Fetal Screening Research Articles

Pre-autism: What a paediatrician should know about early diagnosis of autism‎.

Autism, also known as an autism spectrum disorder, is a complex neurodevelopmental disorder usually diagnosed in the first three years of a child's life. A range of symptoms characterizes it and can be diagnosed at any age, including adolescence and adulthood. However, early diagnosis is crucial for effective management, prognosis, and care. Unfortunately, there are no established fetal, prenatal, or newborn screening programs for autism, making early detection difficult. This review aims to shed light on the early detection of autism prenatally, natally, and early in life, during a stage we call as "pre-autism" when typical symptoms are not yet apparent. Some fetal, neonatal, and infant biomarkers may predict an increased risk of autism in the coming baby. By developing a biomarker array, we can create an objective diagnostic tool to diagnose and rank the severity of autism for each patient. These biomarkers could be genetic, immunological, hormonal, metabolic, amino acids, acute phase reactants, neonatal brainstem function biophysical activity, behavioral profile, body measurements, or radiological markers. However, every biomarker has its accuracy and limitations. Several factors can make early detection of autism a real challenge. To improve early detection, we need to overcome various challenges, such as raising community awareness of early signs of autism, improving access to diagnostic tools, reducing the stigma attached to the diagnosis of autism, and addressing various culturally sensitive concepts related to the disorder.

Quantitative anatomy of the primary ossification center of the squamous part of temporal bone in the human fetus

Detailed numerical data about the development of primary ossification centers in human fetuses may influence both better evaluation and early detection of skeletal dysplasias, which are associated with delayed development and mineralization of ossification centers. To the best of our knowledge, this is the first report in the medical literature to morphometrically analyze the primary ossification center of the squamous part of temporal bone in human fetuses based on computed tomography imaging. The present study offers a precise quantitative foundation for ossification of the squamous part of temporal bone that may contribute to enhanced prenatal care and improved outcomes for fetuses with inherited cranial defects and skeletodysplasias. The examinations were carried out on 37 human fetuses of both sexes (16 males and 21 females) aged 18–30 weeks of gestation, which had been preserved in 10% neutral formalin solution. Using CT, digital image analysis software, 3D reconstruction and statistical methods, the size of the primary ossification center of the squamous part of temporal bone was evaluated. With neither sex nor laterality differences, the best-fit growth patterns for the primary ossification center of the squamous part of temporal bone was modelled by the linear function: y = −0.7270 + 0.7682 × age ± 1.256 for its vertical diameter, and the four-degree polynomial functions: y = 5.434 + 0.000019 × (age)4 ± 1.617 for its sagittal diameter, y = −4.086 + 0.00029 × (age)4 ± 2.230 for its projection surface area and y = −25.213 + 0.0004 × (age)4 ± 3.563 for its volume. The CT-based numerical data and growth patterns of the primary ossification center of the squamous part of temporal bone may serve as age-specific normative intervals of relevance for gynecologists, obstetricians, pediatricians and radiologists during screening ultrasound scans of fetuses. Our findings for the growing primary ossification center of the squamous part of temporal bone may be conducive in daily clinical practice, while ultrasonically monitoring normal fetal growth and screening for inherited cranial faults and skeletodysplasias.

Discordant performances of non-invasive prenatal testing for foetal trisomy 21 screening in subgroups of pregnancies

Background Non-invasive prenatal testing (NIPT) has been widely adopted as an approach for foetal aneuploidy screening. This study was to evaluate the performance of NIPT for foetal T21 detection in subgroups of pregnancies and the correlation between Z-score and discordant positive predictive values (PPVs). Methods We retrospectively reviewed the NIPT results among 22361 pregnancies undergoing combined second-trimester screening (cSTS) previously. Sixty-four cases with positive NIPT results for foetal T21 were validated by invasive prenatal diagnosis. Results In pregnancies with cSTS-T21 low-, intermediate-, and high-risk, the PPVs at NIPT were 14.3%, 64.3%, and 86.4%, respectively. Mean Z-scores of positive NIPT cases with cSTS-T21 high- and intermediate-risk were comparable, while were higher than that of cases with pre-test low-risk. Furthermore, PPVs for positive NIPT cases at 3 < Z < 5, 5 ≤ Z < 9, and Z ≥ 9 were 16.7%, 63.2%, and 100.0%, respectively. Conclusions This study suggested that Z-score value of positive cases might be associated with discordant PPVs for T21 screening in subgroups of pregnancies.

