the High Tech Agenda Bavaria to JH, the NIHR Advanced Fellowship to LS [NIHR3016640], the MRC grants [MR/W019469/1] and [MR/X010007/1], and the Wellcome/EPSRC Centre [WT203148/Z/16/Z]. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The fetal MRI data used in this study were acquired at St.Thomas' Hospital, London as part of the ethically approved MEERKAT [REC: 21/LO/0742], MiBirth [REC: 23/LO/0685] and NANO [REC: 22/YH/0210] studies. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The code for the proposed Gadgetron-based D/SVR scanner integration for 0.55T fetal MRI is publicly available at gadgetron-svrtk-integration SVRTK GitHub repository. * MRI : magnetic resonance imaging SVR : slice-to-volume registration

Purpose: Widening the availability of fetal MRI with fully automatic real-time planning of radiological brain planes on 0.55T MRI. Methods: Deep learning-based detection of key brain landmarks on a whole-uterus EPI scan enables the subsequent fully automatic planning of the radiological single-shot Turbo Spin Echo acquisitions. The landmark detection pipeline was trained on over 120 datasets from varying field strength, echo times and resolutions and quantitatively evaluated. The entire automatic planning solution was tested prospectively in nine fetal subjects between 20 and 37 weeks. Comprehensive evaluation of all steps, the distance between manual and automatic landmarks, the planning quality and the resulting image quality was conducted. Results: Prospective automatic planning was performed in real-time without latency in all subjects. The landmark detection accuracy was 4.21+-2.56 mm for the fetal eyes and 6.47+-3.23 for the cerebellum, planning quality was 2.44/3 (compared to 2.56/3 for manual planning) and diagnostic image quality was 2.14 compared to 2.07 for manual planning. Conclusions: Real-time automatic planning of all three key fetal brain planes was successfully achieved and will pave the way towards simplifying the acquisition of fetal MRI thereby widening the availability of this modality in non-specialist centres.

OBJECTIVES:Evaluating craniofacial phenotype-genotype correlations prenatally is increasingly important; however, it is subjective and challenging with 3D ultrasound. We developed an automated label propagation pipeline using 3D motion- corrected, slice-to-volume reconstructed (SVR) fetal MRI for craniofacial measurements. METHODS:A literature review and expert consensus identified 31 craniofacial biometrics for fetal MRI. An MRI atlas with defined anatomical landmarks served as a template for subject registration, auto-labelling, and biometric calculation. We assessed 108 healthy controls and 24 fetuses with Down syndrome (T21) in the third trimester (29-36 weeks gestational age, GA) to identify meaningful biometrics in T21. Reliability and reproducibility were evaluated in 10 random datasets by four observers. RESULTS:Automated labels were produced for all 132 subjects with a 0.3% placement error rate. Seven measurements, including anterior base of skull length and maxillary length, showed significant differences with large effect sizes between T21 and control groups (ANOVA, p<0.001). Manual measurements took 25-35 minutes per case, while automated extraction took approximately 5 minutes. Bland-Altman plots showed agreement within manual observer ranges except for mandibular width, which had higher variability. Extended GA growth charts (19-39 weeks), based on 280 control fetuses, were produced for future research. CONCLUSION:This is the first automated atlas-based protocol using 3D SVR MRI for fetal craniofacial biometrics, accurately revealing morphological craniofacial differences in a T21 cohort. Future work should focus on improving measurement reliability, larger clinical cohorts, and technical advancements, to enhance prenatal care and phenotypic characterisation.

