Risk of major congenital heart disease in pregestational maternal diabetes is modified by hemoglobin A1c.

OBJECTIVES: The association between pregestational diabetes mellitus (PDM) and risk of congenital heart disease (CHD) is well recognized; however, the importance of glycemic control and other coexisting risk factors during pregnancy is less clear. We sought to determine the relative risk (RR) of major CHD (mCHD) among offspring from pregnancies complicated by PDM and the effect of first-trimester glycemic control on mCHD risk. METHODS: We determined the incidence of mCHD (requiring surgery within 1 year of birth or resulting in pregnancy termination or fetal demise) among registered births in Alberta, Canada. Linkage of diabetes status, maximum hemoglobin A1c (HbA1c) at < 16 weeks' gestation and other covariates was performed using data from the Alberta Perinatal Health Program registry. Risk of mCHD according to HbA1c was estimated as an adjusted RR (aRR), calculated using log-binomial modeling. RESULTS: Of 1412 cases of mCHD in 594 773 (2.37/1000) births in the study period, mCHD was present in 48/7497 with PDM (6.4/1000; RR, 2.8 (95% CI, 2.1-3.7); P < 0.0001). In the entire cohort, increased maternal age (aRR, 1.03 (95% CI, 1.02-1.04); P < 0.0001) and multiple gestation (aRR, 1.37 (95% CI, 1.1-1.8); P = 0.02) were also associated with mCHD risk, whereas maternal prepregnancy weight > 91 kg was not. The stratified risk for mCHD associated with HbA1c ≤ 6.1%, > 6.1-8.0% and > 8.0% was 4.2/1000, 6.8/1000 and 17.1/1000 PDM/gestational diabetes mellitus births, respectively; the aRR of mCHD associated with PDM and HbA1c > 8.0% was 8.5 (95% CI, 5.0-14.4) compared to those without diabetes and 5.5 (95% CI, 1.6-19.4) compared to PDM with normal HbA1c (≤ 6.1%). CONCLUSIONS: PDM is associated with a RR of 2.8 for mCHD, increasing to 8.5 in those with HbA1c > 8%. These data should facilitate refinement of referral indications for high-risk pregnancy screening. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?

OBJECTIVES: Artificial intelligence (AI) has shown promise in improving the performance of fetal ultrasound screening in detecting congenital heart disease (CHD). The effect of giving AI advice to human operators has not been studied in this context. Giving additional information about AI model workings, such as confidence scores for AI predictions, may be a way of further improving performance. Our aims were to investigate whether AI advice improved overall diagnostic accuracy (using a single CHD lesion as an exemplar), and to determine what, if any, additional information given to clinicians optimized the overall performance of the clinician-AI team. METHODS: An AI model was trained to classify a single fetal CHD lesion (atrioventricular septal defect (AVSD)), using a retrospective cohort of 121 130 cardiac four-chamber images extracted from 173 ultrasound scan videos (98 with normal hearts, 75 with AVSD); a ResNet50 model architecture was used. Temperature scaling of model prediction probability was performed on a validation set, and gradient-weighted class activation maps (grad-CAMs) produced. Ten clinicians (two consultant fetal cardiologists, three trainees in pediatric cardiology and five fetal cardiac sonographers) were recruited from a center of fetal cardiology to participate. Each participant was shown 2000 fetal four-chamber images in a random order (1000 normal and 1000 AVSD). The dataset comprised 500 images, each shown in four conditions: (1) image alone without AI output; (2) image with binary AI classification; (3) image with AI model confidence; and (4) image with grad-CAM image overlays. The clinicians were asked to classify each image as normal or AVSD. RESULTS: A total of 20 000 image classifications were recorded from 10 clinicians. The AI model alone achieved an accuracy of 0.798 (95% CI, 0.760-0.832), a sensitivity of 0.868 (95% CI, 0.834-0.902) and a specificity of 0.728 (95% CI, 0.702-0.754), and the clinicians without AI achieved an accuracy of 0.844 (95% CI, 0.834-0.854), a sensitivity of 0.827 (95% CI, 0.795-0.858) and a specificity of 0.861 (95% CI, 0.828-0.895). Showing a binary (normal or AVSD) AI model output resulted in significant improvement in accuracy to 0.865 (P < 0.001). This effect was seen in both experienced and less-experienced participants. Giving incorrect AI advice resulted in a significant deterioration in overall accuracy, from 0.761 to 0.693 (P < 0.001), which was driven by an increase in both Type-I and Type-II errors by the clinicians. This effect was worsened by showing model confidence (accuracy, 0.649; P < 0.001) or grad-CAM (accuracy, 0.644; P < 0.001). CONCLUSIONS: AI has the potential to improve performance when used in collaboration with clinicians, even if the model performance does not reach expert level. Giving additional information about model workings such as model confidence and class activation map image overlays did not improve overall performance, and actually worsened performance for images for which the AI model was incorrect. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Umbilical Vein Flows and Cardiac Size, Shape, and Ventricular Contractility in Fetuses With Estimated Weight Less-Than 10th Centile.

