Wang Jin, Yang Xin, Wu Yinnan, Peng Yanqing, Zou Yan, Lu Xiduo, Chen Shuangxi, Pan Xiaoyi, Ni Dong, Sun Litao
Department of Ultrasound Medicine, Cancer Center, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
Medical UltraSound Image Computing (MUSIC) Lab, Shenzhen University, Shenzhen, China; National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.
Am J Obstet Gynecol. 2025 Jan;232(1):112.e1-112.e12. doi: 10.1016/j.ajog.2024.07.021. Epub 2024 Jul 19.
No universally recognized transperineal ultrasound parameters are available for evaluating stress urinary incontinence. The information captured by commonly used perineal ultrasound parameters is limited and insufficient for a comprehensive assessment of stress urinary incontinence. Although bladder neck motion plays a major role in stress urinary incontinence, objective and visual methods to evaluate its impact on stress urinary incontinence remain lacking.
To use a deep learning-based system to evaluate bladder neck motion using 2-dimensional transperineal ultrasound videos, exploring motion parameters for diagnosing and evaluating stress urinary incontinence. We hypothesized that bladder neck motion parameters are associated with stress urinary incontinence and are useful for stress urinary incontinence diagnosis and evaluation.
This retrospective study including 217 women involved the following parameters: maximum and average speeds of bladder neck descent, β angle, urethral rotation angle, and duration of the Valsalva maneuver. The fitted curves were derived to visualize bladder neck motion trajectories. Comparative analyses were conducted to assess these parameters between stress urinary incontinence and control groups. Logistic regression and receiver operating characteristic curve analyses were employed to evaluate the diagnostic performance of each motion parameter and their combinations for stress urinary incontinence.
Overall, 173 women were enrolled in this study (82, stress urinary incontinence group; 91, control group). No significant differences were observed in the maximum and average speeds of bladder neck descent and in the speed variance of bladder neck descent. The maximum and average speed of the β and urethral rotation angles were faster in the stress urinary incontinence group than in the control group (151.2 vs 109.0 mm/s, P=.001; 6.0 vs 3.1 mm/s, P<.001; 105.5 vs 69.6 mm/s, P<.001; 10.1 vs 7.9 mm/s, P=.011, respectively). The speed variance of the β and urethral rotation angles were higher in the stress urinary incontinence group (844.8 vs 336.4, P<.001; 347.6 vs 131.1, P<.001, respectively). The combination of the average speed of the β angle, maximum speed of the urethral rotation angle, and duration of the Valsalva maneuver demonstrated a strong diagnostic performance (area under the curve, 0.87). When 0.481∗β angle+0.013∗URA+0.483∗D=7.405, the diagnostic sensitivity was 70% and specificity was 92%, highlighting the significant role of bladder neck motion in stress urinary incontinence, particularly changes in the speed of the β and urethral rotation angles.
A system utilizing deep learning can describe the motion of the bladder neck in women with stress urinary incontinence during the Valsalva maneuver, making it possible to visualize and quantify bladder neck motion on transperineal ultrasound. The speeds of the β and urethral rotation angles and duration of the Valsalva maneuver were relatively reliable diagnostic parameters.
目前尚无普遍认可的经会阴超声参数可用于评估压力性尿失禁。常用的会阴超声参数所获取的信息有限，不足以全面评估压力性尿失禁。尽管膀胱颈移动在压力性尿失禁中起主要作用，但仍缺乏客观且可视的方法来评估其对压力性尿失禁的影响。
使用基于深度学习的系统，通过二维经会阴超声视频评估膀胱颈移动，探索用于诊断和评估压力性尿失禁的移动参数。我们假设膀胱颈移动参数与压力性尿失禁相关，且对压力性尿失禁的诊断和评估有用。
这项回顾性研究纳入了217名女性，涉及以下参数：膀胱颈下降的最大速度和平均速度、β角、尿道旋转角以及瓦尔萨尔瓦动作的持续时间。通过拟合曲线来直观显示膀胱颈移动轨迹。对压力性尿失禁组和对照组之间的这些参数进行比较分析。采用逻辑回归和受试者工作特征曲线分析来评估每个移动参数及其组合对压力性尿失禁的诊断性能。
总体而言，本研究共纳入173名女性（82名压力性尿失禁组；91名对照组）。在膀胱颈下降的最大速度和平均速度以及膀胱颈下降的速度方差方面，未观察到显著差异。压力性尿失禁组的β角和尿道旋转角的最大速度和平均速度均高于对照组（分别为151.2对109.0毫米/秒，P = 0.001；6.0对3.1毫米/秒，P < 0.001；105.5对69.6毫米/秒，P < 0.001；10.1对7.9毫米/秒，P = 0.011）。压力性尿失禁组的β角和尿道旋转角的速度方差更高（分别为844.8对336.4，P < 0.001；347.6对131.1，P < 0.001）。β角平均速度、尿道旋转角最大速度和瓦尔萨尔瓦动作持续时间的组合显示出较强的诊断性能（曲线下面积为0.87）。当0.481×β角 + 0.013×尿道旋转角 + 0.483×持续时间 = 7.405时，诊断敏感性为70%，特异性为92%，突出了膀胱颈移动在压力性尿失禁中的重要作用，尤其是β角和尿道旋转角速度的变化。
利用深度学习的系统能够描述压力性尿失禁女性在瓦尔萨尔瓦动作期间膀胱颈的移动，使得在经会阴超声上可视化和量化膀胱颈移动成为可能。β角和尿道旋转角的速度以及瓦尔萨尔瓦动作的持续时间是相对可靠的诊断参数。
