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AbstractObjectivesTo investigate the effectiveness of routine ultrasonography in the third trimester in reducing adverse perinatal outcomes in low risk pregnancies compared with usual care and the effect of this policy on maternal outcomes and obstetric interventions.DesignPragmatic, multicentre, stepped wedge cluster randomised trial.Setting60 midwifery practices in the Netherlands.Participants13 046 women aged 16 years or older with a low risk singleton pregnancy.Interventions60 midwifery practices offered usual care (serial fundal height measurements with clinically indicated ultrasonography). After 3, 7, and 10 months, a third of the practices were randomised to the intervention strategy. As well as receiving usual care, women in the intervention strategy were offered two routine biometry scans at 28-30 and 34-36 weeks’ gestation. The same multidisciplinary protocol for detecting and managing fetal growth restriction was used in both strategies.Main outcome measuresThe primary outcome measure was a composite of severe adverse perinatal outcomes: perinatal death, Apgar score <4, impaired consciousness, asphyxia, seizures, assisted ventilation, septicaemia, meningitis, bronchopulmonary dysplasia, intraventricular haemorrhage, periventricular leucomalacia, or necrotising enterocolitis. Secondary outcomes were two composite measures of severe maternal morbidity, and spontaneous labour and birth.ResultsBetween 1 February 2015 and 29 February 2016, 60 midwifery practices enrolled 13 520 women in mid-pregnancy (mean 22.8 (SD 2.4) weeks’ gestation). 13 046 women (intervention n=7067, usual care n=5979) with data based on the national Dutch perinatal registry or hospital records were included in the analyses. Small for gestational age at birth was significantly more often detected in the intervention group than in the usual care group (179 of 556 (32%) v 78 of 407 (19%), P<0.001). The incidence of severe adverse perinatal outcomes was 1.7% (n=118) for the intervention strategy and 1.8% (n=106) for usual care. After adjustment for confounders, the difference between the groups was not significant (odds ratio 0.88, 95% confidence interval 0.70 to 1.20). The intervention strategy showed a higher incidence of induction of labour (1.16, 1.04 to 1.30) and a lower incidence of augmentation of labour (0.78, 0.71 to 0.85). Maternal outcomes and other obstetric interventions did not differ between the strategies.ConclusionIn low risk pregnancies, routine ultrasonography in the third trimester along with clinically indicated ultrasonography was associated with higher antenatal detection of small for gestational age fetuses but not with a reduced incidence of severe adverse perinatal outcomes compared with usual care alone. The findings do not support routine ultrasonography in the third trimester for low risk pregnancies.Trial registrationNetherlands Trial Register NTR4367.

The goal of this study was to evaluate the maturity of current Deep Learning classification techniques for their application in a real maternal-fetal clinical environment. A large dataset of routinely acquired maternal-fetal screening ultrasound images (which will be made publicly available) was collected from two different hospitals by several operators and ultrasound machines. All images were manually labeled by an expert maternal fetal clinician. Images were divided into 6 classes: four of the most widely used fetal anatomical planes (Abdomen, Brain, Femur and Thorax), the mother’s cervix (widely used for prematurity screening) and a general category to include any other less common image plane. Fetal brain images were further categorized into the 3 most common fetal brain planes (Trans-thalamic, Trans-cerebellum, Trans-ventricular) to judge fine grain categorization performance. The final dataset is comprised of over 12,400 images from 1,792 patients, making it the largest ultrasound dataset to date. We then evaluated a wide variety of state-of-the-art deep Convolutional Neural Networks on this dataset and analyzed results in depth, comparing the computational models to research technicians, which are the ones currently performing the task daily. Results indicate for the first time that computational models have similar performance compared to humans when classifying common planes in human fetal examination. However, the dataset leaves the door open on future research to further improve results, especially on fine-grained plane categorization.