OBJECTIVES: In a cohort of patients with estimated fetal weights (EFWs) <10th centile, we aimed 1) to compare the prevalence of abnormalities of fetal 4-chamber view (4CV) cardiac size, shape, and ventricular contractility in fetal growth restricted (FGR) and small-for-gestational-age (SGA) fetuses and 2) to compare umbilical vein flow (UVF) measurements to standard Doppler surveillance in predicting abnormalities of cardiac function. METHODS: Prospective observational cohort study of fetuses with EFW <10th percentile. Measurements of size and shape used were 4CV transverse width, 4CV cardiac area, 4CV global sphericity index, and right-to-left ventricular mid-chamber width ratio. Variables of contractility used were fractional shortening change at the mid-ventricle chamber, global longitudinal strain, fractional area change, and left ventricular cardiac output. The UVF and standard Doppler surveillance including umbilical artery (UA), middle cerebral artery, and cerebroplacental ratio (CPR) were collected. Control data were from previously published studies. RESULTS: A total of 95 fetuses with EFWs <10th centile were included in the study. The rates of abnormalities of cardiac size and shape and ventricular contractility were all significantly elevated compared with normally grown control fetuses but similar between FGR and SGA fetuses. In a subset of 76 patients with UVF data, evaluation UVF identified more patients with any abnormality of contractility compared with UA (37.9 vs 17.2%, P = .02). CONCLUSIONS: The addition of UVF doubled the detection rate of ventricular contractility abnormalities. The addition of UVF should be considered in the surveillance of FGR and SGA fetuses to further stratify the severity of hypoxemia and to identify those at greater risk for future cardiovascular dysfunction.

Machine Learning to Predict Outcomes of Fetal Cardiac Disease: A Pilot Study.

Prediction of outcomes following a prenatal diagnosis of congenital heart disease (CHD) is challenging. Machine learning (ML) algorithms may be used to reduce clinical uncertainty and improve prognostic accuracy. We performed a pilot study to train ML algorithms to predict postnatal outcomes based on clinical data. Specific objectives were to predict (1) in utero or neonatal death, (2) high-acuity neonatal care and (3) favorable outcomes. We included all fetuses with cardiac disease at Sunnybrook Health Sciences Centre, Toronto, Canada, from 2012 to 2021. Prediction models were created using the XgBoost algorithm (tree-based) with fivefold cross-validation. Among 211 cases of fetal cardiac disease, 61 were excluded (39 terminations, 21 lost to follow-up, 1 isolated arrhythmia), leaving a cohort of 150 fetuses. Fifteen (10%) demised (10 neonates) and 65 (48%) of live births required high acuity neonatal care. Of those with clinical follow-up, 60/87 (69%) had a favorable outcome. Prediction models for fetal or neonatal death, high acuity neonatal care and favorable outcome had AUCs of 0.76, 0.84 and 0.73, respectively. The most important predictors for death were the presence of non-cardiac abnormalities combined with more severe CHD. High acuity of postnatal care was predicted by anti Ro antibody and more severe CHD. Favorable outcome was most predicted by no right heart disease combined with genetic abnormalities, and maternal medications. Prediction models using ML provide good discrimination of key prenatal and postnatal outcomes among fetuses with congenital heart disease.

Utilizing ChatGPT to Facilitate Referrals for Fetal Echocardiography.

