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冠状动脉血流储备分数的验证预测模型。

A validated predictive model of coronary fractional flow reserve.

机构信息

Department of Biomedical Engineering, Surgery, and Cellular and Integrative Physiology, Indiana University Purdue University Indianapolis (IUPUI), Indianapolis, IN 46202, USA.

出版信息

J R Soc Interface. 2012 Jun 7;9(71):1325-38. doi: 10.1098/rsif.2011.0605. Epub 2011 Nov 23.

Abstract

Myocardial fractional flow reserve (FFR), an important index of coronary stenosis, is measured by a pressure sensor guidewire. The determination of FFR, only based on the dimensions (lumen diameters and length) of stenosis and hyperaemic coronary flow with no other ad hoc parameters, is currently not possible. We propose an analytical model derived from conservation of energy, which considers various energy losses along the length of a stenosis, i.e. convective and diffusive energy losses as well as energy loss due to sudden constriction and expansion in lumen area. In vitro (constrictions were created in isolated arteries using symmetric and asymmetric tubes as well as an inflatable occluder cuff) and in vivo (constrictions were induced in coronary arteries of eight swine by an occluder cuff) experiments were used to validate the proposed analytical model. The proposed model agreed well with the experimental measurements. A least-squares fit showed a linear relation as (Δp or FFR)(experiment) = a(Δp or FFR)(theory) + b, where a and b were 1.08 and -1.15 mmHg (r(2) = 0.99) for in vitro Δp, 0.96 and 1.79 mmHg (r(2) = 0.75) for in vivo Δp, and 0.85 and 0.1 (r(2) = 0.7) for FFR. Flow pulsatility and stenosis shape (e.g. eccentricity, exit angle divergence, etc.) had a negligible effect on myocardial FFR, while the entrance effect in a coronary stenosis was found to contribute significantly to the pressure drop. We present a physics-based experimentally validated analytical model of coronary stenosis, which allows prediction of FFR based on stenosis dimensions and hyperaemic coronary flow with no empirical parameters.

摘要

心肌血流储备分数(FFR)是评估冠状动脉狭窄的重要指标,它通过压力传感器导丝进行测量。目前,仅基于狭窄部位和充血状态下的冠状动脉血流的尺寸(管腔直径和长度)来确定 FFR 是不可能的,还需要其他特定的参数。我们提出了一个基于能量守恒的解析模型,该模型考虑了狭窄部位沿长度方向的各种能量损失,包括对流和扩散能量损失以及由于管腔面积突然收缩和扩张而导致的能量损失。通过体外(使用对称和非对称管以及可充气闭塞器袖套在离体动脉中创建狭窄部位)和体内(在 8 头猪的冠状动脉中通过闭塞器袖套诱导狭窄部位)实验对提出的解析模型进行了验证。结果表明,该模型与实验测量结果吻合良好。最小二乘法拟合显示出线性关系,即(Δp 或 FFR)(实验)= a(Δp 或 FFR)(理论)+ b,其中 a 和 b 分别为体外 Δp 时的 1.08 和-1.15mmHg(r(2) = 0.99),体内 Δp 时的 0.96 和 1.79mmHg(r(2) = 0.75),FFR 时的 0.85 和 0.1(r(2) = 0.7)。血流脉动和狭窄部位形状(例如偏心度、出口角度发散等)对心肌 FFR 的影响可以忽略不计,而冠状动脉狭窄部位的入口效应被发现对压降有显著贡献。我们提出了一种基于物理原理并经过实验验证的冠状动脉狭窄解析模型,该模型允许根据狭窄部位的尺寸和充血状态下的冠状动脉血流预测 FFR,无需使用经验参数。

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