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利用最新的计算机科学工具推进核心脏病学。

Leveraging latest computer science tools to advance nuclear cardiology.

机构信息

Department of Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Ste. A047N, Los Angeles, CA, 90048, USA.

出版信息

J Nucl Cardiol. 2019 Oct;26(5):1501-1504. doi: 10.1007/s12350-019-01873-y. Epub 2019 Sep 5.

Abstract

Nuclear cardiology has unique advantages compared to other modalities, since the image analysis is already much more automated compared to what is currently clinically performed for CT, MR, or echocardiography imaging. The diverse image and clinical data available to assess coronary disease function, perfusion, flow, and associated CT data provide new opportunities, but logistically these additional assessments increase the overall complexity of SPECT/PET reporting, necessitating additional expertise and time. The advances in artificial intelligence software can be leveraged to obtain comprehensive risk predictions and diagnoses from all available data. They will allow nuclear cardiology to retain competitive edge compared to other modalities and improve its overall clinical utility. These tools will enhance diagnosis and risk prediction beyond what is possible by subjective visual analysis and mental integration of data by physicians.

摘要

核医学与其他影像学方法相比具有独特的优势,因为与目前 CT、MR 或超声心动图成像在临床上所进行的分析相比,其图像分析已经更加自动化。评估冠心病功能、灌注、流量和相关 CT 数据的多样化图像和临床数据提供了新的机会,但从逻辑上讲,这些额外的评估增加了 SPECT/PET 报告的整体复杂性,需要额外的专业知识和时间。人工智能软件的进步可以用来从所有可用数据中获得全面的风险预测和诊断。这些工具将使核医学与其他影像学方法相比保持竞争优势,并提高其整体临床实用性。这些工具将通过医生主观视觉分析和数据的心理综合来增强诊断和风险预测。

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