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Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization
BACKGROUND: The purpose of this study is presenting a method to predict the presence of an open urinary tract and the position of the opening in laparoscopic partial nephrectomy from three dimensional (3D) computed tomography (CT) images by using novel image segmentation and visualization techniques...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074416/ https://www.ncbi.nlm.nih.gov/pubmed/24927795 http://dx.doi.org/10.1186/1471-2490-14-47 |
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author | Ueno, Daiki Makiyama, Kazuhide Yamanaka, Hiroyuki Ijiri, Takashi Yokota, Hideo Kubota, Yoshinobu |
author_facet | Ueno, Daiki Makiyama, Kazuhide Yamanaka, Hiroyuki Ijiri, Takashi Yokota, Hideo Kubota, Yoshinobu |
author_sort | Ueno, Daiki |
collection | PubMed |
description | BACKGROUND: The purpose of this study is presenting a method to predict the presence of an open urinary tract and the position of the opening in laparoscopic partial nephrectomy from three dimensional (3D) computed tomography (CT) images by using novel image segmentation and visualization techniques. METHODS: From CT images of patients who underwent laparoscopic partial nephrectomy, 3D regions of the kidney, urinary tract, and tumor were segmented. For each patient, multiple virtual resection planes of the kidney with different surgical margins (1 mm to 5 mm, every 1 mm) were generated and the presence of an open urinary tract and the position of the opening were predicted from the images. RESULTS: We compared the predictions with actual operations in 5 cases by using recorded video of the operations and operative notes. In terms of the presence of an open urinary tract, agreement of the predictions and the intraoperative results was obtained in all patients. The expected positions of the openings were close to those in the actual operations. CONCLUSIONS: We have developed a method to virtually visualize the resection plane of laparoscopic partial nephrectomy. Image segmentation methods used in this study were precise and effective. The comparison indicated that our method accurately predicted the presence of an open urinary tract and the position of the opening and provided useful preoperative information. |
format | Online Article Text |
id | pubmed-4074416 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40744162014-06-29 Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization Ueno, Daiki Makiyama, Kazuhide Yamanaka, Hiroyuki Ijiri, Takashi Yokota, Hideo Kubota, Yoshinobu BMC Urol Technical Advance BACKGROUND: The purpose of this study is presenting a method to predict the presence of an open urinary tract and the position of the opening in laparoscopic partial nephrectomy from three dimensional (3D) computed tomography (CT) images by using novel image segmentation and visualization techniques. METHODS: From CT images of patients who underwent laparoscopic partial nephrectomy, 3D regions of the kidney, urinary tract, and tumor were segmented. For each patient, multiple virtual resection planes of the kidney with different surgical margins (1 mm to 5 mm, every 1 mm) were generated and the presence of an open urinary tract and the position of the opening were predicted from the images. RESULTS: We compared the predictions with actual operations in 5 cases by using recorded video of the operations and operative notes. In terms of the presence of an open urinary tract, agreement of the predictions and the intraoperative results was obtained in all patients. The expected positions of the openings were close to those in the actual operations. CONCLUSIONS: We have developed a method to virtually visualize the resection plane of laparoscopic partial nephrectomy. Image segmentation methods used in this study were precise and effective. The comparison indicated that our method accurately predicted the presence of an open urinary tract and the position of the opening and provided useful preoperative information. BioMed Central 2014-06-13 /pmc/articles/PMC4074416/ /pubmed/24927795 http://dx.doi.org/10.1186/1471-2490-14-47 Text en Copyright © 2014 Ueno et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Technical Advance Ueno, Daiki Makiyama, Kazuhide Yamanaka, Hiroyuki Ijiri, Takashi Yokota, Hideo Kubota, Yoshinobu Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization |
title | Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization |
title_full | Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization |
title_fullStr | Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization |
title_full_unstemmed | Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization |
title_short | Prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization |
title_sort | prediction of open urinary tract in laparoscopic partial nephrectomy by virtual resection plane visualization |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4074416/ https://www.ncbi.nlm.nih.gov/pubmed/24927795 http://dx.doi.org/10.1186/1471-2490-14-47 |
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