Heseltine Thomas D, Murray Scott W, Ruzsics Balazs, Fisher Michael
Royal Liverpool University Hospital, Liverpool, UK.
Liverpool Centre for Cardiovascular Science, Liverpool, UK.
Eur Cardiol. 2020 Feb 26;15:1-7. doi: 10.15420/ecr.2019.14.2. eCollection 2020 Feb.
Recent rapid technological advancements in cardiac CT have improved image quality and reduced radiation exposure to patients. Furthermore, key insights from large cohort trials have helped delineate cardiovascular disease risk as a function of overall coronary plaque burden and the morphological appearance of individual plaques. The advent of CT-derived fractional flow reserve promises to establish an anatomical and functional test within one modality. Recent data examining the short-term impact of CT-derived fractional flow reserve on downstream care and clinical outcomes have been published. In addition, machine learning is a concept that is being increasingly applied to diagnostic medicine. Over the coming decade, machine learning will begin to be integrated into cardiac CT, and will potentially make a tangible difference to how this modality evolves. The authors have performed an extensive literature review and comprehensive analysis of the recent advances in cardiac CT. They review how recent advances currently impact on clinical care and potential future directions for this imaging modality.
近年来，心脏CT技术的快速发展提高了图像质量，并减少了患者的辐射暴露。此外，大型队列试验的关键见解有助于将心血管疾病风险描述为总体冠状动脉斑块负荷和单个斑块形态外观的函数。CT衍生的血流储备分数的出现有望在一种检查方式中建立解剖学和功能测试。最近发表了关于CT衍生的血流储备分数对下游治疗和临床结果的短期影响的数据。此外，机器学习是一个越来越多地应用于诊断医学的概念。在未来十年中，机器学习将开始融入心脏CT，并可能对这种检查方式的发展产生切实影响。作者对心脏CT的最新进展进行了广泛的文献综述和全面分析。他们回顾了最近的进展如何影响当前的临床护理以及这种成像方式未来可能的发展方向。