Retracted: Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation

Retracted: Adoption of Compound Echocardiography under Artificial Intelligence Algorithm in Fetal Congenial Heart Disease Screening during Gestation

Fetal health screening model and element analysis

The United Nations Sustainable Development Goals has mentioned to reduce child mortality. That is also a crucial indicator of human progress. The UN hopes that all countries will eradicate preventable deaths of newborns at the end of 2030. Cardiotocogram (CTG) can be used to identify in-danger women during pregnancy. The aim of this article is to apply machine learning algorithm techniques on CTG data to ensure fetal well-being. CTG data of 2126 samples and 22 variables were obtained from the CTG exams on Kaggle. Two different classification models were trained through the data. In order to predict Normal, Suspect, and Pathological fetal states, each class had its own sensitivity, precision and F1 score. Each model has its overall accuracy. Determined by obstetricians interpretation of CTG, Normal state accounted for 57%, Suspect state accounted for 23% and Pathological state accounted for 20%. The classification models generated by Logistic Regression and Random Forest to predict the suspect and pathological state of the fetus by tracing CTG. They had high precision of 86% and 94% respectively. However, the classification model developed by Random Forest had higher prediction accuracy for a negative fetal outcome. Healthcare workers without professional training in low-income countries have the opportunity to utilize this model for the purpose of prioritizing pregnant women in hard-to-reach regions, ensuring they receive timely referrals and appropriate follow-up care.

A cohort study to investigate the potential indicators for prenatal echocardiographic detection of suspected coarctation of the aorta.

Suspected coarctation of the aorta (CoA) is a common fetal echocardiographic presentation. However, the prenatal findings did not indicate a satisfied accuracy in determining the truly CoA after birth, which made the prenatal diagnosis of CoA still as a critical challenge with high false positive rate. Thus, this research is aimed to distinguish the potential prenatal parameters influencing the fetal echocardiographic images and enhance the true positive diagnostic rate of CoA fetuses which require early clinical intervention in postnatal life. A retrospective study had been designed and fetuses with suspected with CoA had been included from Jan 2016 to Dec 2021 in our center. The fetal echocardiography and related clinical information had been collected. And the postnatal diagnosis had been reached by echocardiography or CTA. Then, all the parameters had been analyzed by univariate analysis, and a multivariate logistic regression analysis was further involved to determine the independent parameters influencing the accuracy of diagnosis CoA fetuses. Moreover, such results had been validated by nomogram analysis and ROC curve. Among the included 44 liveborn infants who presented suspected CoA in fetal cardiac screening, 18 cases had been proved to be CoA postnatally (Group P). The true positive rate for this study was 40.9% (18/44). The abnormal atrial hemodynamic status (AAHs) and the gestational week of delivery (GWoD) were associated with the postnatal CoA confirmation among prenatal suspected fetuses. The ROC curve of predicting probability of the mode combined with two independent factors of absence of AAH and GWoD (AUC = 0.880, 95% CI 0.763-0.997) presented a satisfied efficacy in distinguishing postnatal positive CoA diagnosis. The nomogram plot had been be utilized in CoA prediction (model likelihood ratio test, p < 0.0001). AAH and GWoD had been identified as independent factors of predictive accuracy in detecting postnatal CoA among prenatal suspected fetuses. The prediction mode based on nomogram scores could be used to predict the risk of occurring CoA fetuses.

Diagnostic yield of prenatal exome sequencing in the genetic screening of fetuses with brain anomalies detected by MRI and ultrasonography: A systematic review and meta-analysis.

