论著摘要 |【AI-CT】冠状动脉CT血管成像分流血储备(双语版)

2018-01-10 11:57:21 admin 0
标签:   人工智能 冠状动脉 CT血管造影 深度学习 机器学习 CT

Coronary CT Angiography-derived Fractional Flow Reserve.

发表日期: 2017.10.01   来源:Radiology. 2017 Oct;285(1):17-33.

作者:

Tesche C1, De Cecco CN1, Albrecht MH1, Duguay TM1, Bayer RR 2nd1 , Litwin SE1, Steinberg DH1, Schoepf UJ1.

作者介绍:

1. From the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science (C.T., C.N.D.C., M.H.A., T.M.D., R.R.B., S.E.L., U.J.S.), and Division of Cardiology, Department of Medicine (R.R.B., S.E.L., D.H.S., U.J.S.), Medical University of South Carolina, Ashley River Tower, 25 Courtenay Dr, Charleston, SC 29425-2260.

摘要

冠状动脉疾病(CAD)功能评估的确定性参考标准通过压力线技术测量分流量储备(FFR)的侵入性冠状动脉造影(ICA)。与ICA相比,冠状动脉CT血管造影(CT)血管造影已经成为直接评估CAD和斑块特征的非侵入性方法,诊断准确率高。然而,与冠状动脉CT血管造影和ICA一起提供的唯一解剖学评估对于缺血诱导损伤具有较差的辨别能力。来自标准冠状动脉CT血管造影(FFRCT)数据集的FFR通过使用几种先进的计算分析方法中的任何一种,通过单一无创测试能够对冠状动脉病变的解剖和血液动力学进行组合评估。 当前计算FFRC的技术方法包括基于全阶和低阶计算流体动力学建模的算法,以及人工智能深度机器学习。越来越多的证据证实了FFRCT技术与侵入性FFR相比的诊断准确性。已经证实了改进的治疗指导,显示了FFRCT可以简化并合理化怀疑患有CAD的患者的护理并改善结果,同时降低总体医疗保健成本。 本评价的目的是描述各种FFRCT方法,其前体和相关成像测试的科学原理,临床验证和实施。

Abstact

Invasive coronary angiography (ICA) with measurement of fractional flow reserve (FFR) by means of a pressure wire technique is the established reference standard for the functional assessment of coronary artery disease (CAD). Coronary computed tomographic (CT) angiography has emerged as a noninvasive method for direct assessment of CAD and plaque characterization with high diagnostic accuracy compared with ICA. However, the solely anatomic assessment provided with both coronary CT angiography and ICA has poor discriminatory power for ischemia-inducing lesions. FFR derived from standard coronary CT angiography (FFRCT) data sets by using any of several advanced computational analytic approaches enables combined anatomic and hemodynamic assessment of a coronary lesion by a single noninvasive test. Current technical approaches to the calculation of FFRCTinclude algorithms based on full- and reduced-order computational fluid dynamic modeling, as well as artificial intelligence deep machine learning. A growing body of evidence has validated the diagnostic accuracy of FFRCT techniques compared with invasive FFR. Improved therapeutic guidance has been demonstrated, showing the potential of FFRCT to streamline and rationalize the care of patients suspected of having CAD and improve outcomes while reducing overall health care costs . The purpose of this review is to describe the scientific principles, clinical validation, and implementation of various FFRCT approaches, their precursors, and related imaging tests.

阅读原文:PMID: 28926310  DOI: 10.1148/radiol.2017162641


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