Fetal Cardiac Screening

Sklansky, Mark; DeVore, Greggory R.

doi:10.7863/ultra.15.07021

Cited by 20 publications

(2 citation statements)

References 21 publications

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“…Although many cases critical CHD diagnoses occur either prenatally or subsequently through newborn screening, one in five cases of critical CHD are not diagnosed until after the fourth week of life [ 10 ]. Despite advances in fetal echocardiography, up to 60% of CHD diagnoses are diagnosed postnatally [ 12 , 13 ]. Late diagnosis of critical CHD is associated with increased risk of morbidity and mortality, increased hospital length of stay, and 35% higher inpatient costs during infancy [ 8 , 9 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Discordant congenital heart defects in monochorionic twins: Risk factors and proposed pathophysiology

et al. 2021

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A six-fold increase in congenital heart defects (CHD) exists among monochorionic (MC) twins compared to singleton or dichorionic twin pregnancies. Though MC twins share an identical genotype, discordant phenotypes related to CHD and other malformations have been described, with reported rates of concordance for various congenital anomalies at less than 20%. Our objective was to characterize the frequency and spectrum of CHD in a contemporary cohort of MC twins, coupled with genetic and clinical variables to provide insight into risk factors and pathophysiology of discordant CHD in MC twins. Retrospective analysis of all twins receiving prenatal fetal echocardiography at a single institution from January 2010 –March 2020 (N = 163) yielded 23 MC twin pairs (46 neonates) with CHD (n = 5 concordant CHD, n = 18 discordant CHD). The most common lesions were septal defects (60% and 45.5% in concordant and discordant cohorts, respectively) and right heart lesions (40% and 18.2% in concordant and discordant cohorts, respectively). Diagnostic genetic testing was abnormal for 20% of the concordant and 5.6% of the discordant pairs, with no difference in rate of abnormal genetic results between the groups (p = 0.395). No significant association was found between clinical risk factors and development of discordant CHD (p>0.05). This data demonstrates the possibility of environmental and epigenetic influences versus genotypic factors in the development of discordant CHD in monochorionic twins.

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Section: Introductionmentioning

confidence: 99%

Discordant congenital heart defects in monochorionic twins: Risk factors and proposed pathophysiology

et al. 2021

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“…Two reasons for this gap between possible and commonplace CHD detection are (i) inadequate expertise in interpretation and/or (ii) inadequate acquisition of diagnostic-quality images 16,17 . Causes of inadequate imaging include poor acoustic windows, fetal motion, and the small size of the fetal heart.…”

Section: Introductionmentioning

confidence: 99%

Expert-level prenatal detection of complex congenital heart disease from screening ultrasound using deep learning

Arnaout

Curran

Zhao

et al. 2020

Preprint

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Congenital heart disease (CHD) is the most common birth defect. Fetal survey ultrasound is recommended worldwide, including five views of the heart that together could detect 90% of complex CHD. In practice, however, sensitivity is as low as 30%. We hypothesized poor detection results from challenges in acquiring and interpreting diagnostic-quality cardiac views, and that deep learning could improve complex CHD detection. Using 107,823 images from 1,326 retrospective echocardiograms and surveys from 18-24 week fetuses, we trained an ensemble of neural networks to (i) identify recommended cardiac views and (ii) distinguish between normal hearts and complex CHD. Finally, (iii) we used segmentation models to calculate standard fetal cardiothoracic measurements. In a test set of 4,108 fetal surveys (0.9% CHD, >4.4 million images, about 400 times the size of the training dataset) the model achieved an AUC of 0.99, 95% sensitivity (95%CI, 84-99), 96% specificity (95%CI, 95-97), and 100% NPV in distinguishing normal from abnormal hearts. Sensitivity was comparable to clinicians' task-for-task and remained robust on external and lower-quality images. The model's decisions were based on clinically relevant features. Cardiac measurements correlated with reported measures for normal and abnormal hearts. Applied to guidelines-recommended imaging, ensemble learning models could significantly improve detection of fetal CHD and expand telehealth options for prenatal care at a time when the COVID-19 pandemic has further limited patient access to trained providers. This is the first use of deep learning to approximately double standard clinical performance on a critical and global diagnostic challenge.

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It's All About the Foot Pedal: One Small Step for the Obstetric Sonographer, One Big Step for the Prenatal Detection of Congenital Heart Disease

Sklansky

Satou

DeVore

2018

J of Ultrasound Medicine

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Fetal Cardiac Screening

Cited by 20 publications

References 21 publications

Discordant congenital heart defects in monochorionic twins: Risk factors and proposed pathophysiology

Discordant congenital heart defects in monochorionic twins: Risk factors and proposed pathophysiology

Expert-level prenatal detection of complex congenital heart disease from screening ultrasound using deep learning

It's All About the Foot Pedal: One Small Step for the Obstetric Sonographer, One Big Step for the Prenatal Detection of Congenital Heart Disease

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