INTRODUCTION: OpenAI's GPT-4 (artificial intelligence [AI]) is being studied for its use as a medical decision support tool. This research examines its accuracy in refining referrals for fetal echocardiography (FE) to improve early detection and outcomes related to congenital heart defects (CHDs). METHODS: Past FE data referred to our institution were evaluated separately by pediatric cardiologist, gynecologist (human experts [experts]), and AI, according to established guidelines. We compared experts and AI's agreement on referral necessity, with experts addressing discrepancies. RESULTS: Total of 59 FE cases were addressed retrospectively. Cardiologist, gynecologist, and AI recommended performing FE in 47.5%, 49.2%, and 59.0% of cases, respectively. Comparing AI recommendations to experts indicated agreement of around 80.0% with both experts (p < 0.001). Notably, AI suggested more echocardiographies for minor CHD (64.7%) compared to experts (47.1%), and for major CHD, experts recommended performing FE in all cases (100%) while AI recommended in majority of cases (90.9%). Discrepancies between AI and experts are detailed and reviewed. CONCLUSIONS: The evaluation found moderate agreement between AI and experts. Contextual misunderstandings and lack of specialized medical knowledge limit AI, necessitating clinical guideline guidance. Despite shortcomings, AI's referrals comprised 65% of minor CHD cases versus experts 47%, suggesting its potential as a cautious decision aid for clinicians.

Learning deep architectures for the interpretation of first-trimester fetal echocardiography (LIFE) - a study protocol for developing an automated intelligent decision support system for early fetal echocardiography.

BACKGROUND: Congenital Heart Disease represents the most frequent fetal malformation. The lack of prenatal identification of congenital heart defects can have adverse consequences for the neonate, while a correct prenatal diagnosis of specific cardiac anomalies improves neonatal care neurologic and surgery outcomes. Sonographers perform prenatal diagnosis manually during the first or second-trimester scan, but the reported detection rates are low. This project's primary objective is to develop an Intelligent Decision Support System that uses two-dimensional video files of cardiac sweeps obtained during the standard first-trimester fetal echocardiography (FE) to signal the presence/absence of previously learned key features. METHODS: The cross-sectional study will be divided into a training part of the machine learning approaches and the testing phase on previously unseen frames and eventually on actual video scans. Pregnant women in their 12-13 + 6 weeks of gestation admitted for routine first-trimester anomaly scan will be consecutively included in a two-year study, depending on the availability of the experienced sonographers in early fetal cardiac imaging involved in this research. The Data Science / IT department (DSIT) will process the key planes identified by the sonographers in the two- dimensional heart cine loop sweeps: four-chamber view, left and right ventricular outflow tracts, three vessels, and trachea view. The frames will be grouped into the classes representing the plane views, and then different state-of-the- art deep-learning (DL) pre-trained algorithms will be tested on the data set. The sonographers will validate all the intermediary findings at the frame level and the meaningfulness of the video labeling. DISCUSSION: FE is feasible and efficient during the first trimester. Still, the continuous training process is impaired by the lack of specialists or their limited availability. Therefore, in our study design, the sonographer benefits from a second opinion provided by the developed software, which may be very helpful, especially if a more experienced colleague is unavailable. In addition, the software may be implemented on the ultrasound device so that the process could take place during the live examination. TRIAL REGISTRATION: The study is registered under the name "Learning deep architectures for the Interpretation of Fetal Echocardiography (LIFE)", project number 408PED/2020, project code PN-III-P2-2.1-PED-2019. TRIAL REGISTRATION: ClinicalTrials.gov , unique identifying number NCT05090306, date of registration 30.10.2020.

Prenatal Diagnosis Rate of Critical Congenital Heart Disease Remains Inadequate with Significant Racial/Ethnic and Socioeconomic Disparities and Technical Barriers.

Prenatal diagnosis (preDx) of critical congenital heart disease (CCHD) decreases neonatal morbidity and mortality. Obstetrical fetal cardiac imaging guidelines in 2013 aimed to increase preDx. The objectives of this study were to determine the contemporary preDx rate of CCHD and identify maternal-fetal factors and variations in prenatal care that may be potential barriers. This retrospective single center study evaluated maternal demographics and characteristics of infants with CCHD (requiring cardiac catheterization or surgical intervention before 6 months-old) between 2016 and 2019. 58% of the 339 infants with CCHD had preDx. Infants with preDx were more likely to have mothers ≥ 35 years-old (p = 0.028), family history of CHD (p = 0.017), health insurance (p = 0.002), or anatomic scan with perinatology (p < 0.001). Hispanic infants were less likely to have preDx (45.6%, p = 0.005). PreDx rates were higher in infants with extracardiac/genetic anomalies (p < 0.001) and significantly different between CCHD subtypes (76% for single ventricle, 51% for biventricular/four-chamber view, 59% for proximal outflow tract anomalies, and 48% for distal great artery anomalies; p = 0.024). In infants without preDx, 25% of their mothers had indication for, but did not undergo, fetal echocardiography. PreDx rates of CCHD remains inadequate across subtypes detectable by standard fetal cardiac screening views, particularly in uninsured and Hispanic communities.

