Presentation
27 April 2016 Aortic endothelium detection using spectral estimation optical coherence tomography (Conference Presentation)
Author Affiliations +
Abstract
The evaluation of the endothelium coverage on the vessel wall is most wanted by cardiologists. Arterial endothelial cells play a crucial role in keeping low-density lipoprotein and leukocytes from entering into the intima. The damage of endothelial cells is considered as the first step of atherosclerosis development and the presence of endothelial cells is an indicator of arterial healing after stent implantation. Intravascular OCT (IVOCT) is the highest-resolution coronary imaging modality, but it is still limited by an axial resolution of 10-15 µm. This limitation in axial resolution hinders our ability to visualize cellular level details associated with coronary atherosclerosis. Spectral estimation optical coherence tomography (SE-OCT) uses modern spectral estimation techniques and may help reveal the microstructures underlying the resolution limit. In this presentation, we conduct an ex vivo study using SE-OCT to image the endothelium cells on the fresh swine aorta. We find that in OCT images with an axial resolution of 10 µm, we may gain the visibility of individual endothelium cells by applying the autoregressive spectral estimation techniques to enhance the axial resolution. We believe the SE-OCT can provide a potential to evaluate the coverage of endothelium cells using current IVOCT with a 10-µm axial resolution.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xinyu Liu Sr., Si Chen M.D., Yuemei Luo, En Bo, Nanshuo Wang, Xiaojun Yu, and Linbo Liu "Aortic endothelium detection using spectral estimation optical coherence tomography (Conference Presentation)", Proc. SPIE 9689, Photonic Therapeutics and Diagnostics XII, 96893G (27 April 2016); https://doi.org/10.1117/12.2211297
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KEYWORDS
Optical coherence tomography

Image resolution

Spectral resolution

Image enhancement

Resolution enhancement technologies

Visibility

Visualization

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