Marcel Gärtner1, Jan Krhut2,3, Petr Hurtik4, Michal Burda4, Katarina Zvarova5, Peter Zvara3,6. 1. Department of Obstetrics and Gynecology, University Hospital, Ostrava, Czech Republic. 2. Department of Urology, University Hospital, Ostrava, Czech Republic. 3. Department of Surgical Studies, Ostrava University, Ostrava, Czech Republic. 4. Institute for Research and Applications of Fuzzy Modeling, Centre of Excellence IT4Innovations, University of Ostrava, Ostrava, Czech Republic. 5. Department of Physiology, Slovak Medical University, Bratislava, Slovak Republic. 6. Department of Surgery, University of Vermont, Burlington, Vermont, USA.
Abstract
OBJECTIVES: Sonouroflowmetry represents a novel method for estimating urinary flow parameters. The aim of this study was to compare the urinary flow parameters acquired using sonouroflowmetry with those of standard uroflowmetry in healthy female volunteers. METHODS: Thirty-six healthy female volunteers (aged 25-54 years) were subjected to standard uroflowmetry. Simultaneously, subjects dialed a dedicated number on a mobile phone and kept recording until urination was finished. Sound data were analyzed and compared to the uroflowmetry data. Of 218 recordings, 183 were included in the final analysis. Thirty-four measurements were excluded for voided volume <150 mL or technical problems during the recording. A linear model was fitted to calculate the urinary flow parameters and the voided volume from data obtained by sonouroflowmetry. Subsequently the matching datasets of UF and SUF were compared with respect to flow time, voided volume, maximum (Qmax ) and average (Qave ) flow rate. Pearson's correlation coefficient (PCC) was used to compare parameters recorded by uroflowmetry with those calculated based on sonouroflowmetry recordings. RESULTS: A strong correlation (PCC = 0.95) was noted between uroflowmetry recorded flow time and duration of the sonouroflowmetry sound signal. The voided volume measured by uroflowmetry showed a moderate correlation (PCC = 0.68) with the calculated area under the sonouroflowmetry curve. Qmax recorded using uroflowmetry and sonouroflowmetry recorded peak sound intensity showed a weak correlation (PCC = 0.38). CONCLUSIONS: This study validates the basic concept of using sound analysis to estimate urinary flow parameters and voided volume.
OBJECTIVES: Sonouroflowmetry represents a novel method for estimating urinary flow parameters. The aim of this study was to compare the urinary flow parameters acquired using sonouroflowmetry with those of standard uroflowmetry in healthy female volunteers. METHODS: Thirty-six healthy female volunteers (aged 25-54 years) were subjected to standard uroflowmetry. Simultaneously, subjects dialed a dedicated number on a mobile phone and kept recording until urination was finished. Sound data were analyzed and compared to the uroflowmetry data. Of 218 recordings, 183 were included in the final analysis. Thirty-four measurements were excluded for voided volume <150 mL or technical problems during the recording. A linear model was fitted to calculate the urinary flow parameters and the voided volume from data obtained by sonouroflowmetry. Subsequently the matching datasets of UF and SUF were compared with respect to flow time, voided volume, maximum (Qmax ) and average (Qave ) flow rate. Pearson's correlation coefficient (PCC) was used to compare parameters recorded by uroflowmetry with those calculated based on sonouroflowmetry recordings. RESULTS: A strong correlation (PCC = 0.95) was noted between uroflowmetry recorded flow time and duration of the sonouroflowmetry sound signal. The voided volume measured by uroflowmetry showed a moderate correlation (PCC = 0.68) with the calculated area under the sonouroflowmetry curve. Qmax recorded using uroflowmetry and sonouroflowmetry recorded peak sound intensity showed a weak correlation (PCC = 0.38). CONCLUSIONS: This study validates the basic concept of using sound analysis to estimate urinary flow parameters and voided volume.
Authors: Jean F Wyman; Jincheng Zhou; D Yvette LaCoursiere; Alayne D Markland; Elizabeth R Mueller; Laura Simon; Ann Stapleton; Carolyn R T Stoll; Haitao Chu; Siobhan Sutcliffe Journal: Neurourol Urodyn Date: 2020-01-09 Impact factor: 2.696
Authors: Dong-Gi Lee; Jonathan Gerber; Vinaya Bhatia; Nicolette Janzen; Paul F Austin; Chester J Koh; Sang Hoon Song Journal: Int Neurourol J Date: 2021-12-31 Impact factor: 2.835