Prenatal Congenital Heart Disease-It Takes a Multidisciplinary Village.

Prenatal diagnosis of congenital heart disease (CHD) allows for thoughtful multidisciplinary planning about location, timing, and need for medical interventions at birth. We sought to assess the accuracy of our prenatal cardiac diagnosis, and postnatal needs for patients with CHD utilizing a multidisciplinary approach. We performed a retrospective chart review of fetal CHD patients between 1/1/18 and 4/30/19. Maternal and infant charts were reviewed for delivery planning, subspecialty care needs, genetic evaluation, prenatal and postnatal cardiac diagnoses, need for prostaglandin (PGE) and neonatal cardiac intervention. 82 maternal-fetal dyads met inclusion criteria during the study period and delivered at a median of 38w2d gestation. 32 (39%) dyads had CHD and other anomalies or genetic abnormalities. All dyads met with a genetic counselor and neonatologist. 11 patients delivered at outside hospitals as planned (all with isolated CHD not requiring neonatal intervention), and 5 chose a palliative delivery. 30 patients were counseled to expect a neonatal cardiac intervention and 25 (83%) underwent an intervention within the expected time period. No neonates required an uncounseled cardiac intervention. 29 patients planned for PGE at birth and 31 received PGE. Of the 79 postnatal echocardiograms, 60 (76%) were entirely consistent with the fetal diagnosis. A multidisciplinary approach to the prenatal diagnosis of CHD in maternal-fetal dyads is optimal and utilizing this method we were able to accurately predict postnatal physiology and ensure that patients delivered in the correct location with an appropriate supportive structure in place.

Performance of a single-ventricle home-monitoring programme: survival and predictors of adverse outcome.

INTRODUCTION AND BACKGROUND: Mortality between stages 1 and 2 single-ventricle palliation is significant. Home-monitoring programmes are suggested to reduce mortality. Outcomes and risk factors for adverse outcomes for European programmes have not been published. AIMS: To evaluate the performance of a home-monitoring programme at a medium-sized United Kingdom centre with regards survival and compare performance with other home-monitoring programmes in the literature. METHODS: All fetal and postnatal diagnosis of a single ventricle were investigated with in-depth analysis of those undergoing stage 1 palliation and entered the home-monitoring programme between 2016 and 2020. The primary outcome was survival. Secondary outcomes included multiple parameters as potential predictors of death or adverse outcome. RESULTS: Of 217 fetal single-ventricle diagnoses during the period 2016-2020, 50.2% progressed to live birth, 35.4% to stage 1 and 29.5% to stage 2. Seventy-four patients (including 10 with postnatal diagnosis) entered the home-monitoring programme with six deaths making home-monitoring programme mortality 8.1%. Risk factors for death were the hybrid procedure as the only primary procedure (OR 33.0, p < 0.01), impaired cardiac function (OR 10.3, p < 0.025), Asian ethnicity (OR 9.3, p < 0.025), lower mean birth-weight (2.69 kg versus 3.31 kg, p < 0.01), and lower mean weight centiles during interstage follow-up (mean centiles of 3.1 versus 10.8, p < 0.01). CONCLUSION: Survival in the home-monitoring programme is comparable with other home-monitoring programmes in the literature. Hybrid procedure, cardiac dysfunction, sub-optimal weight gain, and Asian ethnicity were significant risk factors for death. Home-monitoring programmes should continue to raise awareness of these factors and seek solutions to mitigate adverse events. Future work to generalise home-monitoring programme and single-ventricle fetus to stage 2 outcomes in the United Kingdom will require multi-centre collaboration.

Impact of rural residence and low socioeconomic status on rate and timing of prenatal detection of major congenital heart disease in a jurisdiction of universal health coverage.

