論文

査読有り 国際誌
2019年

Development and evaluation of automated ultrasonographic detection of bladder diameter for estimation of bladder urine volume.

PloS one
  • Masaru Matsumoto
  • ,
  • Takuya Tsutaoka
  • ,
  • Koichi Yabunaka
  • ,
  • Mayumi Handa
  • ,
  • Mikako Yoshida
  • ,
  • Gojiro Nakagami
  • ,
  • Hiromi Sanada

14
9
開始ページ
e0219916
終了ページ
記述言語
英語
掲載種別
DOI
10.1371/journal.pone.0219916

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, R2 = 0.96) and manual estimation (β = 1.05, R2 = 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.

リンク情報
DOI
https://doi.org/10.1371/journal.pone.0219916
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/31487299
PubMed Central
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728037
ID情報
  • DOI : 10.1371/journal.pone.0219916
  • PubMed ID : 31487299
  • PubMed Central 記事ID : PMC6728037

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