Brain anomalies (BAs) have been the focus of research, as they have a high impact on fetal health but therapeutic and diagnostic approaches are limited. In this study, the application and efficiency of exome sequencing (ES) in detecting different cases of BAs in fetuses were evaluated and compared with chromosomal microarray analysis (CMA). To conduct this study, three databases including PubMed, Web of Science and Embase were utilised with the keywords 'prenatal', 'diagnoses', 'brain anomalies' and 'exome sequencing'. Studies were included based on the STARD checklist, for which the ES and CMA diagnostic yields were calculated. Meta-analysis was performed on the included studies using a random-effects model and subgroup analysis to define the risk difference between them. We included 11 studies representing 779 fetuses that implemented ES along with imaging techniques. The pooled ES diagnostic yield in fetuses with BAs detected through magnetic resonance imaging (MRI) and ultrasonography was 26.53%, compared with 3.46% for CMA. The risk difference between ES and CMA for complex BAs was 0.36 [95% confidence interval (CI) 0.24-0.47], which was higher than for single BAs (0.22; 95% CI 0.18-0.25]. ES is a useful method with a significantly higher diagnostic yield than CMA for genetic assessment of fetuses with complex BAs detected by imaging techniques. Moreover, ES could be applied to suspected fetuses with related family histories to predict congenital diseases with high efficiency.

Our experience with management of congenital urological pathologies in adulthood: What pediatric urologists should know and adult urologists adopt in pediatric practice experience.

To summarize our experience in the management of congenital anomalies in the kidney and urinary tract (CAKUT) in adults. We conducted a retrospective chart review of all adult patients who underwent primary surgical intervention for CAKUT between 1998 and 2021. The study included 102 patients with a median age of 25 (interquartile range, 23-36.5). Of these, 85 (83.3%) patients reported normal prenatal ultrasound, and the remaining 17 (16.7%) patients were diagnosed with antenatal hydronephrosis. These patients were followed-up conservatively postnatally and were discharged from follow-up because of the absence of indications for surgical intervention or because they decided to leave medical care. All studied adult patients presented with the following pathologies: 67 ureteropelvic junction obstructions, 14 ectopic ureters, 9 ureteroceles, and 6 primary obstructive megaureters, and the remaining 6 patients were diagnosed with vesicoureteral reflux. Forty-three percent of the patients had poorly functioning moieties associated with ectopic ureters or ureteroceles. Notably, 67% of patients underwent pyeloplasty, 9% underwent endoscopic puncture of ureterocele, 3% underwent ureteral reimplantation, 6% underwent endoscopic correction of reflux, 7% underwent partial nephrectomy of non-functioning moiety, and the remaining 9% underwent robotic-assisted laparoscopic ureteroureterostomy. The median follow-up period after surgery was 33 months (interquartile range, 12-54). Post-operative complications occurred in 5 patients (Clavien-Dindo 1-2). Patients with CAKUT present clinical symptoms later in life. Parents of patients diagnosed during fetal screening and treated conservatively should be aware of this possibility, and children should be appropriately counseled when they enter adolescence. Similar surgical skills and operative techniques used in the pediatric population may be applied to adults.

Hunting for the elusive target antigen in gestational alloimmune liver disease (GALD).

The prevailing concept is that gestational alloimmune liver disease (GALD) is caused by maternal antibodies targeting a currently unknown antigen on the liver of the fetus. This leads to deposition of complement on the fetal hepatocytes and death of the fetal hepatocytes and extensive liver injury. In many cases, the newborn dies. In subsequent pregnancies early treatment of the woman with intravenous immunoglobulin can be instituted, and the prognosis for the fetus will be excellent. Without treatment the prognosis can be severe. Crucial improvements of diagnosis require identification of the target antigen. For this identification, this work was based on two hypotheses: 1. The GALD antigen is exclusively expressed in the fetal liver during normal fetal life in all pregnancies; 2. The GALD antigen is an alloantigen expressed in the fetal liver with the woman being homozygous for the minor allele and the father being, most frequently, homozygous for the major allele. We used three different experimental approaches to identify the liver target antigen of maternal antibodies from women who had given birth to a baby with the clinical GALD diagnosis: 1. Immunoprecipitation of antigens from either a human liver cell line or human fetal livers by immunoprecipitation with maternal antibodies followed by mass spectrometry analysis of captured antigens; 2. Construction of a cDNA expression library from human fetal liver mRNA and screening about 1.3 million recombinants in Escherichia coli using antibodies from mothers of babies diagnosed with GALD; 3. Exome/genome sequencing of DNA from 26 presumably unrelated women who had previously given birth to a child with GALD with husband controls and supplementary HLA typing. In conclusion, using the three experimental approaches we did not identify the GALD target antigen and the exome/genome sequencing results did not support the hypothesis that the GALD antigen is an alloantigen, but the results do not yield basis for excluding that the antigen is exclusively expressed during fetal life., which is the hypothesis we favor.

