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The superiority of manual over automated methods in identifying bronchial trees on identical CT images

The purpose of this study was to compare a manual bronchoscopic navigation technique, the direct oblique method (DOM), with conventional virtual bronchoscopic navigation software in terms of bronchial identification ability involving reconstruction of a whole bronchial tree from identical CT images....

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Autores principales: Takata, So, Miyake, Kotaro, Kumanogoh, Atsushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8969159/
https://www.ncbi.nlm.nih.gov/pubmed/35354903
http://dx.doi.org/10.1038/s41598-022-09401-8
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author Takata, So
Miyake, Kotaro
Kumanogoh, Atsushi
author_facet Takata, So
Miyake, Kotaro
Kumanogoh, Atsushi
author_sort Takata, So
collection PubMed
description The purpose of this study was to compare a manual bronchoscopic navigation technique, the direct oblique method (DOM), with conventional virtual bronchoscopic navigation software in terms of bronchial identification ability involving reconstruction of a whole bronchial tree from identical CT images. A whole bronchial tree was drawn using manual bronchial recognition with the DOM. The tree was compared with that reconstructed by SYNAPSE VINCENT bronchoscopic navigation-dedicated software. The number of bronchial generations at each terminal tip was then compared between the two approaches. Physicians spent 20 h tracing all bronchi on CT scan images and obtained a bronchial tree. The hand-made bronchial tree had five times the number of tips as that reconstructed by automatic bronchial recognition (1482 vs. 279 tips, respectively). The number of bronchial generations prior to each terminal tip was larger with the DOM than with VINCENT (median, 10; interquartile range (IQR), 9–11 vs. median, 5; IQR, 5–7, respectively; p-value < 0.001). Using the CT image data in this case, manual bronchial recognition with the DOM identified more bronchi than automatic bronchial recognition. This result implies that manual bronchial recognition is a valid basis for detailed bronchoscopic navigation analysis.
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spelling pubmed-89691592022-04-01 The superiority of manual over automated methods in identifying bronchial trees on identical CT images Takata, So Miyake, Kotaro Kumanogoh, Atsushi Sci Rep Article The purpose of this study was to compare a manual bronchoscopic navigation technique, the direct oblique method (DOM), with conventional virtual bronchoscopic navigation software in terms of bronchial identification ability involving reconstruction of a whole bronchial tree from identical CT images. A whole bronchial tree was drawn using manual bronchial recognition with the DOM. The tree was compared with that reconstructed by SYNAPSE VINCENT bronchoscopic navigation-dedicated software. The number of bronchial generations at each terminal tip was then compared between the two approaches. Physicians spent 20 h tracing all bronchi on CT scan images and obtained a bronchial tree. The hand-made bronchial tree had five times the number of tips as that reconstructed by automatic bronchial recognition (1482 vs. 279 tips, respectively). The number of bronchial generations prior to each terminal tip was larger with the DOM than with VINCENT (median, 10; interquartile range (IQR), 9–11 vs. median, 5; IQR, 5–7, respectively; p-value < 0.001). Using the CT image data in this case, manual bronchial recognition with the DOM identified more bronchi than automatic bronchial recognition. This result implies that manual bronchial recognition is a valid basis for detailed bronchoscopic navigation analysis. Nature Publishing Group UK 2022-03-30 /pmc/articles/PMC8969159/ /pubmed/35354903 http://dx.doi.org/10.1038/s41598-022-09401-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) .
spellingShingle Article
Takata, So
Miyake, Kotaro
Kumanogoh, Atsushi
The superiority of manual over automated methods in identifying bronchial trees on identical CT images
title The superiority of manual over automated methods in identifying bronchial trees on identical CT images
title_full The superiority of manual over automated methods in identifying bronchial trees on identical CT images
title_fullStr The superiority of manual over automated methods in identifying bronchial trees on identical CT images
title_full_unstemmed The superiority of manual over automated methods in identifying bronchial trees on identical CT images
title_short The superiority of manual over automated methods in identifying bronchial trees on identical CT images
title_sort superiority of manual over automated methods in identifying bronchial trees on identical ct images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8969159/
https://www.ncbi.nlm.nih.gov/pubmed/35354903
http://dx.doi.org/10.1038/s41598-022-09401-8
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