Background:Pre-eclampsia is a multiorgan disease of pregnancy that has short- and long-term implications for the woman and fetus, whose immediate impact is poorly understood. We present a novel multi-system approach to MRI investigation of pre-eclampsia, with acquisition of maternal cardiac, placental, and fetal brain anatomical and functional imaging.Methods:A prospective study was carried out recruiting pregnant women with pre-eclampsia, chronic hypertension, or no medical complications, and a non-pregnant female cohort. All women underwent a cardiac MRI, and pregnant women underwent a fetal-placental MRI. Cardiac analysis for structural, morphological and flow data was undertaken; placenta and fetal brain volumetric and T2* data were obtained. All results were corrected for gestational age.Results:Seventy-eight MRIs were obtained during pregnancy. Pregnancies affected by pre-eclampsia demonstrated lower placental and fetal brain T2*. Within the pre-eclampsia group, three placental T2* results were within the normal range, these were the only cases with normal placental histopathology. Similarly, three fetal brain T2* results were within the normal range; these cases had no evidence of cerebral redistribution on fetal Dopplers. Cardiac MRI analysis demonstrated higher left ventricular mass in pre-eclampsia with 3D modelling revealing additional specific characteristics of eccentricity and outflow track remodelling.Conclusions:We present the first holistic assessment of the immediate implications of pre-eclampsia on the placenta, maternal heart, and fetal brain. As well as having potential clinical implications for the risk-stratification and management of women with pre-eclampsia, this gives an insight into disease mechanism.

We assessed cortical microstructure in children with drug-resistant focal epilepsy using T1 and T2 relaxometry (qT1 and qT2). We show widespread, depth-mediated qT1 and qT2 increases, and alterations in intracortical organisation in patients. Changes did not correlate with clinical parameters, suggesting that they may be independent of disease severity. Using a random forest algorithm, we also show that qT1 and qT2 surface-features from patients with radiologically defined abnormalities (MRI-positive) and controls, can classify patients without reported radiological abnormalities (MRI-negative). This suggests a common imaging endophenotype of focal epilepsy irrespective of visible abnormalities that may be present at a pre-symptomatic disease-stage.

Objectives We assessed cortical changes in children with drug-resistant focal epilepsy using surface-based T1 and T2 relaxometry (qT1 and qT2), to probe alterations in tissue-microstructure, and their relationship to clinical parameters. Methods Data Acquisition 89 children were scanned unsedated on a 3T Achieva-TX scanner (Philips Healthcare) – 43 with drug-resistant focal epilepsy [mean age=12yrs] and 46 healthy controls [mean age=11.5yrs] (See table 1 for acquisition parameters). All images were motion-corrected.¹ Analysis Surface-reconstruction: FLAIR and T1w images were analysed to reconstruct white/grey matter (WM/GM) and pial surfaces.² These surfaces were used to compute equi-volume cortical surface depths by sampling the surface vertices in steps of 20% of cortical volume (0%: WM/GM, 100%: pial surface). qT1 and qT2 surface-mapping: qT1 and qT2 images³ were rigidly co-registered to their corresponding MPRAGE volume, smoothed, and projected to each depth. Group differences in qT1 and qT2: Surface outputs from the HCP structural pipeline are left-right symmetrical, therefore we flipped qT1 and qT2 surface maps of patients with right hemispheric focus and analysed them with left focus patients. Group-wise alterations at each cortical depth were tested.4 Additionally, vertex-wise qT1 and qT2 values at 20% depth were subtracted from those at 80% depth, and group-differences in cortical gradients were tested as an index of intracortical organisation. Associations between qT1 and qT2 changes in patients and disease duration/number of seizures per year were assessed. Age, sex, cortical thickness and curvature were included as covariates.5 6 TFCE was employed as test statistic, and FWE-correction was applied across modalities and contrasts. Results Figure 2A displays depth-wise group differences in qT1 and qT2. Bilateral qT2 increases and ipsilateral qT1 increases were detected in patients in the outermost cortical depths. The detected changes were not associated with clinical variables. Figure 2B displays group differences in qT1 and qT2 cortical gradients. We detected steeper gradients in patients, with increasingly high qT1 and qT2 in the outermost cortical depths bilaterally. The detected changes were not associated with clinical variables. Conclusions We report the presence of widespread, depth-mediated qT1 and qT2 increases in children with focal epilepsy. Changes appear unrelated to focus laterality, and likely represent gliosis, myelin and iron changes, oedema-associated free-water increases, or a combination of these.7 Based on the typically shorter disease duration in children, and on the lack of associations with disease-severity measures, such changes may represent antecedent neurobiological alterations, rather than the cumulative effect of seizure-activity or medication side-effects. References Cordero-Grande L, et al. Motion-corrected MRI with DISORDER: Distributed and incoherent sample orders for reconstruction deblurring using encoding redundancy. Magnetic Resonance in Medicine 2020;84:713–726. Glasser MF, et al. The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage 2013;80:105–124. Teixeira RPAG, Malik SJ, Hajnal JV. Joint system relaxometry (JSR) and Crámer-Rao lower bound optimization of sequence parameters: A framework for enhanced precision of DESPOT T1 and T2 estimation. Magn Reson Med 2018;79:234–245. Winkler AM, Webster MA, Brooks JC, Tracey I, Smith SM, Nichols TE. Non-parametric combination and related permutation tests for neuroimaging. Human Brain Mapping. 2016;37(4):1486–1511. doi:10.1002/hbm.23115 Galovic M, et al. Resective surgery prevents progressive cortical thinning in temporal lobe epilepsy. Brain 2020;143:3262–3272. Annese J, Pitiot A, Dinov ID, Toga AW. A myelo-architectonic method for the structural classification of cortical areas. NeuroImage 2004;21:15–26. Cercignani M, Dowell NG, Tofts PS. Quantitative MRI of the Brain: Principles of Physical Measurement, Second edition. (CRC Press, 2018).