A novel artificial intelligence model for fetal facial profile marker measurement during the first trimester

BackgroundTo study the validity of an artificial intelligence (AI) model for measuring fetal facial profile markers, and to evaluate the clinical value of the AI model for identifying fetal abnormalities during the first trimester.MethodsThis retrospective study used two-dimensional mid-sagittal fetal profile images taken during singleton pregnancies at 11–13+ 6 weeks of gestation. We measured the facial profile markers, including inferior facial angle (IFA), maxilla-nasion-mandible (MNM) angle, facial-maxillary angle (FMA), frontal space (FS) distance, and profile line (PL) distance using AI and manual measurements. Semantic segmentation and landmark localization were used to develop an AI model to measure the selected markers and evaluate the diagnostic value for fetal abnormalities. The consistency between AI and manual measurements was compared using intraclass correlation coefficients (ICC). The diagnostic value of facial markers measured using the AI model during fetal abnormality screening was evaluated using receiver operating characteristic (ROC) curves.ResultsA total of 2372 normal fetuses and 37 with abnormalities were observed, including 18 with trisomy 21, 7 with trisomy 18, and 12 with CLP. Among them, 1872 normal fetuses were used for AI model training and validation, and the remaining 500 normal fetuses and all fetuses with abnormalities were used for clinical testing. The ICCs (95%CI) of the IFA, MNM angle, FMA, FS distance, and PL distance between the AI and manual measurement for the 500 normal fetuses were 0.812 (0.780–0.840), 0.760 (0.720–0.795), 0.766 (0.727-0.800), 0.807 (0.775–0.836), and 0.798 (0.764–0.828), respectively. IFA clinically significantly identified trisomy 21 and trisomy 18, with areas under the ROC curve (AUC) of 0.686 (95%CI, 0.585–0.788) and 0.729 (95%CI, 0.621–0.837), respectively. FMA effectively predicted trisomy 18, with an AUC of 0.904 (95%CI, 0.842–0.966). MNM angle and FS distance exhibited good predictive value in CLP, with AUCs of 0.738 (95%CI, 0.573–0.902) and 0.677 (95%CI, 0.494–0.859), respectively.ConclusionsThe consistency of fetal facial profile marker measurements between the AI and manual measurement was good during the first trimester. The AI model is a convenient and effective tool for the early screen for fetal trisomy 21, trisomy 18, and CLP, which can be generalized to first-trimester scanning (FTS).

Cell-Free Fetal DNA Screening Analysis in Korean Pregnant Women: Six Years of Experience and a Retrospective Study of 9327 Patients Analyzed from 2017 to 2022.

Cell-free DNA (cfDNA) screening for normal fetal aneuploidy has been widely adopted worldwide due to its convenience, non-invasiveness, and high positive predictive rate. We retrospectively evaluated 9327 Korean women with single pregnancies who underwent a non-invasive prenatal test (NIPT) to investigate how various factors such as maternal weight, age, and the method of conception affect the fetal fraction (FF). The average FF was 9.15 ± 3.31%, which decreased significantly as the maternal body mass index (BMI) increased (p < 0.001). The highly obese group showed a 'no-call' rate of 8.01%, which is higher than that of the normal weight group (0.33%). The FF was 8.74 ± 3.20% when mothers were in their 40s, and lower than that when in their 30s (9.23 ± 3.34, p < 0.001) and in the natural pregnancy group (9.31% ± 3.33). The FF of male fetuses was observed to be approximately 2.76% higher on average than that of female fetuses. As the gestational age increased, there was no significant increase in the fraction of fetuses up to 21 weeks compared to that at 10-12 weeks, and a significant increase was observed in the case of 21 weeks or more. The FFs in the NIPT high-risk result group compared to that in the low-risk group were not significantly different (p = 0.62). In conclusion, BMI was the factor most associated with the fetal fraction. Although the NIPT is a highly prevalent method in prenatal analysis, factors affecting the fetal fraction should be thoroughly analyzed to obtain more accurate results.