In this paper we present a computer aided detection (CAD) system for automated measurement of the fetal head circumference (HC) in 2D ultrasound images for all trimesters of the pregnancy. The HC can be used to estimate the gestational age and monitor growth of the fetus. Automated HC assessment could be valuable in developing countries, where there is a severe shortage of trained sonographers. The CAD system consists of two steps: First, Haar-like features were computed from the ultrasound images to train a random forest classifier to locate the fetal skull. Secondly, the HC was extracted using Hough transform, dynamic programming and an ellipse fit. The CAD system was trained on 999 images and validated on an independent test set of 335 images from all trimesters. The test set was manually annotated by an experienced sonographer and a medical researcher. The reference gestational age (GA) was estimated using the crown-rump length measurement (CRL). The mean difference between the reference GA and the GA estimated by the experienced sonographer was 0.8 ± 2.6, -0.0 ± 4.6 and 1.9 ± 11.0 days for the first, second and third trimester, respectively. The mean difference between the reference GA and the GA estimated by the medical researcher was 1.6 ± 2.7, 2.0 ± 4.8 and 3.9 ± 13.7 days. The mean difference between the reference GA and the GA estimated by the CAD system was 0.6 ± 4.3, 0.4 ± 4.7 and 2.5 ± 12.4 days. The results show that the CAD system performs comparable to an experienced sonographer. The presented system shows similar or superior results compared to systems published in literature. This is the first automated system for HC assessment evaluated on a large test set which contained data of all trimesters of the pregnancy.

Purpose To evaluate the diagnostic yield of chromosomal microarray (CMA) in pregnancies with normal ultrasound. Methods This retrospective cohort analysis included all pregnancies with normal ultrasound undergoing CMA testing between the years 2010 and 2016. We calculated the rate of detection of clinically significant CMA findings in the whole cohort and according to various indications. Results Of 5541 CMA analyses, clinically significant findings were yielded in 78 cases (1.4%). Of these, 31 (39.7%) variants could have theoretically been detected by karyotyping (e.g., sized above 10 Mb), and 28 (35.9%) by noninvasive prenatal screening aimed at five common aneuploidies. Of the 47 submicroscopic findings detectable by CMA only, the majority (37 cases, 78.7%) represented known recurrent syndromes. Detection of clinically significant CMA findings in women with no indication for invasive testing was 0.76% (21/2752), which was significantly lower compared with 1.8% in advanced maternal age group (41/2336), 2.8% in abnormal biochemical serum screening (6/211), and 4.1% (10/242) in fetuses with sonographic soft markers. Conclusion Clinically significant CMA aberrations are detected in 1 of 71 pregnancies with normal ultrasound, and in 1 of 131 women with no indication for invasive testing. Thus, CMA might be recommended a first-tier test in pregnancies with normal ultrasound.

The effectiveness of screening for macrosomia is not well established. One of the critical elements of an effective screening program is the diagnostic accuracy of a test at predicting the condition. The objective of this study is to investigate the diagnostic effectiveness of universal ultrasonic fetal biometry in predicting the delivery of a macrosomic infant, shoulder dystocia, and associated neonatal morbidity in low- and mixed-risk populations. We conducted a predefined literature search in Medline, Excerpta Medica database (EMBASE), the Cochrane library and ClinicalTrials.gov from inception to May 2020. No language restrictions were applied. We included studies where the ultrasound was performed as part of universal screening and those that included low- and mixed-risk pregnancies and excluded studies confined to high risk pregnancies. We used the estimated fetal weight (EFW) (multiple formulas and thresholds) and the abdominal circumference (AC) to define suspected large for gestational age (LGA). Adverse perinatal outcomes included macrosomia (multiple thresholds), shoulder dystocia, and other markers of neonatal morbidity. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Meta-analysis was carried out using the hierarchical summary receiver operating characteristic (ROC) and the bivariate logit-normal (Reitsma) models. We identified 41 studies that met our inclusion criteria involving 112,034 patients in total. These included 11 prospective cohort studies (N = 9986), one randomized controlled trial (RCT) (N = 367), and 29 retrospective cohort studies (N = 101,681). The quality of the studies was variable, and only three studies blinded the ultrasound findings to the clinicians. Both EFW >4,000 g (or 90th centile for the gestational age) and AC >36 cm (or 90th centile) had >50% sensitivity for predicting macrosomia (birthweight above 4,000 g or 90th centile) at birth with positive likelihood ratios (LRs) of 8.74 (95% confidence interval [CI] 6.84-11.17) and 7.56 (95% CI 5.85-9.77), respectively. There was significant heterogeneity at predicting macrosomia, which could reflect the different study designs, the characteristics of the included populations, and differences in the formulas used. An EFW >4,000 g (or 90th centile) had 22% sensitivity at predicting shoulder dystocia with a positive likelihood ratio of 2.12 (95% CI 1.34-3.35). There was insufficient data to analyze other markers of neonatal morbidity. In this study, we found that suspected LGA is strongly predictive of the risk of delivering a large infant in low- and mixed-risk populations. However, it is only weakly (albeit statistically significantly) predictive of the risk of shoulder dystocia. There was insufficient data to analyze other markers of neonatal morbidity.

