Benign prostatic hyperplasia (BPH) is a common condition that causes lower urinary tract symptoms (LUTS) in middle-aged and elderly men. Existing bladder function monitoring methods, such as ultrasound and urodynamic studies (UDS), have limitations including invasiveness, lack of dynamic capability, poor portability, and susceptibility to psychological interference. Electrical impedance tomography (EIT) technology, with its potential for non-invasiveness, non-ionizing during monitoring, portability, and real-time dynamic imaging, offers a new approach to address this clinical challenge.
This study aims to evaluate whether an intelligent wearable EIT device can achieve clinically acceptable agreement with standard uroflowmetry for dynamic monitoring of bladder volume and urinary flow rate in patients with BPH. This is a single-centre, self-controlled diagnostic consistency study. We plan to enroll 40 eligible patients with BPH. All participants will undergo simultaneous monitoring with the EIT wearable device and a conventional uroflowmeter during voiding. The primary outcomes are maximum flow rate (Qmax), average flow rate (Qave), and voided volume (VV) measured by both methods. Clinically acceptable agreement will be evaluated primarily by Bland-Altman analysis with 95% limits of agreement, with intraclass correlation coefficient (ICC) used as a supplementary measure of consistency; curve similarity will be explored using dynamic time warping (DTW) distance and Pearson correlation. Secondary outcomes include the device's capability for real-time dynamic bladder volume monitoring during filling and voiding, and the development of an artificial intelligence (AI)-enhanced analytical framework for future home-based telemedicine applications.
This trial will systematically validate whether EIT-based wearable technology can achieve non-invasive, accurate, and dynamic monitoring of voiding function in patients with BPH. If successful, it may provide a practical alternative to traditional uroflowmetry by enabling continuous physiological assessment in a near-natural state, and ultimately support long-term home-based self-management and remote urological care.
This trial was registered with ClinicalTrials.gov on 12 January 2026 with the trial ID NCT07357012, accessible at https://clinicaltrials.gov.
Translational andrology and urology. 2026 May 26 [Epub]
Zhuo Liu, Xiushi Lin, Lin Zhuo, Qiang Li, Jiyuan Chen, Zexin Zhu, Xiaolin Li, Chunlei Xiao, Shudong Zhang, Jiangtao Sun, Ke Liu
Department of Urology, Peking University Third Hospital, Beijing, China., Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China., Department of Urology, Beijing Zhongguancun Hospital, Beijing, China., School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China.