Sahashi Yuki, Ouyang David, Okura Hiroyuki, Kagiyama Nobuyuki
Department of Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Department of Cardiology, Gifu University Graduate School of Medicine, Gifu, Japan.
Department of Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA; Division of Artificial Intelligence in Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
J Cardiol. 2025 Jun;85(6):458-464. doi: 10.1016/j.jjcc.2025.02.005. Epub 2025 Mar 1.
Echocardiography, which provides detailed evaluations of cardiac structure and pathology, is central to cardiac imaging. Traditionally, the assessment of disease severity, treatment effectiveness, and prognosis prediction relied on detailed parameters obtained by trained sonographers and the expertise of specialists, which can limit access and availability. Recent advancements in deep learning and large-scale computing have enabled the automatic acquisition of parameters in a short time using vast amounts of historical training data. These technologies have been shown to predict the presence of diseases and future cardiovascular events with or without relying on quantitative parameters. Additionally, with the advent of large-scale language models, zero-shot prediction that does not require human labeling and automatic echocardiography report generation are also expected. The field of AI-enhanced echocardiography is poised for further development, with the potential for more widespread use in routine clinical practice. This review discusses the capabilities of deep learning models developed using echocardiography, their limitations, current applications, and research utilizing generative artificial intelligence technologies.
超声心动图可对心脏结构和病理状况进行详细评估，是心脏成像的核心手段。传统上，疾病严重程度评估、治疗效果评估以及预后预测依赖于训练有素的超声检查人员获取的详细参数以及专家的专业知识，这可能会限制其获取途径和可用性。深度学习和大规模计算方面的最新进展使得能够利用大量历史训练数据在短时间内自动获取参数。这些技术已被证明无论是否依赖定量参数，都能预测疾病的存在和未来心血管事件。此外，随着大规模语言模型的出现，预计还会实现无需人工标注的零样本预测以及自动生成超声心动图报告。人工智能增强型超声心动图领域有望进一步发展，有可能在常规临床实践中得到更广泛应用。本综述讨论了利用超声心动图开发的深度学习模型的能力、局限性、当前应用以及利用生成式人工智能技术开展的研究。
