scholarly journals Computational Analysis of Haemodynamic Indices in Synthetic Atherosclerotic Coronary Netwroks

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2221
Author(s):  
Sergey Simakov ◽  
Timur Gamilov ◽  
Fuyou Liang ◽  
Philipp Kopylov
Keyword(s):  
Computed Tomography ◽  
Coronary Stenosis ◽  
Coronary Flow ◽  
Computational Analysis ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Novel Approach ◽  
Tomography Data ◽  
Elevated Heart Rate

Haemodynamic indices are widely used in clinical practice when deciding on a particular type of treatment. Low quality of the computed tomography data and tachycardia complicate interpretation of the measured or simulated values. In this work, we present a novel approach for evaluating resistances in terminal coronary arteries. Using 14 measurements from 10 patients, we show that this algorithm retains the accuracy of 1D haemodynamic simulations in less detailed (truncated) geometric models of coronary networks. We also apply the variable systole fraction model to study the effect of elevated heart rate on the values of fractional flow reserve (FFR), coronary flow reserve (CFR) and instantaneous wave-free ratio (iFR). We conclude that tachycardia may produce both overestimation or underestimation of coronary stenosis significance.

scholarly journals Computational Analysis of Haemodynamic Indices in Synthetic Atherosclerotic Coronary Netwroks

2021 ◽  
Author(s):  
Sergey Simakov ◽  
Timur Gamilov ◽  
Philipp Kopylov ◽  
Fuyou Liang
Keyword(s):  
Heart Rate ◽  
Clinical Practice ◽  
Coronary Arteries ◽  
Coronary Stenosis ◽  
Computational Analysis ◽  
Geometric Models ◽  
Novel Approach ◽  
Ct Data ◽  
Elevated Heart Rate

Haemodynamic indices are widely used in clinical practice for deciding on a particular type of treatment. Low quality of the CT data and tachycardia complicate interpretation of the measured or simulated values. In this work, we present a novel approach for evaluating resistances in terminal coronary arteries. Using 14 measurements from 10 patients, we show that this algorithm retains the accuracy of 1D haemodynamic simulations in less detailed (truncated) geometric models of coronary networks. We also apply the variable systole fraction model to study the effect of elevated heart rate on the values of FFR, CFR and iFR. We conclude that tachycardia may produce both overestimation or underestimation of coronary stenosis significance.

Abstract 14743: Usefulness of Estimated Coronary Flow Velocity Using Quantitative Flow Ratio for Intermediate Coronary Stenosis

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Eiji Ichimoto ◽  
Nao Konagai ◽  
Sawako Horie ◽  
Atsushi Hasegawa ◽  
Hirofumi Miyahara ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Coronary Stenosis ◽  
Coronary Flow ◽  
Flow Ratio ◽  
Operating Characteristics ◽  
Fractional Flow ◽  
Coronary Flow Velocity ◽  
Flow Reserve ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

Introduction: Quantitative flow ratio (QFR) is a diagnostic modality for functional assessment for intermediate coronary stenosis without the use of pressure wire. QFR is calculated from 3-dimensional quantitative CAG (3D-QCA) using an advanced algorithm that enables fast computation of the pressure drop caused by coronary stenosis. Hypothesis: We assessed the usefulness of QFR and the association with an estimated coronary flow velocity (eCFV) for intermediate coronary stenosis. Methods: A total of 100 lesions in 80 consecutive patients were assessed Fractional Flow Reserve (FFR) for intermediate coronary stenosis between January 2011 and April 2019. Of these, 97 lesions in 77 patients who underwent QFR were included in this study. Patients were classified into two groups (FFR ≤ 0.80 or FFR > 0.80). QFR and eCFV using contrast were measured by Thrombolysis in Myocardial Infarction (TIMI) frame counts. Results: There was no significant differences in target vessels (p = 0.90) and diffuse lesions (p = 0.06) between the two groups (FFR ≤ 0.80 or FFR > 0.80). Mean FFR and QFR values were 0.78 ± 0.12 and 0.77 ± 0.11, respectively. QFR had a good correlation with FFR values (r = 0.86, p < 0.0001). The diagnostic accuracy, sensitivity, and specificity on QFR ≤ 0.80 were 91.8%, 92.7% and 90.5%, respectively. The eCFV of FFR ≤ 0.80 was greater than that of FFR > 0.80 (0.19 ± 0.08 m/s vs. 0.14 ± 0.06 m/s, p<0.001). Figure showed that the eCFV correlated with FFR values (r = -0.29, p < 0.01). Moreover, the eCFV had a high area under the curve (AUC = 0.71, p < 0.01) on Receiver operating characteristics curve (ROC) analysis with FFR ≤ 0.80. Conclusions: QFR was useful for the assessment of functional stenosis severity. As eCFV was faster, FFR was lower for intermediate coronary stenosis. The eCFV had a good correlation with FFR and may become one of the evaluations for ischemia.

scholarly journals A validated predictive model of coronary fractional flow reserve

2011 ◽  
Vol 9 (71) ◽  
pp. 1325-1338 ◽  
Author(s):  
Yunlong Huo ◽  
Mark Svendsen ◽  
Jenny Susana Choy ◽  
Z.-D. Zhang ◽  
Ghassan S. Kassab
Keyword(s):  
Analytical Model ◽  
Fractional Flow Reserve ◽  
Coronary Stenosis ◽  
Coronary Flow ◽  
Energy Losses ◽  
Fractional Flow ◽  
Conservation Of Energy ◽  
Flow Reserve

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 (Δ p or FFR) experiment = a (Δ p or FFR) theory + b , where a and b were 1.08 and −1.15 mmHg ( r 2 = 0.99) for in vitro Δ p , 0.96 and 1.79 mmHg ( r 2 = 0.75) for in vivo Δ p , 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.

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