Key result
Advanced echocardiography and AI enhance detection and structural assessment in complex congenital heart defects.
Why the study?
Congenital heart defects remain a leading cause of infant mortality with limitations in traditional echocardiographic modalities for visualizing complex anomalies.
The integration of advanced echocardiographic modalities and AI algorithms significantly enhances diagnostic accuracy and workflow efficiency for congenital heart diseases across prenatal and pediatric populations.
Answers are grounded in this paper and cite their sources.
May enhance detection of complex congenital heart defects; leaves open the need for prospective validation before routine adoption.
Congenital heart defects (CHDs) are the most prevalent congenital condition globally, affecting approximately 1% of live births and contributing to significant morbidity and mortality. While advancements in diagnostic imaging have improved early detection and management, CHDs remain a leading cause of infant mortality, particularly in low- and middle-income regions. Echocardiography has evolved as a cornerstone in CHD diagnosis, with traditional modalities such as 2D echocardiography, M-mode, and Doppler imaging providing essential structural and hemodynamic assessments. However, these conventional approaches have limitations in visualizing complex congenital anomalies. The emergence of advanced echocardiographic techniques, including three-dimensional echocardiography, fetal echocardiography, speckle tracking echocardiography (STE), and stress echocardiography (SE), has significantly enhanced diagnostic accuracy, preoperative planning, and long-term monitoring. Furthermore, recent innovations in artificial intelligence (AI), deep learning, digital signal processing, and contrast-enhanced echocardiography are revolutionizing the field by automating image analysis, improving image quality, and enabling predictive modeling for CHD prognosis. This review critically compares traditional and advanced echocardiographic modalities, evaluating their respective strengths, limitations, and impact on early CHD detection. Additionally, it explores emerging AI-driven technologies and their potential to optimize echocardiographic workflows, reduce diagnostic variability, and enhance patient outcomes. By synthesizing current evidence, this review aims to provide clinicians, researchers, and healthcare policymakers with insights into the evolving role of echocardiography in CHD diagnosis and management.
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Humayun et al. (2026) conducted a review in Congenital heart defects. Advanced echocardiographic techniques and artificial intelligence vs. Traditional echocardiography was evaluated. Advanced echocardiographic modalities and artificial intelligence significantly improve the early detection, structural assessment, and management of complex congenital heart defects compared to traditional imaging methods.
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