Computational imaging of aortic vasa vasorum and neovascularization in rabbits using contrast-enhanced intravascular ultrasound: Association with histological analysis
1First Department of Cardiology, Hippokration Hospital, Biomedical Engineering Unit, Medical School, National and Kapodistrian University; Athens-Greece
2Centre of Clinical, Experimental Surgery and Translational Research, Experimental Surgery Unit, Biomedical Research Foundation of the Academy of Athens; Athens-Greece
3Department of Cardiology, “Laiko” General Hospital; Athens-Greece
4Department of Pathology, Medical School, National and Kapodistrian University; Athens-Greece
5Computational Biomedicine Lab, Department of Computer Science, University of Houston; TX-USA
Anatol J Cardiol 2018; 2(20): 117-124 PubMed ID: 30088486 DOI: 10.14744/AnatolJCardiol.2018.35761
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Abstract

Objective: Neoangiogenesis is pathophysiologically related to atherosclerotic plaque growth and vulnerability. We examined the in vivo performance of a computational method using contrast-enhanced intravascular ultrasound (CE-IVUS) to detect and quantify aortic wall neovascularization in rabbits. We also compared these findings with histological data.
Materials and Methods: Nine rabbits were fed with a hyperlipidemic diet. IVUS image sequences were continuously recorded before and after the injection of a contrast agent. Mean enhancement of intensity of a region of interest (MEIR) was calculated using differential imaging algorithm. The percent difference of MEIR before and after the injection of microbubbles (d_MEIR) was used as an index of the density of plaque or/and adventitial neovascularization. Aortic segments were excised for histological analysis.
Results: CE-IVUS and histological analysis were performed in 11 arterial segments. MEIR was significantly increased (~20%) after microbubble injection (from 8.1±0.9 to 9.7±1.8, p=0.016). Segments with increased VV/neovessels in the tunica adventitia (histological scores 2 and 3) had significantly higher d_MEIR compared with segments with low presence of VV/neovessels (score 1); 40.5±22.9 vs. 8±14.6, p=0.024, respectively.
Conclusion: It is possible to detect VV or neovessels in vivo using computational analysis of CE-IVUS images, which is in agreement with histological data. These findings may have critical implications on vulnerable plaque assessment and risk stratification.