OBJECTIVE: Socioeconomic status (SES) and distance of residence from tertiary care may impact fetal detection of congenital heart disease (CHD), partly through reduced access to and quality of obstetric ultrasound screening. It is unknown whether SES and remoteness of residence (RoR) affect prenatal detection of CHD in jurisdictions with universal health coverage. We examined the impact of SES and RoR on the rate and timing of prenatal diagnosis of major CHD within the province of Alberta in Canada. METHODS: In this retrospective study, we identified all fetuses and infants diagnosed with major CHD in Alberta, from 2008 to 2018, that underwent cardiac surgical intervention within the first year after birth, died preoperatively, were stillborn or underwent termination. Using maternal residence postal code and geocoding, Chan SES index quintile, geographic distance from a tertiary-care fetal cardiology center and the Canadian Index of Remoteness (IoR) were calculated. Outcome measures included rates of prenatal diagnosis and diagnosis after 22 weeks' gestation. Risk ratios (RR) were calculated using log-binomial regression and stratified by rural (≥ 100 km from tertiary care) or metropolitan (< 100 km from tertiary care) residence, adjusting for year of birth and the obstetric ultrasound screening view in which CHD would most likely be detected (four-chamber view; outflow-tract view; three-vessel or three-vessels-and-trachea or non-standard view; septal view). RESULTS: Of 1405 fetuses/infants with major CHD, prenatal diagnosis occurred in 814 (57.9%). Residence ≥ 100 km from tertiary care (adjusted RR, 1.19; 95% CI, 1.05-1.34) and higher IoR (adjusted RR, 1.9; 95% CI, 1.1-3.3) were associated with missed prenatal diagnosis of major CHD. Similarly, residence ≥ 100 km from tertiary care (adjusted RR, 1.41; 95% CI, 1.22-1.62) and higher IoR (adjusted RR, 3.6; 95% CI, 2.2-8.2) were associated with prenatal diagnosis after 22 weeks. Although adjusted and unadjusted analyses showed no association between Chan SES index quintile and prenatal-diagnosis rate overall nor for residence in rural areas, in metropolitan regions, lower SES quintiles were associated with missed prenatal diagnosis (quintile 1: RR, 1.24; 95% CI, 1.02-1.50) and higher risk of diagnosis after 22 weeks' gestation (quintile 1: RR, 1.46; 95% CI, 1.10-1.93; quintile 2: RR, 1.66; 95% CI, 1.24-2.23). CONCLUSIONS: Despite universal healthcare, rural residence in Alberta is associated with lower rate of prenatal diagnosis of major CHD and higher risk of late prenatal diagnosis (≥ 22 weeks). Within metropolitan regions, lower SES impacts negatively prenatal-diagnosis rate and timing. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Valvuloplasty in 103 fetuses with critical aortic stenosis: outcome and new predictors for postnatal circulation.

OBJECTIVES: To review our experience with fetal aortic valvuloplasty (FAV) in fetuses with critical aortic stenosis (CAS) and evolving hypoplastic left heart syndrome (eHLHS), including short- and medium-term postnatal outcome, and to refine selection criteria for FAV by identifying preprocedural predictors of biventricular (BV) outcome. METHODS: This was a retrospective review of all fetuses with CAS and eHLHS undergoing FAV at our center between December 2001 and September 2020. Echocardiograms and patient charts were analyzed for pre-FAV ventricular and valvular dimensions and hemodynamics and for postnatal procedures and outcomes. The primary endpoints were type of circulation 28 days after birth and at 1 year of age. Classification and regression-tree analysis was performed to investigate the predictive capacity of pre-FAV parameters for BV circulation at 1 year of age. RESULTS: During the study period, 103 fetuses underwent 125 FAVs at our center, of which 87.4% had a technically successful procedure. Technical success per fetus was higher in the more recent period (from 2014) than in the earlier period (96.2% (51/53) vs 78.0% (39/50); P = 0.0068). Eighty fetuses were liveborn after successful intervention and received further treatment. BV outcome at 1 year of age was achieved in 55% of liveborn patients in our cohort after successful FAV, which is significantly higher than the BV-outcome rate (23.7%) in a previously published natural history cohort fulfilling the same criteria for eHLHS (P = 0.0015). Decision-tree analysis based on the ratio of right to left ventricular (RV/LV) length combined with LV pressure (mitral valve regurgitation maximum velocity (MR-Vmax)) had a sensitivity of 96.97% and a specificity of 94.44% for predicting BV outcome without signs of pulmonary arterial hypertension at 1 year of age. The highest probability for a BV outcome was reached for fetuses with a pre-FAV RV/LV length ratio of < 1.094 (96.4%) and for those fetuses with a RV/LV length ratio ≥ 1.094 to < 1.135 combined with a MR-Vmax of ≥ 3.14 m/s (100%). CONCLUSIONS: FAV could be performed with high success rates and an acceptable risk with improving results after a learning curve. Pre-FAV RV/LV length ratio combined with LV pressure estimates were able to predict a successful BV outcome at 1 year of age with high sensitivity and specificity. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Third Trimester Fetal Heart Rates in Antibody-Mediated Complete Heart Block Predict Need for Neonatal Pacemaker Placement.