The development of connectivity between the thalamus and maturing cortex is a fundamental process in the second half of human gestation, establishing the neural circuits that are the basis for several important brain functions. In this study, we acquired high-resolution in utero diffusion magnetic resonance imaging (MRI) from 140 fetuses as part of the Developing Human Connectome Project, to examine the emergence of thalamocortical white matter over the second to third trimester. We delineate developing thalamocortical pathways and parcellate the fetal thalamus according to its cortical connectivity using diffusion tractography. We then quantify microstructural tissue components along the tracts in fetal compartments that are critical substrates for white matter maturation, such as the subplate and intermediate zone. We identify patterns of change in the diffusion metrics that reflect critical neurobiological transitions occurring in the second to third trimester, such as the disassembly of radial glial scaffolding and the lamination of the cortical plate. These maturational trajectories of MR signal in transient fetal compartments provide a normative reference to complement histological knowledge, facilitating future studies to establish how developmental disruptions in these regions contribute to pathophysiology.

Objective Tissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes, treatment-related side-effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilised quantitative MRI, which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. Methods To assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy [age-range=4-18 years] and 46 typically-developing children [age-range=2-18 years]. We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically-defined abnormalities (MRI-positive) and healthy controls, and tested if this could classify patients without reported radiological abnormalities (MRI-negative). Results We uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 62% at 100% specificity on held-out MRI-negative patients. Significance These findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically-identified abnormalities, and potentially evident pre-symptomatically. Key Points We assessed cortical microstructure in children with focal epilepsy Quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in the neocortex Patients showed extensive qT1/qT2 increases and intracortical organization changes Alterations may appear during cerebral development, prior to disease onset

The aim of this study was to gather data from children on their subjective experiences when undergoing high field MRI and compare this to adult data collected with similar questionnaires. Seventeen children and twenty-six healthy adults had brain imaging at 7T. Their experiences which included: (a) acoustic noise, (b) anxiety, (c) metallic taste (d) vertigo (dizziness) and e) involuntary eye movement (nystagmus) or flashing lights were evaluated. We found that children scanned at 7T reported similar experiences to adults.

With development of fast imaging techniques and powerful motion correcting reconstruction techniques, high resolution 3D fetal brain images with a high level of anatomical detail are possible to acquire. A quantitative framework has been proposed that leverages fast imaging techniques and motion correcting reconstruction techniques to build quantitative T2 maps of the fetal brain. This study proposes a simulated phantom that modifies the FaBiaN fetal MRI simulated phantom to enable validation of this quantitative framework. We found that the slice-to-volume reconstruction (SVR) algorithm preserves quantitative T2 measurements and, therefore the proposed pipeline is suitable for reconstruction of quantitative T2 maps of fetal brain tissue.

