In vivo assessment of optimal viewing angles from X-ray coronary angiography
| Autor: | Xudong Song, Aihua Chen, Xiang-long Wei, Pei-yuan Hao, Gerhard Koning, Johan H. C. Reiber, Shengxian Tu |
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| Rok vydání: | 2011 |
| Předmět: |
Coronary angiography
business.industry X-Rays Target vessel Viewing angle Coronary Angiography Software Imaging Three-Dimensional Stent deployment percutaneous coronary intervention quantitative coronary angiography three-dimensional reconstruction eluting stent implantation quantitative-analysis artery-disease medium-term reconstruction restenosis stenosis safety Medicine Humans Computer vision Artificial intelligence Cardiology and Cardiovascular Medicine business Algorithms |
| Zdroj: | Eurointervention, 7(1), 112-120 |
| ISSN: | 1969-6213 |
| Popis: | Aims: To propose and validate a novel approach to determine the optimal angiographic viewing angles for a selected coronary (target) segment from X-ray coronary angiography, without the need to reconstruct the entire coronary tree in three-dimensions (3D), such that subsequent interventions are carried out from the best view. Methods and results: The approach starts with standard quantitative coronary angiography (QCA) of the target vessel in two angiographic views. Next, the target vessel is reconstructed in 3D, and in a very simple and intuitive manlier, the possible overlap of the target vessel and other vessel segments can be assessed, resulting in the best view with minimum foreshortening and overlap. A retrospective study including 67 patients was set up for the validation. The overlap prediction result was compared with the true overlap on the available angiographic views (TEST views). The foreshortening for the views proposed by the new approach software viewing angle (SVA) and the views used during the stent deployment software viewing angle (EVA) were compared. Two experienced interventional cardiologists visually evaluated the success of SVA with respect to EVA. The evaluation results were graded into five values ranging from -2 to 2. The overlap prediction algorithm successfully predicted the overlap condition for all 235 TEST views. EVA was associated with more foreshortening than SVA (8.9%+/- 8.2% vs. 1.6%+/- 1.5%, p |
| Databáze: | OpenAIRE |
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