Alsharqi Maryam, Edelman Elazer R
Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
J Soc Cardiovasc Angiogr Interv. 2025 Mar 18;4(3Part B):102558. doi: 10.1016/j.jscai.2024.102558. eCollection 2025 Mar.
Artificial intelligence (AI) has revolutionized the field of cardiovascular imaging, serving as a unifying force that brings together multiple modalities under a single platform. The utility of noninvasive imaging ranges from diagnostic assessment and guiding interventions to prognostic stratification. Multimodality imaging has demonstrated important potential, particularly in patients with heterogeneous diseases, such as heart failure and atrial fibrillation. Facilitating complex interventional procedures requires accurate image acquisition and interpretation along with precise decision-making. The unique nature of interventional cardiology procedures benefiting from different imaging modalities presents an ideal target for the development of AI-assisted decision-making tools to improve workflow in the catheterization laboratory and personalize the need for transcatheter interventions. This review explores the advancements of AI in noninvasive cardiovascular imaging and interventional cardiology, addressing the clinical use and challenges of current imaging modalities, emerging trends, and promising applications as well as considerations for safe implementation of AI tools in clinical practice. Current practice has moved well beyond the question of whether we should or should not use AI in clinical health care settings. AI, in all its forms, has become deeply embedded in clinical workflows, particularly in cardiovascular imaging and interventional cardiology. It can, in the future, not only add precision and quantification but also serve as a means by which to fuse and link multimodalities together. It is only by understanding how AI techniques work, that the field can be harnessed for the greater good and avoid uninformed bias or misleading diagnoses.
人工智能(AI)已经彻底改变了心血管成像领域,成为一种统一的力量,将多种模式整合在一个平台下。无创成像的用途涵盖诊断评估、指导干预措施以及预后分层。多模态成像已展现出重要潜力,尤其是在患有诸如心力衰竭和心房颤动等异质性疾病的患者中。实施复杂的介入手术需要准确的图像采集与解读以及精确的决策。受益于不同成像模式的介入心脏病学手术的独特性质,为开发人工智能辅助决策工具提供了理想目标,以改善导管实验室的工作流程并使经导管干预的需求个性化。本综述探讨了人工智能在无创心血管成像和介入心脏病学方面的进展,阐述了当前成像模式的临床应用和挑战、新趋势、有前景的应用以及在临床实践中安全实施人工智能工具的注意事项。目前的实践早已超越了我们是否应该在临床医疗环境中使用人工智能这一问题。各种形式的人工智能已深深融入临床工作流程,尤其是在心血管成像和介入心脏病学领域。未来,它不仅可以提高精准度和实现量化,还能作为一种将多模态融合与连接的手段。只有了解人工智能技术的工作原理,该领域才能更好地为人类造福,避免盲目偏见或误导性诊断。