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开发和评估自动超声检测膀胱直径以估计膀胱尿量的方法。

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

机构信息

Department of Imaging Nursing Science, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.

Imaging Technology Center, Research & Development Management Headquarters, FUJIFILM Corporation, Minato-ku, Tokyo, Japan.

出版信息

PLoS One. 2019 Sep 5;14(9):e0219916. doi: 10.1371/journal.pone.0219916. eCollection 2019.

Abstract

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.

摘要

膀胱尿量曾通过基于从二维超声图像外推的三轴测量的椭圆体方法进行估计。本研究旨在实现该过程的自动化,并确定自动化估计方法对正常和少量尿液的准确性。使用来自健康志愿者的在平板电脑型超声设备上收集的 81 对横向和纵向超声图像的训练集,开发了一种自动检测工具。使用来自其他 27 名健康志愿者的 27 对横向/纵向超声图像对该工具进行了评估。成像后,参与者排空尿液并测量尿量。为了确定准确性,计算了估计的膀胱体积与尿量之间的回归系数。此外,还评估了 50ml 和 100ml 膀胱体积阈值的灵敏度和特异性。纳入了 50 例操作的数据。自动估计(β=0.99,R2=0.96)和手动估计(β=1.05,R2=0.97)方法之间的回归系数非常相似。对于 100ml,自动估计方法的灵敏度和特异性分别为 88.5%和 100.0%,对于 50ml,分别为 94.1%和 100.0%。新开发的自动工具能够准确可靠地估计两个不同体积阈值(约 50ml 和 100ml)的膀胱体积。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a45/6728037/ca27ddb43f61/pone.0219916.g001.jpg

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