Advances in fetal three‐dimensional (3D) ultrasound (US) and magnetic resonance imaging (MRI) have revolutionized the study of fetal brain development, enabling detailed analysis of brain structures and growth. Despite their complementary capabilities, these modalities capture fundamentally different physical signals, potentially leading to systematic differences in image‐derived phenotypes (IDPs). Here, we evaluate the agreement of IDPs between US and MRI by comparing the volumes of eight brain structures from 90 subjects derived using deep‐learning algorithms from majority same‐day imaging (days between scans: mean = 1.2, mode = 0 and max = 4). Excellent agreement (intra‐class correlation coefficient, ICC>0.75 $$ ICC>0.75 $$ ) was observed for the cerebellum, cavum septum pellucidum, thalamus, white matter and deep grey matter volumes, with significant correlations p<0.001 $$ \\left(p<0.001\\right) $$for most structures, except the ventricular system. Bland–Altman analysis revealed some systematic biases: intracranial and cortical plate volumes were larger on US than MRI, by an average of 35cm3 $$ 35\\ {\\mathrm{cm}}^3 $$and 4.1cm3 $$ 4.1\\ {\\mathrm{cm}}^3 $$ , respectively. Finally, we found the labels of the brainstem and ventricular system were not comparable between the modalities. These findings highlight the necessity of structure‐specific adjustments when interpreting fetal brain IPDs across modalities and underscore the complementary roles of US and MRI in advancing fetal neuroimaging. This study investigates the agreement of image derived‐phenotypes (IDPs) from eight fetal brain structures derived from same‐day MRI and 3D US volumes. Strong agreement was observed for the CSP, Th, CB, WMDGM, whereas, systematic biases were revealed for ICV and CoP.

Fetal brain imaging is essential for prenatal care, with ultrasound (US) and magnetic resonance imaging (MRI) providing complementary strengths. While MRI has superior soft tissue contrast, US offers portable and inexpensive screening of neurological abnormalities. Despite the great potential synergy of combined fetal brain US and MR imaging to enhance diagnostic accuracy, little effort has been made to integrate these modalities. An essential step towards this integration is accurate automatic spatial alignment, which is technically very challenging due to the inherent differences in contrast and modality-specific imaging artifacts. In this work, we present a novel atlas-assisted multi-task learning technique to address this problem. Instead of training the registration model solely with intra-subject US-MR image pairs, our approach enables the network to also learn from domain-specific image-to-atlas registration tasks. This leads to an end-to-end multi-task learning framework with superior registration performance. Our proposed method was validated using a dataset of same-day intra-subject 3D US-MR image pairs. The results show that our method outperforms conventional optimization-based methods and recent learning-based techniques for rigid image registration. Specifically, the average target registration error for our method is less than 4 mm, which is significantly better than existing methods. Extensive experiments have also shown that our method has a much wider capture range and is robust to brain abnormalities. Given these advantages over existing techniques, our method is more suitable for deployment in clinical workflows and may contribute to streamlined multimodal imaging pipelines for fetal brain assessment. •Atlas-assisted multi-task learning method for 3D US-MR fetal brain registration.•Achieves average registration error under 4 mm, outperforming existing methods.•Offers a wider tracking range and robustness to brain abnormalities.•Suitable for clinical workflows and multimodal imaging pipelines.