Development and validation of an artificial intelligence assisted prenatal ultrasonography screening system for trainees.

Fetal anomaly screening via ultrasonography, which involves capturing and interpreting standard views, is highly challenging for inexperienced operators. We aimed to develop and validate a prenatal-screening artificial intelligence system (PSAIS) for real-time evaluation of the quality of anatomical images, indicating existing and missing structures. Still ultrasonographic images obtained from fetuses of 18-32 weeks of gestation between 2017 and 2018 were used to develop PSAIS based on YOLOv3 with global (anatomic site) and local (structures) feature extraction that could evaluate the image quality and indicate existing and missing structures in the fetal anatomical images. The performance of the PSAIS in recognizing 19 standard views was evaluated using retrospective real-world fetal scan video validation datasets from four hospitals. We stratified sampled frames (standard, similar-to-standard, and background views at approximately 1:1:1) for experts to blindly verify the results. The PSAIS was trained using 134 696 images and validated using 836 videos with 12 697 images. For internal and external validations, the multiclass macro-average areas under the receiver operating characteristic curve were 0.943 (95% confidence interval [CI], 0.815-1.000) and 0.958 (0.864-1.000); the micro-average areas were 0.974 (0.970-0.979) and 0.973 (0.965-0.981), respectively. For similar-to-standard views, the PSAIS accurately labeled 90.9% (90.0%-91.4%) with key structures and indicated missing structures. An artificial intelligence system developed to assist trainees in fetal anomaly screening demonstrated high agreement with experts in standard view identification.

Information sharing and communication in management of large for gestational age babies in non‐diabetic mothers

Key content There is no specific UK guideline on how to identify or manage large for gestational age (LGA) fetuses in non‐diabetic mothers. There is conflicting evidence with regard to the optimal mode and timing of delivery in such women and babies in order to minimise the possible risks. Pre‐delivery patient–clinician discussion on management and mode of delivery in LGA babies can be challenging due to the lack of conclusive evidence and guidance for both screening and interventions, but it is crucial in order to facilitate information sharing, counselling and collaborative decision making. Decision‐making tools could help to facilitate these discussions and ensure ‘material risks’ are discussed. Learning objectives To be aware of the limitations of available methods for screening for LGA fetuses, specifically symphyseal fundal height and ultrasound estimation of fetal weight. To understand the lack of robust evidence for obstetric interventions, which makes it difficult to convey clear information in a practical and useful way. To consider the use of decision‐making tools (such as BRAIN and iDECIDE), which can provide a framework for shared decision making, particularly when the evidence is limited or conflicting. These tools offer a structure which empowers patients to weigh up information as well as assist clinicians in determining what is considered ‘material risk’ when counselling in line with the Montgomery ruling. Ethical issues The Montgomery ruling advises that doctors must discuss any ‘material risks’ involved in a proposed treatment and offer other reasonable alternatives. Clinicians, therefore, have a duty to be transparent about the lack of strong evidence to recommend one mode of birth over another but at the same time acknowledge that individual preference and perceptions need to be explored to enable personalised decision making.

EP24.14: Explainable AI to support examiners for abnormality detection in fetal cardiac ultrasound screening

EP24.14: Explainable AI to support examiners for abnormality detection in fetal cardiac ultrasound screening

EP06.08: Diagnostic yield of prenatal‐exome sequencing in the genetic screening of fetuses with brain anomalies: a systematic review and meta‐analysis

EP06.08: Diagnostic yield of prenatal‐exome sequencing in the genetic screening of fetuses with brain anomalies: a systematic review and meta‐analysis

EP08.04: First trimester fetal screening in our hospital

EP08.04: First trimester fetal screening in our hospital

Fast fetal head compounding from multi-view 3D ultrasound.

