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Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume
Bladder urine volume has been estimated using an ellipsoid method based on triaxial measurements of the bladder extrapolated from two-dimensional ultrasound images. This study aimed to automate this process and to determine the accuracy of the automated estimation method for normal and small amounts...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728037/ https://www.ncbi.nlm.nih.gov/pubmed/31487299 http://dx.doi.org/10.1371/journal.pone.0219916 |
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author | Matsumoto, Masaru Tsutaoka, Takuya Yabunaka, Koichi Handa, Mayumi Yoshida, Mikako Nakagami, Gojiro Sanada, Hiromi |
author_facet | Matsumoto, Masaru Tsutaoka, Takuya Yabunaka, Koichi Handa, Mayumi Yoshida, Mikako Nakagami, Gojiro Sanada, Hiromi |
author_sort | Matsumoto, Masaru |
collection | PubMed |
description | Bladder urine volume has been estimated using an ellipsoid method based on triaxial measurements of the bladder extrapolated from two-dimensional ultrasound images. This study aimed to automate this process and to determine the accuracy of the automated estimation method for normal and small amounts of urine. A training set of 81 pairs of transverse and longitudinal ultrasound images were collected from healthy volunteers on a tablet-type ultrasound device, and an automatic detection tool was developed using them. The tool was evaluated using paired transverse/longitudinal ultrasound images from 27 other healthy volunteers. After imaging, the participants voided and their urine volume was measured. For determining accuracy, regression coefficients were calculated between estimated bladder volume and urine volume. Further, sensitivity and specificity for 50 and 100 ml bladder volume thresholds were evaluated. Data from 50 procedures were included. The regression coefficient was very similar between the automatic estimation (β = 0.99, R(2) = 0.96) and manual estimation (β = 1.05, R(2) = 0.97) methods. The sensitivity and specificity of the automatic estimation method were 88.5% and 100.0%, respectively, for 100 ml and were 94.1% and 100.0%, respectively, for 50 ml. The newly-developed automated tool accurately and reliably estimated bladder volume at two different volume thresholds of approximately 50 ml and 100 ml. |
format | Online Article Text |
id | pubmed-6728037 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-67280372019-09-16 Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume Matsumoto, Masaru Tsutaoka, Takuya Yabunaka, Koichi Handa, Mayumi Yoshida, Mikako Nakagami, Gojiro Sanada, Hiromi PLoS One Research Article Bladder urine volume has been estimated using an ellipsoid method based on triaxial measurements of the bladder extrapolated from two-dimensional ultrasound images. This study aimed to automate this process and to determine the accuracy of the automated estimation method for normal and small amounts of urine. A training set of 81 pairs of transverse and longitudinal ultrasound images were collected from healthy volunteers on a tablet-type ultrasound device, and an automatic detection tool was developed using them. The tool was evaluated using paired transverse/longitudinal ultrasound images from 27 other healthy volunteers. After imaging, the participants voided and their urine volume was measured. For determining accuracy, regression coefficients were calculated between estimated bladder volume and urine volume. Further, sensitivity and specificity for 50 and 100 ml bladder volume thresholds were evaluated. Data from 50 procedures were included. The regression coefficient was very similar between the automatic estimation (β = 0.99, R(2) = 0.96) and manual estimation (β = 1.05, R(2) = 0.97) methods. The sensitivity and specificity of the automatic estimation method were 88.5% and 100.0%, respectively, for 100 ml and were 94.1% and 100.0%, respectively, for 50 ml. The newly-developed automated tool accurately and reliably estimated bladder volume at two different volume thresholds of approximately 50 ml and 100 ml. Public Library of Science 2019-09-05 /pmc/articles/PMC6728037/ /pubmed/31487299 http://dx.doi.org/10.1371/journal.pone.0219916 Text en © 2019 Matsumoto et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Matsumoto, Masaru Tsutaoka, Takuya Yabunaka, Koichi Handa, Mayumi Yoshida, Mikako Nakagami, Gojiro Sanada, Hiromi Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume |
title | Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume |
title_full | Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume |
title_fullStr | Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume |
title_full_unstemmed | Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume |
title_short | Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume |
title_sort | development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728037/ https://www.ncbi.nlm.nih.gov/pubmed/31487299 http://dx.doi.org/10.1371/journal.pone.0219916 |
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