This appendix has been provided by the authors to give readers additional information about their work.
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Computational Simulation Studies. Numerical simulation was performed using a commercial computational fluid dynamics simulation code, ANSYS FLUENT
®
release 13.0. It uses a cellcentered finite-volume method to solve hemodynamics of arterial blood flow. Blood flow was postulated as a Newtonian, viscous, and incompressible. Viscosity and density of blood was assumed as 0.0035 kg/ms and 1060 kg/m 3 , respectively. Also, RNG kused to acquire better simulation results for local turbulent flow which can occur at very narrow and high velocity region. For all the simulation models, for more useful and effective comparison of simulation results, both of 2D axisymmetric and 3D simulation models were used.
On the other hand, a built-in porous media model in ANSYS FLUENT
®
release 13.0 was used to simulate microvascular bed resistance change of myocardium due to change of coronary severity under hyperemic flow condition. It has been controversial that microvascular bed resistance is variable or constant under hyperemia. However, recently there has been a study 1 showing that microvascular bed resistance is variable with respect to different distal pressure of a coronary artery due to different severity of the artery and the relationship between distal pressure and coronary flow has both of linear and non-linear relationship under physiological pressure range (higher than 40 mmHg) of distal pressure and the lower range, respectively. In this work, clinical pressure-flow relationship was incorporated into the built-in porous media model to simulate physiological autonomous change of microvascular bed resistance according to different severity of the various coronary arterial simulation models.
2,3
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Appendix Table 1.
Angiographic and IVUS data in 1066 non-LM lesions.
Angiographic findings
Proximal reference lumen diameter, mm
Distal reference lumen diameter, mm
Averaged reference lumen diameter, mm
Interpolated reference lumen diameter, mm
Minimal lumen diameter, mm
Diameter stenosis, %
Lesion length (mm)
3.4±0.5
2.8±0.5
3.1±0.5
3.2±0.5
1.5±0.4
51.4±12.2
19.4±12.2
IVUS findings
Proximal reference mean lumen area, mm 2
Proximal reference mean EEM area, mm 2
Distal reference mean lumen area, mm 2
Distal reference mean EEM area, mm 2
Minimal lumen area, mm 2
EEM area at the minimal lumen area site, mm 2
Plaque burden at the minimal lumen area site, %
Plaque rupture
EEM= external elastic membrane
9.10±3.3
15.6±4.9
7.3±2.9
11.4±4.9
2.7±1.2
11.2±4.4
73.6±12.1
123 (11.5%)
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Appendix Table 2.
Angiographic and IVUS data in 63 LM lesions.
Angiographic findings
Proximal reference lumen diameter, mm
Distal reference lumen diameter, mm
Averaged reference lumen diameter, mm
Interpolated reference lumen diameter, mm
Minimal lumen diameter, mm
Diameter stenosis, %
Lesion length (mm)
3.8±0.6
3.4±0.5
3.6±0.5
3.7±0.5
1.9±0.5
47.0±11.1
11.1±8.3
IVUS findings
Minimal lumen area, mm 2
EEM at the minimal lumen area site, mm 2
Plaque burden at the minimal lumen area site, %
Plaque rupture
5.0±2.1
18.0±5.4
70.3±14.4
22 (34.9%)
EEM= external elastic membrane
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Appendix Table 3.
Correlations of angiographic and IVUS variables with FFR
LM lesions non-LM lesions r p
Angiographic diameter stenosis -0.395
p<0.001
r
-0.428
p p<0.001
Angiographic minimal lumen diameter
Lesion length
Minimal lumen area
Plaque burden
0.414
-0.235
0.467
-0.350
p<0.001
p<0.001 p<0.001
p<0.001
0.436
0.560
-0.216
-0.473
p<0.001
0.089 p<0.001
p<0.001
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Appendix Table 4.
Univariable analysis of factors predicting “mismatch” and “reverse mismatch” between angiographic DS and FFR.