Congenital complete heart block (CCHB) affects 1 in 20,000 newborns. This study evaluates fetal and neonatal risk factors predictive of neonatal pacemaker placement in antibody-mediated complete heart block. The Children's Hospital Los Angeles institutional fetal, pacemaker, and medical record databases were queried for confirmed SSA/SSB cases of CCHB between January 2004 and July 2019. Cases excluded were those with a diagnosis beyond the neonatal period, diagnosis of a channelopathy, or if maternal antibody status was unknown. We recorded the gestational age (GA), birth weight (BW), fetal heart rates (FHRs) of the last echocardiogram before delivery, specific neonatal ECG and echocardiogram findings, age at pacemaker placement, and mortality. Of 43 neonates identified with CCHB, 27 had confirmed maternal antibody exposure. Variables associated with neonatal pacemaker implantation were FHRs < 50 bpm (p = 0.005), neonatal heart rates < 52 bpm (p = 0.015), and neonatal left ventricular fractional shortening (FS) percentages < 34% (p = 0.03). On multivariate analysis, FHR remained significant (p = 0.03) and demonstrated an increased risk of neonatal pacemaker placement by an odds ratio of 12.5 (95% CI 1.3-116, p = 0.05). The median GA at which the FHR was obtained was 34 weeks (IQR 26-35 weeks). Neonatal pacemaker placement was highly associated with a FHR < 50 bpm, neonatal HR < 52 bpm, and neonatal FS < 34%. FHRs at 34 weeks GA (IQR 26-35 weeks) correlated well with postnatal heart rates and were predictive of neonatal pacemaker placement.

Prenatal ultrasound combined with cardiovascular casts diagnose symmetrically complex cardiac malformations in two fetuses.

Dextrocardia with a ductus arteriosus (DA) malformation is extremely rare. Here, we present a case of dextrocardia complicated with a right DA that is circuitously connecting the pulmonary artery and the right brachiocephalic artery. Coincidentally, the deformities of this fetus are almost symmetrical with those in another fetus (also presented here), which is astonishing and meaningful. Dextrocardia is rare, complicated, and not well understood. In this report, we carefully compared prenatal echocardiographic images and cardiovascular casts from two fetuses. Our report of these cases may provide new insights for cardiologists to better understand dextrocardia and its associated malformations.

Expanding Access to Fetal Telecardiology During the COVID-19 Pandemic.

Background: This study aims to describe one center's experience in expanding a fetal telecardiology program through collaborative work with maternal fetal medicine (MFM) clinics with the goal of safely reaching mothers during the COVID-19 pandemic. We sought to define the extent of fetal telehealth conversion at a large fetal cardiac care center and evaluate the diagnostic accuracy for studies performed. Methods: At our center, fetal telemedicine expanded from one MFM site before the pandemic to four additional sites by May 2020. A retrospective review of fetal telecardiology visits between March 15 and July 15, 2020, was performed. The chart was reviewed for confirmation of diagnosis postnatally. Results: With pandemic onset, there was a large increase in the number of telemedicine visits with a total of 122 mothers seen between five MFM clinics. Fourteen mothers (11.5%) had abnormal fetal echocardiograms requiring additional follow-up, and seven mothers (5.8%) had a fetal echocardiogram suspicious for a critical congenital heart disease (CCHD). All the fetal echocardiograms suspicious for CCHD were confirmed on postnatal echocardiogram. To our knowledge, none of the normal fetal echocardiograms were found to have congenital heart disease postnatally. Conclusions: In response to the COVID-19 pandemic, we rapidly transitioned to fetal telecardiology using a variety of formats. This has reduced potential infectious exposure for pregnant mothers and minimized contact between physicians without compromising diagnostic accuracy. In our experience, the expansion of a telemedicine program requires strong initial infrastructure, prior relationships with MFM providers, and appropriate training among obstetric sonographers.

Early Postnatal Echocardiography in Neonates with a Prenatal Suspicion of Coarctation of the Aorta.

