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An adaptive optimal viewing angle determination algorithm for TEVAR operation
BACKGROUND: The determination of the right x-ray angiography viewing angle is an important issue during the treatment of thoracic endovascular aortic repair (TEVAR). An inaccurate projection angle (manually determined today by the physicians according to their personal experience) may affect the pla...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487120/ https://www.ncbi.nlm.nih.gov/pubmed/34600478 http://dx.doi.org/10.1186/s12880-021-00676-3 |
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author | Sun, Weiya Yang, Guanyu Chen, Yang Shu, Huazhong |
author_facet | Sun, Weiya Yang, Guanyu Chen, Yang Shu, Huazhong |
author_sort | Sun, Weiya |
collection | PubMed |
description | BACKGROUND: The determination of the right x-ray angiography viewing angle is an important issue during the treatment of thoracic endovascular aortic repair (TEVAR). An inaccurate projection angle (manually determined today by the physicians according to their personal experience) may affect the placement of the stent and cause vascular occlusion or endoleak. METHODS: Based on the acquisition of a computed tomography angiography (CTA) image before TEVAR, an adaptive optimization algorithm is proposed to determine the optimal viewing angle of the angiogram automatically. This optimal view aims at avoiding any overlapping between the left common carotid artery and the left subclavian artery. Moreover, the proposed optimal procedure exploits the patient-specific morphology to adaptively reduce the potential foreshortening effect. RESULTS: Experimental results conducted on thirty-five patients demonstrate that the optimal angiographic viewing angle based on the proposed method has no significant difference when compared with the expert practice (p = 0.0678). CONCLUSION: We propose a method that utilizes the CTA image acquired before TEVAR to automatically calculate the optimal C-arm angle. This method has the potential to assist surgeons during their interventional procedure by providing a shorter procedure time, less radiation exposure, and less contrast injection. |
format | Online Article Text |
id | pubmed-8487120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84871202021-10-04 An adaptive optimal viewing angle determination algorithm for TEVAR operation Sun, Weiya Yang, Guanyu Chen, Yang Shu, Huazhong BMC Med Imaging Research BACKGROUND: The determination of the right x-ray angiography viewing angle is an important issue during the treatment of thoracic endovascular aortic repair (TEVAR). An inaccurate projection angle (manually determined today by the physicians according to their personal experience) may affect the placement of the stent and cause vascular occlusion or endoleak. METHODS: Based on the acquisition of a computed tomography angiography (CTA) image before TEVAR, an adaptive optimization algorithm is proposed to determine the optimal viewing angle of the angiogram automatically. This optimal view aims at avoiding any overlapping between the left common carotid artery and the left subclavian artery. Moreover, the proposed optimal procedure exploits the patient-specific morphology to adaptively reduce the potential foreshortening effect. RESULTS: Experimental results conducted on thirty-five patients demonstrate that the optimal angiographic viewing angle based on the proposed method has no significant difference when compared with the expert practice (p = 0.0678). CONCLUSION: We propose a method that utilizes the CTA image acquired before TEVAR to automatically calculate the optimal C-arm angle. This method has the potential to assist surgeons during their interventional procedure by providing a shorter procedure time, less radiation exposure, and less contrast injection. BioMed Central 2021-10-02 /pmc/articles/PMC8487120/ /pubmed/34600478 http://dx.doi.org/10.1186/s12880-021-00676-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Sun, Weiya Yang, Guanyu Chen, Yang Shu, Huazhong An adaptive optimal viewing angle determination algorithm for TEVAR operation |
title | An adaptive optimal viewing angle determination algorithm for TEVAR operation |
title_full | An adaptive optimal viewing angle determination algorithm for TEVAR operation |
title_fullStr | An adaptive optimal viewing angle determination algorithm for TEVAR operation |
title_full_unstemmed | An adaptive optimal viewing angle determination algorithm for TEVAR operation |
title_short | An adaptive optimal viewing angle determination algorithm for TEVAR operation |
title_sort | adaptive optimal viewing angle determination algorithm for tevar operation |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487120/ https://www.ncbi.nlm.nih.gov/pubmed/34600478 http://dx.doi.org/10.1186/s12880-021-00676-3 |
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