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

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.

Fig 1. Measurements of three axial diameters on two-dimensional images.

a (Transverse section): Two points on the bladder contour with the longest distance on a line parallel to (or small slope against) the horizontal axis. b (Longitudinal section): Two points on the bladder contour with the longest distance. c: Two points on the bladder contour with the longest distance on a line orthogonal to line b.

Fig 2. Methodological overview: Automated bladder volume measurement.

Users collect one transverse and longitudinal image each, and the subsequent processing is automated. Bladder area segmentation is performed by a deep learning algorithm, measurement of the three diameters is performed by ellipse fitting, and bladder volume is mathematically calculated as an ellipsoid. Even if the bladder protrudes from the view, the correct value can be determined by an artificial intelligence (AI) approach by training under expert advice.

Fig 3. Scatter plots of the actual voided volume versus sonographer-calculated (manual) and AI-calculated (automatic) volumes.

Dotted horizontal lines indicate the approximate straight line of the regression equation shown in the square.

Fig 4. Two cases of false negatives.

(a, b) Transverse and longitudinal ultrasound (US) images of the same male aged approximately 20 years. (c, d) transverse and longitudinal US images of the same male aged approximately 30 years. Actual: Urine volume actually urinated by the subject. AI: Value of bladder urine volume estimated by automatic estimation tool. Yellow lines are detected by AI as bladder diameters.