Introduction: The CARP study aims to investigate placental function, cardiac function and fetal growth comprehensively during pregnancy, a time of maximal cardiac stress, to work towards disentangling the complex cardiac and placental interactions presenting in the aetiology of pre-eclampsia as well as predicting maternal Cardiovascular Disease (CVD) risk in later life. Background: The involvement of the cardiovascular system in pre-eclampsia, one of the most serious complications of pregnancy, is evident. While the manifestations of pre-eclampsia during pregnancy (high blood pressure, multi-organ disease, and placental dysfunction) resolve after delivery, a lifelong elevated CVD risk remains. Method: An assessment including both cardiac and placental Magnetic Resonance Imaging (MRI) optimised for use in pregnancy and bespoke to the expected changes was developed. Simultaneous structural and functional MRI data from the placenta, the heart and the fetus were obtained in a total of 32 pregnant women (gestational ages from 18.1 to 37.5 weeks), including uncomplicated pregnancies and five cases with early onset pre-eclampsia. Results: The achieved comprehensive MR acquisition was able to demonstrate a phenotype associated with pre-eclampsia linking both placental and cardiac factors, reduced mean T2* (p < 0.005), increased heterogeneity (p < 0.005) and a trend towards an increase in cardiac work, larger average mass (109.4 vs 93.65 gr), wall thickness (7.0 vs 6.4 mm), blood pool volume (135.7 vs 127.48 mL) and mass to volume ratio (0.82 vs 0.75). The cardiac output in the controls was, controlling for gestational age, positively correlated with placental volume (p < 0.05). Discussion: The CARP study constitutes the first joint assessment of functional and structural properties of the cardiac system and the placenta during pregnancy. Early indications of cardiac remodelling in pre-eclampsia were demonstrated paving the way for larger studies.

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.

Fetal Magnetic Resonance Imaging (Fetal MRI) allows insights into human development before birth, complementing conventional Ultrasound imaging with its high resolution and available numerous contrast options. Significant challenges still exist including geometric distortion caused by maternal bowel gas in echo-planar imaging, and restrictions in bore size limiting access to MRI in the obese and or claustrophobic population. Recent developments of clinical low-field scanners can meet these challenges and thus render fetal MRI more accessible. This study shows anatomical imaging and quantitative T2* mapping on a 0.55T system with an analysis pipeline for both placenta and fetal brain. Results show an expected increased overall T2* compared to higher fields, with values decreasing over gestation as shown at higher field. Future work will be directed towards exploring additional types of relaxometry and the use of the presented techniques in subjects with higher Body Mass Index. Included data and analysis code are publicly available.

BACKGROUND AND PURPOSE: Head motion causes image degradation in brain MR imaging examinations, negatively impacting image quality, especially in pediatric populations. Here, we used a retrospective motion correction technique in children and assessed image quality improvement for 3D MR imaging acquisitions. MATERIALS AND METHODS: We prospectively acquired brain MR imaging at 3T using 3D sequences, T1-weighted MPRAGE, T2-weighted TSE, and FLAIR in 32 unsedated children, including 7 with epilepsy (age range, 2–18 years). We implemented a novel motion correction technique through a modification of k-space data acquisition: Distributed and Incoherent Sample Orders for Reconstruction Deblurring by using Encoding Redundancy (DISORDER). For each participant and technique, we obtained 3 reconstructions as acquired (Aq), after DISORDER motion correction (Di), and Di with additional outlier rejection (DiOut). We analyzed 288 images quantitatively, measuring 2 objective no-reference image quality metrics: gradient entropy (GE) and MPRAGE white matter (WM) homogeneity. As a qualitative metric, we presented blinded and randomized images to 2 expert neuroradiologists who scored them for clinical readability. RESULTS: Both image quality metrics improved after motion correction for all modalities, and improvement correlated with the amount of intrascan motion. Neuroradiologists also considered the motion corrected images as of higher quality (Wilcoxon z = −3.164 for MPRAGE; z = −2.066 for TSE; z = −2.645 for FLAIR; all P < .05). CONCLUSIONS: Retrospective image motion correction with DISORDER increased image quality both from an objective and qualitative perspective. In 75% of sessions, at least 1 sequence was improved by this approach, indicating the benefit of this technique in unsedated children for both clinical and research environments.