Beta SE p-value
Crude odds 95% confidence ratio intervals
Predictors for “Mismatch”
*
Age
0.034 0.009
Female
0.490 0.201
LAD location
-0.988 0.191
Plaque rupture
-0.687 0.264
Averaged RLD
0.489 0.179
Lesion length
-0.037 0.007
IVUS-MLA
1.045 0.132
Plaque burden
-0.079 0.014
Proximal location
0.173 0.178
QCA-MLD (10mm)
0.170 0.028
Predictors for “Reverse - mismatch”
*
<0.001
0.015
<0.001
0.009
0.007
<0.001
<0.001
<0.001
0.334
<0.001
1.034
1.633
0.372
0.503
1.632
0.963
2.844
0.924
1.188
1.185
1.016 – 1.053
1.102 – 2.419
0.256 – 0.542
0.300 – 0.844
1.147 – 2.320
0.950 – 0.977
2.196 – 3.684
0.898 – 0.950
0.837 – 1.687
1.122 – 1.253
Age
Female
-0.034 0.014 0.017 0.967 0.940 – 0.994
LAD location
Plaque rupture
-0.408 0.328
1.664 0.441
0.231
0.000
0.665
5.278
0.350 – 1.264
2.223 – 12.535
0.947 0.394 0.016 2.578 1.191 – 5.579
Averaged RLD
-0.635 0.342 0.063 0.530 0.271 – 1.036
Lesion length
IVUS-MLA
0.015 0.010 0.151 1.015 0.995 – 1.035
-1.033 0.182 <0.001 0.356 0.249 – 0.509
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Plaque burden
0.054
Proximal location
-0.036
QCA-MLD (10mm)
-0.163
MLA= minimal lumen area
RLD= reference lumen diameter
0.017
0.286
0.053
0.002
0.901
0.002
MLD= minimal lumen diameter
* assessed by GEE in 856 patients with 974 non-LM lesions
1.055
0.965
0.850
1.021 – 1.090
0.550 – 1.692
0.767 – 0.942
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Appendix figure 1.
Cut-off value of angiographic DS for predicting FFR <0.80. A: non-LMCA lesions B: LMCA lesions
Appendix figure 2.
Angiographic and IVUS criteria and their accuracies for predicting FFR
<0.80. A: cut-off value of angiographic lesion length (LL) in non-LMCA lesions. B: cut-off value of MLA in non-LMCA lesions. C: cut-off value of plaque burden (PB) in non-LMCA lesions. D: cut-off value of LL in -LMCA lesions. E: cut-off value of MLA in LMCA lesions. F: cut-off value of PB in LMCA lesions
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Appendix figure 3.
A: For the simple sine wave shape of stenosis, when diameter stenosis (DS) increases from 30 to 50 and 70 %, the FFR increases from 0.91 to 0.8 and 0.58, respectively. B:
In a given DS of 50%, change of the lesion length also affects on the different FFR value.
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Appendix figure 4.
Pressure gradient (A) and velocity vector (B) were simulated for the three models with different shapes of stenosis. In a given stenosis degree (DS 50 %), the stenotic lesions with linear, sine wave and abrupt shapes showed different FFR values (0.76 vs. 0.71 vs.
0.61).
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Appendix figure 5.
Effects of surface roughness and luminal shape originated from plaque eccentricity on FFR. A. Using an axisymmetric numerical model with linear shape, diameter stenosis (DS) 50%, and lesion length 20 mm, 4 simulation models with different surface roughness of plaque (smooth surface: no surface microstructures, 0.05 mm, 0.1 mm, and 0.2 mm of average surface roughness [R a
]) were constructed. With a higher roughness (R a
0.2mm), remarkable reduction in FFR was shown (0.54). B: Despite the same lumen area of 1.83 mm 2 in the two 3-D vessel models, FFR was lower in the lesion with eccentric shape of cross-sectional lumen area.
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