Coarctation of the aorta (COA) is suspected prenatally when there is ventricular asymmetry, arterial disproportion, and hypoplasia of the aortic arch/isthmus. The presence of fetal shunts creates difficulty in prenatal confirmation of the diagnosis so serial echocardiography after birth is necessary to confirm or refute the diagnosis. The first neonatal echocardiogram in prenatally suspected cases of COA was assessed for prediction of neonatal COA repair (NCOAR). This included morphological assessment, measurement of the aortic arch and calculation of the distal arch index (DAI = distance between left common carotid and left subclavian artery/diameter of the distal arch). NCOAR was undertaken in 23/60 (38%) cases. Transverse arch, aortic isthmus z-score, and DAI had an area under the receiver operator curve of 0.88 (95% CI 0.77-0.98), 0.86 (95% CI 0.75-0.96), and 0.84 (95% CI 0.74-0.95), respectively for the prediction of NCOAR. Using transverse arch z-score threshold < - 3 gave sensitivity 100%, NPV: 100%, specificity 76%; aortic isthmus z-score < - 3: NPV 92%, specificity 62% and DAI > 1.4: NPV 88%, specificity 78%. The size of the distal aortic arch in infants with a common origin of the innominate artery and left common carotid artery who did not require COA repair was similar to the NCOAR cases (p = 0.22). The early postnatal assessment of the size and morphology of the aortic arch can assist in risk stratification for development of neonatal COA. The branching pattern of the head/neck vessels impacts on the size of the distal aortic arch adding to the complexity of predicting COA based on vessel size.

Machine Learning in Fetal Cardiology: What to Expect.

In fetal cardiology, imaging (especially echocardiography) has demonstrated to help in the diagnosis and monitoring of fetuses with a compromised cardiovascular system potentially associated with several fetal conditions. Different ultrasound approaches are currently used to evaluate fetal cardiac structure and function, including conventional 2-D imaging and M-mode and tissue Doppler imaging among others. However, assessment of the fetal heart is still challenging mainly due to involuntary movements of the fetus, the small size of the heart, and the lack of expertise in fetal echocardiography of some sonographers. Therefore, the use of new technologies to improve the primary acquired images, to help extract measurements, or to aid in the diagnosis of cardiac abnormalities is of great importance for optimal assessment of the fetal heart. Machine leaning (ML) is a computer science discipline focused on teaching a computer to perform tasks with specific goals without explicitly programming the rules on how to perform this task. In this review we provide a brief overview on the potential of ML techniques to improve the evaluation of fetal cardiac function by optimizing image acquisition and quantification/segmentation, as well as aid in improving the prenatal diagnoses of fetal cardiac remodeling and abnormalities.

Fetal Echocardiographic Parameters and Surgical Outcomes in Congenital Left-Sided Cardiac Lesions.

This study aimed to evaluate fetal echocardiographic parameters associated with neonatal intervention and single-ventricle palliation (SVP) in fetuses with suspected left-sided cardiac lesions. Initial fetal echocardiograms (1/2002-1/2017) were interpreted by the contemporary fetal cardiologist as coarctation of the aorta (COA), left heart hypoplasia (LHH), hypoplastic left heart syndrome (HLHS), mitral valve hypoplasia (MVH) ± stenosis, and aortic valve hypoplasia ± stenosis (AS). The cohort comprised 68 fetuses with suspected left-sided cardiac lesions (COA n = 15, LHH n = 9, HLHS n = 39, MVH n = 1, and AS n = 4). Smaller left ventricular (LV) length Z score, aortic valve Z score, ascending aorta Z score, and aorta/pulmonary artery ratio; left-to-right shunting at the foramen ovale; and retrograde flow in the aortic arch were associated with the need for neonatal intervention (p = 0.005-0.04). Smaller mitral valve (MV) Z score, LV length Z score, aortic valve Z score, ascending aorta Z score, aorta/pulmonary artery ratio, and LV ejection fraction, as well as higher tricuspid valve-to-MV (TV/MV) ratio, right ventricular-to-LV (RV/LV) length ratio, left-to-right shunting at the foramen ovale, abnormal pulmonary vein Doppler, absence of prograde aortic flow, and retrograde flow in the aortic arch were associated with SVP (p < 0.001-0.008). The strongest independent variable associated with SVP was RV/LV length ratio (stepwise logistical regression, p = 0.03); an RV/LV length ratio > 1.28 was associated with SVP with a sensitivity of 76% and specificity of 96% (AUC 0.90, p < 0.001). A fetal RV/LV length ratio of > 1.28 may be a useful threshold for identifying fetuses requiring SVP.

Postnatal Outcome Following Prenatal Diagnosis of Discordant Atrioventricular and Ventriculoarterial Connections.