High-risk pregnancies undergo regular antenatal monitoring, including cardiotocography (CTG) and ultrasound. Recently there has been an emergence of sophisticated remote telehealth interventions, potentially enabling care to be shifted into the home setting. Our aim was to evaluate the feasibility and acceptability of home CTG and home ultrasound monitoring for high-risk pregnancies. This was a single center study. Women aged ≥18 years, English speaking, singleton pregnancy, ≥ 32 weeks gestation and had at least one of four high-risk obstetric conditions were eligible. Participants were randomized to one of three groups: (1) home ultrasound; (2) home CTG; and (3) both, whilst continuing their routine antenatal care. The primary outcome was completion of 20 minutes of interpretable fetal heart recording and/or completion of an interpretable fetal ultrasound for each monitoring episode. Ultrasound interpretability was assessed for three validated criteria: fetal heartbeat, fetal movements and liquor volume assessment. Secondary outcomes included monitoring adherence, anxiety management, acceptability and safety. Fifteen participants, within three groups, completed 24 remote ultrasounds and 59 remote CTGs. Overall, the fetal heartbeat, movements and an assessment of the liquor volume were identified in 92%, 83% and 100% of all ultrasound scans respectively. 79% of all scans had all three criteria unanimously assessed. Three-quarters of all CTGs contained at least 20 minutes of continuous interpretable computerized fetal heartrate recording. Neither ethnicity, parity, BMI nor fetal presentation were significant factors for achievement of the primary outcome for both devices. There was non-significant reduction in anxiety scores before and after device usage (p = 0.19). Participants’ monitoring adherence and acceptability ratings were high in all groups. No adverse maternal-fetal outcomes relating to device usage occurred. Home ultrasound and cardiotocography are potentially feasible and acceptable to high-risk pregnant women. Larger studies are required to refine how best to implement such devices into clinical practice. ClinicalTrials ID: NCT06366711.

Small fetuses are defined as those with an ultrasound estimated weight below a threshold, most commonly the 10th centile. The first clinically relevant step is the distinction of ‘true' fetal growth restriction (FGR), associated with signs of abnormal fetoplacental function and poorer perinatal outcome, from constitutional small-for-gestational age, with a near-normal perinatal outcome. Nowadays such a distinction should not be based solely on umbilical artery Doppler, since this index detects only early-onset severe forms. FGR should be diagnosed in the presence of any of the factors associated with a poorer perinatal outcome, including Doppler cerebroplacental ratio, uterine artery Doppler, a growth centile below the 3rd centile, and, possibly in the near future, maternal angiogenic factors. Once the diagnosis is established, differentiating into early- and late-onset FGR is useful mainly for research purposes, because it distinguishes two clear phenotypes with differences in severity, association with preeclampsia, and the natural history of fetal deterioration. As a second clinically relevant step, management of FGR and the decision to deliver aims at an optimal balance between minimizing fetal injury or death versus the risks of iatrogenic preterm delivery. We propose a protocol that integrates current evidence to classify stages of fetal deterioration and establishes follow-up intervals and optimal delivery timings, which may facilitate decisions and reduce practice variability in this complex clinical condition.

Although digital examination of the cervix is the standard method used worldwide for evaluating the progress of delivery, it is subjective. Transperineal ultrasound (TPU) is combined with digital evaluation for accurate assessment of fetal descent and rotation of the advanced part of the fetus. This retrospective study aimed to clarify the impact of introducing TPU on perinatal outcomes at Mie University Hospital. We analyzed singleton pregnant women who underwent delivery management at our hospital between April 2020 and March 2021. Perinatal outcomes were compared between patients who used TPU (TPU+ group) and those who did not (TPU− group). The angle of progression and head direction were measured. The rate of vaginal delivery was significantly increased (90.9% vs. 71.6%; P = 0.0017), and the second stage of labor was significantly prolonged in the TPU+ group (148.1 vs. 75.8 min; P < 0.0001). A significant difference was observed in termination in the latent phase between the TPU+ group [3/8 (37.5%) cases] and TPU− group [20/25 (80.0%) cases] (P = 0.036). The rate of vaginal delivery can be increased through accurate evaluation of the progress of delivery with TPU.