The diagnostic value of ultrasound images may be limited by the presence of artefacts, notably acoustic shadows, lack of contrast and localised signal dropout. Some of these artefacts are dependent on probe orientation and scan technique, with each image giving a distinct, partial view of the imaged anatomy. In this work, we propose a novel method to fuse the partially imaged fetal head anatomy, acquired from numerous views, into a single coherent 3D volume of the full anatomy. Firstly, a stream of freehand 3D US images is acquired using a single probe, capturing as many different views of the head as possible. The imaged anatomy at each time-point is then independently aligned to a canonical pose using a recurrent spatial transformer network, making our approach robust to fast fetal and probe motion. Secondly, images are fused by averaging only the most consistent and salient features from all images, producing a more detailed compounding, while minimising artefacts. We evaluated our method quantitatively and qualitatively, using image quality metrics and expert ratings, yielding state of the art performance in terms of image quality and robustness to misalignments. Being online, fast and fully automated, our method shows promise for clinical use and deployment as a real-time tool in the fetal screening clinic, where it may enable unparallelled insight into the shape and structure of the face, skull and brain.

Prenatal diagnosis of hypoplastic left heart syndrome on ultrasound using artificial intelligence: How does performance compare to a current screening programme?

Artificial intelligence (AI) has the potential to improve prenatal detection of congenital heart disease. We analysed the performance of the current national screening programme in detecting hypoplastic left heart syndrome (HLHS) to compare with our own AI model. Current screening programme performance was calculated from local and national sources. AI models were trained using four-chamber ultrasound views of the fetal heart, using a ResNet classifier. Estimated current fetal screening programme sensitivity and specificity for HLHS were 94.3% and 99.985%, respectively. Depending on calibration, AI models to detect HLHS were either highly sensitive (sensitivity 100%, specificity 94.0%) or highly specific (sensitivity 93.3%, specificity 100%). Our analysis suggests that our highly sensitive model would generate 45,134 screen positive results for a gain of 14 additional HLHS cases. Our highly specific model would be associated with two fewer detected HLHS cases, and 118 fewer false positives. If used independently, our AI model performance is slightly worse than the performance level of the current screening programme in detecting HLHS, and this performance is likely to deteriorate further when used prospectively. This demonstrates that collaboration between humans and AI will be key for effective future clinical use.

Fetal RHD Screening in RH1 Negative Pregnant Women: Experience in Switzerland.

RH1 incompatibility between mother and fetus can cause hemolytic disease of the fetus and newborn. In Switzerland, fetal RHD genotyping from maternal blood has been recommended from gestational age 18 onwards since the year 2020. This facilitates tailored administration of RH immunoglobulin (RHIG) only to RH1 negative women carrying a RH1 positive fetus. Data from 30 months of noninvasive fetal RHD screening is presented. Cell-free DNA was extracted from 7192 plasma samples using a commercial kit, followed by an in-house qPCR to detect RHD exons 5 and 7, in addition to an amplification control. Valid results were obtained from 7072 samples, with 4515 (64%) fetuses typed RHD positive and 2556 (36%) fetuses being RHD negative. A total of 120 samples led to inconclusive results due to the presence of maternal or fetal RHD variants (46%), followed by women being serologically RH1 positive (37%), and technical issues (17%). One sample was typed false positive, possibly due to contamination. No false negative results were observed. We show that unnecessary administration of RHIG can be avoided for more than one third of RH1 negative pregnant women in Switzerland. This reduces the risks of exposure to a blood-derived product and conserves this limited resource to women in actual need.

Pulmonary Sequestration and Congenital Pulmonary Airway Malformation (CPAM) 1 Presented as A Left Suprarenal Mass:ACase Report

Introduction Pulmonary sequestration is a rare condition accounting for 0.1% to 6% of all congenital lung malformations. The correlation with Congenital Pulmonary Airway Malformation (CPAM) type 1 has not been adequately elucidated. Case presentation From routine fetal sonographic screening, a 20-day-old female baby's ultrasound revealed hydronephrosis with enlargement above the left kidney. Magnetic resonance imaging during a follow-up appointment uncovered a left suprarenal lesion of approximately 30 mm, which was not suspected to be adrenal neuroblastoma. After resection, histological analysis was consistent with pulmonary sequestration and confirmed the connection with CPAM type 1. Conclusion Surgery remains the only effective therapeutic choice for intra-abdominal pulmonary sequestration. The definitive diagnosis is confirmed through histological examination.