Chew Lauren E, Hannick Jessica H, Woo Lynn L, Weaver John K, Damaser Margot S
University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
Cleveland Clinic Children's Hospital, Cleveland, OH, USA.
Neurourol Urodyn. 2025 May 14. doi: 10.1002/nau.70074.
Urodynamic studies (UDS) are essential for evaluating lower urinary tract function but are limited by patient discomfort, lack of standardization and diagnostic variability. Advances in technology aim to address these challenges and improve diagnostic accuracy and patient comfort.
AMBULATORY URODYNAMIC MONITORING (AUM): AUM offers physiological assessment by allowing natural bladder filling and monitoring during daily activities. Compared to conventional UDS, AUM demonstrates higher sensitivity for detecting detrusor overactivity and underlying pathophysiology. However, it faces challenges like motion artifacts, catheter-related discomfort, and difficulty measuring continuous bladder volume.
Emerging devices such as Urodynamics Monitor and UroSound offer more patient-friendly alternatives. These tools have the potential to improve diagnostic accuracy for bladder pressure and voiding metrics but remain limited and still require further validation and testing.
Ultrasound-based modalities, including dynamic ultrasonography and shear wave elastography, provide real-time, noninvasive assessment of bladder structure and function. These modalities are promising but will require further development of standardized protocols.
AI and machine learning models enhance diagnostic accuracy and reduce variability in UDS interpretation. Applications include detecting detrusor overactivity and distinguishing bladder outlet obstruction from detrusor underactivity. However, further validation is required for clinical adoption.
Advances in AUM, wearable technologies, ultrasonography, and AI demonstrate potential for transforming UDS into a more accurate, patient-centered tool. Despite significant progress, challenges like technical complexity, standardization, and cost-effectiveness must be addressed to integrate these innovations into routine practice. Nonetheless, these technologies provide the possibility of a future of improved diagnosis and treatment of lower urinary tract dysfunction.
尿动力学研究（UDS）对于评估下尿路功能至关重要，但受患者不适、缺乏标准化以及诊断变异性的限制。技术进步旨在应对这些挑战，提高诊断准确性和患者舒适度。
动态尿动力学监测（AUM）：AUM通过在日常活动期间允许膀胱自然充盈并进行监测来提供生理评估。与传统UDS相比，AUM在检测逼尿肌过度活动和潜在病理生理学方面具有更高的敏感性。然而，它面临诸如运动伪影、导管相关不适以及连续膀胱容量测量困难等挑战。
诸如尿动力学监测仪和尿声等新兴设备提供了更方便患者的选择。这些工具有可能提高膀胱压力和排尿指标的诊断准确性，但仍然有限，仍需要进一步验证和测试。
超声在UDS中的应用：基于超声的方法，包括动态超声成像和剪切波弹性成像，可对膀胱结构和功能进行实时、无创评估。这些方法很有前景，但需要进一步制定标准化方案。
人工智能在UDS中的应用：人工智能和机器学习模型可提高诊断准确性并减少UDS解读中的变异性。应用包括检测逼尿肌过度活动以及区分膀胱出口梗阻与逼尿肌活动低下。然而，临床应用还需要进一步验证。
AUM、可穿戴技术、超声和人工智能的进展表明，有可能将UDS转变为一种更准确、以患者为中心的工具。尽管取得了重大进展，但必须解决技术复杂性、标准化和成本效益等挑战，才能将这些创新整合到常规实践中。尽管如此，这些技术为未来改善下尿路功能障碍的诊断和治疗提供了可能性。
