Validation of biomechanical assessment of coronary plaque vulnerability based on intravascular optical coherence tomography and digital subtraction angiography

Figures

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  Figure 1. The flowchart of the biomechanical assessment of coronary plaque vulnerability based on multimodal image data. IV-OCT, intravascular optical coherence tomography; DSA, digital subtraction angiography; 2D, two-dimensional; FEA, finite-element analysis; 3D, three-dimensional; FSI, fluid-structure interaction.

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  Figure 2. The reconstruction of the 2D geometry and morphometric analysis. (A) The IV-OCT image. (B) The contour extraction. (C) The plaque geometry reconstruction from the contours. (D) The calculation of the geometric features. 2D, two-dimensional; IV-OCT, intravascular optical coherence tomography.

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  Figure 3. 3D patient-specific coronary model reconstruction. (A) The sequence of the segmented IV-OCT contours. (B) The reconstruction of the 3D centerline based on biplane angiographic imaging. (C) The registration process of IV-OCT and the 3D angiographic centerline. (D) The 3D geometry of the patient-specific coronary, including the structure of vessel wall, lumen, and lipid plaque, and calcification plaque. IV-OCT, intravascular optical coherence tomography; 3D, three-dimensional.

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  Figure 4. Comparison of the mechanical parameters between the vulnerable and stable groups. (A) The model reconstruction for the vulnerable and stable plaques. (B,C) The distribution of stress and displacement in the representative slice model, respectively. The red arrows indicate positions with the peak values. (D,E) The box-plots of the average and maximal stress and displacement for the vulnerable and stable plaque groups.

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  Figure 5. Significant correlations between the morphologic features and FEA-derived parameters with R value >0.7. (A-D) Correlations between average stress and lumen area, wall area, NWI, and MWT, respectively. (E,F) Correlations between maximal stress and FCTmin and FCTave, respectively. (G) Correlations between average displacement and FCTave. (H,I) Correlations between maximal displacement and FCTave and FCTmin, respectively. NWI, normalized wall index; MWT, maximal wall thickness; FCTmin, minimum fibrous cap thickness; FCTave, average fibrous cap thickness; FEA, finite-element analysis.

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  Figure 6. Feature selection. (A) The plot of the mean-squared error versus log(λ). Dotted lines were drawn at the optimal values using the λ-min and the λ-1se. (B) The LASSO coefficient path. FCTmin, minimum fibrous cap thickness; λ-min, minimum criteria; λ-1se, one-standard error criteria; LASSO, least absolute shrinkage and selection operator.

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  Figure 7. The distributions of WSS. (A) The WSS patterns of the vessel lumen. (B-F) The representative IV-OCT image cross-sections of five plaques with WSS distributions. The labels highlighted in red indicate the vulnerable plaques, including plaque-1 and plaque-4. WSS, wall shear stress; IV-OCT, intravascular optical coherence tomography.

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  Figure 8. The changing trend of the mechanical parameters along the pullback distance. (A) The representative IV-OCT image cross-sections of five plaques. The images highlighted in red indicate the vulnerable plaques. (B-E) The FEA-derived parameter plots along the pullback distance. The vulnerable plaques are highlighted by red asterisks. IV-OCT, intravascular optical coherence tomography; FEA, finite-element analysis.