Discordant atrioventricular and ventriculoarterial connection(s) (DAVVAC) are a rare group of congenital heart lesions. DAVVAC can be isolated or associated with a variety of other cardiac abnormalities. Previous studies examining the outcome of prenatally diagnosed DAVVAC have described only fetal and early postnatal outcome in small cohorts. We aimed to describe the medium-term outcome of these fetuses. Cases were identified by searching the fetal cardiac databases of two centers. Follow-up data were collected from the electronic patient records. We identified 98 fetuses with DAVVAC. 39 pregnancies were terminated and 51 resulted in a liveborn infant. Postnatal data were available for 43 patients. The median length of follow-up was 9.5 years (range 36 days to 22.7 years). The overall 5-year survival of the cohort was 80% (95% confidence interval 74-86%), no deaths were seen after this period. Associated cardiac lesions had a significant effect on both survival and surgery-free survival. Isolated DAVVAC and DAVVAC with pulmonary stenosis ± ventricular septal defect had a low mortality (89% and 100% 5-year survival, respectively). Poorer survival was seen in the group with Ebstein's anomaly of the tricuspid valve, and other complex cardiac abnormalities. Antenatal tricuspid regurgitation had a significant negative impact on postnatal survival. In conclusion, the short- and medium-term outlook for fetuses with isolated DAVVAC, and those with DAVVAC and pulmonary stenosis are good. Antenatal risk factors for postnatal mortality include Ebstein's anomaly of the tricuspid valve, especially if associated with tricuspid regurgitation, and the presence of complex associated lesions.

Improved technical success, postnatal outcome and refined predictors of outcome for fetal aortic valvuloplasty.

OBJECTIVES: Fetal aortic valvuloplasty (FAV) may prevent progression of mid-gestation aortic stenosis to hypoplastic left heart syndrome (HLHS). The aim of this study was to evaluate whether technical success and biventricular (Biv) outcome after FAV have changed from an earlier (2000-2008) to a more recent (2009-2015) era and identify pre-FAV predictors of Biv outcome. METHODS: We evaluated procedural and postnatal outcomes in 123 fetuses that underwent FAV for evolving HLHS at Boston Children's Hospital between 2000 and 2015. The primary outcome measure was circulation type (Biv vs single ventricle) at the time of neonatal hospital discharge. Classification and regression tree (CART) analysis was performed to construct a stratification algorithm to predict Biv circulation based on pre-FAV fetal variables. RESULTS: The FAV procedure was technically successful in 101/123 (82%) fetuses, with a higher technical success rate in the more recent era than in the earlier one (49/52 (94%) vs 52/71 (73%); P = 0.003). In liveborn patients, the incidence of Biv outcome was higher in the recent than in the earlier era, both in the entire liveborn cohort (29/49 (59%) vs 16/62 (26%); P = 0.001) and in those in whom the procedure was technically successful (27/46 (59%) vs 15/47 (32%); P = 0.007). Independent predictors of Biv outcome were higher left ventricular (LV) pressure, larger ascending aorta, better LV diastolic function and higher LV long-axis Z-score. On CART analysis, fetuses with LV pressure > 47 mmHg and ascending aorta Z-score ≥ 0.57 had a 92% probability of Biv outcome (n = 24). Those with a lower LV pressure, or mitral dimension Z-score < 0.1 and mitral valve inflow time Z-score < -2 (n = 34) were unlikely to have Biv (probability of 9%). The remainder of the patients had an intermediate (∼40-60%) likelihood of Biv circulation. CONCLUSIONS: The proportion of patients achieving Biv outcome after FAV has increased, probably owing to an improved technical success rate and modified selection criteria. Fetal factors, including LV pressure, size of the ascending aorta and diastolic function, are associated with likelihood of Biv circulation after FAV. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Hemodynamic adaptation to suboptimal fetal growth in patients with single ventricle physiology.

BACKGROUND: In fetuses with structurally normal heart and suboptimal fetal growth (SFG), umbilical artery vascular resistance increases as measured by umbilical artery pulsatility index (UA-PI). The objective of this study is to compare hemodynamic responses to SFG in fetuses with single ventricle (SV) and controls with structurally normal heart. METHODS: Fetal echocardiograms around 30 weeks of gestation were reviewed. UA-PI and middle cerebral artery pulsatility index (MCA-PI) were calculated. SFG was defined as a birth weight below 25th percentile for gestational age. RESULTS: Studies from 92 fetuses were reviewed-SV (n = 50) and controls (n = 42). The prevalence of SFG was higher in SV compared to controls (46% vs 21%, P = .02). In patients with normal heart and SFG, UAPI was significantly higher than normal controls (P = .003) suggesting increased placental vascular resistance. In SV with SFG there was no difference in UAPI compared to SV without SFG. There was no difference in MCA-PI between the groups. CONCLUSIONS: The hemodynamic response to SFG in SV varies from fetuses with structurally normal heart. The mechanism of SFG and the placental pathology may be distinct in SV.