The Differentiation in Image Post-processing and 3D Reconstruction During Evaluation of Carotid Plaques From MR and CT Data Sources - Deng, Fengbin; Mu, Changping; Yang, Ling; Yi, Rongqi; Gu, Min; Li, Kang (Frontiers in Physiology, 2021)
Background: Carotid plaque morphology and tissue composition help assess risk stratification of stroke events. Many image post-processing techniques based on CT and MR images have been widely used in related research, such as image segmentation, 3D reconstruction, and computer fluid dynamics. However, the criteria for the 3D numerical model of carotid plaque established by CT and MR angiographic image data remain open to question. Method: We accurately duplicated the geometry and provided it to the computer software to simulate a 3D numerical model. The initial images were obtained by CTA and TOF-MRA. MIMICS (Materialise's interactive medical image control system) software was used to process the images to generate three-dimensional solid models of blood vessels and plaques. The subsequent output was exported to the ANSYS software to generate finite element simulation results for the further hemodynamic study. Results: 3D models of carotid plaque of TOF-MRA and CTA were simulated by using computer software. CTA has a high-density resolution for carotid plaque, the boundary of the CTA image is obvious, and the main component of which is a calcified tissue. However, the density resolution of TOF-MRA for carotid plaque and carotid artery was not as good as that of CTA. The results show that there is a large deviation between the TOF-MRA and CTA 3D model of plaque in the carotid artery due to the unclear recognition of plaque boundary during 3D reconstruction and further affect the simulation results of hemodynamics. Conclusion: In this study, two-dimensional images and three-dimensional models of carotid plaque obtained by two angiographic techniques were compared. The potential of these two imaging methods in clinical diagnosis and fluid dynamics of carotid plaque was evaluated and the selectivity of image post-processing analysis to original medical image acquisition was revealed.